Modeling and prediction of lattice parameters of binary spinel compounds (AM2X4) using support vector regression with Bayesian optimization-Reference-Cited by-同舟云学术

Modeling and prediction of lattice parameters of binary spinel compounds (AM2X4) using support vector regression with Bayesian optimization

Published:2021 Issue:34 Volume:45 Page:15255-15266
ISSN:1144-0546
Container-title:New Journal of Chemistry
language:en
Short-container-title:New J. Chem.

Author:

Alade Ibrahim Olanrewaju¹,Zhang Yun²^ORCID,Xu Xiaojie²

Affiliation:

1. Department of Physics, King Fahd University of Minerals and Petroleum, Saudi Arabia

2. North Carolina State University, Raleigh, NC, 27695, USA

Abstract

The lattice constants of spinel compounds AM2X4 are correlated with the constituent elemental properties using support vector regression (SVR) optimized with Bayesian optimization.

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,General Chemistry,Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2021/NJ/D1NJ01523K

Reference46 articles.

1. A review on magnesium aluminate (MgAl2O4) spinel: synthesis, processing and applications

2. Magnetic Reversal of the Ferroelectric Polarization in a Multiferroic Spinel Oxide

3. Nickel doped spinel lithium manganate – some insights using opto-impedance

4. High critical current density Bi2Sr2CaCu2Ox/Ag wire containing oxide precursor synthesized from nano-oxides

5. Formation of Bi2Sr2CaCu2Ox/Ag multifilamentary metallic precursor powder-in-tube wires

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