Multi-variable Bayesian optimization for a new composition with high Na+ conductivity in the Na3PS4 family
Author:
Affiliation:
1. Department of Advanced Components and Materials Engineering, Sunchon National University, Chonnam 57922, Republic of Korea
2. Faculty of Nanotechnology and Advanced Materials Engineering, Sejong University, Seoul 05006, Republic of Korea
Abstract
Funder
Korea Evaluation Institute of Industrial Technology
National Research Foundation of Korea
Publisher
Royal Society of Chemistry (RSC)
Subject
General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2022/TA/D1TA09886A
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