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@article{wrap184027, volume = {144}, month = {April}, title = {Microcracks in CVD diamond produced by scaife polishing}, author = {Ebrima Saho and Steven A. Hindmarsh and Ana M. S{\'a}nchez and Fraser Birks and James R. Kermode and M. W. Dale and David Fisher and R. Beanland}, publisher = {Elsevier}, year = {2024}, journal = {Diamond \& Related Materials}, url = {https://wrap.warwick.ac.uk/184027/}, abstract = {We investigate sub-surface damage in a CVD diamond, polished on a (110) plane using the traditional scaife method. The damage lies in tracks that consist of microcracks lying perpendicular to the polishing direction. These cracks have an irregular spacing and are comprised mainly of \{111\} facets. Their geometry is consistent with a modified Hertzian fracture, caused by a stick-slip movement of relatively large (micron-sized) diamond particles on the scaife. The interior surface of the cracks shows a 1x1 CH3 surface reconstruction, consistent with a high hydrogen overpressure that results from ingress of hydrocarbons in the polishing lubricant and a relatively low temperature process. The crack edge is ragged, and voids with sizes of a few nm are found up to hundreds of nm from the crack front, particularly where the crack ends at the polished surface. We propose that these features are evidence of significant healing of the cracks once the applied stress is removed. Luminescence at the crack tips is seen, presumably due to impurities trapped in these voids, which quenches with electron irradiation at 10 keV.} }
@article{wrap184511, volume = {8}, number = {3}, month = {March}, author = {Lakshmi Shenoy and Christopher D. Woodgate and Julie B. Staunton and Albert P. Bart{\'o}k and Charlotte S. Becquart and Christophe Domain and James R. Kermode}, title = {Collinear-spin machine learned interatomic potential for Fe7Cr2Ni alloy}, publisher = {American Physical Society}, journal = {Physical Review Materials}, year = {2024}, url = {https://wrap.warwick.ac.uk/184511/}, abstract = {We have developed a machine learned interatomic potential for the prototypical austenitic steel Fe7Cr2Ni, using the Gaussian approximation potential (GAP) framework. This GAP can model the alloy's properties with close to density functional theory (DFT) accuracy, while at the same time allowing us to access larger length and time scales than expensive first-principles methods. We also extended the GAP input descriptors to approximate the effects of collinear spins (spin GAP), and demonstrate how this extended model successfully predicts structural distortions due to antiferromagnetic and paramagnetic spin states. We demonstrate the application of the spin GAP model for bulk properties and vacancies and validate against DFT. These results are a step towards modeling the atomistic origins of ageing in austenitic steels with higher accuracy.} }
@article{wrap182992, volume = {9}, number = {93}, month = {January}, author = {Petr Grigorev and Lucas Fr{\'e}rot and Fraser Birks and Adrien Gola and Jacek Golebiowski and Jan Grie{\ss}er and Johannes L. H{\"o}rmann and Andreas Klemenz and Gianpietro Moras and Wolfram G. N{\"o}hring and Jonas A. Oldenstaedt and Punit Patel and Thomas Reichenbach and Thomas Rocke and Lakshmi Shenoy and Michael Walter and Simon Wengert and Lei Zhang and James R. Kermode and Lars Pastewka}, title = {matscipy : materials science at the atomic scale with Python}, publisher = {The Open Journal}, journal = {Journal of Open Source Software}, year = {2024}, url = {https://wrap.warwick.ac.uk/182992/}, abstract = {Behaviour of materials is governed by physical phenomena that occur at an extreme range of length and time scales. Computational modelling requires multiscale approaches. Simulation techniques operating on the atomic scale serve as a foundation for such approaches, providing necessary parameters for upper-scale models. The physical models employed for atomic simulations can vary from electronic structure calculations to empirical force fields. However, construction, manipulation and analysis of atomic systems are independent of the given physical model but dependent on the specific application. matscipy implements such tools for applications in materials science, including fracture, plasticity, tribology and electrochemistry.} }
@incollection{wrap181718, volume = {5}, author = {Mike W. Finnis and James R. Kermode}, booktitle = {Encyclopedia of Condensed Matter Physics [2nd Edition]}, editor = {Tapash Chakraborty}, address = {Oxford}, title = {Crystal binding (interatomic forces) : ionic bonding and crystals}, publisher = {Academic Press}, year = {2024}, pages = {208--216}, url = {https://wrap.warwick.ac.uk/181718/}, abstract = {We discuss in general terms the models that are appropriate for describing interatomic forces and performing atomistic simulations in ionic materials. In particular we show how the framework of density functional theory (DFT) and second-order perturbation theory provides a unified way of deriving ionic models, including the Born model and shell models, besides variable charge-transfer models, such as charge equilibration models, and the self-consistent tight-binding model. We also discuss progress in the direct numerical fitting of functions to calculated data, which has made significant progress in recent years with the development of machine learning interatomic potentials and other data-driven approaches.} }
@article{wrap171506, volume = {104}, month = {December}, author = {G. Anand and Swarnava Ghosh and Liwei Zhang and Angesh Anupam and Colin L. Freeman and Christoph Ortner and Markus Eisenbach and James R. Kermode}, note = {The authors are thankful to UKIERI and DST for funding the Partnership Development Workshop. The authors are also thankful to US-DOE-ORNL for funding. This research used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. The authors acknowledge the Network Builder Grant from Cardiff Met University.}, title = {Exploiting machine learning in multiscale modelling of materials}, publisher = {Springer}, year = {2023}, journal = {Journal of The Institution of Engineers (India) : Series D}, pages = {867--877}, url = {https://wrap.warwick.ac.uk/171506/}, abstract = {Recent developments in efficient machine learning algorithms have spurred significant interest in the materials community. The inherently complex and multiscale problems in Materials Science and Engineering pose a formidable challenge. The present scenario of machine learning research in Materials Science has a clear lacunae, where efficient algorithms are being developed as a separate endeavour, while such methods are being applied as ?black-box? models by others. The present article aims to discuss pertinent issues related to the development and application of machine learning algorithms for various aspects of multiscale materials modelling. The authors present an overview of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed. } }
@article{wrap179923, volume = {159}, month = {November}, title = {Gaussian Approximation Potentials : theory, software implementation and application examples}, author = {Sascha Klawohn and James P. Darby and James R. Kermode and G{\'a}bor Cs{\'a}nyi and Miguel A. Caro and Albert P. Bart{\'o}k}, publisher = {American Institute of Physics}, year = {2023}, journal = {Journal of Chemical Physics}, url = {https://wrap.warwick.ac.uk/179923/}, abstract = {Gaussian Approximation Potentials (GAPs) are a class of Machine Learned Interatomic Potentials routinely used to model materials and molecular systems on the atomic scale. The software implementation provides the means for both fitting models using ab initio data and using the resulting potentials in atomic simulations. Details of the GAP theory, algorithms and software are presented, together with detailed usage examples to help new and existing users. We review some recent developments to the GAP framework, including Message Passing Interface parallelisation of the fitting code enabling its use on thousands of central processing unit cores and compression of descriptors to eliminate the poor scaling with the number of different chemical elements.} }
@article{wrap180433, volume = {159}, number = {16}, month = {October}, author = {William C. Witt and Cas van der Oord and Elena Gel{\vz}inyt{\.e} and Teemu J{\"a}rvinen and Andres Ross and James P. Darby and Cheuk Hin Ho and William J. Baldwin and Matthias Sachs and James R. Kermode and Noam Bernstein and G{\'a}bor Cs{\'a}nyi and Christoph Ortner}, title = {ACEpotentials.jl : a Julia implementation of the atomic cluster expansion}, publisher = {American Institute of Physics}, journal = {The Journal of Chemical Physics}, year = {2023}, url = {https://wrap.warwick.ac.uk/180433/}, abstract = {We introduce ACEpotentials.jl, a Julia-language software package that constructs interatomic potentials from quantum mechanical reference data using the Atomic Cluster Expansion [R. Drautz, Phys. Rev. B 99, 014104 (2019)]. As the latter provides a complete description of atomic environments, including invariance to overall translation and rotation as well as permutation of like atoms, the resulting potentials are systematically improvable and data efficient. Furthermore, the descriptor?s expressiveness enables use of a linear model, facilitating rapid evaluation and straightforward application of Bayesian techniques for active learning. We summarize the capabilities of ACEpotentials.jl and demonstrate its strengths (simplicity, interpretability, robustness, performance) on a selection of prototypical atomistic modelling workflows.} }
@article{wrap179308, volume = {10}, number = {1}, month = {September}, author = {Luca M. Ghiringhelli and Carsten Baldauf and Tristan Bereau and Sandor Brockhauser and Christian Carbogno and Javad Chamanara and Stefano Cozzini and Stefano Curtarolo and Claudia Draxl and Shyam Dwaraknath and {\'A}d{\'a}m Fekete and James R. Kermode and Christoph T. Koch and Markus K{\"u}hbach and Alvin Noe Ladines and Patrick Lambrix and Maja-Olivia Himmer and Sergey V. Levchenko and Micael Oliveira and Adam Michalchuk and Ronald E. Miller and Berk Onat and Pasquale Pavone and Giovanni Pizzi and Benjamin Regler and Gian-Marco Rignanese and J{\"o}rg Schaarschmidt and Markus Scheidgen and Astrid Schneidewind and Tatyana Sheveleva and Chuanxun Su and Denis Usvyat and Omar Valsson and Christof W{\"o}ll and Matthias Scheffler}, title = {Shared metadata for data-centric materials science}, publisher = {Nature Publishing Group}, journal = {Scientific Data}, year = {2023}, url = {https://wrap.warwick.ac.uk/179308/}, abstract = {The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on ?Shared Metadata and Data Formats for Big-Data Driven Materials Science?. We start from an operative definition of metadata, and the features that a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them.} }
@article{wrap173534, volume = {247}, month = {April}, title = {Calculation of dislocation binding to helium-vacancy defects in tungsten using hybrid ab initio-machine learning methods}, author = {Petr Grigorev and Alexandra M. Goryaeva and Mihai-Cosmin Marinica and James R. Kermode and Thomas D. Swinburne}, publisher = {Pergamon-Elsevier Science Ltd}, year = {2023}, journal = {Acta Materialia}, url = {https://wrap.warwick.ac.uk/173534/}, abstract = {Calculations of dislocation-defect interactions are essential to model metallic strength, but the required system sizes are at or beyond ab initio limits. Current estimates thus have extrapolation or finite size errors that are very challenging to quantify. Hybrid methods offer a solution, embedding small ab initio simulations in an empirical medium. However, current implementations can only match mild elastic deformations at the ab initio boundary. We describe a robust method to employ linear-in-descriptor machine learning potentials as a highly flexible embedding medium, precisely matching dislocation migration pathways whilst keeping at least the elastic properties constant. This advanced coupling allows dislocations to cross the ab initio boundary in fully three dimensional defect geometries. Investigating helium and vacancy segregation to edge and screw dislocations in tungsten, we find long-range relaxations qualitatively change impurity-induced core reconstructions compared to those in short periodic supercells, even when multiple helium atoms are present. We also show that helium-vacancy complexes, considered to be the dominant configuration at low temperatures, have only a very weak binding to screw dislocations. These results are discussed in the context of recent experimental and theoretical studies. More generally, our approach opens a vast range of mechanisms to ab initio investigation and provides new reference data to both validate and improve interatomic potentials.} }
@article{wrap173662, volume = {4}, number = {1}, month = {February}, author = {Sascha Klawohn and James R. Kermode and Albert P. Bart{\'o}k}, note = {** From IOP Publishing via Jisc Publications Router ** History: received 19-10-2022; revised 15-11-2022; oa-requested 16-11-2022; accepted 29-11-2022; epub 16-02-2023; open-access 16-02-2023; ppub 01-03-2023. ** Licence for this article: http://creativecommons.org/licenses/by/4.0}, title = {Massively parallel fitting of Gaussian approximation potentials}, publisher = {IOP Publishing}, year = {2023}, journal = {Machine Learning: Science and Technology}, keywords = {Paper, Gaussian approximation potential, machine learning, interatomic potential, high performance computing, ScaLAPACK, distributed linear algebra, QR decomposition}, url = {https://wrap.warwick.ac.uk/173662/}, abstract = {We present a data-parallel software package for fitting Gaussian approximation potentials (GAPs) on multiple nodes using the ScaLAPACK library with MPI and OpenMP. Until now the maximum training set size for GAP models has been limited by the available memory on a single compute node. In our new implementation, descriptor evaluation is carried out in parallel with no communication requirement. The subsequent linear solve required to determine the model coefficients is parallelised with ScaLAPACK. Our approach scales to thousands of cores, lifting the memory limitation and also delivering substantial speedups. This development expands the applicability of the GAP approach to more complex systems as well as opening up opportunities for efficiently embedding GAP model fitting within higher-level workflows such as committee models or hyperparameter optimisation.} }
@article{wrap168190, volume = {8}, number = {1}, month = {August}, author = {James P. Darby and James R. Kermode and G{\'a}bor Cs{\'a}nyi}, note = { }, title = {Compressing local atomic neighbourhood descriptors}, publisher = {Nature Publishing Group UK}, year = {2022}, journal = {npj Computational Materials}, keywords = {Article, /639/301/1034/1035, /639/301/1034/1037, article}, url = {https://wrap.warwick.ac.uk/168190/}, abstract = {Many atomic descriptors are currently limited by their unfavourable scaling with the number of chemical elements S e.g. the length of body-ordered descriptors, such as the SOAP power spectrum (3-body) and the (ACE) (multiple body-orders), scales as (NS){\ensuremath{\nu}} where {\ensuremath{\nu}} + 1 is the body-order and N is the number of radial basis functions used in the density expansion. We introduce two distinct approaches which can be used to overcome this scaling for the SOAP power spectrum. Firstly, we show that the power spectrum is amenable to lossless compression with respect to both S and N, so that the descriptor length can be reduced from O(N2S2) to ONS. Secondly, we introduce a generalised SOAP kernel, where compression is achieved through the use of the total, element agnostic density, in combination with radial projection. The ideas used in the generalised kernel are equally applicably to any other body-ordered descriptors and we demonstrate this for the (ACSF).} }
@article{wrap167546, volume = {8}, number = {1}, month = {July}, author = {Liwei Zhang and Berk Onat and Genevi{\`e}ve Dusson and Adam McSloy and G. Anand and Reinhard J. Maurer and Christoph Ortner and James R. Kermode}, title = {Equivariant analytical mapping of first principles Hamiltonians to accurate and transferable materials models}, publisher = {Nature Publishing Group }, journal = {npj Computational Materials}, year = {2022}, url = {https://wrap.warwick.ac.uk/167546/}, abstract = {We propose a scheme to construct predictive models for Hamiltonian matrices in atomic orbital representation from ab initio data as a function of atomic and bond environments. The scheme goes beyond conventional tight binding descriptions as it represents the ab initio model to full order, rather than in two-centre or three-centre approximations. We achieve this by introducing an extension to the atomic cluster expansion (ACE) descriptor that represents Hamiltonian matrix blocks that transform equivariantly with respect to the full rotation group. The approach produces analytical linear models for the Hamiltonian and overlap matrices. Through an application to aluminium, we demonstrate that it is possible to train models from a handful of structures computed with density functional theory, and apply them to produce accurate predictions for the electronic structure. The model generalises well and is able to predict defects accurately from only bulk training data.} }
@article{wrap160065, volume = {558}, month = {January}, title = {Atomistic modelling of iodine-oxygen interactions in strained sub-oxides of zirconium}, author = {V. Podgurschi and D. J. M. King and J. Smutna and James R. Kermode and M. R. Wenman}, publisher = {Elsevier Science BV}, year = {2022}, journal = {Journal of Nuclear Materials}, url = {https://wrap.warwick.ac.uk/160065/}, abstract = {In water reactors, iodine stress corrosion cracking is considered the cause of pellet-cladding interaction failures, but the mechanism and chemistry are debated and the protective effect of oxygen is not understood. Density functional theory calculations were used to investigate the interaction of iodine and oxygen with bulk and surface Zr under applied hydrostatic strain (-2 \% to +3 \%) to simulate crack tip conditions in Zr to ZrO, using a variety of intermediate suboxides (ZrO, ZrO, ZrO and ZrO). The formation energy of an iodine octahedral interstitial in Zr was found to decrease with increasing hydrostatic strain, whilst the energy of an iodine substitutional defect was found to be relatively insensitive to strain. As the oxygen content increased, the formation energy of an iodine interstitial increased from 1.03 eV to 8.61 eV supporting the idea that oxygen has a protective effect. At the same time, a +3 \% tensile hydrostatic strain caused the iodine interstitial formation energy to decrease more in structures with higher oxygen content: 4.56 eV decrease in ZrO compared to 1.47 eV decrease for pure Zr. Comparison of the substitutional and interstitial energies of iodine, to the adsorption energy of iodine, in the presence of oxygen, shows the substitutional energy of iodine onto a Zr site is more favourable for all strains and even interstitial iodine is favourable between strains of +1-5\%. Although substitutional defects are preferred to octahedral interstitial defects, in the ordered suboxides, a 3 \% tensile strain significantly narrows the energy gap and higher strains could cause interstitial defects to form.} }
@article{wrap159497, volume = {5}, number = {10}, month = {October}, author = {Alexandra M. Goryaeva and Julien D{\'e}r{\`e}s and Clovis Lapointe and Petr Grigorev and Thomas D. Swinburne and James R. Kermode and Lisa Ventelon and Jacopo Baima and Mihai-Cosmin Marinica}, note = {{\copyright}2021 American Physical Society}, title = {Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W}, publisher = {American Physical Society}, year = {2021}, journal = {Physical Review Materials}, url = {https://wrap.warwick.ac.uk/159497/}, abstract = {Data-driven, or machine learning (ML), approaches have become viable alternatives to semiempirical methods to construct interatomic potentials, due to their capacity to accurately interpolate and extrapolate from first-principles simulations if the training database and descriptor representation of atomic structures are carefully chosen. Here, we present highly accurate interatomic potentials suitable for the study of dislocations, point defects, and their clusters in bcc iron and tungsten, constructed using a linear or quadratic input-output mapping from descriptor space. The proposed quadratic formulation, called quadratic noise ML, differs from previous approaches, being strongly preconditioned by the linear solution. The developed potentials are compared to a wide range of existing ML and semiempirical potentials, and are shown to have sufficient accuracy to distinguish changes in the exchange-correlation functional or pseudopotential in the underlying reference data, while retaining excellent transferability. The flexibility of the underlying approach is able to target properties almost unattainable by traditional methods, such as the negative divacancy binding energy in W or the shape and the magnitude of the Peierls barrier of the 1 2 ? 111 ? screw dislocation in both metals. We also show how the developed potentials can be used to target important observables that require large time-and-space scales unattainable with first-principles methods, though we emphasize the importance of thoughtful database design and degrees of nonlinearity of the descriptor space to achieve the appropriate passage of information to large-scale calculations. As a demonstration, we perform direct atomistic calculations of the relative stability of 1 2 ? 111 ? dislocations loops and three-dimensional C15 clusters in Fe and find the crossover between the formation energies of the two classes of interstitial defects occurs at around 40 self-interstitial atoms. We also compute the kink-pair formation energy of the 1 2 ? 111 ? screw dislocation in Fe and W, finding good agreement with density functional theory informed line tension models that indirectly measure those quantities. Finally, we exploit the excellent finite-temperature properties to compute vacancy formation free energies with full anharmonicity in thermal vibrations. The presented potentials thus open up many avenues for systematic investigation of free-energy landscape of defects with ab initio accuracy.} }
@article{wrap149515, volume = {103}, number = {3}, month = {March}, author = {Maciej Buze and James R. Kermode}, title = {Numerical-continuation-enhanced flexible boundary condition scheme applied to mode-I and mode-III fracture}, publisher = {American Physical Society}, journal = {Physical Review E}, year = {2021}, url = {https://wrap.warwick.ac.uk/149515/} }
@article{wrap148577, volume = {5}, number = {2}, title = {Quantitative prediction of the fracture toughness of amorphous carbon from atomic-scale simulations}, author = {S. Mostafa Khosrownejad and James R. Kermode and Lars Pastewka}, publisher = {American Physical Society}, year = {2021}, journal = {Physical Review Materials}, url = {https://wrap.warwick.ac.uk/148577/} }
@article{wrap143090, volume = {153}, number = {14}, month = {October}, author = {Berk Onat and Christoph Ortner and James R. Kermode}, title = {Sensitivity and dimensionality of atomic environment representations used for machine learning interatomic potentials}, publisher = {American Institute of Physics}, journal = {The Journal of Chemical Physics}, year = {2020}, url = {https://wrap.warwick.ac.uk/143090/}, abstract = {Faithfully representing chemical environments is essential for describing materials and molecules with machine learning approaches. Here, we present a systematic classification of these representations and then investigate (i) the sensitivity to perturbations and (ii) the effective dimensionality of a variety of atomic environment representations and over a range of material datasets. Representations investigated include atom centered symmetry functions, Chebyshev Polynomial Symmetry Functions (CHSF), smooth overlap of atomic positions, many-body tensor representation, and atomic cluster expansion. In area (i), we show that none of the atomic environment representations are linearly stable under tangential perturbations and that for CHSF, there are instabilities for particular choices of perturbation, which we show can be removed with a slight redefinition of the representation. In area (ii), we find that most representations can be compressed significantly without loss of precision and, further, that selecting optimal subsets of a representation method improves the accuracy of regression models built for a given dataset. } }
@article{wrap137320, volume = {22}, number = {21}, month = {June}, author = {Jacek R. Go{\l}{\ke}biowski and James R. Kermode and Peter D. Haynes and Arash A. Mostofi}, note = {** From PubMed via Jisc Publications Router}, title = {Atomistic QM/MM simulations of the strength of covalent interfaces in carbon nanotube-polymer composites}, publisher = {Royal Society of Chemistry}, year = {2020}, journal = {Physical chemistry chemical physics : PCCP}, pages = {12007--12014}, url = {https://wrap.warwick.ac.uk/137320/}, abstract = {We investigate the failure of carbon-nanotube/polymer composites by using a recently-developed hybrid quantum-mechanical/molecular-mechanical (QM/MM) approach to simulate nanotube pull-out from a cross-linked polyethene matrix. Our study focuses on the strength and failure modes of covalently-bonded nanotube-polymer interfaces based on amine, carbene and carboxyl functional groups and a [2+1] cycloaddition. We find that the choice of the functional group linking the polymer matrix to the nanotube determines the effective strength of the interface, which can be increased by up to 50\% (up to the limit dictated by the strength of the polymer backbone itself) by choosing groups with higher interfacial binding energy. We rank the functional groups presented in this work based on the strength of the resulting interface and suggest broad guidelines for the rational design of nanotube functionalisation for nanotube-polymer composites.} }
@article{wrap136477, volume = {32}, number = {30}, month = {May}, author = {James R. Kermode}, note = {** From IOP Publishing via Jisc Publications Router ** History: received 03-01-2020; rev-recd 09-03-2020; accepted 24-03-2020; epub 05-05-2020; open-access 05-05-2020; ppub 15-07-2020. ** Licence for this article: https://creativecommons.org/licenses/by/4.0/}, title = {f90wrap : an automated tool for constructing deep Python interfaces to modern Fortran codes}, publisher = {IOP Publishing}, year = {2020}, journal = {Journal of Physics: Condensed Matter}, keywords = {Paper, Computational and experimental methods, Fortran, Python, f2py, interoperability, interfacing, wrapping codes}, url = {https://wrap.warwick.ac.uk/136477/}, abstract = {Abstract: f90wrap is a tool to automatically generate Python extension modules which interface to Fortran libraries that makes use of derived types. It builds on the capabilities of the popular f2py utility by generating a simpler Fortran 90 interface to the original Fortran code which is then suitable for wrapping with f2py, together with a higher-level Pythonic wrapper that makes the existance of an additional layer transparent to the final user. f90wrap has been used to wrap a number of large software packages of relevance to the condensed matter physics community, including the QUIP molecular dynamics code and the CASTEP density functional theory code.} }
@misc{wrap132290, month = {February}, title = {Data for Hybrid quantum/classical study of hydrogen-decorated screw dislocations in tungsten : ultrafast pipe diffusion, core reconstruction, and effects on glide mechanism}, author = {Petr Grigorev and T. D. Swinburne and James R. Kermode}, publisher = {University of Warwick, School of Engineering}, year = {2020}, url = {https://wrap.warwick.ac.uk/132290/}, abstract = {The interaction of hydrogen (H) with dislocations in tungsten (W) must be understood in order to model the mechanical response of future plasma-facing materials for fusion applications. Here, hybrid quantum mechanics/molecular mechanics (QM/MM) simulations are employed to study the ?111? screw dislocation glide in W in the presence of H, using the virtual work principle to obtain energy barriers for dislocation glide, H segregation, and pipe diffusion. We provide a convincing validation of the QM/MM approach against full DFT energy-based methods. This is possible because the compact core and relatively weak elastic fields of ?111? screw dislocations allow them to be contained in periodic DFT supercells. We also show that H segregation stabilizes the split-core structure while leaving the Peierls barrier almost unchanged. Furthermore, we find an energy barrier of less than 0.05 eV for pipe diffusion of H along dislocation cores. Our quantum-accurate calculations provide important reference data for the construction of larger-scale material models.} }
@article{wrap133258, volume = {4}, month = {February}, title = {Hybrid quantum/classical study of hydrogen-decorated screw dislocations in tungsten : ultrafast pipe diffusion, core reconstruction, and effects on glide mechanism}, author = {Petr Grigorev and T. D. Swinburne and James R. Kermode}, publisher = {American Physical Society}, year = {2020}, journal = {Physical Review Materials}, url = {https://wrap.warwick.ac.uk/133258/}, abstract = {The interaction of hydrogen (H) with dislocations in tungsten (W) must be understood in order to model the mechanical response of future plasma-facing materials for fusion applications. Here, hybrid quantum mechanics/molecular mechanics (QM/MM) simulations are employed to study the ?111? screw dislocation glide in W in the presence of H, using the virtual work principle to obtain energy barriers for dislocation glide, H segregation, and pipe diffusion. We provide a convincing validation of the QM/MM approach against full DFT energy-based methods. This is possible because the compact core and relatively weak elastic fields of ?111? screw dislocations allow them to be contained in periodic DFT supercells. We also show that H segregation stabilizes the split-core structure while leaving the Peierls barrier almost unchanged. Furthermore, we find an energy barrier of less than 0.05 eV for pipe diffusion of H along dislocation cores. Our quantum-accurate calculations provide important reference data for the construction of larger-scale material models.} }
@article{wrap116331, volume = {3}, number = {4}, month = {April}, author = {F. Bianchini and A. Glielmo and James R. Kermode and A. De Vita}, title = {Enabling QM-accurate simulation of dislocation motion in {\ensuremath{\gamma}}?Ni and {\ensuremath{\alpha}}?Fe using a hybrid multiscale approach}, publisher = {American Physical Society}, journal = {Physical Review Materials}, year = {2019}, url = {https://wrap.warwick.ac.uk/116331/}, abstract = {We present an extension of the ?learn on the fly? method to the study of the motion of dislocations in metallic systems, developed with the aim of producing information-efficient force models that can be systematically validated against reference QM calculations. Nye tensor analysis is used to dynamically track the quantum region centered at the core of a dislocation, thus enabling quantum mechanics/molecular mechanics simulations. The technique is used to study the motion of screw dislocations in Ni-Al systems, relevant to plastic deformation in Ni-based alloys, at a variety of temperature/strain conditions. These simulations reveal only a moderate spacing ( {$\sim$} 5 {\rA} ) between Shockley partial dislocations, at variance with the predictions of traditional molecular dynamics (MD) simulation using interatomic potentials, which yields a much larger spacing in the high stress regime. The discrepancy can be rationalized in terms of the elastic properties of an hcp crystal, which influence the behavior of the stacking fault region between Shockley partial dislocations. The transferability of this technique to more challenging systems is addressed, focusing on the expected accuracy of such calculations. The bcc {\ensuremath{\alpha}} ? Fe phase is a prime example, as its magnetic properties at the open surfaces make it particularly challenging for embedding-based QM/MM techniques. Our tests reveal that high accuracy can still be obtained at the core of a dislocation, albeit at a significant computational cost for fully converged results. However, we find this cost can be reduced by using a machine learning approach to progressively reduce the rate of expensive QM calculations required during the dynamical simulations, as the size of the QM database increases.} }
@misc{wrap115558, month = {March}, title = {Data for Enabling QM-accurate simulation of dislocation motion in gamma-Ni and alpha-Fe using a hybrid multiscale approach}, author = {Federico Bianchini and Aldo Glielmo and James R. Kermode and Alessandro De Vita}, publisher = {University of Warwick, School of Engineering}, year = {2019}, url = {https://wrap.warwick.ac.uk/115558/}, abstract = {Molecular dynamics trajectories supporting calculations reported in the accompanying article.} }
@article{wrap114695, volume = {150}, number = {9}, title = {A preconditioning scheme for minimum energy path finding methods}, author = {Stela Makri and Christoph Ortner and James R. Kermode}, publisher = {American Institute of Physics}, year = {2019}, journal = {The Journal of Chemical Physics}, url = {https://wrap.warwick.ac.uk/114695/}, abstract = {Popular methods for identifying transition paths between energy minima, such as the nudged elastic band and string methods, typically do not incorporate potential energy curvature information, leading to slow relaxation to the minimum energy path for typical potential energy surfaces encountered in molecular simulation. We propose a preconditioning scheme which, combined with a new adaptive time step selection algorithm, substantially reduces the computational cost of transition path finding algorithms. We demonstrate the improved performance of our approach in a range of examples including vacancy and dislocation migration modeled with both interatomic potentials and density functional theory.} }
@article{wrap112164, volume = {8}, number = {4}, month = {December}, author = {Albert P. Bart{\'o}k and James R. Kermode and Noam Bernstein and G{\'a}bor Cs{\'a}nyi}, title = {Machine learning a general-purpose interatomic potential for silicon}, publisher = {American Physical Society}, journal = {Physical Review X}, year = {2018}, url = {https://wrap.warwick.ac.uk/112164/}, abstract = {The success of first-principles electronic-structure calculation for predictive modeling in chemistry, solid-state physics, and materials science is constrained by the limitations on simulated length scales and timescales due to the computational cost and its scaling. Techniques based on machine-learning ideas for interpolating the Born-Oppenheimer potential energy surface without explicitly describing electrons have recently shown great promise, but accurately and efficiently fitting the physically relevant space of configurations remains a challenging goal. Here, we present a Gaussian approximation potential for silicon that achieves this milestone, accurately reproducing density-functional-theory reference results for a wide range of observable properties, including crystal, liquid, and amorphous bulk phases, as well as point, line, and plane defects. We demonstrate that this new potential enables calculations such as finite-temperature phase-boundary lines, self-diffusivity in the liquid, formation of the amorphous by slow quench, and dynamic brittle fracture, all of which are very expensive with a first-principles method. We show that the uncertainty quantification inherent to the Gaussian process regression framework gives a qualitative estimate of the potential?s accuracy for a given atomic configuration. The success of this model shows that it is indeed possible to create a useful machine-learning-based interatomic potential that comprehensively describes a material on the atomic scale and serves as a template for the development of such models in the future. } }
@article{wrap111827, volume = {149}, number = {22}, month = {December}, author = {Jacek R. Go{\l}{\ke}biowski and James R. Kermode and Arash A. Mostofi and Peter D. Haynes}, title = {Multiscale simulations of critical interfacial failure in carbon nanotube-polymer composites}, publisher = {American Institute of Physics}, journal = {The Journal of Chemical Physics}, year = {2018}, keywords = {DataAyDn DataSy Datai}, url = {https://wrap.warwick.ac.uk/111827/}, abstract = {Computational investigation of interfacial failure in composite materials is challenging because it is inherently multi-scale: the bond-breaking processes that occur at the covalently bonded interface and initiate failure involve quantum mechanical phenomena, yet the mechanisms by which external stresses are transferred through the matrix occur on length and time scales far in excess of anything that can be simulated quantum mechanically. In this work, we demonstrate and validate an adaptive quantum mechanics (QM)/molecular mechanics simulation method that can be used to address these issues and apply it to study critical failure at a covalently bonded carbon nanotube (CNT)-polymer interface. In this hybrid approach, the majority of the system is simulated with a classical forcefield, while areas of particular interest are identified on-the-fly and atomic forces in those regions are updated based on QM calculations. We demonstrate that the hybrid method results are in excellent agreement with fully QM benchmark simulations and offers qualitative insights missing from classical simulations. We use the hybrid approach to show how the chemical structure at the CNT-polymer interface determines its strength, and we propose candidate chemistries to guide further experimental work in this area. } }
@article{wrap111053, volume = {22}, month = {December}, title = {Accelerating multiscale modelling of fluids with on-the-fly Gaussian process regression}, author = {David Stephenson and James R. Kermode and Duncan A. Lockerby}, publisher = {Springer}, year = {2018}, journal = {Microfluidics and Nanofluidics}, keywords = {DataAyDn DataSn}, url = {https://wrap.warwick.ac.uk/111053/}, abstract = {We present a scheme for accelerating hybrid continuum-atomistic models in multiscale fluidic systems by using Gaussian process regression as a surrogate model for computationally expensive molecular dynamics simulations. Using Gaussian process regression, we are able to accurately predict atomic-scale information purely by consideration of the macroscopic continuum-model inputs and outputs and judge on the fly whether the uncertainty of our prediction is at an acceptable level, else a new molecular simulation is performed to continually augment the database, which is never required to be complete. This provides a substantial improvement over the current generation of hybrid methods, which often require many similar atomistic simulations to be performed, discarding information after it is used once. We apply our hybrid scheme to nano-confined unsteady flow through a high-aspect-ratio converging?diverging channel, and make comparisons between the new scheme and full molecular dynamics simulations for a range of uncertainty thresholds and initial databases. For low thresholds, our hybrid solution is highly accurate{--}around that of thermal noise. As the uncertainty threshold is raised, the accuracy of our scheme decreases and the computational speed-up increases (relative to a full molecular simulation), enabling the compromise between accuracy and efficiency to be tuned. The speed-up of our hybrid solution ranges from an order of magnitude, with no initial database, to cases where an extensive initial database ensures no new MD simulations are required.} }
@article{wrap120435, volume = {22}, number = {12}, month = {December}, author = {David Stephenson and James R. Kermode and Duncan A. Lockerby}, title = {Accelerating multiscale modelling of fluids with on-the-fly Gaussian process regression}, publisher = {Springer}, journal = {Microfluidics and Nanofluidics}, year = {2018}, url = {https://wrap.warwick.ac.uk/120435/} }
@article{wrap106587, volume = {232}, month = {November}, author = {H. Lambert and Adam Fekete and James R. Kermode and A. De Vita}, title = {Imeall : a computational framework for the calculation of the atomistic properties of grain boundaries}, publisher = {Elsevier Science BV}, journal = {Computer Physics Communications}, pages = {256--263}, year = {2018}, keywords = {DataAyDn DataSy Datal}, url = {https://wrap.warwick.ac.uk/106587/}, abstract = {We describe the Imeall package for the calculation and indexing of atomistic properties of grain boundaries in materials. The package provides a structured database for the storage of atomistic structures and their associated properties, equipped with a programmable application interface to interatomic potential calculators. The database adopts a general indexing system that allows storing arbitrary grain boundary structures for any crystalline material. The usefulness of the Imeall package is demonstrated by computing, storing, and analysing relaxed grain boundary structures for a dense range of low index orientation axis symmetric tilt and twist boundaries in -iron for various interatomic potentials. The package?s capabilities are further demonstrated by carrying out automated structure generation, dislocation analysis, interstitial site detection, and impurity segregation energies across the grain boundary range. All computed atomistic properties are exposed via a web framework, providing open access to the grain boundary repository and the analytic tools suite.} }
@article{wrap98590, volume = {53}, month = {May}, author = {O. Barrera and D. Bombac and Y. Chen and T. D. Daff and E. Galindo-Nava and P. Gong and D. Haley and R. Horton and I. Katzarov and James R. Kermode and C. Liverani and M. Stopher and F. Sweeney}, title = {Understanding and mitigating hydrogen embrittlement of steels : a review of experimental, modelling and design progress from atomistic to continuum}, publisher = {Springer}, journal = {Journal of Materials Science}, pages = {6251--6290}, year = {2018}, url = {https://wrap.warwick.ac.uk/98590/}, abstract = {Hydrogen embrittlement is a complex phenomenon, involving several length- and timescales, that affects a large class of metals. It can significantly reduce the ductility and load-bearing capacity and cause cracking and catastrophic brittle failures at stresses below the yield stress of susceptible materials. Despite a large research effort in attempting to understand the mechanisms of failure and in developing potential mitigating solutions, hydrogen embrittlement mechanisms are still not completely understood. There are controversial opinions in the literature regarding the underlying mechanisms and related experimental evidence supporting each of these theories. The aim of this paper is to provide a detailed review up to the current state of the art on the effect of hydrogen on the degradation of metals, with a particular focus on steels. Here, we describe the effect of hydrogen in steels from the atomistic to the continuum scale by reporting theoretical evidence supported by quantum calculation and modern experimental characterisation methods, macroscopic effects that influence the mechanical properties of steels and established damaging mechanisms for the embrittlement of steels. Furthermore, we give an insight into current approaches and new mitigation strategies used to design new steels resistant to hydrogen embrittlement.} }
@article{wrap96346, volume = {3}, number = {12}, month = {December}, author = {Albert P. Bart{\'o}k and Sandip De and Carl Poelking and Noam Bernstein and James R. Kermode and G{\'a}bor Cs{\'a}nyi and Michele Ceriotti}, title = {Machine learning unifies the modeling of materials and molecules}, publisher = {American Association for the Advancement of Science}, journal = {Science Advances}, year = {2017}, keywords = {DataAyDn DataSy Datai Datar}, url = {https://wrap.warwick.ac.uk/96346/}, abstract = {Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a local description of chemical environments and Bayesian statistical learning, provides a unified framework to predict atomic-scale properties. It captures the quantum mechanical effects governing the complex surface reconstructions of silicon, predicts the stability of different classes of molecules with chemical accuracy, and distinguishes active and inactive protein ligands with more than 99\% reliability. The universality and the systematic nature of our framework provide new insight into the potential energy surface of materials and molecules. } }
@article{wrap92999, volume = {96}, month = {October}, title = {Computing energy barriers for rare events from hybrid quantum/classical simulations through the virtual work principle}, author = {Thomas Swinburne and James R. Kermode}, publisher = {American Physical Society}, year = {2017}, journal = {Physical Review B (Condensed Matter and Materials Physics)}, url = {https://wrap.warwick.ac.uk/92999/}, abstract = {Hybrid quantum/classical techniques can flexibly couple ab initio simulations to an empirical or elastic medium to model materials systems that cannot be contained in small periodic supercells. However, due to electronic nonlocality, a total energy cannot be defined, meaning energy barriers cannot be calculated. We provide a general solution using the principle of virtual work in a modified nudged elastic band algorithm. Our method enables ab initio calculations of the kink formation energy for (100 ? edge dislocations in molybdenum and lattice trapping barriers to brittle fracture in silicon.} }
@misc{wrap91747, month = {September}, title = {Data for Computing energy barriers for rare events from hybrid quantum/classical simulations through the virtual work principle}, author = {T. D. Swinburne and James R. Kermode}, publisher = {University of Warwick, School of Engineering}, year = {2017}, url = {https://wrap.warwick.ac.uk/91747/}, abstract = {Hybrid quantum/classical techniques can flexibly couple ab initio simulations to an empirical or elastic medium to model materials systems that cannot be contained in small periodic supercells. However, due to electronic nonlocality, a total energy cannot be defined, meaning energy barriers cannot be calculated. We provide a general solution using the principle of virtual work in a modified nudged elastic band algorithm. Our method enables ab initio calculations of the kink formation energy for (100 ? edge dislocations in molybdenum and lattice trapping barriers to brittle fracture in silicon.} }
@article{wrap90399, volume = {8}, number = {1}, month = {July}, author = {Giorgio Sernicola and Tommaso Giovannini and Punitbhai Patel and James R. Kermode and Daniel S. Balint and T. Ben Britton and Finn Giuliani}, title = {In situ stable crack growth at the micron scale}, publisher = {Nature Publishing Group}, journal = {Nature Communications}, year = {2017}, keywords = {Dataaydn datasy datal}, url = {https://wrap.warwick.ac.uk/90399/}, abstract = {Grain boundaries typically dominate fracture toughness, strength and slow crack growth in ceramics. To improve these properties through mechanistically informed grain boundary engineering, precise measurement of the mechanical properties of individual boundaries is essential, although it is rarely achieved due to the complexity of the task. Here we present an approach to characterize fracture energy at the lengthscale of individual grain boundaries and demonstrate this capability with measurement of the surface energy of silicon carbide single crystals. We perform experiments using an in situ scanning electron microscopy-based double cantilever beam test, thus enabling viewing and measurement of stable crack growth directly. These experiments correlate well with our density functional theory calculations of the surface energy of the same silicon carbide plane. Subsequently, we measure the fracture energy for a bi-crystal of silicon carbide, diffusion bonded with a thin glassy layer. } }
@misc{wrap134816, month = {March}, title = {Data for In situ stable crack growth at the micron scale}, author = {James R. Kermode and Giorgio Sernicola and Tommaso Giovannini and Punitbhai Patel and Daniel S. Balint and Ben Britton and Finn Giuliani}, publisher = {University of Warwick, Warwick Manufacturing Group}, year = {2017}, url = {https://wrap.warwick.ac.uk/134816/}, abstract = {Grain boundaries typically dominate fracture toughness, strength and slow crack growth in ceramics. To improve these properties through mechanistically informed grain boundary engineering, precise measurement of the mechanical properties of individual boundaries is essential, although it is rarely achieved due to the complexity of the task. Here we present an approach to characterize fracture energy at the lengthscale of individual grain boundaries and demonstrate this capability with measurement of the surface energy of silicon carbide single crystals. We perform experiments using an in situ scanning electron microscopy-based double cantilever beam test, thus enabling viewing and measurement of stable crack growth directly. These experiments correlate well with our density functional theory calculations of the surface energy of the same silicon carbide plane. Subsequently, we measure the fracture energy for a bi-crystal of silicon carbide, diffusion bonded with a thin glassy layer.} }
@article{wrap87141, title = {The atomic simulation environment {--} a python library for working with atoms}, author = {Ask Larsen and Jens Mortensen and Jakob Blomqvist and Ivano Castelli and Rune Christensen and Marcin Dulak and Jesper Friis and Michael Groves and Bjork Hammer and Cory Hargus and Eric Hermes and Paul A. Jennings and Peter Jensen and James R. Kermode and John Kitchin and Esben Kolsbjerg and Joseph Kubal and Kristen Kaasbjerg and Steen Lysgaard and Jon Maronsson and Tristan Maxson and Thomas Olsen and Lars Pastewka and Andrew Peterson and Carsten Rostgaard and Jakob Schi{\o}tz and Ole Sch{\"u}tt and Mikkel Strange and Kristian Thygesen and Tejs Vegge and Lasse Vilhelmsen and Michael Walter and Zhenhua Zeng and Karsten Wedel Jacobsen}, publisher = {Institute of Physics Publishing Ltd.}, year = {2017}, journal = {Journal of Physics: Condensed Matter}, keywords = {DataAyDn DataSx}, url = {https://wrap.warwick.ac.uk/87141/}, abstract = {The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple "for-loop" construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations. } }
@article{wrap68012, volume = {115}, number = {16}, month = {August}, author = {Marco Caccin and Zhenwei Li and James R. Kermode and Alessandro De Vita}, title = {A framework for machine-learning-augmented multiscale atomistic simulations on parallel supercomputers}, publisher = {John Wiley \& Sons}, year = {2016}, journal = {International Journal of Quantum Chemistry}, pages = {1129--1139}, keywords = {machine learning; quantum mechanics/molecular mechanics; HPC; fracture; partitioning}, url = {https://wrap.warwick.ac.uk/68012/}, abstract = {Recent advances in quantum mechanical (QM)-based molecular dynamics (MD) simulations have used machine-learning (ML) to predict, rather than recalculate, QM-accurate forces in atomic configurations sufficiently similar to previously encountered ones. Here, we discuss how ML approaches can be deployed within large-scale QM/MM materials simulations on massively parallel supercomputers, making QM zones of {$\gtrsim$}1000 atoms routinely attainable. We argue that the ML approach allows computational effort to be concentrated on the most chemically active subregions of the QM zone, significantly improving the overall efficiency of the simulation. We thus propose a novel method to partition large QM regions into multiple subregions, which can be computed in parallel to achieve optimal scaling. Then we review a recently proposed QM/ML MD scheme (Z. Li, J.R. Kermode, A. De Vita Phys. Rev. Lett., 2015, 114, 096405), discussing how this could be efficiently combined with QM-zone partitioning.} }
@misc{wrap78579, month = {April}, title = {Data for A universal preconditioner for simulating condensed phase materials}, author = {David Packwood and James R. Kermode and Letif Mones and Noam Bernstein and John Woolley and Nicholas Gould and Christoph Ortner and Gabor Csanyi}, publisher = {University of Warwick, School of Engineering}, year = {2016}, url = {https://wrap.warwick.ac.uk/78579/}, abstract = {We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.} }
@article{wrap78334, volume = {24}, number = {4}, month = {April}, author = {Federico Bianchini and James R. Kermode and Alessandro De Vita}, title = {Modelling defects in Ni-Al with EAM and DFT calculations}, publisher = {Institute of Physics Publishing Ltd.}, journal = {Modelling and Simulation in Materials Science and Engineering}, year = {2016}, url = {https://wrap.warwick.ac.uk/78334/}, abstract = {We present detailed comparisons between the results of embedded atom model (EAM) and density functional theory (DFT) calculations on defected Ni alloy systems. We find that the EAM interatomic potentials reproduce low-temperature structural properties in both the {\ensuremath{\gamma}} and \$\{\{{$\backslash$}gamma\}{\^{ }}\{{$\backslash$}prime\}\}\$ phases, and yield accurate atomic forces in bulk-like configurations even at temperatures as high as {\texttt{\char126}}1200 K. However, they fail to describe more complex chemical bonding, in configurations including defects such as vacancies or dislocations, for which we observe significant deviations between the EAM and DFT forces, suggesting that derived properties such as (free) energy barriers to vacancy migration and dislocation glide may also be inaccurate. Testing against full DFT calculations further reveals that these deviations have a local character, and are typically severe only up to the first or second neighbours of the defect. This suggests that a QM/MM approach can be used to accurately reproduce QM observables, fully exploiting the EAM potential efficiency in the MM zone. This approach could be easily extended to ternary systems for which developing a reliable and fully transferable EAM parameterisation would be extremely challenging e.g. Ni alloy model systems with a W or Re-containing QM zone. } }
@article{wrap77127, volume = {311}, month = {April}, author = {Manuel Aldegunde and James R. Kermode and Nicholas Zabaras }, title = {Development of an exchange?correlation functional with uncertainty quantification capabilities for density functional theory}, publisher = {Academic Press Inc. Elsevier Science}, journal = {Journal of Computational Physics}, pages = {173--195}, year = {2016}, url = {https://wrap.warwick.ac.uk/77127/}, abstract = {This paper presents the development of a new exchange?correlation functional from the point of view of machine learning. Using atomization energies of solids and small molecules, we train a linear model for the exchange enhancement factor using a Bayesian approach which allows for the quantification of uncertainties in the predictions. A relevance vector machine is used to automatically select the most relevant terms of the model. We then test this model on atomization energies and also on bulk properties. The average model provides a mean absolute error of only 0.116 eV for the test points of the G2/97 set but a larger 0.314 eV for the test solids. In terms of bulk properties, the prediction for transition metals and monovalent semiconductors has a very low test error. However, as expected, predictions for types of materials not represented in the training set such as ionic solids show much larger errors.} }
@misc{wrap78256, month = {April}, title = {Data for Modelling defects in Ni-Al with EAM and DFT calculations }, author = {Federico Bianchini and James R. Kermode and Alessandro De Vita}, publisher = {University of Warwick, School of Engineering}, year = {2016}, url = {https://wrap.warwick.ac.uk/78256/}, abstract = {We present detailed comparisons between the results of embedded atom model (EAM) and density functional theory (DFT) calculations on defected Ni alloy systems. We find that the EAM interatomic potentials reproduce low-temperature structural properties in both the {\ensuremath{\gamma}} and \$\{\{{$\backslash$}gamma\}{\^{ }}\{{$\backslash$}prime\}\}\$ phases, and yield accurate atomic forces in bulk-like configurations even at temperatures as high as {\texttt{\char126}}1200 K. However, they fail to describe more complex chemical bonding, in configurations including defects such as vacancies or dislocations, for which we observe significant deviations between the EAM and DFT forces, suggesting that derived properties such as (free) energy barriers to vacancy migration and dislocation glide may also be inaccurate. Testing against full DFT calculations further reveals that these deviations have a local character, and are typically severe only up to the first or second neighbours of the defect. This suggests that a QM/MM approach can be used to accurately reproduce QM observables, fully exploiting the EAM potential efficiency in the MM zone. This approach could be easily extended to ternary systems for which developing a reliable and fully transferable EAM parameterisation would be extremely challenging e.g. Ni alloy model systems with a W or Re-containing QM zone.} }
@article{wrap78515, volume = {144}, number = {16}, month = {April}, author = {David Packwood and James R. Kermode and Letif Mones and Noam Bernstein and John Woolley and Nicholas Gould and Christoph Ortner and Gabor Csanyi}, title = {A universal preconditioner for simulating condensed phase materials}, publisher = {American Institute of Physics}, journal = {Journal of Chemical Physics}, year = {2016}, url = {https://wrap.warwick.ac.uk/78515/}, abstract = {We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes. } }
@article{wrap72523, volume = {115}, number = {13}, month = {September}, author = {James R. Kermode and Anna Gleizer and Guy Kovel and Lars Pastewka and Gabor Csanyi and Dov Sherman and Alessandro De Vita}, title = {Low speed crack propagation via kink formation and advance on the silicon (110) cleavage plane}, publisher = {American Physical Society}, year = {2015}, journal = {Physical Review Letters}, pages = {1--5}, url = {https://wrap.warwick.ac.uk/72523/}, abstract = {We present density functional theory based atomistic calculations predicting that slow fracturing of silicon is possible at any chosen crack propagation speed under suitable temperature and load conditions. We also present experiments demonstrating fracture propagation on the Si(110) cleavage plane in the {\texttt{\char126}}100 m/s speed range, consistent with our predictions. These results suggest that many other brittle crystals could be broken arbitrarily slowly in controlled experiments.} }
@article{wrap66611, volume = {Volume 114}, month = {March}, title = {Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces}, author = {Zhenwei Li and James R. Kermode and Alessandro De Vita}, publisher = {American Physical Society}, year = {2015}, journal = {Physical Review Letters}, url = {https://wrap.warwick.ac.uk/66611/}, abstract = {We present a molecular dynamics scheme which combines first-principles and machine-learning (ML) techniques in a single information-efficient approach. Forces on atoms are either predicted by Bayesian inference or, if necessary, computed by on-the-fly quantum-mechanical (QM) calculations and added to a growing ML database, whose completeness is, thus, never required. As a result, the scheme is accurate and general, while progressively fewer QM calls are needed when a new chemical process is encountered for the second and subsequent times, as demonstrated by tests on crystalline and molten silicon.} }
@article{wrap66305, volume = {142}, month = {February}, title = {Accuracy of buffered-force QM/MM simulations of silica}, author = {Anke Peguiron and Lucio Colombi Ciacchi and Alessandro De Vita and James R. Kermode and Gianpietro Moras}, publisher = {American Institute of Physics}, year = {2015}, journal = {Journal of Chemical Physics}, url = {https://wrap.warwick.ac.uk/66305/}, abstract = {We report comparisons between energy-based quantum mechanics/molecular mechanics (QM/MM) and buffered force-based QM/MM simulations in silica. Local quantities{--}such as density of states, charges, forces, and geometries{--}calculated with both QM/MM approaches are compared to the results of full QM simulations. We find the length scale over which forces computed using a finite QM region converge to reference values obtained in full quantum-mechanical calculations is {$\sim$}10 {\rA} rather than the {$\sim$}5 {\rA} previously reported for covalent materials such as silicon. Electrostatic embedding of the QM region in the surrounding classical point charges gives only a minor contribution to the force convergence. While the energy-based approach provides accurate results in geometry optimizations of point defects, we find that the removal of large force errors at the QM/MM boundary provided by the buffered force-based scheme is necessary for accurate constrained geometry optimizations where Si?O bonds are elongated and for finite-temperature molecular dynamics simulations of crack propagation. Moreover, the buffered approach allows for more flexibility, since special-purpose QM/MM coupling terms that link QM and MM atoms are not required and the region that is treated at the QM level can be adaptively redefined during the course of a dynamical simulation.} }
@article{wrap66441, volume = {191}, number = {1}, month = {February}, author = {Erik Bitzek and James R. Kermode and Peter Gumbsch}, title = {Atomistic aspects of fracture}, publisher = {Springer}, year = {2015}, journal = {International Journal of Fracture}, pages = {13--30}, url = {https://wrap.warwick.ac.uk/66441/}, abstract = {Any fracture process ultimately involves the rupture of atomic bonds. Processes at the atomic scale therefore critically influence the toughness and overall fracture behavior of materials. Atomistic simulation methods including large-scale molecular dynamics simulations with classical potentials, density functional theory calculations and advanced concurrent multiscale methods have led to new insights e.g. on the role of bond trapping, dynamic effects, crack- microstructure interactions and chemical aspects on the fracture toughness and crack propagation patterns in metals and ceramics. This review focuses on atomistic aspects of fracture in crystalline materials where significant advances have been achieved over the last ten years and provides an outlook on future perspectives for atomistic modelling of fracture.} }
@misc{wrap67696, title = {A Python interface to CASTEP}, author = {Greg Corbett and James R. Kermode and Dominik Bogdan Jochym and Keith Refson}, address = {Rutherford Appleton Laboratory Technical Reports}, publisher = {Rutherford Appleton Laboratory}, year = {2015}, keywords = {fortran, python, castep}, url = {https://wrap.warwick.ac.uk/67696/}, abstract = {This report documents a successful pilot project and feasibility study for adding a Python interface to the CASTEP first principles materials modelling code. Such an interface will allow the growing Python community within the scientific computing field access to CASTEP functionality, without the requirement of learning Fortran. To achieve this, changes have been made to the CASTEP source code to allow: - Serially re-entrant calling of a major task routine, specifically electronic\_minimisation(). - Automated generation of a Python interface. The reasoning behind these changes has been documented and coding practices that may hinder a full move to serial re-entrancy in future have been noted. To demonstrate the success of the project, top-level task control logic has been written in Python -- using the Fortran 2003 computational core to perform multiple calls to electronic\_minimisation().} }
@article{wrap64442, volume = {189}, number = {1}, month = {September}, author = {Gaurav Singh and James R. Kermode and Alessandro De Vita and Robert W. Zimmerman}, title = {Validity of linear elasticity in the crack-tip region of ideal brittle solids}, publisher = {Springer}, year = {2014}, journal = {International Journal of Fracture}, pages = {103--110}, url = {https://wrap.warwick.ac.uk/64442/}, abstract = {It is a well known that, according to classical elasticity, the stress in the crack-tip region is singular, which has led to a debate over the validity of linear elasticity in this region. In this work, comparisons of finite and small strain theories have been made in the crack-tip region of a brittle crystal to comment on the validity of linear elasticity in the crack tip region. We find that linear elasticity is capable of accurately defining the state of stress very close ({$\sim$}1nm) to a static crack tip.} }
@article{wrap64443, volume = {Volume 3}, month = {June}, author = {James R. Kermode and Giovanni Peralta and Zhenwei Li and Alessandro De Vita}, booktitle = {20th European Conference on Fracture (ECF20)}, title = {Multiscale modelling of materials chemomechanics : brittle fracture of oxides and semiconductors}, publisher = {Elsevier B.V.}, year = {2014}, journal = {Procedia Materials Science}, pages = {1681--1686}, keywords = {atomistic,hybrid,mm simulation,multiscale,qm}, url = {https://wrap.warwick.ac.uk/64443/}, abstract = {Fracture is one of the most challenging ?multi-scale? problems to model: since crack propagation is driven by the concentration of a long-range stress field at an atomically sharp crack tip, an accurate description of the chemical processes occurring in the small crack tip region is therefore essential, as is the inclusion of a much larger region in the model systems. Both these requirements can be met by combining a quantum mechanical description of the crack tip with a classical atomistic model that captures the long-range elastic behaviour of the surrounding crystal matrix. Examples of the application of these techniques to fracture problems include: low-speed dynamical fracture instabilities in silicon; interactions between moving cracks and material defects such as dislocations or impurities; the crossover from thermally activated to catastrophic fracture; very slow crack propagation via kink formation and migration; and chemically activated fracture, where cracks advance under the concerted action of stress and corrosion by chemical species such as oxygen or water.} }
@article{wrap64444, volume = {Volume 112}, number = {Number 11}, month = {March}, author = {Anna Gleizer and Giovanni Peralta and James R. Kermode and Alessandro De Vita and Dov Sherman}, title = {Dissociative chemisorption of O2 inducing stress corrosion cracking in silicon crystals}, publisher = {American Physical Society}, journal = {Physical Review Letters}, year = {2014}, url = {https://wrap.warwick.ac.uk/64444/}, abstract = {Fracture experiments to evaluate the cleavage energy of the (110)[1-10] and (111)[11-2] cleavage systems in silicon at room temperature and humidity give 2.7 +/- 0.3 and 2.2 +/-0.2 J/m{\^{ }}2, respectively, lower than any previous measurement and inconsistent with density functional theory (DFT) surface energy calculations of 3.46 and 2.88 J/m{\^{ }}2. However, in an inert gas environment, we measure values of 3.5 +/- 0.2 and 2.9 +/- 0.2 J/m{\^{ }}2, consistent with DFT, that suggest a previously undetected stress corrosion cracking scenario for Si crack initiation in room conditions. This is fully confirmed by hybrid quantum-mechanics?molecular-mechanics calculations.} }
@article{wrap64446, volume = {Volume 4}, title = {Macroscopic scattering of cracks initiated at single impurity atoms}, author = {James R. Kermode and L. Ben-Bashat and F. Atrash and J. J. Cilliers and D. Sherman and Alessandro De Vita}, publisher = {Nature Publishing Group}, year = {2013}, journal = {Nature Communications}, url = {https://wrap.warwick.ac.uk/64446/}, abstract = {Brittle crystals, such as coloured gems, have long been known to cleave with atomically smooth fracture surfaces, despite being impurity laden, suggesting that isolated atomic impurities do not generally cause cracks to deflect. Whether cracks can ever deviate when hitting an atomic defect, and if so how they can go straight in real brittle crystals, which always contain many such defects, is still an open question. Here we carry out multiscale molecular dynamics simulations and high-resolution experiments on boron-doped silicon, revealing that cracks can be deflected by individual boron atoms. The process, however, requires a characteristic minimum time, which must be less than the time spent by the crack front at the impurity site. Deflection therefore occurs at low crack speeds, leading to surface ridges which intensify when the boron-dopage level is increased, whereas fast-moving cracks are dynamically steered away from being deflected, yielding smooth cleavage surfaces.} }
@incollection{wrap64453, volume = {Volume 9}, month = {November}, author = {Gianpietro Moras and Rathin Choudhury and James R. Kermode and Gabor Csanyi and Mike C. Payne and Alessandro De Vita}, booktitle = {Trends in Computational Nanomechanics : Transcending Length and Time Scales}, editor = {Traian Dumitrica}, title = {Hybrid quantum/classical modeling of material systems : the learn on the fly molecular dynamics scheme}, publisher = {Springer}, year = {2010}, journal = {Trends Comput. Nanomechanics Transcending Length Time Scales}, pages = {1--23}, url = {https://wrap.warwick.ac.uk/64453/}, abstract = {The atomistic simulation of many processes in materials involves large-size model systems where different levels of complexity need to be described simultaneously. While accurate quantum mechanical simulations of large-size systems are usually not affordable, less computationally intensive classical models are not suitable for the description of many chemical processes. Hybrid (quantum/classical) modelling schemes are required in these circumstances. Here, we describe the ?Learn on the fly? (LOTF) hybrid molecular dynamics scheme. Some technical aspects of this technique are illustrated through a series of examples of its applications to multiscale processes in silicon } }
@article{wrap64448, volume = {Volume 133}, number = {Number 9}, title = {A first principles based polarizable O(N) interatomic force field for bulk silica}, author = {James R. Kermode and Silva Cereda and P. Tangney and Alessandro De Vita}, publisher = {American Institute of Physics}, year = {2010}, journal = {Journal of chemical physics}, url = {https://wrap.warwick.ac.uk/64448/}, abstract = {We present a reformulation of the Tangney-Scandolo interatomic force field for silica J. Chem. Phys. 117, 8898 (2002), which removes the requirement to perform an Ewald summation. We use a Yukawa factor to screen electrostatic interactions and a cutoff distance to limit the interatomic potential range to around 10 A?. A reparametrization of the potential is carried out, fitting to data from density functional theory calculations. These calculations were performed within the local density approximation since we find that this choice of functional leads to a better match to the experimental structural and elastic properties of quartz and amorphous silica than the generalized gradient approximation approach used to parametrize the original Tangney-Scandolo force field. The resulting O(N) scheme makes it possible to model hundreds of thousands of atoms with modest computational resources, without compromising the force field accuracy. The new potential is validated by calculating structural, elastic, vibrational, and thermodynamic properties of \${$\backslash$}alpha\$-quartz and amorphous silica.} }
@article{wrap64450, volume = {Volume 72}, number = {Number 2}, title = {Hybrid atomistic simulation methods for materials systems}, author = {Noam Bernstein and James R. Kermode and Gabor Csanyi}, publisher = {Institute of Physics Publishing Ltd.}, year = {2009}, journal = {Reports on Progress in Physics}, keywords = {p05561}, url = {https://wrap.warwick.ac.uk/64450/}, abstract = {We review recent progress in the methodology of hybrid quantum/classical (QM/MM) atomistic simulations for solid-state systems, from the earliest reports in 1993 up to the latest results. A unified terminology is defined into which the various and disparate schemes fit, based on whether the information from the QM andMMcalculations is combined at the level of energies or forces. We discuss the pertinent issues for achieving ?seamless? coupling, the advantages and disadvantages of the proposed schemes and summarize the applications and scientific results that have been obtained to date.} }
@article{wrap64456, volume = {Volume 455}, number = {Number 7217}, month = {July}, author = {James R. Kermode and T. Albaret and Dov Sherman and Noam Bernstein and P. Gumbsch and Mike C. Payne and A. Cs{\'a}nyi and Alessandro De Vita}, title = {Low-speed fracture instabilities in a brittle crystal}, publisher = {Nature Publishing}, year = {2008}, journal = {Nature}, pages = {1224--1227}, keywords = {p00064}, url = {https://wrap.warwick.ac.uk/64456/} }
@incollection{wrap64451, volume = {Volume 104}, author = {Gabor Csanyi and Gianpietro Moras and James R. Kermode and Mike C. Payne and Alison Mainwood and Alessandro De Vita}, series = {Topics in Applied Physics}, booktitle = {Theory of Defects in Semiconductors}, editor = {David A. Drabold and Stefan K. Estreicher }, title = {Multiscale modeling of defects in semiconductors : a novel molecular-dynamics scheme}, address = {Berlin Heidelberg}, publisher = {Springer Berlin Heidelberg}, year = {2007}, journal = {Topics in Applied Physics}, pages = {193--212}, keywords = {p00102}, url = {https://wrap.warwick.ac.uk/64451/}, abstract = {Now that the modeling of simple semiconductor systems has become reliable, accurate and routine, attention is focusing on larger scale, more complex simulations. Many of these necessarily involve multiscale aspects and can only be tackled by addressing the different length scales simultaneously. We discuss some of the types of problems that require multiscale approaches. Finally we describe the LOTF (learn-on-the-fly) hybrid scheme with a series of examples to show its versatility and power.} }