Work

A data-driven framework to accelerate the discovery of hybrid cathode materials for metal-based batteries

Year: 2025

Type: article

Abstract: A data-driven, chemistry-agnostic inverse material design framework to accelerate the discovery of hybrid cathode materials for metal-based batteries.

Source: Journal of Materials Chemistry A

DOI: 10.1039/d5ta01405k

Authors: Ahmed H. Biby, Benjamin S. Rich, Charles B. Musgrave

Institutions: University of Colorado Boulder, University of Utah

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: hybrid

Funders: National Science Foundation, Division of Chemical, Bioengineering, Environmental, and Transport Systems

Awards: Enabling Sulfur-Based Beyond-Lithium Metal Batteries via a Mechanistic Understanding of Advanced Hybrid Cathodes and Borate Electrolytes, G6754102015

OpenAlex ID: W4408969320

FWCI:

Cites: 35

Cited by:

Related to: 10