AI-Based Nano-Scale Material Property Prediction for Li-Ion Batteries
Author:
Affiliation:
1. W Booth School of Engineering Practice and Technology, McMaster University, Hamilton, ON L8S 4L8, Canada
2. Department of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
Abstract
Funder
NSERC Discovery grants program
Publisher
MDPI AG
Subject
Electrical and Electronic Engineering,Electrochemistry,Energy Engineering and Power Technology
Link
https://www.mdpi.com/2313-0105/10/2/51/pdf
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4. Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17;Ruddigkeit;J. Chem. Inf. Model.,2012
5. First-principle study of doping effects (Ti, Cu, and Zn) on electrochemical performance of Li2MnO3 cathode materials for lithium-ion batteries;Moradi;Int. J. Quantum Chem.,2021
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