BEEP: A Python library for Battery Evaluation and Early Prediction-Reference-Cited by-同舟云学术

BEEP: A Python library for Battery Evaluation and Early Prediction

Published:2020-01 Issue: Volume:11 Page:100506
ISSN:2352-7110
Container-title:SoftwareX
language:en
Short-container-title:SoftwareX

Author:

Herring Patrick,Balaji Gopal Chirranjeevi,Aykol Muratahan,Montoya Joseph H.,Anapolsky Abraham,Attia Peter M.,Gent William,Hummelshøj Jens S.,Hung Linda,Kwon Ha-Kyung,Moore Patrick,Schweigert Daniel,Severson Kristen A.,Suram Santosh,Yang Zi,Braatz Richard D.,Storey Brian D.

Publisher

Elsevier BV

Subject

Computer Science Applications,Software

Reference25 articles.

1. Electrical energy storage for transportation—approaching the limits of, and going beyond, lithium-ion batteries

2. Data-Driven Studies of Li-Ion-Battery Materials

3. High-throughput quantum chemistry and virtual screening for lithium ion battery electrolyte additives

4. The Electrolyte Genome project: A big data approach in battery materials discovery

5. Novel mixed polyanions lithium-ion battery cathode materials predicted by high-throughput ab initio computations

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