Issue 38, 2021

Constructing catalyst knowledge networks from catalyst big data in oxidative coupling of methane for designing catalysts

Abstract

Designing high performance catalysts for the oxidative coupling of methane (OCM) reaction is often hindered by inconsistent catalyst data, which often leads to difficulties in extracting information such as combinatorial effects of elements upon catalyst performance as well as difficulties in reaching yields beyond a particular threshold. In order to investigate C2 yields more systematically, high throughput experiments are conducted in an effort to mass-produce catalyst-related data in a way that provides more consistency and structure. Graph theory is applied in order to visualize underlying trends in the transformation of high-throughput data into networks, which are then used to design new catalysts that potentially result in high C2 yields during the OCM reaction. Transforming high-throughput data in this manner has resulted in a representation of catalyst data that is more intuitive to use and also has resulted in the successful design of a myriad of catalysts that elicit high C2 yields, several of which resulted in yields greater than those originally reported in the high-throughput data. Thus, transforming high-throughput catalytic data into catalyst design-friendly maps provides a new method of catalyst design that is more efficient and has a higher likelihood of resulting in high performance catalysts.

Graphical abstract: Constructing catalyst knowledge networks from catalyst big data in oxidative coupling of methane for designing catalysts

Supplementary files

Article information

Article type
Edge Article
Submitted
10 Aug 2021
Accepted
27 Aug 2021
First published
22 Sep 2021
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2021,12, 12546-12555

Constructing catalyst knowledge networks from catalyst big data in oxidative coupling of methane for designing catalysts

L. Takahashi, T. N. Nguyen, S. Nakanowatari, A. Fujiwara, T. Taniike and K. Takahashi, Chem. Sci., 2021, 12, 12546 DOI: 10.1039/D1SC04390K

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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