This Methods/Protocols article is intended for materials scientists interested in performing
machine learning-centered research. We cover broad guidelines and best practices …

The degree of crystallinity of a polymer is a critical parameter that controls a variety of
polymer properties. A high degree of crystallinity is associated with excellent mechanical …

Materials chemistry is being profoundly influenced by the uptake of machine learning
methodologies. Machine learning techniques, in combination with established techniques …

Machine learning, applied to chemical and materials data, is transforming the field of
materials discovery and design, yet significant work is still required to fully take advantage of …

This review summarizes recent advances in experimental polymer chemistry supported by
data science. The area of polymer informatics is rapidly growing based on cheminformatics …

Combining materials science, artificial intelligence (AI), physical chemistry, and other
disciplines, materials informatics is continuously accelerating the vigorous development of …

The development of novel biomaterials is a challenging process, complicated by a design
space with high dimensionality. Requirements for performance in the complex biological …

Materials research studies are dealing with a large number of images, which can now be
facilitated via image-based machine learning techniques. In this article, we review recent …

The development of advanced materials is an important aspect of modern life. However, the
discovery of novel materials involves searching the vast chemical space to find materials …

Artificial intelligence (AI) has received widespread attention over the last few decades due to
its potential to increase automation and accelerate productivity. In recent years, a large …