Wave Motion in Materials Balogun Research Group

@article{krayev_excitation_2025,
	title = {Excitation {Laser} {Energy} {Dependence} of the {Gap}-{Mode} {TERS} {Spectra} of {WS2} and {MoS2} on {Silver}},
	url = {https://doi.org/10.1021/acsphotonics.4c02257},
	doi = {10.1021/acsphotonics.4c02257},
	journal = {ACS Photonics},
	author = {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},
	month = feb,
	year = {2025},
	note = {Publisher: American Chemical Society},
	annote = {doi: 10.1021/acsphotonics.4c02257},
}

@article{dieppa_quantifying_2024,
	title = {Quantifying {Elastic} {Properties} of {Environmental} {Biofilms} using {Optical} {Coherence} {Elastography}},
	issn = {1940-087X},
	url = {https://www.jove.com/t/66118},
	doi = {10.3791/66118},
	abstract = {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.},
	number = {205},
	journal = {JoVE},
	author = {Dieppa, Evan and Schmitz, Hannah and Wang, Ziwei and Sabba, Fabrizio and Wells, George and Balogun, Oluwaseyi},
	month = mar,
	year = {2024},
	note = {Publisher: MyJoVE Corp},
	keywords = {This Month in JoVE},
	pages = {e66118},
}

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.

@article{isotta_heat_2024,
	title = {Heat {Transport} at {Silicon} {Grain} {Boundaries}},
	issn = {1616-301X},
	url = {https://doi.org/10.1002/adfm.202405413},
	doi = {10.1002/adfm.202405413},
	abstract = {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.},
	urldate = {2024-07-03},
	journal = {Advanced Functional Materials},
	author = {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},
	month = jul,
	year = {2024},
	note = {Publisher: John Wiley \& Sons, Ltd},
	keywords = {grain boundaries, coincident site lattices, multicrystalline silicon, structure-property relations, thermal conductivity imaging},
	pages = {2405413},
}

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.

@article{isotta_microscale_2023,
	title = {Microscale {Imaging} of {Thermal} {Conductivity} {Suppression} at {Grain} {Boundaries}},
	copyright = {© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH},
	issn = {1521-4095},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.202302777},
	doi = {10.1002/adma.202302777},
	abstract = {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.},
	language = {en},
	urldate = {2023-09-20},
	journal = {Advanced Materials},
	author = {Isotta, Eleonora and Jiang, Shizhou and Moller, Gregory and Zevalkink, Alexandra and Snyder, G. Jeffrey and Balogun, Oluwaseyi},
	month = jun,
	year = {2023},
	keywords = {frequency domain thermoreflectance, Gibbs excess, grain boundaries, Kapitza resistance, SnTe, thermal conductivity, thermal imaging},
	pages = {2302777},
	file = {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},
}

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.

@article{ahmed_molecular_2023,
	title = {Molecular {Dynamics} {Modeling} of {Thermal} {Conductivity} of {Several} {Hydrocarbon} {Base} {Oils}},
	volume = {71},
	issn = {1573-2711},
	url = {https://doi.org/10.1007/s11249-023-01738-z},
	doi = {10.1007/s11249-023-01738-z},
	abstract = {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.},
	language = {en},
	number = {2},
	urldate = {2023-09-20},
	journal = {Tribology Letters},
	author = {Ahmed, Jannat and Wang, Q. Jane and Balogun, Oluwaseyi and Ren, Ning and England, Roger and Lockwood, Frances},
	month = may,
	year = {2023},
	keywords = {Force fields, Hydrocarbon base oils, MD simulation, Size effect, Thermal conductivity},
	pages = {70},
	file = {Full Text PDF:C\:\\Users\\Evan\\Zotero\\storage\\HD35I6B8\\Ahmed et al. - 2023 - Molecular Dynamics Modeling of Thermal Conductivit.pdf:application/pdf},
}

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.

@misc{lebedev_quantitative_2023,
	title = {Quantitative {Characterization} of the {Anisotropic} {Thermal} {Properties} of {Encapsulated} {Two}-{Dimensional} {MoS2} {Nanofilms} {\textbar} {ACS} {Applied} {Materials} \& {Interfaces}},
	url = {https://pubs.acs.org/doi/full/10.1021/acsami.2c18755},
	urldate = {2023-09-20},
	author = {Lebedev, Dmitry and Jiang, Shizhou and {Andrews, Loren} and {Gish, J Tyler} and {Song, Thomas W} and {Hersam, Mark C} and {Balogun, Oluwaseyi}},
	month = feb,
	year = {2023},
	file = {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},
}

@article{wang_nanomechanical_2022,
	title = {Nanomechanical property evaluation of tungsten thin film via frequency-domain photoacoustic microscopy},
	volume = {742},
	issn = {00406090},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0040609021005332},
	doi = {10.1016/j.tsf.2021.139050},
	language = {en},
	urldate = {2022-01-08},
	journal = {Thin Solid Films},
	author = {Wang, Ziwei and Balogun, Oluwaseyi and Kim, Yun Young},
	month = jan,
	year = {2022},
	pages = {139050},
}

@article{chen_gan-duf_2022,
	title = {{GAN}-{DUF}: {Hierarchical} {Deep} {Generative} {Models} for {Design} {Under} {Free}-{Form} {Geometric} {Uncertainty}},
	volume = {145},
	issn = {1050-0472},
	shorttitle = {{GAN}-{DUF}},
	url = {https://doi.org/10.1115/1.4055898},
	doi = {10.1115/1.4055898},
	abstract = {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.},
	number = {011703},
	urldate = {2023-09-20},
	journal = {Journal of Mechanical Design},
	author = {Chen, Wei (Wayne) and Lee, Doksoo and Balogun, Oluwaseyi and Chen, Wei},
	month = oct,
	year = {2022},
	file = {Full Text PDF:C\:\\Users\\Evan\\Zotero\\storage\\7GQCVJS6\\Chen et al. - 2022 - GAN-DUF Hierarchical Deep Generative Models for D.pdf:application/pdf},
}

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.

@article{candry_tailoring_2022,
	title = {Tailoring polyvinyl alcohol-sodium alginate ({PVA}-{SA}) hydrogel beads by controlling crosslinking {pH} and time},
	volume = {12},
	copyright = {2022 The Author(s)},
	issn = {2045-2322},
	url = {https://www.nature.com/articles/s41598-022-25111-7},
	doi = {10.1038/s41598-022-25111-7},
	abstract = {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.},
	language = {en},
	number = {1},
	urldate = {2023-09-20},
	journal = {Scientific Reports},
	author = {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},
	month = dec,
	year = {2022},
	note = {Number: 1
Publisher: Nature Publishing Group},
	keywords = {Biotechnology, Chemical engineering, Gels and hydrogels},
	pages = {20822},
	file = {Full Text PDF:C\:\\Users\\Evan\\Zotero\\storage\\X8X9BHUF\\Candry et al. - 2022 - Tailoring polyvinyl alcohol-sodium alginate (PVA-S.pdf:application/pdf},
}

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.