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\n  \n 2023\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Understanding the emergence of the boson peak in molecular glasses.\n \n \n \n \n\n\n \n González-Jiménez, M.; Barnard, T.; Russell, B. A.; Tukachev, N. V.; Javornik, U.; Hayes, L.; Farrell, A. J.; Guinane, S.; Senn, H. M.; Smith, A. J.; Wilding, M.; Mali, G.; Nakano, M.; Miyazaki, Y.; McMillan, P.; Sosso, G. C.; and Wynne, K.\n\n\n \n\n\n\n Nature Communications, 14(1): 215. January 2023.\n Number: 1 Publisher: Nature Publishing Group\n\n\n\n
\n\n\n\n \n \n \"UnderstandingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{gonzalez-jimenez_understanding_2023,\n\ttitle = {Understanding the emergence of the boson peak in molecular glasses},\n\tvolume = {14},\n\tcopyright = {2023 The Author(s)},\n\tissn = {2041-1723},\n\turl = {https://www.nature.com/articles/s41467-023-35878-6},\n\tdoi = {10.1038/s41467-023-35878-6},\n\tabstract = {A common feature of glasses is the “boson peak”, observed as an excess in the heat capacity over the crystal or as an additional peak in the terahertz vibrational spectrum. The microscopic origins of this peak are not well understood; the emergence of locally ordered structures has been put forward as a possible candidate. Here, we show that depolarised Raman scattering in liquids consisting of highly symmetric molecules can be used to isolate the boson peak, allowing its detailed observation from the liquid into the glass. The boson peak in the vibrational spectrum matches the excess heat capacity. As the boson peak intensifies on cooling, wide-angle x-ray scattering shows the simultaneous appearance of a pre-peak due to molecular clusters consisting of circa 20 molecules. Atomistic molecular dynamics simulations indicate that these are caused by over-coordinated molecules. These findings represent an essential step toward our understanding of the physics of vitrification.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-02-22},\n\tjournal = {Nature Communications},\n\tauthor = {González-Jiménez, Mario and Barnard, Trent and Russell, Ben A. and Tukachev, Nikita V. and Javornik, Uroš and Hayes, Laure-Anne and Farrell, Andrew J. and Guinane, Sarah and Senn, Hans M. and Smith, Andrew J. and Wilding, Martin and Mali, Gregor and Nakano, Motohiro and Miyazaki, Yuji and McMillan, Paul and Sosso, Gabriele C. and Wynne, Klaas},\n\tmonth = jan,\n\tyear = {2023},\n\tnote = {Number: 1\nPublisher: Nature Publishing Group},\n\tkeywords = {Structure of solids and liquids},\n\tpages = {215},\n}\n\n
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\n\n\n
\n A common feature of glasses is the “boson peak”, observed as an excess in the heat capacity over the crystal or as an additional peak in the terahertz vibrational spectrum. The microscopic origins of this peak are not well understood; the emergence of locally ordered structures has been put forward as a possible candidate. Here, we show that depolarised Raman scattering in liquids consisting of highly symmetric molecules can be used to isolate the boson peak, allowing its detailed observation from the liquid into the glass. The boson peak in the vibrational spectrum matches the excess heat capacity. As the boson peak intensifies on cooling, wide-angle x-ray scattering shows the simultaneous appearance of a pre-peak due to molecular clusters consisting of circa 20 molecules. Atomistic molecular dynamics simulations indicate that these are caused by over-coordinated molecules. These findings represent an essential step toward our understanding of the physics of vitrification.\n
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\n  \n 2022\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n \n The role of structural order in heterogeneous ice nucleation.\n \n \n \n \n\n\n \n C. Sosso, G.; Sudera, P.; T. Backes, A.; F. Whale, T.; Fröhlich-Nowoisky, J.; Bonn, M.; Michaelides, A.; and G. Backus, E. H.\n\n\n \n\n\n\n Chemical Science, 13(17): 5014–5026. 2022.\n Publisher: Royal Society of Chemistry\n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{csosso_role_2022,\n\ttitle = {The role of structural order in heterogeneous ice nucleation},\n\tvolume = {13},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2022/sc/d1sc06338c},\n\tdoi = {10.1039/D1SC06338C},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2023-01-10},\n\tjournal = {Chemical Science},\n\tauthor = {C. Sosso, Gabriele and Sudera, Prerna and T. Backes, Anna and F. Whale, Thomas and Fröhlich-Nowoisky, Janine and Bonn, Mischa and Michaelides, Angelos and G. Backus, Ellen H.},\n\tyear = {2022},\n\tnote = {Publisher: Royal Society of Chemistry},\n\tpages = {5014--5026},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Understanding the emergence of the boson peak in molecular glasses.\n \n \n \n \n\n\n \n González-Jiménez, M.; Barnard, T.; Russell, B.; Tukachev, N.; Javornik, U.; Hayes, L.; Farrell, A.; Guinane, S.; Senn, H.; Smith, A.; Wilding, M.; Mali, G.; Nakano, M.; Miyazaki, Y.; McMillan, P.; Sosso, G.; and Wynne, K.\n\n\n \n\n\n\n December 2022.\n \n\n\n\n
\n\n\n\n \n \n \"UnderstandingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@misc{gonzalez-jimenez_understanding_2022,\n\ttitle = {Understanding the emergence of the boson peak in molecular glasses},\n\turl = {https://chemrxiv.org/engage/chemrxiv/article-details/639b24dae9d0fd62f41df5f7},\n\tdoi = {10.26434/chemrxiv-2022-25q9h-v4},\n\tabstract = {A common feature of glasses is the “boson peak”, observed as an excess in the heat capacity over the crystal or as an additional peak in the terahertz vibrational spectrum. The microscopic origins of this peak are not well understood; the emergence of locally ordered structures has been put forward as a possible candidate. Here, we show that depolarised Raman scattering in liquids consisting of highly symmetric molecules can be used to isolate the boson peak, allowing its detailed observation from the liquid into the glass. The boson peak in the vibrational spectrum matches the excess heat capacity. As the boson peak intensifies on cooling, wide-angle x-ray scattering shows the simultaneous appearance of a pre-peak due to molecular clusters consisting of circa 20 molecules. Atomistic molecular dynamics simulations indicate that these are caused by over-coordinated molecules. These findings represent an essential step toward our understanding of the physics of vitrification.},\n\tlanguage = {en},\n\turldate = {2023-01-10},\n\tpublisher = {ChemRxiv},\n\tauthor = {González-Jiménez, Mario and Barnard, Trent and Russell, Ben and Tukachev, Nikita and Javornik, Uroš and Hayes, Laure-Anne and Farrell, Andrew and Guinane, Sarah and Senn, Hans and Smith, Andrew and Wilding, Martin and Mali, Gregor and Nakano, Motohiro and Miyazaki, Yuji and McMillan, Paul and Sosso, Gabriele and Wynne, Klaas},\n\tmonth = dec,\n\tyear = {2022},\n\tkeywords = {DFT, FTIR, Raman, Vogel-Fulcher-Tammann, WAXS, boson peak, calorimetry, glass transition, molecular dynamics, optical Kerr effect, ssNMR, structure, supercooling, terahertz, viscometry, vitrification},\n}\n\n
\n
\n\n\n
\n A common feature of glasses is the “boson peak”, observed as an excess in the heat capacity over the crystal or as an additional peak in the terahertz vibrational spectrum. The microscopic origins of this peak are not well understood; the emergence of locally ordered structures has been put forward as a possible candidate. Here, we show that depolarised Raman scattering in liquids consisting of highly symmetric molecules can be used to isolate the boson peak, allowing its detailed observation from the liquid into the glass. The boson peak in the vibrational spectrum matches the excess heat capacity. As the boson peak intensifies on cooling, wide-angle x-ray scattering shows the simultaneous appearance of a pre-peak due to molecular clusters consisting of circa 20 molecules. Atomistic molecular dynamics simulations indicate that these are caused by over-coordinated molecules. These findings represent an essential step toward our understanding of the physics of vitrification.\n
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\n \n\n \n \n \n \n \n \n Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor.\n \n \n \n \n\n\n \n Barnard, T.; Steng, S.; Darby, J.; Bartók, A. P.; Broo, A.; and Sosso, G. C.\n\n\n \n\n\n\n Molecular Systems Design & Engineering. November 2022.\n Publisher: The Royal Society of Chemistry\n\n\n\n
\n\n\n\n \n \n \"LeveragingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{barnard_leveraging_2022,\n\ttitle = {Leveraging genetic algorithms to maximise the predictive capabilities of the {SOAP} descriptor},\n\tissn = {2058-9689},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2022/me/d2me00149g},\n\tdoi = {10.1039/D2ME00149G},\n\tabstract = {The Smooth Overlap of Atomic Positions (SOAP) descriptor represents an increasingly common approach to encode local atomic environments in a form readily digestible to machine learning algorithms. The SOAP descriptor is obtained by using a local expansion of a Gaussian smeared atomic density with orthonormal functions based on spherical harmonics and radial basis functions. To construct this representation, one has to choose a number of parameters. Whilst the knowledge of the dataset of interest can and should guide this choice, more often than not some optimisation method is required to pinpoint the most effective combinations of SOAP parameters in terms of both accuracy and computational cost. In this work, we present SOAP\\_GAS, a simple, freely available computational tool that leverages genetic algorithms to optimise the parameters relative to any given SOAP descriptor. To explore the capabilities of the algorithm, we have applied SOAP\\_GAS to a prototypical molecular dataset of relevance for drug design. In this process, we have realised that a diverse portfolio of different combinations of SOAP parameters can result in equally substantial improvements in terms of the accuracy of the SOAP descriptor. This is especially true when dealing with the concurrent optimisation of the SOAP parameters for multiple SOAP descriptors, which we found it often leads to further accuracy gains. Overall, we show that SOAP\\_GAS offers an often superior alternative to e.g. randomised grid search approaches to enhanced the predictive capabilities of SOAP descriptors in a largely automatised fashion.},\n\tlanguage = {en},\n\turldate = {2022-11-09},\n\tjournal = {Molecular Systems Design \\& Engineering},\n\tauthor = {Barnard, Trent and Steng, Steven and Darby, James and Bartók, Albert P. and Broo, Anders and Sosso, Gabriele Cesare},\n\tmonth = nov,\n\tyear = {2022},\n\tnote = {Publisher: The Royal Society of Chemistry},\n}\n\n
\n
\n\n\n
\n The Smooth Overlap of Atomic Positions (SOAP) descriptor represents an increasingly common approach to encode local atomic environments in a form readily digestible to machine learning algorithms. The SOAP descriptor is obtained by using a local expansion of a Gaussian smeared atomic density with orthonormal functions based on spherical harmonics and radial basis functions. To construct this representation, one has to choose a number of parameters. Whilst the knowledge of the dataset of interest can and should guide this choice, more often than not some optimisation method is required to pinpoint the most effective combinations of SOAP parameters in terms of both accuracy and computational cost. In this work, we present SOAP_GAS, a simple, freely available computational tool that leverages genetic algorithms to optimise the parameters relative to any given SOAP descriptor. To explore the capabilities of the algorithm, we have applied SOAP_GAS to a prototypical molecular dataset of relevance for drug design. In this process, we have realised that a diverse portfolio of different combinations of SOAP parameters can result in equally substantial improvements in terms of the accuracy of the SOAP descriptor. This is especially true when dealing with the concurrent optimisation of the SOAP parameters for multiple SOAP descriptors, which we found it often leads to further accuracy gains. Overall, we show that SOAP_GAS offers an often superior alternative to e.g. randomised grid search approaches to enhanced the predictive capabilities of SOAP descriptors in a largely automatised fashion.\n
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\n \n\n \n \n \n \n \n \n Minimalistic ice recrystallisation inhibitors based on phenylalanine.\n \n \n \n \n\n\n \n T. Warren, M.; Galpin, I.; Hasan, M.; A. Hindmarsh, S.; D. Padrnos, J.; Edwards-Gayle, C.; T. Mathers, R.; J. Adams, D.; C. Sosso, G.; and I. Gibson, M.\n\n\n \n\n\n\n Chemical Communications, 58(55): 7658–7661. 2022.\n Publisher: Royal Society of Chemistry\n\n\n\n
\n\n\n\n \n \n \"MinimalisticPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{twarren_minimalistic_2022,\n\ttitle = {Minimalistic ice recrystallisation inhibitors based on phenylalanine},\n\tvolume = {58},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2022/cc/d2cc02531k},\n\tdoi = {10.1039/D2CC02531K},\n\tlanguage = {en},\n\tnumber = {55},\n\turldate = {2022-09-07},\n\tjournal = {Chemical Communications},\n\tauthor = {T. Warren, Matthew and Galpin, Iain and Hasan, Muhammad and A. Hindmarsh, Steven and D. Padrnos, John and Edwards-Gayle, Charlotte and T. Mathers, Robert and J. Adams, Dave and C. Sosso, Gabriele and I. Gibson, Matthew},\n\tyear = {2022},\n\tnote = {Publisher: Royal Society of Chemistry},\n\tpages = {7658--7661},\n}\n\n
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\n \n\n \n \n \n \n \n \n Ice Recrystallization Inhibition by Amino Acids: The Curious Case of Alpha- and Beta-Alanine.\n \n \n \n \n\n\n \n Warren, M. T.; Galpin, I.; Bachtiger, F.; Gibson, M. I.; and Sosso, G. C.\n\n\n \n\n\n\n The Journal of Physical Chemistry Letters, 13(9): 2237–2244. March 2022.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"IcePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{warren_ice_2022,\n\ttitle = {Ice {Recrystallization} {Inhibition} by {Amino} {Acids}: {The} {Curious} {Case} of {Alpha}- and {Beta}-{Alanine}},\n\tvolume = {13},\n\tshorttitle = {Ice {Recrystallization} {Inhibition} by {Amino} {Acids}},\n\turl = {https://doi.org/10.1021/acs.jpclett.1c04080},\n\tdoi = {10.1021/acs.jpclett.1c04080},\n\tabstract = {Extremophiles produce macromolecules which inhibit ice recrystallization, but there is increasing interest in discovering and developing small molecules that can modulate ice growth. Realizing their potential requires an understanding of how these molecules function at the atomistic level. Here, we report the discovery that the amino acid l-α-alanine demonstrates ice recrystallization inhibition (IRI) activity, functioning at 100 mM (∼10 mg/mL). We combined experimental assays with molecular simulations to investigate this IRI agent, drawing comparison to β-alanine, an isomer of l-α-alanine which displays no IRI activity. We found that the difference in the IRI activity of these molecules does not originate from their ice binding affinity, but from their capacity to (not) become overgrown, dictated by the degree of structural (in)compatibility within the growing ice lattice. These findings shed new light on the microscopic mechanisms of small molecule cryoprotectants, particularly in terms of their molecular structure and overgrowth by ice.},\n\tnumber = {9},\n\turldate = {2022-05-10},\n\tjournal = {The Journal of Physical Chemistry Letters},\n\tauthor = {Warren, Matthew T. and Galpin, Iain and Bachtiger, Fabienne and Gibson, Matthew I. and Sosso, Gabriele C.},\n\tmonth = mar,\n\tyear = {2022},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {2237--2244},\n}\n\n
\n
\n\n\n
\n Extremophiles produce macromolecules which inhibit ice recrystallization, but there is increasing interest in discovering and developing small molecules that can modulate ice growth. Realizing their potential requires an understanding of how these molecules function at the atomistic level. Here, we report the discovery that the amino acid l-α-alanine demonstrates ice recrystallization inhibition (IRI) activity, functioning at 100 mM (∼10 mg/mL). We combined experimental assays with molecular simulations to investigate this IRI agent, drawing comparison to β-alanine, an isomer of l-α-alanine which displays no IRI activity. We found that the difference in the IRI activity of these molecules does not originate from their ice binding affinity, but from their capacity to (not) become overgrown, dictated by the degree of structural (in)compatibility within the growing ice lattice. These findings shed new light on the microscopic mechanisms of small molecule cryoprotectants, particularly in terms of their molecular structure and overgrowth by ice.\n
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\n \n\n \n \n \n \n \n \n Lipid bilayers as potential ice nucleating agents.\n \n \n \n \n\n\n \n Miles, C. M.; Hsu, P.; Dixon, A. M.; Khalid, S.; and Sosso, G. C.\n\n\n \n\n\n\n Physical Chemistry Chemical Physics, 24(11): 6476–6491. March 2022.\n Publisher: The Royal Society of Chemistry\n\n\n\n
\n\n\n\n \n \n \"LipidPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{miles_lipid_2022,\n\ttitle = {Lipid bilayers as potential ice nucleating agents},\n\tvolume = {24},\n\tissn = {1463-9084},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2022/cp/d1cp05465a},\n\tdoi = {10.1039/D1CP05465A},\n\tabstract = {Cellular damage is a key issue in the context of cryopreservation. Much of this damage is believed to be caused by extracellular ice formation at temperatures well above the homogeneous freezing point of pure water. Hence the question: what initiates ice nucleation during cryopreservation? In this paper, we assess whether cellular membranes could be responsible for facilitating the ice nucleation process, and what characteristics would make them good or bad ice nucleating agents. By means of molecular dynamics simulations, we investigate a number of phospholipids and lipopolysaccharide bilayers at the interface with supercooled liquid water. While these systems certainly appear to act as ice nucleating agents, it is likely that other impurities might also play a role in initiating extracellular ice nucleation. Furthermore, we elucidate the factors which affect a bilayer's ability to act as an ice nucleating agent; these are complex, with specific reference to both chemical and structural factors. These findings represent a first attempt to pinpoint the origin of extracellular ice nucleation, with important implications for the cryopreservation process.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2022-05-10},\n\tjournal = {Physical Chemistry Chemical Physics},\n\tauthor = {Miles, Christopher M. and Hsu, Pin-Chia and Dixon, Ann M. and Khalid, Syma and Sosso, Gabriele C.},\n\tmonth = mar,\n\tyear = {2022},\n\tnote = {Publisher: The Royal Society of Chemistry},\n\tpages = {6476--6491},\n}\n\n
\n
\n\n\n
\n Cellular damage is a key issue in the context of cryopreservation. Much of this damage is believed to be caused by extracellular ice formation at temperatures well above the homogeneous freezing point of pure water. Hence the question: what initiates ice nucleation during cryopreservation? In this paper, we assess whether cellular membranes could be responsible for facilitating the ice nucleation process, and what characteristics would make them good or bad ice nucleating agents. By means of molecular dynamics simulations, we investigate a number of phospholipids and lipopolysaccharide bilayers at the interface with supercooled liquid water. While these systems certainly appear to act as ice nucleating agents, it is likely that other impurities might also play a role in initiating extracellular ice nucleation. Furthermore, we elucidate the factors which affect a bilayer's ability to act as an ice nucleating agent; these are complex, with specific reference to both chemical and structural factors. These findings represent a first attempt to pinpoint the origin of extracellular ice nucleation, with important implications for the cryopreservation process.\n
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\n  \n 2021\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n \n Recovering local structure information from high-pressure total scattering experiments.\n \n \n \n \n\n\n \n Herlihy, A.; Geddes, H. S.; Sosso, G. C.; Bull, C. L.; Ridley, C. J.; Goodwin, A. L.; Senn, M. S.; and Funnell, N. P.\n\n\n \n\n\n\n Journal of Applied Crystallography, 54(6): 1546–1554. December 2021.\n \n\n\n\n
\n\n\n\n \n \n \"RecoveringPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{herlihy_recovering_2021,\n\ttitle = {Recovering local structure information from high-pressure total scattering experiments},\n\tvolume = {54},\n\tissn = {1600-5767},\n\turl = {https://scripts.iucr.org/cgi-bin/paper?S1600576721009420},\n\tdoi = {10.1107/S1600576721009420},\n\tabstract = {High pressure is a powerful thermodynamic tool for exploring the structure and the phase behaviour of the crystalline state, and is now widely used in conventional crystallographic measurements. High-pressure local structure measurements using neutron diffraction have, thus far, been limited by the presence of a strongly scattering, perdeuterated, pressure-transmitting medium (PTM), the signal from which contaminates the resulting pair distribution functions (PDFs). Here, a method is reported for subtracting the pairwise correlations of the commonly used 4:1 methanol:ethanol PTM from neutron PDFs obtained under hydrostatic compression. The method applies a molecular-dynamics-informed empirical correction and a non-negative matrix factorization algorithm to recover the PDF of the pure sample. Proof of principle is demonstrated, producing corrected high-pressure PDFs of simple crystalline materials, Ni and MgO, and benchmarking these against simulated data from the average structure. Finally, the first local structure determination of α-quartz under hydrostatic pressure is presented, extracting compression behaviour of the real-space structure.},\n\tlanguage = {en},\n\tnumber = {6},\n\turldate = {2022-01-05},\n\tjournal = {Journal of Applied Crystallography},\n\tauthor = {Herlihy, Anna and Geddes, Harry S. and Sosso, Gabriele C. and Bull, Craig L. and Ridley, Christopher J. and Goodwin, Andrew L. and Senn, Mark S. and Funnell, Nicholas P.},\n\tmonth = dec,\n\tyear = {2021},\n\tpages = {1546--1554},\n}\n\n
\n
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\n High pressure is a powerful thermodynamic tool for exploring the structure and the phase behaviour of the crystalline state, and is now widely used in conventional crystallographic measurements. High-pressure local structure measurements using neutron diffraction have, thus far, been limited by the presence of a strongly scattering, perdeuterated, pressure-transmitting medium (PTM), the signal from which contaminates the resulting pair distribution functions (PDFs). Here, a method is reported for subtracting the pairwise correlations of the commonly used 4:1 methanol:ethanol PTM from neutron PDFs obtained under hydrostatic compression. The method applies a molecular-dynamics-informed empirical correction and a non-negative matrix factorization algorithm to recover the PDF of the pure sample. Proof of principle is demonstrated, producing corrected high-pressure PDFs of simple crystalline materials, Ni and MgO, and benchmarking these against simulated data from the average structure. Finally, the first local structure determination of α-quartz under hydrostatic pressure is presented, extracting compression behaviour of the real-space structure.\n
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\n \n\n \n \n \n \n \n \n The seven deadly sins: When computing crystal nucleation rates, the devil is in the details.\n \n \n \n \n\n\n \n Blow, K. E.; Quigley, D.; and Sosso, G. C.\n\n\n \n\n\n\n The Journal of Chemical Physics, 155(4): 040901. July 2021.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{blow_seven_2021,\n\ttitle = {The seven deadly sins: {When} computing crystal nucleation rates, the devil is in the details},\n\tvolume = {155},\n\tissn = {0021-9606, 1089-7690},\n\tshorttitle = {The seven deadly sins},\n\turl = {https://aip.scitation.org/doi/10.1063/5.0055248},\n\tdoi = {10.1063/5.0055248},\n\tabstract = {The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model—let alone to actually understand—be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavor almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects, such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2021-09-10},\n\tjournal = {The Journal of Chemical Physics},\n\tauthor = {Blow, Katarina E. and Quigley, David and Sosso, Gabriele C.},\n\tmonth = jul,\n\tyear = {2021},\n\tpages = {040901},\n}\n\n
\n
\n\n\n
\n The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model—let alone to actually understand—be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavor almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects, such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n A minimalistic cyclic ice-binding peptide from phage display.\n \n \n \n \n\n\n \n Stevens, C. A.; Bachtiger, F.; Kong, X.; Abriata, L. A.; Sosso, G. C.; Gibson, M. I.; and Klok, H.\n\n\n \n\n\n\n Nature Communications, 12(1): 2675. May 2021.\n Bandiera_abtest: a Cc_license_type: cc_by Cg_type: Nature Research Journals Number: 1 Primary_atype: Research Publisher: Nature Publishing Group Subject_term: Biopolymers;Peptides Subject_term_id: biopolymers;peptides\n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{stevens_minimalistic_2021,\n\ttitle = {A minimalistic cyclic ice-binding peptide from phage display},\n\tvolume = {12},\n\tcopyright = {2021 The Author(s)},\n\tissn = {2041-1723},\n\turl = {https://www.nature.com/articles/s41467-021-22883-w},\n\tdoi = {10.1038/s41467-021-22883-w},\n\tabstract = {Developing molecules that emulate the properties of naturally occurring ice-binding proteins (IBPs) is a daunting challenge. Rather than relying on the (limited) existing structure–property relationships that have been established for IBPs, here we report the use of phage display for the identification of short peptide mimics of IBPs. To this end, an ice-affinity selection protocol is developed, which enables the selection of a cyclic ice-binding peptide containing just 14 amino acids. Mutational analysis identifies three residues, Asp8, Thr10 and Thr14, which are found to be essential for ice binding. Molecular dynamics simulations reveal that the side chain of Thr10 hydrophobically binds to ice revealing a potential mechanism. To demonstrate the biotechnological potential of this peptide, it is expressed as a fusion (‘Ice-Tag’) with mCherry and used to purify proteins directly from cell lysate.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2021-06-22},\n\tjournal = {Nature Communications},\n\tauthor = {Stevens, Corey A. and Bachtiger, Fabienne and Kong, Xu-Dong and Abriata, Luciano A. and Sosso, Gabriele C. and Gibson, Matthew I. and Klok, Harm-Anton},\n\tmonth = may,\n\tyear = {2021},\n\tnote = {Bandiera\\_abtest: a\nCc\\_license\\_type: cc\\_by\nCg\\_type: Nature Research Journals\nNumber: 1\nPrimary\\_atype: Research\nPublisher: Nature Publishing Group\nSubject\\_term: Biopolymers;Peptides\nSubject\\_term\\_id: biopolymers;peptides},\n\tpages = {2675},\n}\n\n
\n
\n\n\n
\n Developing molecules that emulate the properties of naturally occurring ice-binding proteins (IBPs) is a daunting challenge. Rather than relying on the (limited) existing structure–property relationships that have been established for IBPs, here we report the use of phage display for the identification of short peptide mimics of IBPs. To this end, an ice-affinity selection protocol is developed, which enables the selection of a cyclic ice-binding peptide containing just 14 amino acids. Mutational analysis identifies three residues, Asp8, Thr10 and Thr14, which are found to be essential for ice binding. Molecular dynamics simulations reveal that the side chain of Thr10 hydrophobically binds to ice revealing a potential mechanism. To demonstrate the biotechnological potential of this peptide, it is expressed as a fusion (‘Ice-Tag’) with mCherry and used to purify proteins directly from cell lysate.\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Modelling the interactions and diffusion of NO in amorphous SiO2.\n \n \n \n \n\n\n \n Mistry, M. V.; Cottom, J.; Patel, K.; Shluger, A. L.; Sosso, G. C.; and Pobegen, G.\n\n\n \n\n\n\n Modelling and Simulation in Materials Science and Engineering, 29(3): 035008. March 2021.\n Publisher: IOP Publishing\n\n\n\n
\n\n\n\n \n \n \"ModellingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{mistry_modelling_2021,\n\ttitle = {Modelling the interactions and diffusion of {NO} in amorphous {SiO2}},\n\tvolume = {29},\n\tissn = {0965-0393},\n\turl = {https://doi.org/10.1088/1361-651x/abdc69},\n\tdoi = {10.1088/1361-651X/abdc69},\n\tabstract = {Nitric oxide (NO) is often used for the passivation of SiC/SiO2 metal oxide semiconductor (MOS) devices. Although it is established experimentally, using XPS, EELS, and SIMS measurements, that the 4H-SiC/SiO2 interface is extensively nitridated, the mechanisms of NO incorporation and diffusion in amorphous (a)-SiO2 films are still poorly understood. We used density functional theory (DFT) to simulate the incorporation and diffusion of NO through a-SiO2 and correlate local steric environment in amorphous network to interstitial NO (NO i ) incorporation energy and migration barriers. Shapes and volumes of structural cages in amorphous structures are characterised using a methodology based on the Voronoi S-network. Using an efficient sampling technique we identify the energy minima and transition states for neutral and negatively charged NO i molecules. Neutral NO i interacts with the amorphous network only weakly with the smallest incorporation energies in bigger cages. On the other hand binds at the network sites with wide O–Si–O bond angles, which also serve as the intrinsic precursor sites for electron trapping.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2021-05-12},\n\tjournal = {Modelling and Simulation in Materials Science and Engineering},\n\tauthor = {Mistry, M. V. and Cottom, J. and Patel, K. and Shluger, A. L. and Sosso, G. C. and Pobegen, G.},\n\tmonth = mar,\n\tyear = {2021},\n\tnote = {Publisher: IOP Publishing},\n\tpages = {035008},\n}\n\n
\n
\n\n\n
\n Nitric oxide (NO) is often used for the passivation of SiC/SiO2 metal oxide semiconductor (MOS) devices. Although it is established experimentally, using XPS, EELS, and SIMS measurements, that the 4H-SiC/SiO2 interface is extensively nitridated, the mechanisms of NO incorporation and diffusion in amorphous (a)-SiO2 films are still poorly understood. We used density functional theory (DFT) to simulate the incorporation and diffusion of NO through a-SiO2 and correlate local steric environment in amorphous network to interstitial NO (NO i ) incorporation energy and migration barriers. Shapes and volumes of structural cages in amorphous structures are characterised using a methodology based on the Voronoi S-network. Using an efficient sampling technique we identify the energy minima and transition states for neutral and negatively charged NO i molecules. Neutral NO i interacts with the amorphous network only weakly with the smallest incorporation energies in bigger cages. On the other hand binds at the network sites with wide O–Si–O bond angles, which also serve as the intrinsic precursor sites for electron trapping.\n
\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Microscopic Kinetics Pathway of Salt Crystallization in Graphene Nanocapillaries.\n \n \n \n \n\n\n \n Wang, L.; Chen, J.; Cox, S.; Liu, L.; Sosso, G.; Li, N.; Gao, P.; Michaelides, A.; Wang, E.; and Bai, X.\n\n\n \n\n\n\n Physical Review Letters, 126(13): 136001. March 2021.\n Publisher: American Physical Society\n\n\n\n
\n\n\n\n \n \n \"MicroscopicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{wang_microscopic_2021,\n\ttitle = {Microscopic {Kinetics} {Pathway} of {Salt} {Crystallization} in {Graphene} {Nanocapillaries}},\n\tvolume = {126},\n\turl = {http://0.link.aps.org/doi/10.1103/PhysRevLett.126.136001},\n\tdoi = {10.1103/PhysRevLett.126.136001},\n\tabstract = {The fundamental understanding of crystallization, in terms of microscopic kinetic and thermodynamic details, remains a key challenge in the physical sciences. Here, by using in situ graphene liquid cell transmission electron microscopy, we reveal the atomistic mechanism of NaCl crystallization from solutions confined within graphene cells. We find that rock salt NaCl forms with a peculiar hexagonal morphology. We also see the emergence of a transitory graphitelike phase, which may act as an intermediate in a two-step pathway. With the aid of density functional theory calculations, we propose that these observations result from a delicate balance between the substrate-solute interaction and thermodynamics under confinement. Our results highlight the impact of confinement on both the kinetics and thermodynamics of crystallization, offering new insights into heterogeneous crystallization theory and a potential avenue for materials design.},\n\tnumber = {13},\n\turldate = {2021-04-07},\n\tjournal = {Physical Review Letters},\n\tauthor = {Wang, Lifen and Chen, Ji and Cox, Stephen J. and Liu, Lei and Sosso, Gabriele C. and Li, Ning and Gao, Peng and Michaelides, Angelos and Wang, Enge and Bai, Xuedong},\n\tmonth = mar,\n\tyear = {2021},\n\tnote = {Publisher: American Physical Society},\n\tpages = {136001},\n}\n\n
\n
\n\n\n
\n The fundamental understanding of crystallization, in terms of microscopic kinetic and thermodynamic details, remains a key challenge in the physical sciences. Here, by using in situ graphene liquid cell transmission electron microscopy, we reveal the atomistic mechanism of NaCl crystallization from solutions confined within graphene cells. We find that rock salt NaCl forms with a peculiar hexagonal morphology. We also see the emergence of a transitory graphitelike phase, which may act as an intermediate in a two-step pathway. With the aid of density functional theory calculations, we propose that these observations result from a delicate balance between the substrate-solute interaction and thermodynamics under confinement. Our results highlight the impact of confinement on both the kinetics and thermodynamics of crystallization, offering new insights into heterogeneous crystallization theory and a potential avenue for materials design.\n
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\n \n\n \n \n \n \n \n \n The atomistic details of the ice recrystallisation inhibition activity of PVA.\n \n \n \n \n\n\n \n Bachtiger, F.; Congdon, T. R.; Stubbs, C.; Gibson, M. I.; and Sosso, G. C.\n\n\n \n\n\n\n Nature Communications, 12(1): 1323. February 2021.\n Number: 1 Publisher: Nature Publishing Group\n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{bachtiger_atomistic_2021,\n\ttitle = {The atomistic details of the ice recrystallisation inhibition activity of {PVA}},\n\tvolume = {12},\n\tcopyright = {2021 The Author(s)},\n\tissn = {2041-1723},\n\turl = {https://www.nature.com/articles/s41467-021-21717-z},\n\tdoi = {10.1038/s41467-021-21717-z},\n\tabstract = {Understanding the ice recrystallisation inhibition (IRI) activity of antifreeze biomimetics is crucial to the development of the next generation of cryoprotectants. In this work, we bring together molecular dynamics simulations and quantitative experimental measurements to unravel the microscopic origins of the IRI activity of poly(vinyl)alcohol (PVA)—the most potent of biomimetic IRI agents. Contrary to the emerging consensus, we find that PVA does not require a “lattice matching” to ice in order to display IRI activity: instead, it is the effective volume of PVA and its contact area with the ice surface which dictates its IRI strength. We also find that entropic contributions may play a role in the ice-PVA interaction and we demonstrate that small block co-polymers (up to now thought to be IRI-inactive) might display significant IRI potential. This work clarifies the atomistic details of the IRI activity of PVA and provides novel guidelines for the rational design of cryoprotectants.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2021-04-07},\n\tjournal = {Nature Communications},\n\tauthor = {Bachtiger, Fabienne and Congdon, Thomas R. and Stubbs, Christopher and Gibson, Matthew I. and Sosso, Gabriele C.},\n\tmonth = feb,\n\tyear = {2021},\n\tnote = {Number: 1\nPublisher: Nature Publishing Group},\n\tpages = {1323},\n}\n\n
\n
\n\n\n
\n Understanding the ice recrystallisation inhibition (IRI) activity of antifreeze biomimetics is crucial to the development of the next generation of cryoprotectants. In this work, we bring together molecular dynamics simulations and quantitative experimental measurements to unravel the microscopic origins of the IRI activity of poly(vinyl)alcohol (PVA)—the most potent of biomimetic IRI agents. Contrary to the emerging consensus, we find that PVA does not require a “lattice matching” to ice in order to display IRI activity: instead, it is the effective volume of PVA and its contact area with the ice surface which dictates its IRI strength. We also find that entropic contributions may play a role in the ice-PVA interaction and we demonstrate that small block co-polymers (up to now thought to be IRI-inactive) might display significant IRI potential. This work clarifies the atomistic details of the IRI activity of PVA and provides novel guidelines for the rational design of cryoprotectants.\n
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\n
\n  \n 2020\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n \n Less may be more: an informed reflection on molecular descriptors for drug design and discovery.\n \n \n \n \n\n\n \n Barnard, T.; Hagan, H.; Tseng, S.; and Sosso, G. C.\n\n\n \n\n\n\n Molecular Systems Design & Engineering, 5(1): 317–329. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"LessPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{barnard_less_2020,\n\ttitle = {Less may be more: an informed reflection on molecular descriptors for drug design and discovery},\n\tvolume = {5},\n\tissn = {2058-9689},\n\tshorttitle = {Less may be more},\n\turl = {http://xlink.rsc.org/?DOI=C9ME00109C},\n\tdoi = {10.1039/C9ME00109C},\n\tabstract = {The phenomenal advances of machine learning in the context of drug design have led to the development of a plethora of molecular descriptors. And yet, there might be value in using just a handful of them – inspired by our physical intuition.\n          , \n            \n              The phenomenal advances of machine learning in the context of drug design and discovery have led to the development of a plethora of molecular descriptors. In fact, many of these “standard” descriptors are now readily available\n              via\n              open source, easy-to-use computational tools. As a result, it is not uncommon to take advantage of large numbers – up to thousands in some cases – of these descriptors to predict the functional properties of drug-like molecules. This “strength in numbers” approach does usually provide excellent flexibility – and thus, good numerical accuracy – to the machine learning framework of choice; however, it suffers from a lack of transparency, in that it becomes very challenging to pinpoint the – usually, few – descriptors that are playing a key role in determining the functional properties of a given molecule. In this work, we show that just a handful of well-tailored molecular descriptors may often be capable to predict the functional properties of drug-like molecules with an accuracy comparable to that obtained by using hundreds of standard descriptors. In particular, we apply feature selection and genetic algorithms to in-house descriptors we have developed building on junction trees and symmetry functions, respectively. We find that information from as few as 10–20 molecular fragments is often enough to predict with decent accuracy even complex biomedical activities. In addition, we demonstrate that the usage of small sets of optimised symmetry functions may pave the way towards the prediction of the physical properties of drugs in their solid phases – a pivotal challenge for the pharmaceutical industry. Thus, this work brings strong arguments in support of the usage of small numbers of selected descriptors to discover the structure–function relation of drug-like molecules – as opposed to blindly leveraging the flexibility of the thousands of molecular descriptors currently available.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-04-24},\n\tjournal = {Molecular Systems Design \\& Engineering},\n\tauthor = {Barnard, Trent and Hagan, Harry and Tseng, Steven and Sosso, Gabriele C.},\n\tyear = {2020},\n\tpages = {317--329},\n}\n\n
\n
\n\n\n
\n The phenomenal advances of machine learning in the context of drug design have led to the development of a plethora of molecular descriptors. And yet, there might be value in using just a handful of them – inspired by our physical intuition. , The phenomenal advances of machine learning in the context of drug design and discovery have led to the development of a plethora of molecular descriptors. In fact, many of these “standard” descriptors are now readily available via open source, easy-to-use computational tools. As a result, it is not uncommon to take advantage of large numbers – up to thousands in some cases – of these descriptors to predict the functional properties of drug-like molecules. This “strength in numbers” approach does usually provide excellent flexibility – and thus, good numerical accuracy – to the machine learning framework of choice; however, it suffers from a lack of transparency, in that it becomes very challenging to pinpoint the – usually, few – descriptors that are playing a key role in determining the functional properties of a given molecule. In this work, we show that just a handful of well-tailored molecular descriptors may often be capable to predict the functional properties of drug-like molecules with an accuracy comparable to that obtained by using hundreds of standard descriptors. In particular, we apply feature selection and genetic algorithms to in-house descriptors we have developed building on junction trees and symmetry functions, respectively. We find that information from as few as 10–20 molecular fragments is often enough to predict with decent accuracy even complex biomedical activities. In addition, we demonstrate that the usage of small sets of optimised symmetry functions may pave the way towards the prediction of the physical properties of drugs in their solid phases – a pivotal challenge for the pharmaceutical industry. Thus, this work brings strong arguments in support of the usage of small numbers of selected descriptors to discover the structure–function relation of drug-like molecules – as opposed to blindly leveraging the flexibility of the thousands of molecular descriptors currently available.\n
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\n \n\n \n \n \n \n \n \n Unraveling Molecular Mechanism on Dilute Surfactant Solution Controlled Ice Recrystallization.\n \n \n \n \n\n\n \n Fan, Q.; Gao, Y.; Zhu, C.; Liu, J.; Zhao, L.; Mao, J.; Wu, S.; Xue, H.; Francisco, J. S.; Zeng, X. C.; and Wang, J.\n\n\n \n\n\n\n Langmuir, 36(7): 1691–1698. February 2020.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"UnravelingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{fan_unraveling_2020,\n\ttitle = {Unraveling {Molecular} {Mechanism} on {Dilute} {Surfactant} {Solution} {Controlled} {Ice} {Recrystallization}},\n\tvolume = {36},\n\tissn = {0743-7463},\n\turl = {https://doi.org/10.1021/acs.langmuir.9b03417},\n\tdoi = {10.1021/acs.langmuir.9b03417},\n\tabstract = {Ice recrystallization (IR) is ubiquitous, playing an important role in many areas of science, such as cryobiology, food science, and atmospheric physics. However, controllable ice recrystallization remains a challenging task largely due to an incomplete understanding of the physical mechanism associated with ice recrystallization. Herein, we explore the molecular mechanism underlying the controlling of ice recrystallization by using different small amphiphilic molecules (surfactants) through joint experimental measurements and molecular dynamics simulation. Our experiment shows that in nonionic/zwitterionic surfactant solutions, the mean size of the recrystallized ice grains increases monotonically with the concentration of surfactants, whereas in the ionic surfactant solutions, the mean size of the recrystallized ice grains tends to increase first and then decrease with increasing the concentration, yielding a peak typically at ∼5 μM. Further sequential ice affinity purification experiments and molecular dynamics simulations show that the surfactants actually do not bind to ice directly. Rather, the different spatial distributions of counter ions and molecular surfactants in the interfacial regions (ice–water interface and water–air interface) and bulk region can markedly affect the mean size of the recrystallized ice grain.},\n\tnumber = {7},\n\turldate = {2022-01-20},\n\tjournal = {Langmuir},\n\tauthor = {Fan, Qingrui and Gao, Yurui and Zhu, Chongqin and Liu, Jie and Zhao, Lishan and Mao, Junqiang and Wu, Shuwang and Xue, Han and Francisco, Joseph S. and Zeng, Xiao Cheng and Wang, Jianjun},\n\tmonth = feb,\n\tyear = {2020},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {1691--1698},\n}\n\n
\n
\n\n\n
\n Ice recrystallization (IR) is ubiquitous, playing an important role in many areas of science, such as cryobiology, food science, and atmospheric physics. However, controllable ice recrystallization remains a challenging task largely due to an incomplete understanding of the physical mechanism associated with ice recrystallization. Herein, we explore the molecular mechanism underlying the controlling of ice recrystallization by using different small amphiphilic molecules (surfactants) through joint experimental measurements and molecular dynamics simulation. Our experiment shows that in nonionic/zwitterionic surfactant solutions, the mean size of the recrystallized ice grains increases monotonically with the concentration of surfactants, whereas in the ionic surfactant solutions, the mean size of the recrystallized ice grains tends to increase first and then decrease with increasing the concentration, yielding a peak typically at ∼5 μM. Further sequential ice affinity purification experiments and molecular dynamics simulations show that the surfactants actually do not bind to ice directly. Rather, the different spatial distributions of counter ions and molecular surfactants in the interfacial regions (ice–water interface and water–air interface) and bulk region can markedly affect the mean size of the recrystallized ice grain.\n
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\n \n\n \n \n \n \n \n \n Insights into the Emerging Networks of Voids in Simulated Supercooled Water.\n \n \n \n \n\n\n \n Ansari, N.; Onat, B.; Sosso, G. C.; and Hassanali, A.\n\n\n \n\n\n\n The Journal of Physical Chemistry B, 124(11): 2180–2190. March 2020.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"InsightsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{ansari_insights_2020,\n\ttitle = {Insights into the {Emerging} {Networks} of {Voids} in {Simulated} {Supercooled} {Water}},\n\tvolume = {124},\n\tissn = {1520-6106},\n\turl = {https://doi.org/10.1021/acs.jpcb.9b10144},\n\tdoi = {10.1021/acs.jpcb.9b10144},\n\tabstract = {The structural evolution of supercooled liquid water as we approach the glass transition temperature continues to be an active area of research. Here, we use molecular dynamics simulations of TIP4P/ice water to study the changes in the connected regions of empty space within the liquid, which we investigate using the Voronoi-voids network. We observe two important features: supercooling enhances the fraction of nonspherical voids and different sizes of voids tend to cluster forming a percolating network. By examining order parameters such as the local structure index (LSI), tetrahedrality and topological defects, we show that water molecules near large void clusters tend to be slightly more tetrahedral than those near small voids, with a lower population of under- and overcoordinated defects. We show further that the distribution of closed rings of water molecules around small and large void clusters maintain a balance between 6 and 7 membered rings. Our results highlight the changes of the dual voids and water network as a structural hallmark of supercooling and provide insights into the molecular origins of cooperative effects underlying density fluctuations on the subnanometer and nanometer length scale. In addition, the percolation of the voids and the hydrogen bond network around the voids may serve as useful order parameters to investigate density fluctuations in supercooled water.},\n\tnumber = {11},\n\turldate = {2020-06-03},\n\tjournal = {The Journal of Physical Chemistry B},\n\tauthor = {Ansari, Narjes and Onat, Berk and Sosso, Gabriele C. and Hassanali, Ali},\n\tmonth = mar,\n\tyear = {2020},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {2180--2190},\n}\n\n
\n
\n\n\n
\n The structural evolution of supercooled liquid water as we approach the glass transition temperature continues to be an active area of research. Here, we use molecular dynamics simulations of TIP4P/ice water to study the changes in the connected regions of empty space within the liquid, which we investigate using the Voronoi-voids network. We observe two important features: supercooling enhances the fraction of nonspherical voids and different sizes of voids tend to cluster forming a percolating network. By examining order parameters such as the local structure index (LSI), tetrahedrality and topological defects, we show that water molecules near large void clusters tend to be slightly more tetrahedral than those near small voids, with a lower population of under- and overcoordinated defects. We show further that the distribution of closed rings of water molecules around small and large void clusters maintain a balance between 6 and 7 membered rings. Our results highlight the changes of the dual voids and water network as a structural hallmark of supercooling and provide insights into the molecular origins of cooperative effects underlying density fluctuations on the subnanometer and nanometer length scale. In addition, the percolation of the voids and the hydrogen bond network around the voids may serve as useful order parameters to investigate density fluctuations in supercooled water.\n
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\n \n\n \n \n \n \n \n \n Combining high-resolution scanning tunnelling microscopy and first-principles simulations to identify halogen bonding.\n \n \n \n \n\n\n \n Lawrence, J.; Sosso, G. C.; Đorđević, L.; Pinfold, H.; Bonifazi, D.; and Costantini, G.\n\n\n \n\n\n\n Nature Communications, 11(1): 2103. December 2020.\n \n\n\n\n
\n\n\n\n \n \n \"CombiningPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{lawrence_combining_2020,\n\ttitle = {Combining high-resolution scanning tunnelling microscopy and first-principles simulations to identify halogen bonding},\n\tvolume = {11},\n\tissn = {2041-1723},\n\turl = {http://www.nature.com/articles/s41467-020-15898-2},\n\tdoi = {10.1038/s41467-020-15898-2},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2020-05-05},\n\tjournal = {Nature Communications},\n\tauthor = {Lawrence, James and Sosso, Gabriele C. and Đorđević, Luka and Pinfold, Harry and Bonifazi, Davide and Costantini, Giovanni},\n\tmonth = dec,\n\tyear = {2020},\n\tpages = {2103},\n}\n\n
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\n \n\n \n \n \n \n \n \n Atomistic simulations of thermal conductivity in GeTe nanowires.\n \n \n \n \n\n\n \n Bosoni, E; Campi, D; Donadio, D; Sosso, G C; Behler, J; and Bernasconi, M\n\n\n \n\n\n\n Journal of Physics D: Applied Physics, 53(5): 054001. January 2020.\n \n\n\n\n
\n\n\n\n \n \n \"AtomisticPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{bosoni_atomistic_2020,\n\ttitle = {Atomistic simulations of thermal conductivity in {GeTe} nanowires},\n\tvolume = {53},\n\tissn = {0022-3727, 1361-6463},\n\turl = {https://iopscience.iop.org/article/10.1088/1361-6463/ab5478},\n\tdoi = {10.1088/1361-6463/ab5478},\n\tabstract = {The thermal conductivity of GeTe crystalline nanowires has been computed by means of non-equilibrium molecular dynamics simulations employing a machine learning interatomic potential. This material is of interest for application in phase change non-volatile memories. The resulting lattice thermal conductivity of an ultrathin nanowire (7.3 nm diameter) of 1.57 W m−1 K−1 is sizably lower than the corresponding bulk value of 3.15 W m−1 K−1 obtained within the same framework. The analysis of the phonon dispersion relations and lifetimes reveals that the lower thermal conductivity in the nanowire is mostly due to a reduction in the phonon group velocities. We further predict the presence of a minimum in the lattice thermal conductivity for thicker nanowires.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2019-11-21},\n\tjournal = {Journal of Physics D: Applied Physics},\n\tauthor = {Bosoni, E and Campi, D and Donadio, D and Sosso, G C and Behler, J and Bernasconi, M},\n\tmonth = jan,\n\tyear = {2020},\n\tpages = {054001},\n}\n\n
\n
\n\n\n
\n The thermal conductivity of GeTe crystalline nanowires has been computed by means of non-equilibrium molecular dynamics simulations employing a machine learning interatomic potential. This material is of interest for application in phase change non-volatile memories. The resulting lattice thermal conductivity of an ultrathin nanowire (7.3 nm diameter) of 1.57 W m−1 K−1 is sizably lower than the corresponding bulk value of 3.15 W m−1 K−1 obtained within the same framework. The analysis of the phonon dispersion relations and lifetimes reveals that the lower thermal conductivity in the nanowire is mostly due to a reduction in the phonon group velocities. We further predict the presence of a minimum in the lattice thermal conductivity for thicker nanowires.\n
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\n  \n 2019\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n \n Ice is born in low-mobility regions of supercooled liquid water.\n \n \n \n \n\n\n \n Fitzner, M.; Sosso, G. C.; Cox, S. J.; and Michaelides, A.\n\n\n \n\n\n\n Proceedings of the National Academy of Sciences, 116(6): 2009–2014. February 2019.\n Publisher: Proceedings of the National Academy of Sciences\n\n\n\n
\n\n\n\n \n \n \"IcePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{fitzner_ice_2019,\n\ttitle = {Ice is born in low-mobility regions of supercooled liquid water},\n\tvolume = {116},\n\turl = {https://www.pnas.org/doi/abs/10.1073/pnas.1817135116},\n\tdoi = {10.1073/pnas.1817135116},\n\tabstract = {When an ice crystal is born from liquid water, two key changes occur: (i) The molecules order and (ii) the mobility of the molecules drops as they adopt their lattice positions. Most research on ice nucleation (and crystallization in general) has focused on understanding the former with less attention paid to the latter. However, supercooled water exhibits fascinating and complex dynamical behavior, most notably dynamical heterogeneity (DH), a phenomenon where spatially separated domains of relatively mobile and immobile particles coexist. Strikingly, the microscopic connection between the DH of water and the nucleation of ice has yet to be unraveled directly at the molecular level. Here we tackle this issue via computer simulations which reveal that (i) ice nucleation occurs in low-mobility regions of the liquid, (ii) there is a dynamical incubation period in which the mobility of the molecules drops before any ice-like ordering, and (iii) ice-like clusters cause arrested dynamics in surrounding water molecules. With this we establish a clear connection between dynamics and nucleation. We anticipate that our findings will pave the way for the examination of the role of dynamical heterogeneities in heterogeneous and solution-based nucleation.},\n\tnumber = {6},\n\turldate = {2023-01-10},\n\tjournal = {Proceedings of the National Academy of Sciences},\n\tauthor = {Fitzner, Martin and Sosso, Gabriele C. and Cox, Stephen J. and Michaelides, Angelos},\n\tmonth = feb,\n\tyear = {2019},\n\tnote = {Publisher: Proceedings of the National Academy of Sciences},\n\tpages = {2009--2014},\n}\n\n
\n
\n\n\n
\n When an ice crystal is born from liquid water, two key changes occur: (i) The molecules order and (ii) the mobility of the molecules drops as they adopt their lattice positions. Most research on ice nucleation (and crystallization in general) has focused on understanding the former with less attention paid to the latter. However, supercooled water exhibits fascinating and complex dynamical behavior, most notably dynamical heterogeneity (DH), a phenomenon where spatially separated domains of relatively mobile and immobile particles coexist. Strikingly, the microscopic connection between the DH of water and the nucleation of ice has yet to be unraveled directly at the molecular level. Here we tackle this issue via computer simulations which reveal that (i) ice nucleation occurs in low-mobility regions of the liquid, (ii) there is a dynamical incubation period in which the mobility of the molecules drops before any ice-like ordering, and (iii) ice-like clusters cause arrested dynamics in surrounding water molecules. With this we establish a clear connection between dynamics and nucleation. We anticipate that our findings will pave the way for the examination of the role of dynamical heterogeneities in heterogeneous and solution-based nucleation.\n
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\n \n\n \n \n \n \n \n \n Enhancement of Macromolecular Ice Recrystallization Inhibition Activity by Exploiting Depletion Forces.\n \n \n \n \n\n\n \n Ishibe, T.; Congdon, T.; Stubbs, C.; Hasan, M.; Sosso, G. C.; and Gibson, M. I.\n\n\n \n\n\n\n ACS Macro Letters, 8(8): 1063–1067. August 2019.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"EnhancementPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{ishibe_enhancement_2019,\n\ttitle = {Enhancement of {Macromolecular} {Ice} {Recrystallization} {Inhibition} {Activity} by {Exploiting} {Depletion} {Forces}},\n\tvolume = {8},\n\turl = {https://doi.org/10.1021/acsmacrolett.9b00386},\n\tdoi = {10.1021/acsmacrolett.9b00386},\n\tabstract = {Antifreeze (glyco) proteins (AF(G)Ps) are potent inhibitors of ice recrystallization and may have biotechnological applications. The most potent AF(G)Ps function at concentrations a thousand times lower than synthetic mimics such as poly(vinyl alcohol), PVA. Here, we demonstrate that PVA’s ice recrystallization activity can be rescued at concentrations where it does not normally function, by the addition of noninteracting polymeric depletants, due to PVA forming colloids in the concentrated saline environment present between ice crystals. These depletants shift the equilibrium toward ice binding and, hence, enable PVA to inhibit ice growth at lower concentrations. Using theory and experiments, we show this effect requires polymeric depletants, not small molecules, to enhance activity. These results increase our understanding of how to design new ice growth inhibitors, but also offer opportunities to enhance activity by exploiting depletion forces, without re-engineering ice-binding materials. It also shows that when screening for IRI activity that polymer contaminants in buffers may give rise to false positive results.},\n\tnumber = {8},\n\turldate = {2023-01-10},\n\tjournal = {ACS Macro Letters},\n\tauthor = {Ishibe, Toru and Congdon, Thomas and Stubbs, Christopher and Hasan, Muhammad and Sosso, Gabriele C. and Gibson, Matthew I.},\n\tmonth = aug,\n\tyear = {2019},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {1063--1067},\n}\n\n
\n
\n\n\n
\n Antifreeze (glyco) proteins (AF(G)Ps) are potent inhibitors of ice recrystallization and may have biotechnological applications. The most potent AF(G)Ps function at concentrations a thousand times lower than synthetic mimics such as poly(vinyl alcohol), PVA. Here, we demonstrate that PVA’s ice recrystallization activity can be rescued at concentrations where it does not normally function, by the addition of noninteracting polymeric depletants, due to PVA forming colloids in the concentrated saline environment present between ice crystals. These depletants shift the equilibrium toward ice binding and, hence, enable PVA to inhibit ice growth at lower concentrations. Using theory and experiments, we show this effect requires polymeric depletants, not small molecules, to enhance activity. These results increase our understanding of how to design new ice growth inhibitors, but also offer opportunities to enhance activity by exploiting depletion forces, without re-engineering ice-binding materials. It also shows that when screening for IRI activity that polymer contaminants in buffers may give rise to false positive results.\n
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\n \n\n \n \n \n \n \n \n Priming effects in the crystallization of the phase change compound GeTe from atomistic simulations.\n \n \n \n \n\n\n \n Gabardi, S.; Sosso, G. G.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Faraday Discussions, 213: 287–301. 2019.\n \n\n\n\n
\n\n\n\n \n \n \"PrimingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{gabardi_priming_2019,\n\ttitle = {Priming effects in the crystallization of the phase change compound {GeTe} from atomistic simulations},\n\tvolume = {213},\n\tissn = {1359-6640, 1364-5498},\n\turl = {http://xlink.rsc.org/?DOI=C8FD00101D},\n\tdoi = {10.1039/C8FD00101D},\n\tabstract = {Molecular dynamics simulations provide insights into the priming effects in the crystallization of the phase change compound GeTe.\n          , \n            \n              Strategies to reduce the incubation time for crystal nucleation and thus the stochasticity of the set process are of relevance for the operation of phase change memories in ultra-scaled geometries. With these premises, in this work we investigate the crystallization kinetics of the phase change compound GeTe. We have performed large scale molecular dynamics simulations using an interatomic potential, generated previously from a neural network fitting of a database of\n              ab initio\n              energies. We have addressed the crystallization of models of amorphous GeTe annealed at different temperatures above the glass transition. The results on the distribution of subcritical nuclei and on the crystal growth velocity of postcritical ones are compared with our previous simulations of the supercooled liquid quenched from the melt. We find that a large population of subcritical nuclei can form at the lower temperatures where the nucleation rate is large. This population partially survives upon fast annealing, which leads to a dramatic reduction of the incubation time at high temperatures where the crystal growth velocity is maximal. This priming effect could be exploited to enhance the speed of the set process in phase change memories.},\n\tlanguage = {en},\n\turldate = {2020-02-28},\n\tjournal = {Faraday Discussions},\n\tauthor = {Gabardi, Silvia and Sosso, Gabriele G. and Behler, Joerg and Bernasconi, Marco},\n\tyear = {2019},\n\tpages = {287--301},\n}\n\n
\n
\n\n\n
\n Molecular dynamics simulations provide insights into the priming effects in the crystallization of the phase change compound GeTe. , Strategies to reduce the incubation time for crystal nucleation and thus the stochasticity of the set process are of relevance for the operation of phase change memories in ultra-scaled geometries. With these premises, in this work we investigate the crystallization kinetics of the phase change compound GeTe. We have performed large scale molecular dynamics simulations using an interatomic potential, generated previously from a neural network fitting of a database of ab initio energies. We have addressed the crystallization of models of amorphous GeTe annealed at different temperatures above the glass transition. The results on the distribution of subcritical nuclei and on the crystal growth velocity of postcritical ones are compared with our previous simulations of the supercooled liquid quenched from the melt. We find that a large population of subcritical nuclei can form at the lower temperatures where the nucleation rate is large. This population partially survives upon fast annealing, which leads to a dramatic reduction of the incubation time at high temperatures where the crystal growth velocity is maximal. This priming effect could be exploited to enhance the speed of the set process in phase change memories.\n
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\n \n\n \n \n \n \n \n \n Harnessing machine learning potentials to understand the functional properties of phase-change materials.\n \n \n \n \n\n\n \n Sosso, G.; and Bernasconi, M.\n\n\n \n\n\n\n MRS Bulletin, 44(09): 705–709. September 2019.\n \n\n\n\n
\n\n\n\n \n \n \"HarnessingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_harnessing_2019,\n\ttitle = {Harnessing machine learning potentials to understand the functional properties of phase-change materials},\n\tvolume = {44},\n\tissn = {0883-7694, 1938-1425},\n\turl = {https://www.cambridge.org/core/product/identifier/S0883769419002021/type/journal_article},\n\tdoi = {10.1557/mrs.2019.202},\n\tlanguage = {en},\n\tnumber = {09},\n\turldate = {2019-11-01},\n\tjournal = {MRS Bulletin},\n\tauthor = {Sosso, G.C. and Bernasconi, M.},\n\tmonth = sep,\n\tyear = {2019},\n\tpages = {705--709},\n}\n\n
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\n \n\n \n \n \n \n \n \n Promoting transparency and reproducibility in enhanced molecular simulations.\n \n \n \n \n\n\n \n Bonomi, M.; Bussi, G.; Camilloni, C.; Tribello, G. A.; Banáš, P.; Barducci, A.; Bernetti, M.; Bolhuis, P. G.; Bottaro, S.; Branduardi, D.; Capelli, R.; Carloni, P.; Ceriotti, M.; Cesari, A.; Chen, H.; Chen, W.; Colizzi, F.; De, S.; De La Pierre, M.; Donadio, D.; Drobot, V.; Ensing, B.; Ferguson, A. L.; Filizola, M.; Fraser, J. S.; Fu, H.; Gasparotto, P.; Gervasio, F. L.; Giberti, F.; Gil-Ley, A.; Giorgino, T.; Heller, G. T.; Hocky, G. M.; Iannuzzi, M.; Invernizzi, M.; Jelfs, K. E.; Jussupow, A.; Kirilin, E.; Laio, A.; Limongelli, V.; Lindorff-Larsen, K.; Löhr, T.; Marinelli, F.; Martin-Samos, L.; Masetti, M.; Meyer, R.; Michaelides, A.; Molteni, C.; Morishita, T.; Nava, M.; Paissoni, C.; Papaleo, E.; Parrinello, M.; Pfaendtner, J.; Piaggi, P.; Piccini, G.; Pietropaolo, A.; Pietrucci, F.; Pipolo, S.; Provasi, D.; Quigley, D.; Raiteri, P.; Raniolo, S.; Rydzewski, J.; Salvalaglio, M.; Sosso, G. C.; Spiwok, V.; Šponer, J.; Swenson, D. W. H.; Tiwary, P.; Valsson, O.; Vendruscolo, M.; Voth, G. A.; White, A.; and The PLUMED consortium\n\n\n \n\n\n\n Nature Methods, 16(8): 670–673. August 2019.\n \n\n\n\n
\n\n\n\n \n \n \"PromotingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{bonomi_promoting_2019,\n\ttitle = {Promoting transparency and reproducibility in enhanced molecular simulations},\n\tvolume = {16},\n\tissn = {1548-7105},\n\turl = {https://doi.org/10.1038/s41592-019-0506-8},\n\tdoi = {10.1038/s41592-019-0506-8},\n\tabstract = {The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.},\n\tnumber = {8},\n\tjournal = {Nature Methods},\n\tauthor = {Bonomi, Massimiliano and Bussi, Giovanni and Camilloni, Carlo and Tribello, Gareth A. and Banáš, Pavel and Barducci, Alessandro and Bernetti, Mattia and Bolhuis, Peter G. and Bottaro, Sandro and Branduardi, Davide and Capelli, Riccardo and Carloni, Paolo and Ceriotti, Michele and Cesari, Andrea and Chen, Haochuan and Chen, Wei and Colizzi, Francesco and De, Sandip and De La Pierre, Marco and Donadio, Davide and Drobot, Viktor and Ensing, Bernd and Ferguson, Andrew L. and Filizola, Marta and Fraser, James S. and Fu, Haohao and Gasparotto, Piero and Gervasio, Francesco Luigi and Giberti, Federico and Gil-Ley, Alejandro and Giorgino, Toni and Heller, Gabriella T. and Hocky, Glen M. and Iannuzzi, Marcella and Invernizzi, Michele and Jelfs, Kim E. and Jussupow, Alexander and Kirilin, Evgeny and Laio, Alessandro and Limongelli, Vittorio and Lindorff-Larsen, Kresten and Löhr, Thomas and Marinelli, Fabrizio and Martin-Samos, Layla and Masetti, Matteo and Meyer, Ralf and Michaelides, Angelos and Molteni, Carla and Morishita, Tetsuya and Nava, Marco and Paissoni, Cristina and Papaleo, Elena and Parrinello, Michele and Pfaendtner, Jim and Piaggi, Pablo and Piccini, GiovanniMaria and Pietropaolo, Adriana and Pietrucci, Fabio and Pipolo, Silvio and Provasi, Davide and Quigley, David and Raiteri, Paolo and Raniolo, Stefano and Rydzewski, Jakub and Salvalaglio, Matteo and Sosso, Gabriele Cesare and Spiwok, Vojtěch and Šponer, Jiří and Swenson, David W. H. and Tiwary, Pratyush and Valsson, Omar and Vendruscolo, Michele and Voth, Gregory A. and White, Andrew and {The PLUMED consortium}},\n\tmonth = aug,\n\tyear = {2019},\n\tpages = {670--673},\n}\n\n
\n
\n\n\n
\n The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.\n
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\n  \n 2018\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n \n Unravelling the origins of ice nucleation on organic crystals.\n \n \n \n \n\n\n \n Sosso, G. C.; Whale, T. F.; Holden, M. A.; Pedevilla, P.; Murray, B. J.; and Michaelides, A.\n\n\n \n\n\n\n Chemical Science, 9(42): 8077–8088. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"UnravellingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_unravelling_2018,\n\ttitle = {Unravelling the origins of ice nucleation on organic crystals},\n\tvolume = {9},\n\tissn = {2041-6520, 2041-6539},\n\turl = {http://xlink.rsc.org/?DOI=C8SC02753F},\n\tdoi = {10.1039/C8SC02753F},\n\tlanguage = {en},\n\tnumber = {42},\n\turldate = {2019-01-25},\n\tjournal = {Chemical Science},\n\tauthor = {Sosso, Gabriele C. and Whale, Thomas F. and Holden, Mark A. and Pedevilla, Philipp and Murray, Benjamin J. and Michaelides, Angelos},\n\tyear = {2018},\n\tpages = {8077--8088},\n}\n\n
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\n \n\n \n \n \n \n \n \n High and low density patches in simulated liquid water.\n \n \n \n \n\n\n \n Ansari, N.; Dandekar, R.; Caravati, S.; Sosso, G.; and Hassanali, A.\n\n\n \n\n\n\n The Journal of Chemical Physics, 149(20): 204507. November 2018.\n \n\n\n\n
\n\n\n\n \n \n \"HighPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{ansari_high_2018,\n\ttitle = {High and low density patches in simulated liquid water},\n\tvolume = {149},\n\tissn = {0021-9606, 1089-7690},\n\turl = {http://aip.scitation.org/doi/10.1063/1.5053559},\n\tdoi = {10.1063/1.5053559},\n\tlanguage = {en},\n\tnumber = {20},\n\turldate = {2018-12-21},\n\tjournal = {The Journal of Chemical Physics},\n\tauthor = {Ansari, N. and Dandekar, R. and Caravati, S. and Sosso, G.C. and Hassanali, A.},\n\tmonth = nov,\n\tyear = {2018},\n\tpages = {204507},\n}\n\n
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\n \n\n \n \n \n \n \n \n Understanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials.\n \n \n \n \n\n\n \n Sosso, G. C.; Deringer, V. L.; Elliott, S. R.; and Csányi, G.\n\n\n \n\n\n\n Molecular Simulation, 44(11): 866–880. July 2018.\n \n\n\n\n
\n\n\n\n \n \n \"UnderstandingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_understanding_2018,\n\ttitle = {Understanding the thermal properties of amorphous solids using machine-learning-based interatomic potentials},\n\tvolume = {44},\n\tissn = {0892-7022, 1029-0435},\n\turl = {https://www.tandfonline.com/doi/full/10.1080/08927022.2018.1447107},\n\tdoi = {10.1080/08927022.2018.1447107},\n\tabstract = {Understanding the thermal properties of disordered systems is of fundamental importance for condensed matter physics - and for practical applications as well. While quantities such as the thermal conductivity are usually well characterised experimentally, their microscopic origin is often largely unknown - hence the pressing need for molecular simulations. However, the time and length scales involved with thermal transport phenomena are typically well beyond the reach of ab initio calculations. On the other hand, many amorphous materials are characterised by a complex structure, which prevents the construction of classical interatomic potentials. One way to get past this deadlock is to harness machine-learning (ML) algorithms to build interatomic potentials: these can be nearly as computationally efficient as classical force fields while retaining much of the accuracy of first-principles calculations. Here, we discuss neural network potentials (NNPs) and Gaussian approximation potentials (GAPs), two popular ML frameworks. We review the work that has been devoted to investigate, via NNPs, the thermal properties of phase-change materials, systems widely used in non-volatile memories. In addition, we present recent results on the vibrational properties of amorphous carbon, studied via GAPs. In light of these results, we argue that ML-based potentials are among the best options available to further our understanding of the vibrational and thermal properties of complex amorphous solids.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2018-11-21},\n\tjournal = {Molecular Simulation},\n\tauthor = {Sosso, Gabriele C. and Deringer, Volker L. and Elliott, Stephen R. and Csányi, Gábor},\n\tmonth = jul,\n\tyear = {2018},\n\tpages = {866--880},\n}\n\n
\n
\n\n\n
\n Understanding the thermal properties of disordered systems is of fundamental importance for condensed matter physics - and for practical applications as well. While quantities such as the thermal conductivity are usually well characterised experimentally, their microscopic origin is often largely unknown - hence the pressing need for molecular simulations. However, the time and length scales involved with thermal transport phenomena are typically well beyond the reach of ab initio calculations. On the other hand, many amorphous materials are characterised by a complex structure, which prevents the construction of classical interatomic potentials. One way to get past this deadlock is to harness machine-learning (ML) algorithms to build interatomic potentials: these can be nearly as computationally efficient as classical force fields while retaining much of the accuracy of first-principles calculations. Here, we discuss neural network potentials (NNPs) and Gaussian approximation potentials (GAPs), two popular ML frameworks. We review the work that has been devoted to investigate, via NNPs, the thermal properties of phase-change materials, systems widely used in non-volatile memories. In addition, we present recent results on the vibrational properties of amorphous carbon, studied via GAPs. In light of these results, we argue that ML-based potentials are among the best options available to further our understanding of the vibrational and thermal properties of complex amorphous solids.\n
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\n \n\n \n \n \n \n \n \n Heterogeneous seeded molecular dynamics as a tool to probe the ice nucleating ability of crystalline surfaces.\n \n \n \n \n\n\n \n Pedevilla, P.; Fitzner, M.; Sosso, G. C.; and Michaelides, A.\n\n\n \n\n\n\n The Journal of Chemical Physics, 149(7): 072327. June 2018.\n \n\n\n\n
\n\n\n\n \n \n \"HeterogeneousPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{pedevilla_heterogeneous_2018,\n\ttitle = {Heterogeneous seeded molecular dynamics as a tool to probe the ice nucleating ability of crystalline surfaces},\n\tvolume = {149},\n\tissn = {0021-9606},\n\turl = {https://aip.scitation.org/doi/10.1063/1.5029336},\n\tdoi = {10.1063/1.5029336},\n\tnumber = {7},\n\turldate = {2018-06-28},\n\tjournal = {The Journal of Chemical Physics},\n\tauthor = {Pedevilla, Philipp and Fitzner, Martin and Sosso, Gabriele C. and Michaelides, Angelos},\n\tmonth = jun,\n\tyear = {2018},\n\tpages = {072327},\n}\n\n
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\n
\n  \n 2017\n \n \n (7)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n On the Role of Nonspherical Cavities in Short Length-Scale Density Fluctuations in Water.\n \n \n \n \n\n\n \n Sosso, G. C.; Caravati, S.; Rotskoff, G.; Vaikuntanathan, S.; and Hassanali, A.\n\n\n \n\n\n\n The Journal of Physical Chemistry A, 121(1): 370–380. January 2017.\n \n\n\n\n
\n\n\n\n \n \n \"OnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_role_2017,\n\ttitle = {On the {Role} of {Nonspherical} {Cavities} in {Short} {Length}-{Scale} {Density} {Fluctuations} in {Water}},\n\tvolume = {121},\n\tissn = {1089-5639, 1520-5215},\n\turl = {https://pubs.acs.org/doi/10.1021/acs.jpca.6b11168},\n\tdoi = {10.1021/acs.jpca.6b11168},\n\tabstract = {Density fluctuations in liquid water are at the heart of numerous phenomena associated with hydrophobic effects such as protein folding and the interaction between biomolecules. One of the most fundamental processes in this regard is the solvation of hydrophobic solutes in water. The vast majority of theoretical and numerical studies examine density fluctuations at the short length scale focusing exclusively on spherical cavities. In this work, we use both first-principles and classical molecular dynamics simulations to demonstrate that density fluctuations in liquid water can deviate significantly from the canonical spherical shapes. We show that regions of empty space are frequently characterized by exotic, highly asymmetric shapes that can be quite delocalized over the hydrogen bond network. Interestingly, density fluctuations of these shapes are characterized by Gaussian statistics with larger fluctuations. An important consequence of this is that the work required to create non spherical cavities can be substantially smaller than that of spheres. This feature is also qualitatively captured by the Lum−Chandler−Weeks theory. The scaling behavior of the free energy as a function of the volume at short length scales is qualitatively different for the nonspherical entities. We also demonstrate that nonspherical density fluctuations are important for accommodating the hydrophobic amino acid alanine and are thus likely to have significant implications when it comes to solvating highly asymmetrical species such as alkanes, polymers, or biomolecules.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-01-10},\n\tjournal = {The Journal of Physical Chemistry A},\n\tauthor = {Sosso, Gabriele Cesare and Caravati, Sebastiano and Rotskoff, Grant and Vaikuntanathan, Suriyanarayan and Hassanali, Ali},\n\tmonth = jan,\n\tyear = {2017},\n\tpages = {370--380},\n}\n\n
\n
\n\n\n
\n Density fluctuations in liquid water are at the heart of numerous phenomena associated with hydrophobic effects such as protein folding and the interaction between biomolecules. One of the most fundamental processes in this regard is the solvation of hydrophobic solutes in water. The vast majority of theoretical and numerical studies examine density fluctuations at the short length scale focusing exclusively on spherical cavities. In this work, we use both first-principles and classical molecular dynamics simulations to demonstrate that density fluctuations in liquid water can deviate significantly from the canonical spherical shapes. We show that regions of empty space are frequently characterized by exotic, highly asymmetric shapes that can be quite delocalized over the hydrogen bond network. Interestingly, density fluctuations of these shapes are characterized by Gaussian statistics with larger fluctuations. An important consequence of this is that the work required to create non spherical cavities can be substantially smaller than that of spheres. This feature is also qualitatively captured by the Lum−Chandler−Weeks theory. The scaling behavior of the free energy as a function of the volume at short length scales is qualitatively different for the nonspherical entities. We also demonstrate that nonspherical density fluctuations are important for accommodating the hydrophobic amino acid alanine and are thus likely to have significant implications when it comes to solvating highly asymmetrical species such as alkanes, polymers, or biomolecules.\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Pre-critical fluctuations and what they disclose about heterogeneous crystal nucleation.\n \n \n \n \n\n\n \n Fitzner, M.; Sosso, G. C.; Pietrucci, F.; Pipolo, S.; and Michaelides, A.\n\n\n \n\n\n\n Nature Communications, 8(1): 2257. December 2017.\n \n\n\n\n
\n\n\n\n \n \n \"Pre-criticalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{fitzner_pre-critical_2017,\n\ttitle = {Pre-critical fluctuations and what they disclose about heterogeneous crystal nucleation},\n\tvolume = {8},\n\tcopyright = {2017 The Author(s)},\n\tissn = {2041-1723},\n\turl = {https://www.nature.com/articles/s41467-017-02300-x},\n\tdoi = {10.1038/s41467-017-02300-x},\n\tabstract = {Heterogeneous nucleation is a process that mediates the birth of many crystalline materials, but is not fully understood. Here, the authors show that the study of precritical cluster fluctuations paves new ways for the identification of polymorphism, polymorphic control and theoretical modeling.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2018-10-07},\n\tjournal = {Nature Communications},\n\tauthor = {Fitzner, Martin and Sosso, Gabriele C. and Pietrucci, Fabio and Pipolo, Silvio and Michaelides, Angelos},\n\tmonth = dec,\n\tyear = {2017},\n\tpages = {2257},\n}\n\n
\n
\n\n\n
\n Heterogeneous nucleation is a process that mediates the birth of many crystalline materials, but is not fully understood. Here, the authors show that the study of precritical cluster fluctuations paves new ways for the identification of polymorphism, polymorphic control and theoretical modeling.\n
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\n \n\n \n \n \n \n \n \n Is High-Density Amorphous Ice Simply a “Derailed” State along the Ice I to Ice IV Pathway?.\n \n \n \n \n\n\n \n Shephard, J. J.; Ling, S.; Sosso, G. C.; Michaelides, A.; Slater, B.; and Salzmann, C. G.\n\n\n \n\n\n\n The Journal of Physical Chemistry Letters, 8(7): 1645–1650. April 2017.\n \n\n\n\n
\n\n\n\n \n \n \"IsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{shephard_is_2017,\n\ttitle = {Is {High}-{Density} {Amorphous} {Ice} {Simply} a “{Derailed}” {State} along the {Ice} {I} to {Ice} {IV} {Pathway}?},\n\tvolume = {8},\n\tissn = {1948-7185},\n\turl = {http://pubs.acs.org/doi/10.1021/acs.jpclett.7b00492},\n\tdoi = {10.1021/acs.jpclett.7b00492},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Physical Chemistry Letters},\n\tauthor = {Shephard, Jacob J. and Ling, Sanliang and Sosso, Gabriele C. and Michaelides, Angelos and Slater, Ben and Salzmann, Christoph G.},\n\tmonth = apr,\n\tyear = {2017},\n\tpages = {1645--1650},\n}\n\n
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\n \n\n \n \n \n \n \n \n Grüneisen parameters and thermal conductivity in the phase change compound GeTe.\n \n \n \n \n\n\n \n Bosoni, E.; Sosso, G. C.; and Bernasconi, M.\n\n\n \n\n\n\n Journal of Computational Electronics, 16(4): 997–1002. December 2017.\n \n\n\n\n
\n\n\n\n \n \n \"GrüneisenPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{bosoni_gruneisen_2017,\n\ttitle = {Grüneisen parameters and thermal conductivity in the phase change compound {GeTe}},\n\tvolume = {16},\n\tissn = {1569-8025, 1572-8137},\n\turl = {http://link.springer.com/10.1007/s10825-017-1040-5},\n\tdoi = {10.1007/s10825-017-1040-5},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2018-04-16},\n\tjournal = {Journal of Computational Electronics},\n\tauthor = {Bosoni, Emanuele and Sosso, Gabriele Cesare and Bernasconi, Marco},\n\tmonth = dec,\n\tyear = {2017},\n\tpages = {997--1002},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Atomistic Simulations of the Crystallization and Aging of GeTe Nanowires.\n \n \n \n \n\n\n \n Gabardi, S.; Baldi, E.; Bosoni, E.; Campi, D.; Caravati, S.; Sosso, G. C.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n The Journal of Physical Chemistry C, 121(42): 23827–23838. October 2017.\n \n\n\n\n
\n\n\n\n \n \n \"AtomisticPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{gabardi_atomistic_2017,\n\ttitle = {Atomistic {Simulations} of the {Crystallization} and {Aging} of {GeTe} {Nanowires}},\n\tvolume = {121},\n\tissn = {1932-7447, 1932-7455},\n\turl = {http://pubs.acs.org/doi/10.1021/acs.jpcc.7b09862},\n\tdoi = {10.1021/acs.jpcc.7b09862},\n\tlanguage = {en},\n\tnumber = {42},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Physical Chemistry C},\n\tauthor = {Gabardi, S. and Baldi, E. and Bosoni, E. and Campi, D. and Caravati, S. and Sosso, G. C. and Behler, J. and Bernasconi, M.},\n\tmonth = oct,\n\tyear = {2017},\n\tpages = {23827--23838},\n}\n\n
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\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Analyzing and Driving Cluster Formation in Atomistic Simulations.\n \n \n \n \n\n\n \n Tribello, G. A.; Giberti, F.; Sosso, G. C.; Salvalaglio, M.; and Parrinello, M.\n\n\n \n\n\n\n Journal of Chemical Theory and Computation, 13(3): 1317–1327. March 2017.\n \n\n\n\n
\n\n\n\n \n \n \"AnalyzingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{tribello_analyzing_2017,\n\ttitle = {Analyzing and {Driving} {Cluster} {Formation} in {Atomistic} {Simulations}},\n\tvolume = {13},\n\tissn = {1549-9618, 1549-9626},\n\turl = {http://pubs.acs.org/doi/10.1021/acs.jctc.6b01073},\n\tdoi = {10.1021/acs.jctc.6b01073},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2018-04-16},\n\tjournal = {Journal of Chemical Theory and Computation},\n\tauthor = {Tribello, Gareth A. and Giberti, Federico and Sosso, Gabriele C. and Salvalaglio, Matteo and Parrinello, Michele},\n\tmonth = mar,\n\tyear = {2017},\n\tpages = {1317--1327},\n}\n\n
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\n \n\n \n \n \n \n \n \n Communication: Truncated non-bonded potentials can yield unphysical behavior in molecular dynamics simulations of interfaces.\n \n \n \n \n\n\n \n Fitzner, M.; Joly, L.; Ma, M.; Sosso, G. C.; Zen, A.; and Michaelides, A.\n\n\n \n\n\n\n The Journal of Chemical Physics, 147(12): 121102. September 2017.\n \n\n\n\n
\n\n\n\n \n \n \"Communication:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{fitzner_communication:_2017,\n\ttitle = {Communication: {Truncated} non-bonded potentials can yield unphysical behavior in molecular dynamics simulations of interfaces},\n\tvolume = {147},\n\tissn = {0021-9606, 1089-7690},\n\tshorttitle = {Communication},\n\turl = {http://aip.scitation.org/doi/10.1063/1.4997698},\n\tdoi = {10.1063/1.4997698},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Chemical Physics},\n\tauthor = {Fitzner, Martin and Joly, Laurent and Ma, Ming and Sosso, Gabriele C. and Zen, Andrea and Michaelides, Angelos},\n\tmonth = sep,\n\tyear = {2017},\n\tpages = {121102},\n}\n
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\n  \n 2016\n \n \n (6)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Direct calculation of the X-ray structure factor of ionic liquids.\n \n \n \n \n\n\n \n Liu, H.; and Paddison, S. J.\n\n\n \n\n\n\n Physical Chemistry Chemical Physics, 18(16): 11000–11007. April 2016.\n Publisher: The Royal Society of Chemistry\n\n\n\n
\n\n\n\n \n \n \"DirectPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{liu_direct_2016,\n\ttitle = {Direct calculation of the {X}-ray structure factor of ionic liquids},\n\tvolume = {18},\n\tissn = {1463-9084},\n\turl = {http://0.pubs.rsc.org/en/content/articlelanding/2016/cp/c5cp06199g},\n\tdoi = {10.1039/C5CP06199G},\n\tabstract = {A conceptually simple and computationally efficient direct method to calculate the total X-ray structure factor of ionic liquids from molecular simulations is advocated to be complementary to the popular Fourier transform (FT) method. The validity of the direct method is well formulated and established by comparison with FT results. The effectiveness is demonstrated through versatile partition schemes using tetradecyltrihexylphosphonium bis(trifluoromethylsulfonyl)amide P14,666 Tf2N as a model system. Three characteristic intermolecular peaks were observed below 2 Å−1, consistent with experimental X-ray measurements. The prepeak corresponds to the polarity alternation leading to structural heterogeneity and the intermediate shoulder is due to the ubiquitous charge ordering of the ionic liquid. The intense peak is mainly attributed to the adjacent contact of apolar cationic tails. The cationic head–anion correlation function is found to be a unique signature for all three characteristic length scales even if a certain peak is concealed by fortuitous cancellation in the X-ray structure factor. The proposed direct formulation can be readily extended to neutron scattering experiments.},\n\tlanguage = {en},\n\tnumber = {16},\n\turldate = {2022-02-23},\n\tjournal = {Physical Chemistry Chemical Physics},\n\tauthor = {Liu, Hongjun and Paddison, Stephen J.},\n\tmonth = apr,\n\tyear = {2016},\n\tnote = {Publisher: The Royal Society of Chemistry},\n\tpages = {11000--11007},\n}\n\n
\n
\n\n\n
\n A conceptually simple and computationally efficient direct method to calculate the total X-ray structure factor of ionic liquids from molecular simulations is advocated to be complementary to the popular Fourier transform (FT) method. The validity of the direct method is well formulated and established by comparison with FT results. The effectiveness is demonstrated through versatile partition schemes using tetradecyltrihexylphosphonium bis(trifluoromethylsulfonyl)amide P14,666 Tf2N as a model system. Three characteristic intermolecular peaks were observed below 2 Å−1, consistent with experimental X-ray measurements. The prepeak corresponds to the polarity alternation leading to structural heterogeneity and the intermediate shoulder is due to the ubiquitous charge ordering of the ionic liquid. The intense peak is mainly attributed to the adjacent contact of apolar cationic tails. The cationic head–anion correlation function is found to be a unique signature for all three characteristic length scales even if a certain peak is concealed by fortuitous cancellation in the X-ray structure factor. The proposed direct formulation can be readily extended to neutron scattering experiments.\n
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\n \n\n \n \n \n \n \n \n O-Aryl-Glycoside Ice Recrystallization Inhibitors as Novel Cryoprotectants: A Structure–Function Study.\n \n \n \n \n\n\n \n Capicciotti, C. J.; Mancini, R. S.; Turner, T. R.; Koyama, T.; Alteen, M. G.; Doshi, M.; Inada, T.; Acker, J. P.; and Ben, R. N.\n\n\n \n\n\n\n ACS Omega, 1(4): 656–662. October 2016.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"O-Aryl-GlycosidePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{capicciotti_o-aryl-glycoside_2016,\n\ttitle = {O-{Aryl}-{Glycoside} {Ice} {Recrystallization} {Inhibitors} as {Novel} {Cryoprotectants}: {A} {Structure}–{Function} {Study}},\n\tvolume = {1},\n\tshorttitle = {O-{Aryl}-{Glycoside} {Ice} {Recrystallization} {Inhibitors} as {Novel} {Cryoprotectants}},\n\turl = {https://doi.org/10.1021/acsomega.6b00163},\n\tdoi = {10.1021/acsomega.6b00163},\n\tabstract = {Low-molecular-weight ice recrystallization inhibitors (IRIs) are ideal cryoprotectants that control the growth of ice and mitigate cell damage during freezing. Herein, we describe a detailed study correlating the ice recrystallization inhibition activity and the cryopreservation ability with the structure of O-aryl-glycosides. Many effective IRIs are efficient cryoadditives for the freezing of red blood cells (RBCs). One effective cryoadditive did not inhibit ice recrystallization but instead inhibited ice nucleation, demonstrating the significance of inhibiting both processes and illustrating the importance of this emerging class of cryoprotectants.},\n\tnumber = {4},\n\turldate = {2022-01-20},\n\tjournal = {ACS Omega},\n\tauthor = {Capicciotti, Chantelle J. and Mancini, Ross S. and Turner, Tracey R. and Koyama, Toshie and Alteen, Matthew G. and Doshi, Malay and Inada, Takaaki and Acker, Jason P. and Ben, Robert N.},\n\tmonth = oct,\n\tyear = {2016},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {656--662},\n}\n\n
\n
\n\n\n
\n Low-molecular-weight ice recrystallization inhibitors (IRIs) are ideal cryoprotectants that control the growth of ice and mitigate cell damage during freezing. Herein, we describe a detailed study correlating the ice recrystallization inhibition activity and the cryopreservation ability with the structure of O-aryl-glycosides. Many effective IRIs are efficient cryoadditives for the freezing of red blood cells (RBCs). One effective cryoadditive did not inhibit ice recrystallization but instead inhibited ice nucleation, demonstrating the significance of inhibiting both processes and illustrating the importance of this emerging class of cryoprotectants.\n
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\n \n\n \n \n \n \n \n \n Atomic mobility in the overheated amorphous GeTe compound for phase change memories: Atomic mobility in overheated amorphous GeTe.\n \n \n \n \n\n\n \n Sosso, G. C.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Physica Status Solidi A, 213(2): 329–334. February 2016.\n \n\n\n\n
\n\n\n\n \n \n \"AtomicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_atomic_2016,\n\ttitle = {Atomic mobility in the overheated amorphous {GeTe} compound for phase change memories: {Atomic} mobility in overheated amorphous {GeTe}},\n\tvolume = {213},\n\tissn = {18626300},\n\tshorttitle = {Atomic mobility in the overheated amorphous {GeTe} compound for phase change memories},\n\turl = {http://doi.wiley.com/10.1002/pssa.201532378},\n\tdoi = {10.1002/pssa.201532378},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2018-04-16},\n\tjournal = {Physica Status Solidi A},\n\tauthor = {Sosso, G. C. and Behler, J. and Bernasconi, M.},\n\tmonth = feb,\n\tyear = {2016},\n\tpages = {329--334},\n}\n\n
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\n \n\n \n \n \n \n \n \n Microscopic Mechanism and Kinetics of Ice Formation at Complex Interfaces: Zooming in on Kaolinite.\n \n \n \n \n\n\n \n Sosso, G. C.; Li, T.; Donadio, D.; Tribello, G. A.; and Michaelides, A.\n\n\n \n\n\n\n The Journal of Physical Chemistry Letters, 7(13): 2350–2355. July 2016.\n \n\n\n\n
\n\n\n\n \n \n \"MicroscopicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_microscopic_2016,\n\ttitle = {Microscopic {Mechanism} and {Kinetics} of {Ice} {Formation} at {Complex} {Interfaces}: {Zooming} in on {Kaolinite}},\n\tvolume = {7},\n\tissn = {1948-7185},\n\tshorttitle = {Microscopic {Mechanism} and {Kinetics} of {Ice} {Formation} at {Complex} {Interfaces}},\n\turl = {http://pubs.acs.org/doi/10.1021/acs.jpclett.6b01013},\n\tdoi = {10.1021/acs.jpclett.6b01013},\n\tlanguage = {en},\n\tnumber = {13},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Physical Chemistry Letters},\n\tauthor = {Sosso, Gabriele C. and Li, Tianshu and Donadio, Davide and Tribello, Gareth A. and Michaelides, Angelos},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {2350--2355},\n}\n\n
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\n \n\n \n \n \n \n \n \n Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations.\n \n \n \n \n\n\n \n Sosso, G. C.; Chen, J.; Cox, S. J.; Fitzner, M.; Pedevilla, P.; Zen, A.; and Michaelides, A.\n\n\n \n\n\n\n Chemical Reviews, 116(12): 7078–7116. June 2016.\n \n\n\n\n
\n\n\n\n \n \n \"CrystalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_crystal_2016,\n\ttitle = {Crystal {Nucleation} in {Liquids}: {Open} {Questions} and {Future} {Challenges} in {Molecular} {Dynamics} {Simulations}},\n\tvolume = {116},\n\tissn = {0009-2665, 1520-6890},\n\tshorttitle = {Crystal {Nucleation} in {Liquids}},\n\turl = {http://pubs.acs.org/doi/10.1021/acs.chemrev.5b00744},\n\tdoi = {10.1021/acs.chemrev.5b00744},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2018-04-16},\n\tjournal = {Chemical Reviews},\n\tauthor = {Sosso, Gabriele C. and Chen, Ji and Cox, Stephen J. and Fitzner, Martin and Pedevilla, Philipp and Zen, Andrea and Michaelides, Angelos},\n\tmonth = jun,\n\tyear = {2016},\n\tpages = {7078--7116},\n}\n\n
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\n \n\n \n \n \n \n \n \n Ice formation on kaolinite: Insights from molecular dynamics simulations.\n \n \n \n \n\n\n \n Sosso, G. C.; Tribello, G. A.; Zen, A.; Pedevilla, P.; and Michaelides, A.\n\n\n \n\n\n\n The Journal of Chemical Physics, 145(21): 211927. December 2016.\n \n\n\n\n
\n\n\n\n \n \n \"IcePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_ice_2016,\n\ttitle = {Ice formation on kaolinite: {Insights} from molecular dynamics simulations},\n\tvolume = {145},\n\tissn = {0021-9606, 1089-7690},\n\tshorttitle = {Ice formation on kaolinite},\n\turl = {http://aip.scitation.org/doi/10.1063/1.4968796},\n\tdoi = {10.1063/1.4968796},\n\tlanguage = {en},\n\tnumber = {21},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Chemical Physics},\n\tauthor = {Sosso, Gabriele C. and Tribello, Gareth A. and Zen, Andrea and Pedevilla, Philipp and Michaelides, Angelos},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {211927},\n}\n\n
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\n  \n 2015\n \n \n (6)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n The Many Faces of Heterogeneous Ice Nucleation: Interplay Between Surface Morphology and Hydrophobicity.\n \n \n \n \n\n\n \n Fitzner, M.; Sosso, G. C.; Cox, S. J.; and Michaelides, A.\n\n\n \n\n\n\n Journal of the American Chemical Society, 137(42): 13658–13669. October 2015.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{fitzner_many_2015,\n\ttitle = {The {Many} {Faces} of {Heterogeneous} {Ice} {Nucleation}: {Interplay} {Between} {Surface} {Morphology} and {Hydrophobicity}},\n\tvolume = {137},\n\tissn = {0002-7863, 1520-5126},\n\tshorttitle = {The {Many} {Faces} of {Heterogeneous} {Ice} {Nucleation}},\n\turl = {http://pubs.acs.org/doi/10.1021/jacs.5b08748},\n\tdoi = {10.1021/jacs.5b08748},\n\tlanguage = {en},\n\tnumber = {42},\n\turldate = {2018-04-16},\n\tjournal = {Journal of the American Chemical Society},\n\tauthor = {Fitzner, Martin and Sosso, Gabriele C. and Cox, Stephen J. and Michaelides, Angelos},\n\tmonth = oct,\n\tyear = {2015},\n\tpages = {13658--13669},\n}\n\n
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\n \n\n \n \n \n \n \n \n Heterogeneous Crystallization of the Phase Change Material GeTe via Atomistic Simulations.\n \n \n \n \n\n\n \n Sosso, G. C.; Salvalaglio, M.; Behler, J.; Bernasconi, M.; and Parrinello, M.\n\n\n \n\n\n\n The Journal of Physical Chemistry C, 119(11): 6428–6434. March 2015.\n \n\n\n\n
\n\n\n\n \n \n \"HeterogeneousPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_heterogeneous_2015,\n\ttitle = {Heterogeneous {Crystallization} of the {Phase} {Change} {Material} {GeTe} via {Atomistic} {Simulations}},\n\tvolume = {119},\n\tissn = {1932-7447, 1932-7455},\n\turl = {http://pubs.acs.org/doi/10.1021/acs.jpcc.5b00296},\n\tdoi = {10.1021/acs.jpcc.5b00296},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Physical Chemistry C},\n\tauthor = {Sosso, Gabriele C. and Salvalaglio, Matteo and Behler, Jörg and Bernasconi, Marco and Parrinello, Michele},\n\tmonth = mar,\n\tyear = {2015},\n\tpages = {6428--6434},\n}\n\n
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\n \n\n \n \n \n \n \n \n Functional Properties of Phase Change Materials from Atomistic Simulations.\n \n \n \n \n\n\n \n Caravati, S.; Sosso, G. C.; and Bernasconi, M.\n\n\n \n\n\n\n In Massobrio, C.; Du, J.; Bernasconi, M.; and Salmon, P. S., editor(s), Molecular Dynamics Simulations of Disordered Materials, volume 215, pages 415–440. Springer International Publishing, Cham, 2015.\n \n\n\n\n
\n\n\n\n \n \n \"FunctionalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@incollection{massobrio_functional_2015,\n\taddress = {Cham},\n\ttitle = {Functional {Properties} of {Phase} {Change} {Materials} from {Atomistic} {Simulations}},\n\tvolume = {215},\n\tisbn = {978-3-319-15674-3 978-3-319-15675-0},\n\turl = {http://link.springer.com/10.1007/978-3-319-15675-0_15},\n\tlanguage = {en},\n\turldate = {2018-04-16},\n\tbooktitle = {Molecular {Dynamics} {Simulations} of {Disordered} {Materials}},\n\tpublisher = {Springer International Publishing},\n\tauthor = {Caravati, Sebastiano and Sosso, Gabriele C. and Bernasconi, Marco},\n\teditor = {Massobrio, Carlo and Du, Jincheng and Bernasconi, Marco and Salmon, Philip S.},\n\tyear = {2015},\n\tdoi = {10.1007/978-3-319-15675-0_15},\n\tpages = {415--440},\n}\n\n
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\n \n\n \n \n \n \n \n \n Electron–phonon interaction and thermal boundary resistance at the interfaces of Ge2Sb2Te5 with metals and dielectrics.\n \n \n \n \n\n\n \n Campi, D; Baldi, E; Graceffa, G; Sosso, G C; and Bernasconi, M\n\n\n \n\n\n\n Journal of Physics: Condensed Matter, 27(17): 175009. May 2015.\n \n\n\n\n
\n\n\n\n \n \n \"Electron–phononPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{campi_electronphonon_2015,\n\ttitle = {Electron–phonon interaction and thermal boundary resistance at the interfaces of {Ge2Sb2Te5} with metals and dielectrics},\n\tvolume = {27},\n\tissn = {0953-8984, 1361-648X},\n\turl = {http://stacks.iop.org/0953-8984/27/i=17/a=175009?key=crossref.4d7b664bea22f99f7f0ff0ceb7d10aa7},\n\tdoi = {10.1088/0953-8984/27/17/175009},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2018-04-16},\n\tjournal = {Journal of Physics: Condensed Matter},\n\tauthor = {Campi, D and Baldi, E and Graceffa, G and Sosso, G C and Bernasconi, M},\n\tmonth = may,\n\tyear = {2015},\n\tpages = {175009},\n}\n\n
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\n \n\n \n \n \n \n \n \n Microscopic origin of resistance drift in the amorphous state of the phase-change compound GeTe.\n \n \n \n \n\n\n \n Gabardi, S.; Caravati, S.; Sosso, G. C.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Physical Review B, 92(5). August 2015.\n \n\n\n\n
\n\n\n\n \n \n \"MicroscopicPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{gabardi_microscopic_2015,\n\ttitle = {Microscopic origin of resistance drift in the amorphous state of the phase-change compound {GeTe}},\n\tvolume = {92},\n\tissn = {1098-0121, 1550-235X},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevB.92.054201},\n\tdoi = {10.1103/PhysRevB.92.054201},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2018-04-16},\n\tjournal = {Physical Review B},\n\tauthor = {Gabardi, S. and Caravati, S. and Sosso, G. C. and Behler, J. and Bernasconi, M.},\n\tmonth = aug,\n\tyear = {2015},\n}\n\n
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\n \n\n \n \n \n \n \n \n Electron-phonon interaction and thermal boundary resistance at the crystal-amorphous interface of the phase change compound GeTe.\n \n \n \n \n\n\n \n Campi, D.; Donadio, D.; Sosso, G. C.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Journal of Applied Physics, 117(1): 015304. January 2015.\n \n\n\n\n
\n\n\n\n \n \n \"Electron-phononPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{campi_electron-phonon_2015,\n\ttitle = {Electron-phonon interaction and thermal boundary resistance at the crystal-amorphous interface of the phase change compound {GeTe}},\n\tvolume = {117},\n\tissn = {0021-8979, 1089-7550},\n\turl = {http://aip.scitation.org/doi/10.1063/1.4904910},\n\tdoi = {10.1063/1.4904910},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2018-04-16},\n\tjournal = {Journal of Applied Physics},\n\tauthor = {Campi, Davide and Donadio, Davide and Sosso, Gabriele C. and Behler, Jörg and Bernasconi, Marco},\n\tmonth = jan,\n\tyear = {2015},\n\tpages = {015304},\n}\n\n
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\n  \n 2014\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n The role of the umbrella inversion mode in proton diffusion.\n \n \n \n \n\n\n \n Hassanali, A. A.; Giberti, F.; Sosso, G. C.; and Parrinello, M.\n\n\n \n\n\n\n Chemical Physics Letters, 599: 133–138. April 2014.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{hassanali_role_2014,\n\ttitle = {The role of the umbrella inversion mode in proton diffusion},\n\tvolume = {599},\n\tissn = {00092614},\n\turl = {http://linkinghub.elsevier.com/retrieve/pii/S0009261414001857},\n\tdoi = {10.1016/j.cplett.2014.03.034},\n\tlanguage = {en},\n\turldate = {2018-04-16},\n\tjournal = {Chemical Physics Letters},\n\tauthor = {Hassanali, Ali A. and Giberti, Federico and Sosso, Gabriele C. and Parrinello, Michele},\n\tmonth = apr,\n\tyear = {2014},\n\tpages = {133--138},\n}\n\n
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\n \n\n \n \n \n \n \n \n Dynamical Heterogeneity in the Supercooled Liquid State of the Phase Change Material GeTe.\n \n \n \n \n\n\n \n Sosso, G. C.; Colombo, J.; Behler, J.; Del Gado, E.; and Bernasconi, M.\n\n\n \n\n\n\n The Journal of Physical Chemistry B, 118(47): 13621–13628. November 2014.\n \n\n\n\n
\n\n\n\n \n \n \"DynamicalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_dynamical_2014,\n\ttitle = {Dynamical {Heterogeneity} in the {Supercooled} {Liquid} {State} of the {Phase} {Change} {Material} {GeTe}},\n\tvolume = {118},\n\tissn = {1520-6106, 1520-5207},\n\turl = {http://pubs.acs.org/doi/10.1021/jp507361f},\n\tdoi = {10.1021/jp507361f},\n\tlanguage = {en},\n\tnumber = {47},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Physical Chemistry B},\n\tauthor = {Sosso, Gabriele C. and Colombo, Jader and Behler, Jörg and Del Gado, Emanuela and Bernasconi, Marco},\n\tmonth = nov,\n\tyear = {2014},\n\tpages = {13621--13628},\n}\n\n
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\n  \n 2013\n \n \n (4)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n The importance of hydrophobic moieties in ice recrystallization inhibitors.\n \n \n \n \n\n\n \n Balcerzak, A. K.; Febbraro, M.; and Ben, R. N.\n\n\n \n\n\n\n RSC Advances, 3(10): 3232–3236. February 2013.\n Publisher: The Royal Society of Chemistry\n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{balcerzak_importance_2013,\n\ttitle = {The importance of hydrophobic moieties in ice recrystallization inhibitors},\n\tvolume = {3},\n\tissn = {2046-2069},\n\turl = {https://pubs.rsc.org/en/content/articlelanding/2013/ra/c3ra23220d},\n\tdoi = {10.1039/C3RA23220D},\n\tabstract = {Structurally diverse lysine-based surfactants/gelators and anti-ice nucleating agents (anti-INAs) were investigated as ice recrystallization inhibitors (IRIs). The results indicate that long alkyl chains are important for potent IRI activity and that the position of these alkyl chains is essential. Additionally, no correlation was found between IRI activity and critical micelle concentrations, gelation or anti-ice nucleation activity, although the counterion of some lysine surfactants did affect IRI activity.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2022-01-20},\n\tjournal = {RSC Advances},\n\tauthor = {Balcerzak, Anna K. and Febbraro, Michela and Ben, Robert N.},\n\tmonth = feb,\n\tyear = {2013},\n\tnote = {Publisher: The Royal Society of Chemistry},\n\tpages = {3232--3236},\n}\n\n
\n
\n\n\n
\n Structurally diverse lysine-based surfactants/gelators and anti-ice nucleating agents (anti-INAs) were investigated as ice recrystallization inhibitors (IRIs). The results indicate that long alkyl chains are important for potent IRI activity and that the position of these alkyl chains is essential. Additionally, no correlation was found between IRI activity and critical micelle concentrations, gelation or anti-ice nucleation activity, although the counterion of some lysine surfactants did affect IRI activity.\n
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\n \n\n \n \n \n \n \n \n Nanosession: Phase Change Materials.\n \n \n \n \n\n\n \n Mazzarello, R.; Sosso, G. C.; Miceli, G.; Caravati, S.; Donadio, D.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n In Frontiers in Electronic Materials, pages 155–162. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, April 2013.\n \n\n\n\n
\n\n\n\n \n \n \"Nanosession:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@incollection{mazzarello_nanosession:_2013,\n\taddress = {Weinheim, Germany},\n\ttitle = {Nanosession: {Phase} {Change} {Materials}},\n\tisbn = {978-3-527-66770-3 978-3-527-41191-7},\n\tshorttitle = {Nanosession},\n\turl = {http://doi.wiley.com/10.1002/9783527667703.ch37},\n\tlanguage = {en},\n\turldate = {2018-04-16},\n\tbooktitle = {Frontiers in {Electronic} {Materials}},\n\tpublisher = {Wiley-VCH Verlag GmbH \\& Co. KGaA},\n\tauthor = {Mazzarello, Riccardo and Sosso, Gabriele Cesare and Miceli, Giacomo and Caravati, Sebastiano and Donadio, Davide and Behler, Jörg and Bernasconi, Marco},\n\tmonth = apr,\n\tyear = {2013},\n\tdoi = {10.1002/9783527667703.ch37},\n\tpages = {155--162},\n}\n\n
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\n \n\n \n \n \n \n \n \n Fast Crystallization of the Phase Change Compound GeTe by Large-Scale Molecular Dynamics Simulations.\n \n \n \n \n\n\n \n Sosso, G. C.; Miceli, G.; Caravati, S.; Giberti, F.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n The Journal of Physical Chemistry Letters, 4(24): 4241–4246. December 2013.\n \n\n\n\n
\n\n\n\n \n \n \"FastPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_fast_2013,\n\ttitle = {Fast {Crystallization} of the {Phase} {Change} {Compound} {GeTe} by {Large}-{Scale} {Molecular} {Dynamics} {Simulations}},\n\tvolume = {4},\n\tissn = {1948-7185},\n\turl = {http://pubs.acs.org/doi/10.1021/jz402268v},\n\tdoi = {10.1021/jz402268v},\n\tlanguage = {en},\n\tnumber = {24},\n\turldate = {2018-04-16},\n\tjournal = {The Journal of Physical Chemistry Letters},\n\tauthor = {Sosso, Gabriele C. and Miceli, Giacomo and Caravati, Sebastiano and Giberti, Federico and Behler, Jörg and Bernasconi, Marco},\n\tmonth = dec,\n\tyear = {2013},\n\tpages = {4241--4246},\n}\n\n
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\n \n\n \n \n \n \n \n \n Density functional simulations of hexagonal Ge2Sb2Te5 at high pressure.\n \n \n \n \n\n\n \n Caravati, S.; Sosso, G. C.; Bernasconi, M.; and Parrinello, M.\n\n\n \n\n\n\n Physical Review B, 87(9). March 2013.\n \n\n\n\n
\n\n\n\n \n \n \"DensityPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{caravati_density_2013,\n\ttitle = {Density functional simulations of hexagonal {Ge2Sb2Te5} at high pressure},\n\tvolume = {87},\n\tissn = {1098-0121, 1550-235X},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevB.87.094117},\n\tdoi = {10.1103/PhysRevB.87.094117},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2018-04-16},\n\tjournal = {Physical Review B},\n\tauthor = {Caravati, Sebastiano and Sosso, Gabriele C. and Bernasconi, Marco and Parrinello, Michele},\n\tmonth = mar,\n\tyear = {2013},\n}\n\n
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\n  \n 2012\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Breakdown of Stokes-Einstein relation in the supercooled liquid state of phase change materials.\n \n \n \n \n\n\n \n Sosso, G. C.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Physica Status Solidi (b), 249(10): 1880–1885. October 2012.\n \n\n\n\n
\n\n\n\n \n \n \"BreakdownPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_breakdown_2012,\n\ttitle = {Breakdown of {Stokes}-{Einstein} relation in the supercooled liquid state of phase change materials},\n\tvolume = {249},\n\tissn = {03701972},\n\turl = {http://doi.wiley.com/10.1002/pssb.201200355},\n\tdoi = {10.1002/pssb.201200355},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2018-04-16},\n\tjournal = {Physica Status Solidi (b)},\n\tauthor = {Sosso, G. C. and Behler, J. and Bernasconi, M.},\n\tmonth = oct,\n\tyear = {2012},\n\tpages = {1880--1885},\n}\n\n
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\n \n\n \n \n \n \n \n \n Thermal transport in phase-change materials from atomistic simulations.\n \n \n \n \n\n\n \n Sosso, G. C.; Donadio, D.; Caravati, S.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Physical Review B, 86(10). September 2012.\n \n\n\n\n
\n\n\n\n \n \n \"ThermalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_thermal_2012,\n\ttitle = {Thermal transport in phase-change materials from atomistic simulations},\n\tvolume = {86},\n\tissn = {1098-0121, 1550-235X},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevB.86.104301},\n\tdoi = {10.1103/PhysRevB.86.104301},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2018-04-16},\n\tjournal = {Physical Review B},\n\tauthor = {Sosso, Gabriele C. and Donadio, Davide and Caravati, Sebastiano and Behler, Jörg and Bernasconi, Marco},\n\tmonth = sep,\n\tyear = {2012},\n}\n\n
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\n \n\n \n \n \n \n \n \n Neural network interatomic potential for the phase change material GeTe.\n \n \n \n \n\n\n \n Sosso, G. C.; Miceli, G.; Caravati, S.; Behler, J.; and Bernasconi, M.\n\n\n \n\n\n\n Physical Review B, 85(17). May 2012.\n \n\n\n\n
\n\n\n\n \n \n \"NeuralPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_neural_2012,\n\ttitle = {Neural network interatomic potential for the phase change material {GeTe}},\n\tvolume = {85},\n\tissn = {1098-0121, 1550-235X},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevB.85.174103},\n\tdoi = {10.1103/PhysRevB.85.174103},\n\tlanguage = {en},\n\tnumber = {17},\n\turldate = {2018-04-16},\n\tjournal = {Physical Review B},\n\tauthor = {Sosso, Gabriele C. and Miceli, Giacomo and Caravati, Sebastiano and Behler, Jörg and Bernasconi, Marco},\n\tmonth = may,\n\tyear = {2012},\n}\n\n
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\n  \n 2011\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Raman spectra of cubic and amorphous Ge2Sb2Te5 from first principles.\n \n \n \n \n\n\n \n Sosso, G. C.; Caravati, S.; Mazzarello, R.; and Bernasconi, M.\n\n\n \n\n\n\n Physical Review B, 83(13). April 2011.\n \n\n\n\n
\n\n\n\n \n \n \"RamanPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_raman_2011,\n\ttitle = {Raman spectra of cubic and amorphous {Ge2Sb2Te5} from first principles},\n\tvolume = {83},\n\tissn = {1098-0121, 1550-235X},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevB.83.134201},\n\tdoi = {10.1103/PhysRevB.83.134201},\n\tlanguage = {en},\n\tnumber = {13},\n\turldate = {2018-04-16},\n\tjournal = {Physical Review B},\n\tauthor = {Sosso, Gabriele C. and Caravati, Sebastiano and Mazzarello, Riccardo and Bernasconi, Marco},\n\tmonth = apr,\n\tyear = {2011},\n}\n\n
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\n  \n 2009\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n Ice Recrystallization Kinetics in the Presence of Synthetic Antifreeze Glycoprotein Analogues Using the Framework of LSW Theory.\n \n \n \n \n\n\n \n Budke, C.; Heggemann, C.; Koch, M.; Sewald, N.; and Koop, T.\n\n\n \n\n\n\n The Journal of Physical Chemistry B, 113(9): 2865–2873. March 2009.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"IcePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{budke_ice_2009,\n\ttitle = {Ice {Recrystallization} {Kinetics} in the {Presence} of {Synthetic} {Antifreeze} {Glycoprotein} {Analogues} {Using} the {Framework} of {LSW} {Theory}},\n\tvolume = {113},\n\tissn = {1520-6106},\n\turl = {https://doi.org/10.1021/jp805726e},\n\tdoi = {10.1021/jp805726e},\n\tabstract = {The Ostwald ripening of polycrystalline ice in aqueous sucrose solutions was investigated experimentally. The kinetics of this ice recrystallization process was studied at temperatures between −6 and −10 °C and varying ice volume fractions. Using the theory of Lifshitz, Slyozov, and Wagner (LSW), the diffusion-limited rate constant for ice recrystallization was determined. Also, the effects of synthetic analogues of natural antifreeze glycoproteins (AFGP) were studied. These analogues synAFGPmi (i = 3−5) contained monosaccharide side groups instead of disaccharide side groups that occur in natural AFGP. In order to account for the inhibition effect of the synAFGPmi, we have modified classical LSW theory, allowing for the derivation of inhibition rate constants. It was found that the investigated synAFGPmi inhibit ice recrystallization at concentrations down to ∼3 μg mL−1 or, equivalently, ∼1 μmol L−1 for the largest synAFGPmi investigated: synAFGPm5. Hence, our new method is capable of quantitatively assessing the efficiency of very similar AFGP with a sensitivity that is at least 2 orders of magnitude larger than that typical for quantitative thermal hysteresis measurements.},\n\tnumber = {9},\n\turldate = {2022-01-20},\n\tjournal = {The Journal of Physical Chemistry B},\n\tauthor = {Budke, C. and Heggemann, C. and Koch, M. and Sewald, N. and Koop, T.},\n\tmonth = mar,\n\tyear = {2009},\n\tnote = {Publisher: American Chemical Society},\n\tpages = {2865--2873},\n}\n\n
\n
\n\n\n
\n The Ostwald ripening of polycrystalline ice in aqueous sucrose solutions was investigated experimentally. The kinetics of this ice recrystallization process was studied at temperatures between −6 and −10 °C and varying ice volume fractions. Using the theory of Lifshitz, Slyozov, and Wagner (LSW), the diffusion-limited rate constant for ice recrystallization was determined. Also, the effects of synthetic analogues of natural antifreeze glycoproteins (AFGP) were studied. These analogues synAFGPmi (i = 3−5) contained monosaccharide side groups instead of disaccharide side groups that occur in natural AFGP. In order to account for the inhibition effect of the synAFGPmi, we have modified classical LSW theory, allowing for the derivation of inhibition rate constants. It was found that the investigated synAFGPmi inhibit ice recrystallization at concentrations down to ∼3 μg mL−1 or, equivalently, ∼1 μmol L−1 for the largest synAFGPmi investigated: synAFGPm5. Hence, our new method is capable of quantitatively assessing the efficiency of very similar AFGP with a sensitivity that is at least 2 orders of magnitude larger than that typical for quantitative thermal hysteresis measurements.\n
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\n \n\n \n \n \n \n \n \n Vibrational properties of crystalline Sb2Te3 from first principles.\n \n \n \n \n\n\n \n Sosso, G C; Caravati, S; and Bernasconi, M\n\n\n \n\n\n\n Journal of Physics: Condensed Matter, 21(9): 095410. March 2009.\n \n\n\n\n
\n\n\n\n \n \n \"VibrationalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_vibrational_2009,\n\ttitle = {Vibrational properties of crystalline {Sb2Te3} from first principles},\n\tvolume = {21},\n\tissn = {0953-8984, 1361-648X},\n\turl = {http://stacks.iop.org/0953-8984/21/i=9/a=095410?key=crossref.d25774715f64060387b5157f7385914c},\n\tdoi = {10.1088/0953-8984/21/9/095410},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2018-04-16},\n\tjournal = {Journal of Physics: Condensed Matter},\n\tauthor = {Sosso, G C and Caravati, S and Bernasconi, M},\n\tmonth = mar,\n\tyear = {2009},\n\tpages = {095410},\n}\n\n
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\n \n\n \n \n \n \n \n \n Vibrational properties of hexagonal Ge2Sb2Te5 from first principles.\n \n \n \n \n\n\n \n Sosso, G C; Caravati, S; Gatti, C; Assoni, S; and Bernasconi, M\n\n\n \n\n\n\n Journal of Physics: Condensed Matter, 21(24): 245401. June 2009.\n \n\n\n\n
\n\n\n\n \n \n \"VibrationalPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sosso_vibrational_2009-1,\n\ttitle = {Vibrational properties of hexagonal {Ge2Sb2Te5} from first principles},\n\tvolume = {21},\n\tissn = {0953-8984, 1361-648X},\n\turl = {http://stacks.iop.org/0953-8984/21/i=24/a=245401?key=crossref.6ee540f3ac1995e3461defc33aa16c09},\n\tdoi = {10.1088/0953-8984/21/24/245401},\n\tlanguage = {en},\n\tnumber = {24},\n\turldate = {2018-04-16},\n\tjournal = {Journal of Physics: Condensed Matter},\n\tauthor = {Sosso, G C and Caravati, S and Gatti, C and Assoni, S and Bernasconi, M},\n\tmonth = jun,\n\tyear = {2009},\n\tpages = {245401},\n}\n\n
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\n  \n 2005\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Nucleation and growth during recrystallization.\n \n \n \n \n\n\n \n Rios, P. R.; Siciliano Jr, F.; Sandim, H. R. Z.; Plaut, R. L.; and Padilha, A. F.\n\n\n \n\n\n\n Materials Research, 8: 225–238. September 2005.\n Publisher: ABM, ABC, ABPol\n\n\n\n
\n\n\n\n \n \n \"NucleationPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{rios_nucleation_2005,\n\ttitle = {Nucleation and growth during recrystallization},\n\tvolume = {8},\n\tissn = {1516-1439, 1980-5373},\n\turl = {http://www.scielo.br/j/mr/a/FXtGZhF5hfWTsmznwJSDPXz/?lang=en},\n\tdoi = {10.1590/S1516-14392005000300002},\n\tabstract = {The evolution in the understanding of the recrystallization phenomena is summarized in this paper. Initially the main developments concerning recrystallization are presented from a historical perspective. Definitions and concepts involving recrystallization are presented regarding it as a solid-state reaction that occurs by nucleation and growth. The recrystallization nucleation mechanisms are subsequently discussed. Finally, the growth step is highlighted, emphasizing boundary and sub-boundary mobilities and the forces acting on the high angle grain boundaries that sweep the microstructure during recrystallization.},\n\tlanguage = {en},\n\turldate = {2022-01-20},\n\tjournal = {Materials Research},\n\tauthor = {Rios, Paulo Rangel and Siciliano Jr, Fulvio and Sandim, Hugo Ricardo Zschommler and Plaut, Ronald Lesley and Padilha, Angelo Fernando},\n\tmonth = sep,\n\tyear = {2005},\n\tnote = {Publisher: ABM, ABC, ABPol},\n\tkeywords = {growth, nucleation, recovery, recrystallisation, recrystallization},\n\tpages = {225--238},\n}\n\n
\n
\n\n\n
\n The evolution in the understanding of the recrystallization phenomena is summarized in this paper. Initially the main developments concerning recrystallization are presented from a historical perspective. Definitions and concepts involving recrystallization are presented regarding it as a solid-state reaction that occurs by nucleation and growth. The recrystallization nucleation mechanisms are subsequently discussed. Finally, the growth step is highlighted, emphasizing boundary and sub-boundary mobilities and the forces acting on the high angle grain boundaries that sweep the microstructure during recrystallization.\n
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\n  \n 1996\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Kinetics of Ice Recrystallization in Aqueous Fructose Solutions.\n \n \n \n \n\n\n \n Sutton, R. L.; Lips, A.; Piccirillo, G.; and Sztehlo, A.\n\n\n \n\n\n\n Journal of Food Science, 61(4): 741–745. July 1996.\n \n\n\n\n
\n\n\n\n \n \n \"KineticsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sutton_kinetics_1996,\n\ttitle = {Kinetics of {Ice} {Recrystallization} in {Aqueous} {Fructose} {Solutions}},\n\tvolume = {61},\n\tissn = {0022-1147, 1750-3841},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2621.1996.tb12194.x},\n\tdoi = {10.1111/j.1365-2621.1996.tb12194.x},\n\tabstract = {Recrystallization rates of ice in fructose solutions were determined over a range of temperatures and ice phase volumes. Accretive and migratory recrystallization both occur, the dominant mechanism being strongly dependent on the mean size of the crystals. Accretion dominated when crystals were small and close together. Recrystallization rates decreased with decreasing ice phase volume and decreasing temperature. The temperature dependence of the rates was consistent with Williams-LandellFerry kinetics. With a mean field correction for ice phase volume the observed data fit the recrystallization theory of Lifshitz, Slyozov and Wagner reasonably well.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2022-01-20},\n\tjournal = {Journal of Food Science},\n\tauthor = {Sutton, Robin L. and Lips, Alex and Piccirillo, Guiseppe and Sztehlo, Andy},\n\tmonth = jul,\n\tyear = {1996},\n\tpages = {741--745},\n}\n\n
\n
\n\n\n
\n Recrystallization rates of ice in fructose solutions were determined over a range of temperatures and ice phase volumes. Accretive and migratory recrystallization both occur, the dominant mechanism being strongly dependent on the mean size of the crystals. Accretion dominated when crystals were small and close together. Recrystallization rates decreased with decreasing ice phase volume and decreasing temperature. The temperature dependence of the rates was consistent with Williams-LandellFerry kinetics. With a mean field correction for ice phase volume the observed data fit the recrystallization theory of Lifshitz, Slyozov and Wagner reasonably well.\n
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