The development of materials is one of the driving forces to accelerate modern scientific
progress and technological innovation. Machine learning (ML) technology is rapidly …

Solar energy is attractive because it is free, renewable, abundant and sustainable.
Photocatalysis is one of the feasible routes to utilize solar energy for the degradation of …

Trapped by time-consuming traditional trial-and-error methods and vast untapped
composition space, efficiently discovering novel high entropy alloys (HEAs) with exceptional …

With the development of modern society, the requirement for energy has become
increasingly important on a global scale. Therefore, the exploration of novel materials for …

Predicting, monitoring, and optimizing the performance and health of a battery system
entails a variety of complex variables as well as unpredictability in given conditions. Data …

This two‐part Review examines how automation has contributed to different aspects of
discovery in the chemical sciences. In this first part, we describe a classification for …

Lead halide perovskites with superior optoelectrical properties are emerging as a class of
excellent materials for applications in solar cells and light‐emitting devices. However …

Within a short period of time, perovskite solar cells (PSC) have attracted paramount research
interests among the photovoltaic (PV) community. Usage of machine learning (ML) into PSC …

Dual-metal-site catalysts (DMSCs) are emerging as a new frontier in the field of oxygen
reduction reaction (ORR). However, there is a lack of design principles to provide a …

This review highlights recent advances in machine learning (ML)‐assisted design of energy
materials. Initially, ML algorithms were successfully applied to screen materials databases …