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Research Article

Highly efficient metal-free catalyst from cellulose for hydrogen peroxide photoproduction instructed by machine learning and transient photovoltage technology

Yan Liu1, Xiao Wang1, Yajie Zhao1, Qingyao Wu1, Haodong Nie1, Honglin Si1, Hui Huang1( ), Yang Liu1( ), Mingwang Shao1( ), Zhenhui Kang1,2( )
Institute of Functional Nano and Soft Materials Laboratory (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou 215123, China
Macao Institute of Materials Science and Engineering, Macau University of Science and Technology, Taipa, Macau 999078, China
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Graphical Abstract

Metal-free photocatalyst from cellulose shows the high photocatalytic activity and anti-poisoning properties for the photoproduction of H2O2 instructed by transient photovoltage technology and machine learning.

Abstract

Great attention has been paid to green procedures and technologies for the design of environmental catalytic systems. Biomass-derived catalysts represent one of the greener alternatives for green catalysis. Photocatalytic production of hydrogen peroxide (H2O2) from O2 and H2O is an ideal green way and has attracted widespread attention. Here, we show a metal-free photocatalyst from cellulose, which has a high photocatalytic activity for the photoproduction of H2O2 with the reaction rate up to 2,093 μmol/(h·g) and the apparent quantum efficiency of 2.33%. Importantly, a machine learning model was constructed to guide the synthesis of this metal-free photocatalyst. With the help of transient photovoltage (TPV) tests, we optimized their fabrication and catalytic activity, and clearly showed that the formation of carbon dots (CDs) facilitates the generation, separation, and transfer of photo-induced charges on the catalyst surface. This work provides a green way for the highly efficient metal-free photocatalyst design and study from biomass materials with the machine learning and TPV technology.

Keywords

cellulosecarbon dotshydrogen peroxidemachine learningtransient photovoltagemetal-free photocatalyst

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Nano Research
Volume 15 Issue 5,
May 2022
Pages 4000-4007
DOI: 10.1007/s12274-022-4111-2
Cite this article:
Liu Y, Wang X, Zhao Y, et al. Highly efficient metal-free catalyst from cellulose for hydrogen peroxide photoproduction instructed by machine learning and transient photovoltage technology. Nano Research, 2022, 15(5): 4000-4007. https://doi.org/10.1007/s12274-022-4111-2
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Received: 23 November 2021
Revised: 23 December 2021
Accepted: 27 December 2021
Published: 21 February 2022
© Tsinghua University Press 2022
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