The concept of multiscale modelling has emerged over the last few decades to describe
procedures that seek to simulate continuum-scale behaviour using information gleaned from …

Data‐driven science is heralded as a new paradigm in materials science. In this field, data is
the new resource, and knowledge is extracted from materials datasets that are too big or …

The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

Artificial intelligence (AI) based approaches are beginning to impact several domains of
human life, science and technology. Polymer informatics is one such domain where AI and …

Abstract Although Bayesian Optimization (BO) has been employed for accelerating materials
design in computational materials engineering, existing works are restricted to problems …

Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …

In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

Electrochemical and mechanical properties of lithium‐ion battery materials are heavily
dependent on their 3D microstructure characteristics. A quantitative understanding of the …

Identifying the key microstructure representations is crucial for computational materials
design (CMD). However, existing microstructure characterization and reconstruction (MCR) …

Materials informatics employs techniques, tools, and theories drawn from the emerging
fields of data science, internet, computer science and engineering, and digital technologies …