Unveiling gas‐phase oxidative coupling of methane via data analysis. Issue 20 (20th May 2021)

• Record Type: Journal Article
• Authors: Ishioka, Sora; Miyazato, Itsuki; Takahashi, Lauren; Nguyen, Thanh Nhat; Taniike, Toshiaki; Takahashi, Keisuke
• Is Part Of: Journal of computational chemistry. Volume 42:Issue 20(2021)
• Page Start: 1447
• Page End: 1451
• Publication Date: 2021-05-20
• Subjects: Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.26554
• Languages: English
• ISSNs: 0192-8651

Abstract

Abstract: Unveiling the details of the mechanisms of a chemical reaction is a difficult task as reaction mechanisms are strongly coupled with reaction conditions. Here, catalysts informatics combined with high‐throughput experimental data is implemented to understand the oxidative coupling of methane (OCM) reaction. In particular, pairwise correlation and data visualization are performed to reveal the relation between reaction conditions and selectivity/conversion. In addition, machine learning is used to fill the gap between experimental data points; thus, a more detailed understanding of the OCM reaction against reaction conditions can be achieved. Therefore, catalysts informatics is proposed for understanding the details of the reaction mechanism, thereby aiding reaction design. Abstract :