High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La<sub>2</sub>O<sub>3</sub>-based catalysts for the oxidative coupling of methane-Reference-Cited by-同舟云学术

High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La₂O₃-based catalysts for the oxidative coupling of methane

Published:2022 Issue:9 Volume:12 Page:2766-2774
ISSN:2044-4753
Container-title:Catalysis Science & Technology
language:en
Short-container-title:Catal. Sci. Technol.

Author:

Nishimura Shun¹^ORCID,Le Son Dinh¹^ORCID,Miyazato Itsuki²,Fujima Jun²,Taniike Toshiaki¹,Ohyama Junya³^ORCID,Takahashi Keisuke²^ORCID

Affiliation:

1. Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi 923-1292, Japan

2. Department of Chemistry, Hokkaido University, N-10 W-8, Sapporo 060-0810, Japan

3. Faculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan

Abstract

Unique 30 types of multi-component La2O3-based catalysts for oxidative coupling of methane were discovered in 75 types of selected catalysts based on high-throughput screening and literature datasets with multi-output machine learning approaches.

Funder

Japan Science and Technology Agency

Publisher

Royal Society of Chemistry (RSC)

Subject

Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2022/CY/D1CY02206G

Reference55 articles.

1. Synthesis of ethylene via oxidative coupling of methane I. Determination of active catalysts

2. Oxidative coupling technology may offer new route to olefins

3. Breaking Through

4. Economics of the oxidative coupling of methane as an add-on unit for naphtha cracking

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