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Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques
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 …
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
Electrochemical and mechanical properties of lithium‐ion battery materials are heavily
dependent on their 3D microstructure characteristics. A quantitative understanding of the …
dependent on their 3D microstructure characteristics. A quantitative understanding of the …
Deep learning predicts path-dependent plasticity
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 …
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
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 …
modeling of new material systems and structures. The proposed framework integrates three …
Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials
This review highlights recent advances in machine learning (ML)‐assisted design of energy
materials. Initially, ML algorithms were successfully applied to screen materials databases …
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
Organic molecules and polymers have a broad range of applications in biomedical,
chemical, and materials science fields. Traditional design approaches for organic molecules …
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
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 …
design flexibility of parts. However, AM parts are highly anisotropic in material microstructure …
Stochastic microstructure characterization and reconstruction via supervised learning
Microstructure characterization and reconstruction have become indispensable parts of
computational materials science. The main contribution of this paper is to introduce a …
computational materials science. The main contribution of this paper is to introduce a …
An improved 3D microstructure reconstruction approach for porous media
Microstructure reconstruction of porous media is vital for the evaluation of material
properties, which has been applied in many fields. Various approaches have been …
properties, which has been applied in many fields. Various approaches have been …
Uncertainty quantification in multiscale simulation of woven fiber composites
Woven fiber composites have been increasingly employed as light-weight materials in
aerospace, construction, and transportation industries due to their superior properties …
aerospace, construction, and transportation industries due to their superior properties …