Work

Comprehensive thermal-kinetic uncertainty quantification of lithium-ion battery thermal runaway via bayesian chemical reaction neural networks

Year: 2025

Type: article

Source: Chemical Engineering Journal

DOI: 10.1016/j.cej.2025.160402

Authors: Benjamin C. Koenig, Peng Zhao, Sili Deng

Institutions: Massachusetts Institute of Technology, University of Tennessee at Knoxville

Language: English

Topic: Advanced Battery Technologies Research

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: bronze

Funders: National Science Foundation, Russian Science Foundation, National Science Foundation Graduate Research Fellowship Program

Awards: CAREER: Efficient Uncertainty Quantification in Turbulent Combustion Simulations: Theory, Algorithms, and Computations, G3531872738

OpenAlex ID: W4407597344

FWCI: 7

Cites: 74

Cited by: 29

Related to: 10