Modeling of heterogeneous materials and media is a problem of fundamental importance to
a wide class of phenomena and systems, ranging from condensed matter physics, soft …

Automated design synthesis has the potential to revolutionize the modern engineering
design process and improve access to highly optimized and customized products across …

Metamaterials are emerging as a new paradigmatic material system to render
unprecedented and tailorable properties for a wide variety of engineering applications …

Deep learning has recently been applied to various research areas of design optimization.
This study presents the need and effectiveness of adopting deep learning for generative …

For many decades, experimental solid mechanics has played a crucial role in characterizing
and understanding the mechanical properties of natural and novel artificial materials …

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 …

Homogenization is a technique commonly used in multiscale computational science and
engineering for predicting collective response of heterogeneous materials and extracting …

In recent years significant breakthroughs in exploring big data, recognition of complex
patterns, and predicting intricate variables have been made. One efficient way of analyzing …

Data-driven methods are emerging as an important toolset in the studies of multiscale,
multiphysics, materials phenomena. More specifically, data mining and machine learning …

The core materials knowledge needed in the accelerated design, development, and
deployment of new and improved materials is most accessible when cast in the form of …