Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2

Abstract Dozens of Cu zeolites with MOR, FAU, BEA, FER, CHA and MFI frameworks are tested for direct oxidation of CH4 to CH3OH using H2O2 as oxidant. To investigate the active structures of the Cu zeolites, 15 structural variables, which describe the features of the zeolite framework and reflect the...

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Autores principales:	Junya Ohyama, Airi Hirayama, Nahoko Kondou, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Kenji Hirai, Itsuki Miyazato, Keisuke Takahashi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/797275017f444ce6b6872fb7c39cd9fe
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spelling	oai:doaj.org-article:797275017f444ce6b6872fb7c39cd9fe2021-12-02T15:23:47ZData science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O210.1038/s41598-021-81403-42045-2322https://doaj.org/article/797275017f444ce6b6872fb7c39cd9fe2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81403-4https://doaj.org/toc/2045-2322Abstract Dozens of Cu zeolites with MOR, FAU, BEA, FER, CHA and MFI frameworks are tested for direct oxidation of CH4 to CH3OH using H2O2 as oxidant. To investigate the active structures of the Cu zeolites, 15 structural variables, which describe the features of the zeolite framework and reflect the composition, the surface area and the local structure of the Cu zeolite active site, are collected from the Database of Zeolite Structures of the International Zeolite Association (IZA). Also analytical studies based on inductively coupled plasma-optical emission spectrometry (ICP-OES), X-ray fluorescence (XRF), N2 adsorption specific surface area measurement and X-ray absorption fine structure (XAFS) spectral measurement are performed. The relationships between catalytic activity and the structural variables are subsequently revealed by data science techniques, specifically, classification using unsupervised and supervised machine learning and data visualization using pairwise correlation. Based on the unveiled relationships and a detailed analysis of the XAFS spectra, the local structures of the Cu zeolites with high activity are proposed.Junya OhyamaAiri HirayamaNahoko KondouHiroshi YoshidaMasato MachidaShun NishimuraKenji HiraiItsuki MiyazatoKeisuke TakahashiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Junya Ohyama Airi Hirayama Nahoko Kondou Hiroshi Yoshida Masato Machida Shun Nishimura Kenji Hirai Itsuki Miyazato Keisuke Takahashi Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
description	Abstract Dozens of Cu zeolites with MOR, FAU, BEA, FER, CHA and MFI frameworks are tested for direct oxidation of CH4 to CH3OH using H2O2 as oxidant. To investigate the active structures of the Cu zeolites, 15 structural variables, which describe the features of the zeolite framework and reflect the composition, the surface area and the local structure of the Cu zeolite active site, are collected from the Database of Zeolite Structures of the International Zeolite Association (IZA). Also analytical studies based on inductively coupled plasma-optical emission spectrometry (ICP-OES), X-ray fluorescence (XRF), N2 adsorption specific surface area measurement and X-ray absorption fine structure (XAFS) spectral measurement are performed. The relationships between catalytic activity and the structural variables are subsequently revealed by data science techniques, specifically, classification using unsupervised and supervised machine learning and data visualization using pairwise correlation. Based on the unveiled relationships and a detailed analysis of the XAFS spectra, the local structures of the Cu zeolites with high activity are proposed.
format	article
author	Junya Ohyama Airi Hirayama Nahoko Kondou Hiroshi Yoshida Masato Machida Shun Nishimura Kenji Hirai Itsuki Miyazato Keisuke Takahashi
author_facet	Junya Ohyama Airi Hirayama Nahoko Kondou Hiroshi Yoshida Masato Machida Shun Nishimura Kenji Hirai Itsuki Miyazato Keisuke Takahashi
author_sort	Junya Ohyama
title	Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
title_short	Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
title_full	Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
title_fullStr	Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
title_full_unstemmed	Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2
title_sort	data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using h2o2
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/797275017f444ce6b6872fb7c39cd9fe
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Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2

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