Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

Abstract Aqueous Mn2+/MnO2‐based batteries have attracted enormous attentions in
aqueous energy storage fields, owing to their high working voltage and theoretical capacity …

Data-driven machine learning (ML) is widely employed in the analysis of materials structure–
activity relationships, performance optimization and materials design due to its superior …

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

ASA, CSSA and SSSA International Annual Meetings: Author Index W [ International Annual
Meetings - Home Page ] Start Browse by Section/Division of Interest Author Index Author Index …

Rechargeable batteries are vital in the domain of energy storage. However, traditional
experimental or computational simulation methods for rechargeable batteries still pose time …

The development of modern civil industry, energy and information technology is inseparable
from the rapid explorations of new materials. However, only a small fraction of materials …

Machine learning (ML) has been the focus in recent studies aiming to improve battery and
supercapacitor technology. Its application in materials research has demonstrated promising …

While machine learning has emerged in recent years as a useful tool for the rapid prediction
of materials properties, generating sufficient data to reliably train models without overfitting is …

Data-driven approaches have been revolutionizing materials science and materials
discovery in the past years. Especially when coupled with other computational physics …