Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …

Realizing solid‐state lithium batteries with higher energy density and enhanced safety
compared to the conventional liquid lithium‐ion batteries is one of the primary research and …

Batteries are of paramount importance for the energy storage, consumption, and
transportation in the current and future society. Recently machine learning (ML) has …

The development of solid polymer electrolytes for lithium− metal (Li0) batteries (LMBs) with
high energy density and high safety has been a long-standing goal that attracted intensive …

Retired electric-vehicle lithium-ion battery (EV-LIB) packs pose severe environmental
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …

The rapidly growing interest in machine learning (ML) for materials discovery has resulted in
a large body of published work. However, only a small fraction of these publications includes …

It has long remained challenging to predict the properties of complex chemical systems,
such as polymer-based materials and their composites. We have constructed the largest …

Solid polymer electrolytes (SPEs) are considered promising building blocks of next-
generation lithium-ion batteries due to their advantages in safety, cost, and flexibility …

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

Lithium batteries (LBs) have many high demands regarding their application in portable
electronic devices, electric vehicles, and smart grids. Machine learning (ML) can effectively …