# Graphene Oxide Photoreduction Recovers Graphene Hot Electron Cooling Dynamics

Source: [Graphene Oxide Photoreduction Recovers Graphene Hot Electron Cooling Dynamics](<https://www.sota2.com/research/paper/68fa44801e209131ce911c17>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T04:49:54.951Z

Authors: Alden N. Bradley, Spencer G. Thorp, Gina Mayonado, Edward Elliott, Matt W. Graham

Published: 2023-01-30T18:43:21.000Z

## Abstract

Reduced graphene oxide (rGO) is a bulk-processable quasi-amorphous 2D material with broad spectral coverage and fast electronic response. rGO sheets are suspended in a polymer matrix and sequentially photoreduced while measuring the evolving optical spectra and ultrafast electron relaxation dynamics. Photoreduced rGO yields optical absorption spectra that fit with the same Fano lineshape parameters as monolayer graphene. With increasing photoreduction time, rGO transient absorption kinetics accelerate monotonically, reaching an optimal point that matches the hot electron cooling in graphene. All stages of rGO ultrafast kinetics are simulated with a hot-electron cooling model mediated by disorder-assisted supercollisions. While the rGO room temperature 0.31 ps$^{-1}$ electronic cooling rate matches monolayer graphene, subsequent photoreduction can rapidly increase the rate by ~10-12$\\times$. Such accelerated supercollision rates imply a reduced mean-free scattering length caused by photoionized point-defects on the rGO sp$^2$ sub-lattice. For visible range excitations of rGO, photoreduction shows three increasing spectral peaks that match graphene quantum dot (GQD) transitions, while a broad peak from oxygenated defect edge states shrinks. These three confined GQD states donate their hot carriers to the graphene sub-lattice with a 0.17 ps rise-time that accelerates with photoreduction. Collectively, many desirable photophysical properties of 2D graphene are replicated through selectively reducing rGO scaffolded within a 3D bulk polymeric network.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2301.13176>)

[PDF](<https://arxiv.org/pdf/2301.13176.pdf>)