Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …

In this review, we provide a brief history, progress, and applications, and discuss the
remaining challenges of photocontrolled reversible addition–fragmentation chain transfer …

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

Polymers are ubiquitous to almost every aspect of modern society and their use in medical
products is similarly pervasive. Despite this, the diversity in commercial polymers used in …

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 …

Photoinduced atom transfer radical polymerization (photo-ATRP) has risen to the forefront of
modern polymer chemistry as a powerful tool giving access to well-defined materials with …

In the field of polymer informatics, utilizing machine learning (ML) techniques to evaluate the
glass transition temperature T g and other properties of polymers has attracted extensive …

Polymer–protein hybrids are intriguing materials that can bolster protein stability in non‐
native environments, thereby enhancing their utility in diverse medicinal, commercial, and …

The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …

Polymers are an important class of materials with vast arrays of physical and chemical
properties and have been widely used in many applications and industrial products …