Photochemistry dominates over photothermal effects in the laser-induced reduction of graphene oxide by visible light

Maxim Fatkullin, Dmitry Cheshev, Andrey Averkiev, Alina Gorbunova, Gennadiy Murastov, Jianxi Liu, Pavel Postnikov, Chong Cheng (), Raul D. Rodriguez () and Evgeniya Sheremet
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Maxim Fatkullin: Tomsk Polytechnic University
Dmitry Cheshev: Tomsk Polytechnic University
Andrey Averkiev: Tomsk Polytechnic University
Alina Gorbunova: Tomsk Polytechnic University
Gennadiy Murastov: University of Mining Leoben
Jianxi Liu: Northwestern Polytechnical University
Pavel Postnikov: Tomsk Polytechnic University
Chong Cheng: Sichuan University
Raul D. Rodriguez: Tomsk Polytechnic University
Evgeniya Sheremet: Tomsk Polytechnic University

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Graphene oxide (GO) possesses specific properties that are revolutionizing materials science, with applications extending from flexible electronics to advanced nanotechnology. A key method for harnessing GO’s potential is its laser-induced reduction, yet the exact mechanisms — photothermal versus photochemical effects — remain unclear. Herein, we discover the dominant role of photochemical reactions in the laser reduction of GO under visible light, challenging the prevailing assumption that photothermal effects are dominant. Employing a combination of Raman thermometry, X-ray photoelectron and photoluminescence spectroscopies, and electrical atomic force microscopy, we quantify the temperature and map the reduction process across micro and nano scales. Our findings demonstrate that the photochemical cleavage of oxygen-containing groups below a reduction threshold temperature is a decisive factor in GO reduction, leading to distinct characteristics that cannot be replicated by heating alone. This work clarifies the fundamental mechanisms of GO transformation under visible laser irradiation, highlighting the dominant role of photochemical processes. Distinguishing these subtleties enables the development of laser-reduced GO platforms for graphene-based applications compatible with industrial scales. We illustrate this potential by encoding information on GO surfaces as optical storage, allowing us to write binary sequences in long-term memory encoding invisible even through an optical microscope.

Date: 2024
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DOI: 10.1038/s41467-024-53503-y

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