Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques

R Bostanabad, Y Zhang, X Li, T Kearney… - Progress in Materials …, 2018‏ - Elsevier
Building sensible processing-structure-property (PSP) links to gain fundamental insights and
understanding of materials behavior has been the focus of many works in computational …

Guiding the design of heterogeneous electrode microstructures for Li‐ion batteries: microscopic imaging, predictive modeling, and machine learning

H Xu, J Zhu, DP Finegan, H Zhao, X Lu… - Advanced Energy …, 2021‏ - Wiley Online Library
Electrochemical and mechanical properties of lithium‐ion battery materials are heavily
dependent on their 3D microstructure characteristics. A quantitative understanding of the …

Deep learning predicts path-dependent plasticity

M Mozaffar, R Bostanabad, W Chen, K Ehmann… - Proceedings of the …, 2019‏ - pnas.org
Plasticity theory aims at describing the yield loci and work hardening of a material under
general deformation states. Most of its complexity arises from the nontrivial dependence of …

A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality

MA Bessa, R Bostanabad, Z Liu, A Hu… - Computer Methods in …, 2017‏ - Elsevier
A new data-driven computational framework is developed to assist in the design and
modeling of new material systems and structures. The proposed framework integrates three …

Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials

B Mortazavi - Advanced Energy Materials, 2024‏ - Wiley Online Library
This review highlights recent advances in machine learning (ML)‐assisted design of energy
materials. Initially, ML algorithms were successfully applied to screen materials databases …

Machine-learning-assisted de novo design of organic molecules and polymers: opportunities and challenges

G Chen, Z Shen, A Iyer, UF Ghumman, S Tang, J Bi… - Polymers, 2020‏ - mdpi.com
Organic molecules and polymers have a broad range of applications in biomedical,
chemical, and materials science fields. Traditional design approaches for organic molecules …

A framework to link localized cooling and properties of directed energy deposition (DED)-processed Ti-6Al-4V

SJ Wolff, S Lin, EJ Faierson, WK Liu, GJ Wagner, J Cao - Acta Materialia, 2017‏ - Elsevier
Additive manufacturing (AM) of titanium alloys is a rapidly growing field due to an increase in
design flexibility of parts. However, AM parts are highly anisotropic in material microstructure …

Stochastic microstructure characterization and reconstruction via supervised learning

R Bostanabad, AT Bui, W **e, DW Apley, W Chen - Acta Materialia, 2016‏ - Elsevier
Microstructure characterization and reconstruction have become indispensable parts of
computational materials science. The main contribution of this paper is to introduce a …

An improved 3D microstructure reconstruction approach for porous media

KQ Li, Y Liu, ZY Yin - Acta Materialia, 2023‏ - Elsevier
Microstructure reconstruction of porous media is vital for the evaluation of material
properties, which has been applied in many fields. Various approaches have been …

Uncertainty quantification in multiscale simulation of woven fiber composites

R Bostanabad, B Liang, J Gao, WK Liu, J Cao… - Computer Methods in …, 2018‏ - Elsevier
Woven fiber composites have been increasingly employed as light-weight materials in
aerospace, construction, and transportation industries due to their superior properties …