This comprehensive review discusses the recent progress in synthesis, properties,
applications, 3D printing and machine learning of graphene quantum dots (GQDs) in …

Artificial intelligence (AI)-based methods continue to make inroads into accelerated
materials design and development. Here, we review AI-enabled advances made in the …

This review paper comprehensively examines the dynamic landscape of 3D printing and
Machine Learning utilizing biodegradable polymers and their composites, presenting a …

Polymers are a vital part of everyday life. Their chemical universe is so large that it presents
unprecedented opportunities as well as significant challenges to identify suitable application …

Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

Propelled partly by the Materials Genome Initiative, and partly by the algorithmic
developments and the resounding successes of data-driven efforts in other domains …

The uprising demands for electrical power and electrification requires advanced dielectric
functionalities including high capacitance density, high energy density, high current …

The development of accurate and transferable machine learning (ML) potentials for
predicting molecular energetics is a challenging task. The process of data generation to train …

We investigate the impact of choosing regressors and molecular representations for the
construction of fast machine learning (ML) models of 13 electronic ground-state properties of …

The recent successes of the Materials Genome Initiative have opened up new opportunities
for data-centric informatics approaches in several subfields of materials research, including …