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\n  \n 2025\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Excitation Laser Energy Dependence of the Gap-Mode TERS Spectra of WS2 and MoS2 on Silver.\n \n \n \n \n\n\n \n Krayev, A.; Isotta, E.; Hoang, L.; Yang, J. A.; Neilson, K.; Wang, M.; Haughn, N.; Pop, E.; Mannix, A.; Balogun, O.; and Wang, C.\n\n\n \n\n\n\n ACS Photonics. February 2025.\n Publisher: American Chemical Society\n\n\n\n
\n\n\n\n \n \n \"ExcitationPaper\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 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{krayev_excitation_2025,\n\ttitle = {Excitation {Laser} {Energy} {Dependence} of the {Gap}-{Mode} {TERS} {Spectra} of {WS2} and {MoS2} on {Silver}},\n\turl = {https://doi.org/10.1021/acsphotonics.4c02257},\n\tdoi = {10.1021/acsphotonics.4c02257},\n\tjournal = {ACS Photonics},\n\tauthor = {Krayev, Andrey and Isotta, Eleonora and Hoang, Lauren and Yang, Jerry A. and Neilson, Kathryn and Wang, Minyuan and Haughn, Noah and Pop, Eric and Mannix, Andrew and Balogun, Oluwaseyi and Wang, Chih-Feng},\n\tmonth = feb,\n\tyear = {2025},\n\tnote = {Publisher: American Chemical Society},\n\tannote = {doi: 10.1021/acsphotonics.4c02257},\n}\n\n
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\n \n\n \n \n \n \n \n \n A thermal boundary resistance model via mean free path suppression functions and a Gibbs excess approach.\n \n \n \n \n\n\n \n Isotta, E.; Nagahiro, R.; Odufisan, A. R.; Shiomi, J.; Balogun, O.; and Snyder, G. J.\n\n\n \n\n\n\n International Journal of Heat and Mass Transfer, 252: 127417. December 2025.\n \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 \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{isotta_thermal_2025,\n\ttitle = {A thermal boundary resistance model via mean free path suppression functions and a {Gibbs} excess approach},\n\tvolume = {252},\n\tissn = {0017-9310},\n\turl = {https://www.sciencedirect.com/science/article/pii/S0017931025007562},\n\tdoi = {10.1016/j.ijheatmasstransfer.2025.127417},\n\tabstract = {The impact of interfaces and grain boundaries on heat transport is often quantified in terms of thermal boundary resistance. Numerous models have been proposed over the years to describe this resistance. Recent experimental results in thermal conductivity imaging have highlighted the possibility of a local suppression in conductivity around material grain boundaries. In this work, we propose a semi-empirical model to predict the thermal conductivity profile as a function of distance to a boundary, to help explain experimental observations. The model is based on a geometrical suppression in the phonon mean free path and accounts for phonon transmission at the boundary. Calculated excess thermal boundary resistances, extracted from spatially dependent thermal conductivities with a Gibbs excess approach, are well-matched with predictions from the Landauer formalism when considering heat flow normal to the boundary. This agreement holds for different material systems and over temperature. The excess thermal resistance is thus expected to represent well the theoretical boundary resistance. The model in this work provides novel insights on the expected spatial extension of interface thermal effects, aiding the interpretation of thermal conductivity images. Rationalizing the impact of specific defects on heat transport can significantly advance the design of materials and devices for applications in energy, heat management and electronics.},\n\tjournal = {International Journal of Heat and Mass Transfer},\n\tauthor = {Isotta, Eleonora and Nagahiro, Ryohei and Odufisan, Alesanmi R. and Shiomi, Junichiro and Balogun, Oluwaseyi and Snyder, G. Jeffrey},\n\tmonth = dec,\n\tyear = {2025},\n\tkeywords = {Gibbs excess, Grain boundaries, Mean free path, Suppression function, Thermal boundary resistance, Thermal conductivity imaging, Thermal conductivity suppression},\n\tpages = {127417},\n}\n\n
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\n The impact of interfaces and grain boundaries on heat transport is often quantified in terms of thermal boundary resistance. Numerous models have been proposed over the years to describe this resistance. Recent experimental results in thermal conductivity imaging have highlighted the possibility of a local suppression in conductivity around material grain boundaries. In this work, we propose a semi-empirical model to predict the thermal conductivity profile as a function of distance to a boundary, to help explain experimental observations. The model is based on a geometrical suppression in the phonon mean free path and accounts for phonon transmission at the boundary. Calculated excess thermal boundary resistances, extracted from spatially dependent thermal conductivities with a Gibbs excess approach, are well-matched with predictions from the Landauer formalism when considering heat flow normal to the boundary. This agreement holds for different material systems and over temperature. The excess thermal resistance is thus expected to represent well the theoretical boundary resistance. The model in this work provides novel insights on the expected spatial extension of interface thermal effects, aiding the interpretation of thermal conductivity images. Rationalizing the impact of specific defects on heat transport can significantly advance the design of materials and devices for applications in energy, heat management and electronics.\n
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\n \n\n \n \n \n \n \n \n Quantifying Elastic Properties of Environmental Biofilms using Optical Coherence Elastography.\n \n \n \n \n\n\n \n Dieppa, E.; Schmitz, H.; Wang, Z.; Sabba, F.; Wells, G.; and Balogun, O.\n\n\n \n\n\n\n JoVE, (205): e66118. March 2024.\n Publisher: MyJoVE Corp\n\n\n\n
\n\n\n\n \n \n \"QuantifyingPaper\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{dieppa_quantifying_2024,\n\ttitle = {Quantifying {Elastic} {Properties} of {Environmental} {Biofilms} using {Optical} {Coherence} {Elastography}},\n\tissn = {1940-087X},\n\turl = {https://www.jove.com/t/66118},\n\tdoi = {10.3791/66118},\n\tabstract = {Biofilms are complex biomaterials comprising a well-organized network of microbial cells encased in self-produced extracellular polymeric substances (EPS). This paper presents a detailed account of the implementation of optical coherence elastography (OCE) measurements tailored for the elastic characterization of biofilms. OCE is a non-destructive optical technique that enables the local mapping of the microstructure, morphology, and viscoelastic properties of partially transparent soft materials with high spatial and temporal resolution. We provide a comprehensive guide detailing the essential procedures for the correct implementation of this technique, along with a methodology to estimate the bulk Young's modulus of granular biofilms from the collected measurements. These consist of the system setup, data acquisition, and postprocessing. In the discussion, we delve into the underlying physics of the sensors used in OCE and explore the fundamental limitations regarding the spatial and temporal scales of OCE measurements. We conclude with potential future directions for advancing the OCE technique to facilitate elastic measurements of environmental biofilms.},\n\tnumber = {205},\n\tjournal = {JoVE},\n\tauthor = {Dieppa, Evan and Schmitz, Hannah and Wang, Ziwei and Sabba, Fabrizio and Wells, George and Balogun, Oluwaseyi},\n\tmonth = mar,\n\tyear = {2024},\n\tnote = {Publisher: MyJoVE Corp},\n\tkeywords = {This Month in JoVE},\n\tpages = {e66118},\n}\n\n
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\n Biofilms are complex biomaterials comprising a well-organized network of microbial cells encased in self-produced extracellular polymeric substances (EPS). This paper presents a detailed account of the implementation of optical coherence elastography (OCE) measurements tailored for the elastic characterization of biofilms. OCE is a non-destructive optical technique that enables the local mapping of the microstructure, morphology, and viscoelastic properties of partially transparent soft materials with high spatial and temporal resolution. We provide a comprehensive guide detailing the essential procedures for the correct implementation of this technique, along with a methodology to estimate the bulk Young's modulus of granular biofilms from the collected measurements. These consist of the system setup, data acquisition, and postprocessing. In the discussion, we delve into the underlying physics of the sensors used in OCE and explore the fundamental limitations regarding the spatial and temporal scales of OCE measurements. We conclude with potential future directions for advancing the OCE technique to facilitate elastic measurements of environmental biofilms.\n
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\n \n\n \n \n \n \n \n \n Heat Transport at Silicon Grain Boundaries.\n \n \n \n \n\n\n \n Isotta, E.; Jiang, S.; Bueno-Villoro, R.; Nagahiro, R.; Maeda, K.; Mattlat, D. A.; Odufisan, A. R.; Zevalkink, A.; Shiomi, J.; Zhang, S.; Scheu, C.; Snyder, G. J.; and Balogun, O.\n\n\n \n\n\n\n Advanced Functional Materials,2405413. July 2024.\n Publisher: John Wiley & Sons, Ltd\n\n\n\n
\n\n\n\n \n \n \"HeatPaper\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
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@article{isotta_heat_2024,\n\ttitle = {Heat {Transport} at {Silicon} {Grain} {Boundaries}},\n\tissn = {1616-301X},\n\turl = {https://doi.org/10.1002/adfm.202405413},\n\tdoi = {10.1002/adfm.202405413},\n\tabstract = {Abstract Engineering microstructural defects, like grain boundaries, offers superior control over transport properties in energy materials. However, technological advancement requires establishing microstructure-property relations at the micron or finer scales, where most of these defects operate. Here, the first experimental evidence of thermal resistance for individual silicon grain boundaries, estimated with a Gibbs excess approach, is provided. Coincident site lattice boundaries exhibit uniform excess thermal resistance along the same boundary, but notable variations from one boundary to another. Boundaries associated with low interface energy generally exhibit lower resistances, aligning with theoretical expectations and previous simulations, but several exceptions are observed. Transmission electron microscopy reveals that factors like interface roughness and presence of nanotwinning can significantly alter the observed resistance, which ranges from ?0 to up to ?2.3 m2K/GW. In stark contrast, significantly larger and less uniform values - from 5 to 30 m2K/GW - are found for high-angle boundaries in spark-plasma-sintered polycrystalline silicon. Further, finite element analysis suggests that boundary planes that strongly deviate from the sample vertical (beyond ?45°) can show up to 3-times larger excess resistance. Direct correlations of properties with individual defects enable the design of materials with superior thermal performance for applications in energy harvesting and heat management.},\n\turldate = {2024-07-03},\n\tjournal = {Advanced Functional Materials},\n\tauthor = {Isotta, Eleonora and Jiang, Shizhou and Bueno-Villoro, Ruben and Nagahiro, Ryohei and Maeda, Kosuke and Mattlat, Dominique Alexander and Odufisan, Alesanmi R. and Zevalkink, Alexandra and Shiomi, Junichiro and Zhang, Siyuan and Scheu, Christina and Snyder, G. Jeffrey and Balogun, Oluwaseyi},\n\tmonth = jul,\n\tyear = {2024},\n\tnote = {Publisher: John Wiley \\& Sons, Ltd},\n\tkeywords = {grain boundaries, coincident site lattices, multicrystalline silicon, structure-property relations, thermal conductivity imaging},\n\tpages = {2405413},\n}\n\n
\n
\n\n\n
\n Abstract Engineering microstructural defects, like grain boundaries, offers superior control over transport properties in energy materials. However, technological advancement requires establishing microstructure-property relations at the micron or finer scales, where most of these defects operate. Here, the first experimental evidence of thermal resistance for individual silicon grain boundaries, estimated with a Gibbs excess approach, is provided. Coincident site lattice boundaries exhibit uniform excess thermal resistance along the same boundary, but notable variations from one boundary to another. Boundaries associated with low interface energy generally exhibit lower resistances, aligning with theoretical expectations and previous simulations, but several exceptions are observed. Transmission electron microscopy reveals that factors like interface roughness and presence of nanotwinning can significantly alter the observed resistance, which ranges from ?0 to up to ?2.3 m2K/GW. In stark contrast, significantly larger and less uniform values - from 5 to 30 m2K/GW - are found for high-angle boundaries in spark-plasma-sintered polycrystalline silicon. Further, finite element analysis suggests that boundary planes that strongly deviate from the sample vertical (beyond ?45°) can show up to 3-times larger excess resistance. Direct correlations of properties with individual defects enable the design of materials with superior thermal performance for applications in energy harvesting and heat management.\n
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\n \n\n \n \n \n \n \n \n Soft, 3D printed muscle ultrasound phantom with structurally tunable B-mode echo intensity.\n \n \n \n \n\n\n \n Gillespie, S. D; Collins, C. P; Perreault, E. J; Sun, C.; Balogun, O.; and Murray, W. M\n\n\n \n\n\n\n bioRxiv,2024.11.29.625078. January 2024.\n \n\n\n\n
\n\n\n\n \n \n \"Soft,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 abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{gillespie_soft_2024,\n\ttitle = {Soft, {3D} printed muscle ultrasound phantom with structurally tunable {B}-mode echo intensity},\n\turl = {http://biorxiv.org/content/early/2024/12/03/2024.11.29.625078.abstract},\n\tdoi = {10.1101/2024.11.29.625078},\n\tabstract = {OBJECTIVES Imaging phantoms for training and validation are vital to improving the performance and adoption of ultrasound imaging modalities in clinical and pre-clinical applications, and the goal of this study was to assess the viability of 3D printed muscle ultrasound phantoms to meet this need.METHODS We used a soft stereolithography resin to 3D print phantoms that mimicked the fascicle- and perimysium-scale structure of skeletal muscle and compared the long axis B-mode imaging quality and pattern of the phantom to that of healthy, adult Biceps brachii. We used a pulse-echo, time-of-flight method to measure the acoustic impedance of the resin for comparison to skeletal muscle and common soft tissue mimicking materials. We analyzed the echo intensity (EI) of muscle images to establish a physiological range and compared the EI of different phantom designs to assess the ability to control imaging brightness through structural modification.RESULTS A linear, striated hyper-/hypo-echoic B-mode imaging pattern mimicking long axis Biceps brachii muscle images was achieved with two 3D structure paradigms, rod and honeycomb. Acoustic impedance of Elastic 50A resin is higher than skeletal muscle in bulk, but appears suitable for use in a 3D structured phantom. EI measured in the Biceps images were found to vary both within and across images with an overall mean ± SD of 87 ±13 AU. EI measured in honeycomb phantoms (55 ±15 AU) was higher than in rod phantoms (42 ±13 AU), and a latticed honeycomb further increased EI (90 ±11 AU).CONCLUSIONS This study serves as proof-of-concept for soft, 3D printed phantoms that replicate the characteristic muscle ultrasound imaging pattern with the ability to tune clinically relevant EI values via structural design.Competing Interest StatementThe authors have declared no competing interest.},\n\tjournal = {bioRxiv},\n\tauthor = {Gillespie, Samuel D and Collins, Caralyn P and Perreault, Eric J and Sun, Cheng and Balogun, Oluwaseyi and Murray, Wendy M},\n\tmonth = jan,\n\tyear = {2024},\n\tpages = {2024.11.29.625078},\n}\n\n
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\n\n\n
\n OBJECTIVES Imaging phantoms for training and validation are vital to improving the performance and adoption of ultrasound imaging modalities in clinical and pre-clinical applications, and the goal of this study was to assess the viability of 3D printed muscle ultrasound phantoms to meet this need.METHODS We used a soft stereolithography resin to 3D print phantoms that mimicked the fascicle- and perimysium-scale structure of skeletal muscle and compared the long axis B-mode imaging quality and pattern of the phantom to that of healthy, adult Biceps brachii. We used a pulse-echo, time-of-flight method to measure the acoustic impedance of the resin for comparison to skeletal muscle and common soft tissue mimicking materials. We analyzed the echo intensity (EI) of muscle images to establish a physiological range and compared the EI of different phantom designs to assess the ability to control imaging brightness through structural modification.RESULTS A linear, striated hyper-/hypo-echoic B-mode imaging pattern mimicking long axis Biceps brachii muscle images was achieved with two 3D structure paradigms, rod and honeycomb. Acoustic impedance of Elastic 50A resin is higher than skeletal muscle in bulk, but appears suitable for use in a 3D structured phantom. EI measured in the Biceps images were found to vary both within and across images with an overall mean ± SD of 87 ±13 AU. EI measured in honeycomb phantoms (55 ±15 AU) was higher than in rod phantoms (42 ±13 AU), and a latticed honeycomb further increased EI (90 ±11 AU).CONCLUSIONS This study serves as proof-of-concept for soft, 3D printed phantoms that replicate the characteristic muscle ultrasound imaging pattern with the ability to tune clinically relevant EI values via structural design.Competing Interest StatementThe authors have declared no competing interest.\n
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\n \n\n \n \n \n \n \n Quantitative Measurement of Viscoelastic Properties of Soft Membranes Subjected to Finite Deformations Based on Optical Coherence Elastography.\n \n \n \n\n\n \n Balogun, O.; and Wang, Z.\n\n\n \n\n\n\n In Franck, C.; Kasza, K.; Estrada, J.; De Finis, R.; Ólafsson, G.; Gururaja, S.; Furmanski, J.; Forster, A.; Kolluru, P.; Prime, M.; Berfield, T.; and Aydiner, C., editor(s), Challenges in Mechanics of Biological Systems and Materials, Thermomechanics and Infrared Imaging, Time Dependent Materials and Residual Stress, Volume 2, pages 15–19, Cham, 2024. Springer Nature Switzerland\n \n\n\n\n
\n\n\n\n \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 
@inproceedings{balogun_quantitative_2024,\n\taddress = {Cham},\n\ttitle = {Quantitative {Measurement} of {Viscoelastic} {Properties} of {Soft} {Membranes} {Subjected} to {Finite} {Deformations} {Based} on {Optical} {Coherence} {Elastography}},\n\tisbn = {978-3-031-50470-9},\n\tabstract = {Glaucoma is a leading cause of irreversible blindness that affects over 60 million people worldwide. Glaucomatous eyes are associated with risk factors such as elevated intraocular pressure (IOP) and low corneal hysteresis. Reliable non-invasive measurement of IOP remains a formidable challenge that limits the accurate diagnosis of glaucoma and associated intervention therapies. This work investigates the propagation of shear-dominated elastic waves in hydrostatically inflated corneal tissue phantoms based on the optical coherence elastography (OCE) technique. Unlike previous approaches reported in the literature, we analyze the dispersion relation of guided elastic waves in the phantoms by accounting for both small amplitude viscoelastic wave propagation and finite static deformations. The analytical approach we adopted will enable the determination of the storage and loss shear moduli dependence on finite strains in the cornea that results from hydrostatic pressures. This work provides a modeling and experimental framework for accurately characterizing viscoelastic properties and the IOP of corneal tissues.},\n\tbooktitle = {Challenges in {Mechanics} of {Biological} {Systems} and {Materials}, {Thermomechanics} and {Infrared} {Imaging}, {Time} {Dependent} {Materials} and {Residual} {Stress}, {Volume} 2},\n\tpublisher = {Springer Nature Switzerland},\n\tauthor = {Balogun, O. and Wang, Z.},\n\teditor = {Franck, Christian and Kasza, Karen and Estrada, Jon and De Finis, Rosa and Ólafsson, Geir and Gururaja, Suhasini and Furmanski, Jevan and Forster, Aaron and Kolluru, Pavan and Prime, Mike and Berfield, Tom and Aydiner, Cahit},\n\tyear = {2024},\n\tpages = {15--19},\n}\n
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\n Glaucoma is a leading cause of irreversible blindness that affects over 60 million people worldwide. Glaucomatous eyes are associated with risk factors such as elevated intraocular pressure (IOP) and low corneal hysteresis. Reliable non-invasive measurement of IOP remains a formidable challenge that limits the accurate diagnosis of glaucoma and associated intervention therapies. This work investigates the propagation of shear-dominated elastic waves in hydrostatically inflated corneal tissue phantoms based on the optical coherence elastography (OCE) technique. Unlike previous approaches reported in the literature, we analyze the dispersion relation of guided elastic waves in the phantoms by accounting for both small amplitude viscoelastic wave propagation and finite static deformations. The analytical approach we adopted will enable the determination of the storage and loss shear moduli dependence on finite strains in the cornea that results from hydrostatic pressures. This work provides a modeling and experimental framework for accurately characterizing viscoelastic properties and the IOP of corneal tissues.\n
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\n \n\n \n \n \n \n \n \n Microscale Imaging of Thermal Conductivity Suppression at Grain Boundaries.\n \n \n \n \n\n\n \n Isotta, E.; Jiang, S.; Moller, G.; Zevalkink, A.; Snyder, G. J.; and Balogun, O.\n\n\n \n\n\n\n Advanced Materials,2302777. June 2023.\n \n\n\n\n
\n\n\n\n \n \n \"MicroscalePaper\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
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@article{isotta_microscale_2023,\n\ttitle = {Microscale {Imaging} of {Thermal} {Conductivity} {Suppression} at {Grain} {Boundaries}},\n\tcopyright = {© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH},\n\tissn = {1521-4095},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.202302777},\n\tdoi = {10.1002/adma.202302777},\n\tabstract = {Grain-boundary engineering is an effective strategy to tune the thermal conductivity of materials, leading to improved performance in thermoelectric, thermal-barrier coatings, and thermal management applications. Despite the central importance to thermal transport, a clear understanding of how grain boundaries modulate the microscale heat flow is missing, owing to the scarcity of local investigations. Here, thermal imaging of individual grain boundaries is demonstrated in thermoelectric SnTe via spatially resolved frequency-domain thermoreflectance. Measurements with microscale resolution reveal local suppressions in thermal conductivity at grain boundaries. Also, the grain-boundary thermal resistance – extracted by employing a Gibbs excess approach – is found to be correlated with the grain-boundary misorientation angle. Extracting thermal properties, including thermal boundary resistances, from microscale imaging can provide comprehensive understanding of how microstructure affects heat transport, crucially impacting the materials design of high-performance thermal-management and energy-conversion devices.},\n\tlanguage = {en},\n\turldate = {2023-09-20},\n\tjournal = {Advanced Materials},\n\tauthor = {Isotta, Eleonora and Jiang, Shizhou and Moller, Gregory and Zevalkink, Alexandra and Snyder, G. Jeffrey and Balogun, Oluwaseyi},\n\tmonth = jun,\n\tyear = {2023},\n\tkeywords = {frequency domain thermoreflectance, Gibbs excess, grain boundaries, Kapitza resistance, SnTe, thermal conductivity, thermal imaging},\n\tpages = {2302777},\n\tfile = {Full Text PDF:C\\:\\\\Users\\\\Evan\\\\Zotero\\\\storage\\\\ZK3V6DC5\\\\Isotta et al. - Microscale Imaging of Thermal Conductivity Suppres.pdf:application/pdf;Snapshot:C\\:\\\\Users\\\\Evan\\\\Zotero\\\\storage\\\\RC998AYL\\\\adma.html:text/html},\n}\n\n
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\n Grain-boundary engineering is an effective strategy to tune the thermal conductivity of materials, leading to improved performance in thermoelectric, thermal-barrier coatings, and thermal management applications. Despite the central importance to thermal transport, a clear understanding of how grain boundaries modulate the microscale heat flow is missing, owing to the scarcity of local investigations. Here, thermal imaging of individual grain boundaries is demonstrated in thermoelectric SnTe via spatially resolved frequency-domain thermoreflectance. Measurements with microscale resolution reveal local suppressions in thermal conductivity at grain boundaries. Also, the grain-boundary thermal resistance – extracted by employing a Gibbs excess approach – is found to be correlated with the grain-boundary misorientation angle. Extracting thermal properties, including thermal boundary resistances, from microscale imaging can provide comprehensive understanding of how microstructure affects heat transport, crucially impacting the materials design of high-performance thermal-management and energy-conversion devices.\n
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\n \n\n \n \n \n \n \n \n Molecular Dynamics Modeling of Thermal Conductivity of Several Hydrocarbon Base Oils.\n \n \n \n \n\n\n \n Ahmed, J.; Wang, Q. J.; Balogun, O.; Ren, N.; England, R.; and Lockwood, F.\n\n\n \n\n\n\n Tribology Letters, 71(2): 70. May 2023.\n \n\n\n\n
\n\n\n\n \n \n \"MolecularPaper\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
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@article{ahmed_molecular_2023,\n\ttitle = {Molecular {Dynamics} {Modeling} of {Thermal} {Conductivity} of {Several} {Hydrocarbon} {Base} {Oils}},\n\tvolume = {71},\n\tissn = {1573-2711},\n\turl = {https://doi.org/10.1007/s11249-023-01738-z},\n\tdoi = {10.1007/s11249-023-01738-z},\n\tabstract = {This paper is on determination of the thermal conductivities of several hydrocarbon base oils by means of non-equilibrium molecular dynamics simulations using two different force fields. It aims to explore a simulation-based method for lubricant molecular design and analysis concerning heat transfer in electrical vehicle lubrication. Argon was analyzed as a reference for method evaluation, and the results reveal that the calculated conductivity strongly depends on the size of the computational domain. However, for hydrocarbon base oils, the dependence on computation domain size is less prominent as the domain size increases. The method of direct calculation in a sufficiently large computation domain and that of reciprocal extrapolation with data calculated in a much smaller domain are both applicable, and each has a certain value in oil conductivity calculation. The calculated conductivities show certain overpredictions when compared with experimentally measured results, and the overprediction factor is related to number of carbon atoms of the liquid molecules. The results reveal that the thermal conductivity of a single-chain hydrocarbon liquid is linearly proportional to the number of carbon atoms. While each additional branch increases thermal conductivity slightly, the presence of multiple branches reduces it from the ideal linear relationship. A set of equations was formulated to correlate hydrocarbon liquid thermal conductivity with molecular characteristics in terms of number of carbon atoms and number of branches.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2023-09-20},\n\tjournal = {Tribology Letters},\n\tauthor = {Ahmed, Jannat and Wang, Q. Jane and Balogun, Oluwaseyi and Ren, Ning and England, Roger and Lockwood, Frances},\n\tmonth = may,\n\tyear = {2023},\n\tkeywords = {Force fields, Hydrocarbon base oils, MD simulation, Size effect, Thermal conductivity},\n\tpages = {70},\n\tfile = {Full Text PDF:C\\:\\\\Users\\\\Evan\\\\Zotero\\\\storage\\\\HD35I6B8\\\\Ahmed et al. - 2023 - Molecular Dynamics Modeling of Thermal Conductivit.pdf:application/pdf},\n}\n\n
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\n This paper is on determination of the thermal conductivities of several hydrocarbon base oils by means of non-equilibrium molecular dynamics simulations using two different force fields. It aims to explore a simulation-based method for lubricant molecular design and analysis concerning heat transfer in electrical vehicle lubrication. Argon was analyzed as a reference for method evaluation, and the results reveal that the calculated conductivity strongly depends on the size of the computational domain. However, for hydrocarbon base oils, the dependence on computation domain size is less prominent as the domain size increases. The method of direct calculation in a sufficiently large computation domain and that of reciprocal extrapolation with data calculated in a much smaller domain are both applicable, and each has a certain value in oil conductivity calculation. The calculated conductivities show certain overpredictions when compared with experimentally measured results, and the overprediction factor is related to number of carbon atoms of the liquid molecules. The results reveal that the thermal conductivity of a single-chain hydrocarbon liquid is linearly proportional to the number of carbon atoms. While each additional branch increases thermal conductivity slightly, the presence of multiple branches reduces it from the ideal linear relationship. A set of equations was formulated to correlate hydrocarbon liquid thermal conductivity with molecular characteristics in terms of number of carbon atoms and number of branches.\n
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\n \n\n \n \n \n \n \n \n Quantitative Characterization of the Anisotropic Thermal Properties of Encapsulated Two-Dimensional MoS2 Nanofilms \\textbar ACS Applied Materials & Interfaces.\n \n \n \n \n\n\n \n Lebedev, D.; Jiang, S.; Andrews, Loren; Gish, J Tyler; Song, Thomas W; Hersam, Mark C; and Balogun, Oluwaseyi\n\n\n \n\n\n\n February 2023.\n \n\n\n\n
\n\n\n\n \n \n \"QuantitativePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@misc{lebedev_quantitative_2023,\n\ttitle = {Quantitative {Characterization} of the {Anisotropic} {Thermal} {Properties} of {Encapsulated} {Two}-{Dimensional} {MoS2} {Nanofilms} {\\textbar} {ACS} {Applied} {Materials} \\& {Interfaces}},\n\turl = {https://pubs.acs.org/doi/full/10.1021/acsami.2c18755},\n\turldate = {2023-09-20},\n\tauthor = {Lebedev, Dmitry and Jiang, Shizhou and {Andrews, Loren} and {Gish, J Tyler} and {Song, Thomas W} and {Hersam, Mark C} and {Balogun, Oluwaseyi}},\n\tmonth = feb,\n\tyear = {2023},\n\tfile = {Quantitative Characterization of the Anisotropic Thermal Properties of Encapsulated Two-Dimensional MoS2 Nanofilms | ACS Applied Materials & Interfaces:C\\:\\\\Users\\\\Evan\\\\Zotero\\\\storage\\\\EGQJG7QQ\\\\acsami.html:text/html},\n}\n\n
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\n \n\n \n \n \n \n \n \n Nanomechanical property evaluation of tungsten thin film via frequency-domain photoacoustic microscopy.\n \n \n \n \n\n\n \n Wang, Z.; Balogun, O.; and Kim, Y. Y.\n\n\n \n\n\n\n Thin Solid Films, 742: 139050. January 2022.\n \n\n\n\n
\n\n\n\n \n \n \"NanomechanicalPaper\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{wang_nanomechanical_2022,\n\ttitle = {Nanomechanical property evaluation of tungsten thin film via frequency-domain photoacoustic microscopy},\n\tvolume = {742},\n\tissn = {00406090},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0040609021005332},\n\tdoi = {10.1016/j.tsf.2021.139050},\n\tlanguage = {en},\n\turldate = {2022-01-08},\n\tjournal = {Thin Solid Films},\n\tauthor = {Wang, Ziwei and Balogun, Oluwaseyi and Kim, Yun Young},\n\tmonth = jan,\n\tyear = {2022},\n\tpages = {139050},\n}\n\n
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\n \n\n \n \n \n \n \n \n GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty.\n \n \n \n \n\n\n \n Chen, W. (.; Lee, D.; Balogun, O.; and Chen, W.\n\n\n \n\n\n\n Journal of Mechanical Design, 145(011703). October 2022.\n \n\n\n\n
\n\n\n\n \n \n \"GAN-DUF: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 abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{chen_gan-duf_2022,\n\ttitle = {{GAN}-{DUF}: {Hierarchical} {Deep} {Generative} {Models} for {Design} {Under} {Free}-{Form} {Geometric} {Uncertainty}},\n\tvolume = {145},\n\tissn = {1050-0472},\n\tshorttitle = {{GAN}-{DUF}},\n\turl = {https://doi.org/10.1115/1.4055898},\n\tdoi = {10.1115/1.4055898},\n\tabstract = {Deep generative models have demonstrated effectiveness in learning compact and expressive design representations that significantly improve geometric design optimization. However, these models do not consider the uncertainty introduced by manufacturing or fabrication. The past work that quantifies such uncertainty often makes simplifying assumptions on geometric variations, while the “real-world,” “free-form” uncertainty and its impact on design performance are difficult to quantify due to the high dimensionality. To address this issue, we propose a generative adversarial network-based design under uncertainty framework (GAN-DUF), which contains a deep generative model that simultaneously learns a compact representation of nominal (ideal) designs and the conditional distribution of fabricated designs given any nominal design. This opens up new possibilities of (1) building a universal uncertainty quantification model compatible with both shape and topological designs, (2) modeling free-form geometric uncertainties without the need to make any assumptions on the distribution of geometric variability, and (3) allowing fast prediction of uncertainties for new nominal designs. We can combine the proposed deep generative model with robust design optimization or reliability-based design optimization for design under uncertainty. We demonstrated the framework on two real-world engineering design examples and showed its capability of finding the solution that possesses better performance after fabrication.},\n\tnumber = {011703},\n\turldate = {2023-09-20},\n\tjournal = {Journal of Mechanical Design},\n\tauthor = {Chen, Wei (Wayne) and Lee, Doksoo and Balogun, Oluwaseyi and Chen, Wei},\n\tmonth = oct,\n\tyear = {2022},\n\tfile = {Full Text PDF:C\\:\\\\Users\\\\Evan\\\\Zotero\\\\storage\\\\7GQCVJS6\\\\Chen et al. - 2022 - GAN-DUF Hierarchical Deep Generative Models for D.pdf:application/pdf},\n}\n\n
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\n Deep generative models have demonstrated effectiveness in learning compact and expressive design representations that significantly improve geometric design optimization. However, these models do not consider the uncertainty introduced by manufacturing or fabrication. The past work that quantifies such uncertainty often makes simplifying assumptions on geometric variations, while the “real-world,” “free-form” uncertainty and its impact on design performance are difficult to quantify due to the high dimensionality. To address this issue, we propose a generative adversarial network-based design under uncertainty framework (GAN-DUF), which contains a deep generative model that simultaneously learns a compact representation of nominal (ideal) designs and the conditional distribution of fabricated designs given any nominal design. This opens up new possibilities of (1) building a universal uncertainty quantification model compatible with both shape and topological designs, (2) modeling free-form geometric uncertainties without the need to make any assumptions on the distribution of geometric variability, and (3) allowing fast prediction of uncertainties for new nominal designs. We can combine the proposed deep generative model with robust design optimization or reliability-based design optimization for design under uncertainty. We demonstrated the framework on two real-world engineering design examples and showed its capability of finding the solution that possesses better performance after fabrication.\n
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\n \n\n \n \n \n \n \n \n Tailoring polyvinyl alcohol-sodium alginate (PVA-SA) hydrogel beads by controlling crosslinking pH and time.\n \n \n \n \n\n\n \n Candry, P.; Godfrey, B. J.; Wang, Z.; Sabba, F.; Dieppa, E.; Fudge, J.; Balogun, O.; Wells, G.; and Winkler, M. H.\n\n\n \n\n\n\n Scientific Reports, 12(1): 20822. December 2022.\n Number: 1 Publisher: Nature Publishing Group\n\n\n\n
\n\n\n\n \n \n \"TailoringPaper\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
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@article{candry_tailoring_2022,\n\ttitle = {Tailoring polyvinyl alcohol-sodium alginate ({PVA}-{SA}) hydrogel beads by controlling crosslinking {pH} and time},\n\tvolume = {12},\n\tcopyright = {2022 The Author(s)},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/s41598-022-25111-7},\n\tdoi = {10.1038/s41598-022-25111-7},\n\tabstract = {Hydrogel-encapsulated catalysts are an attractive tool for low-cost intensification of (bio)-processes. Polyvinyl alcohol-sodium alginate hydrogels crosslinked with boric acid and post-cured with sulfate (PVA-SA-BS) have been applied in bioproduction and water treatment processes, but the low pH required for crosslinking may negatively affect biocatalyst functionality. Here, we investigate how crosslinking pH (3, 4, and 5) and time (1, 2, and 8 h) affect the physicochemical, elastic, and process properties of PVA-SA-BS beads. Overall, bead properties were most affected by crosslinking pH. Beads produced at pH 3 and 4 were smaller and contained larger internal cavities, while optical coherence tomography suggested polymer cross-linking density was higher. Optical coherence elastography revealed PVA-SA-BS beads produced at pH 3 and 4 were stiffer than pH 5 beads. Dextran Blue release showed that pH 3-produced beads enabled higher diffusion rates and were more porous. Last, over a 28-day incubation, pH 3 and 4 beads lost more microspheres (as cell proxies) than beads produced at pH 5, while the latter released more polymer material. Overall, this study provides a path forward to tailor PVA-SA-BS hydrogel bead properties towards a broad range of applications, such as chemical, enzymatic, and microbially catalyzed (bio)-processes.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2023-09-20},\n\tjournal = {Scientific Reports},\n\tauthor = {Candry, Pieter and Godfrey, Bruce J. and Wang, Ziwei and Sabba, Fabrizio and Dieppa, Evan and Fudge, Julia and Balogun, Oluwaseyi and Wells, George and Winkler, Mari-Karoliina Henriikka},\n\tmonth = dec,\n\tyear = {2022},\n\tnote = {Number: 1\nPublisher: Nature Publishing Group},\n\tkeywords = {Biotechnology, Chemical engineering, Gels and hydrogels},\n\tpages = {20822},\n\tfile = {Full Text PDF:C\\:\\\\Users\\\\Evan\\\\Zotero\\\\storage\\\\X8X9BHUF\\\\Candry et al. - 2022 - Tailoring polyvinyl alcohol-sodium alginate (PVA-S.pdf:application/pdf},\n}\n\n
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\n Hydrogel-encapsulated catalysts are an attractive tool for low-cost intensification of (bio)-processes. Polyvinyl alcohol-sodium alginate hydrogels crosslinked with boric acid and post-cured with sulfate (PVA-SA-BS) have been applied in bioproduction and water treatment processes, but the low pH required for crosslinking may negatively affect biocatalyst functionality. Here, we investigate how crosslinking pH (3, 4, and 5) and time (1, 2, and 8 h) affect the physicochemical, elastic, and process properties of PVA-SA-BS beads. Overall, bead properties were most affected by crosslinking pH. Beads produced at pH 3 and 4 were smaller and contained larger internal cavities, while optical coherence tomography suggested polymer cross-linking density was higher. Optical coherence elastography revealed PVA-SA-BS beads produced at pH 3 and 4 were stiffer than pH 5 beads. Dextran Blue release showed that pH 3-produced beads enabled higher diffusion rates and were more porous. Last, over a 28-day incubation, pH 3 and 4 beads lost more microspheres (as cell proxies) than beads produced at pH 5, while the latter released more polymer material. Overall, this study provides a path forward to tailor PVA-SA-BS hydrogel bead properties towards a broad range of applications, such as chemical, enzymatic, and microbially catalyzed (bio)-processes.\n
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