Issue 24, 2023, Issue in Progress

Effect of defects on optical and electronic properties of graphene quantum dots: a density functional theory study

Abstract

The effects of different types of defects (vacancy, Stone–Wales defects, and heteroatom doping) and varying defect concentrations (single and double defects) on the structure, electronic, and optical properties of graphene quantum dots (GQDs) are systematically investigated using time-dependent density functional theory (TD-DFT). The results reveal that most defects induce noticeable structural distortions, with increasing deformation at higher defect concentrations. Compared to pristine GQD model C96 (with a maximum absorption peak at 592 nm), the absorption spectra of 6 defective C96 exhibit blue shifts ranging from 554 to 591 nm, while 12 defective C96 lead to red shifts (598–668 nm). The HOMO–LUMO gaps vary from 0.62 to 2.04 eV (2.10 eV for pristine C96). Quantitative analysis of the absorption spectra and molecular orbital energy levels demonstrate that the electronic and optical properties of defective C96 strongly depend on the types, concentrations, and locations of defects. NTO analysis illustrates that higher electron localization exists in defective C96, which is attributed to the disruption of the original π-conjugation caused by structural distortions and different orbital hybridizations. These findings offer a comprehensive insight into the impact of defects on GQDs and provide valuable guidance for exploiting the unique features of GQDs to expand new applications in various fields.

Graphical abstract: Effect of defects on optical and electronic properties of graphene quantum dots: a density functional theory study

Supplementary files

Article information

Article type
Paper
Submitted
18 Apr 2023
Accepted
25 May 2023
First published
31 May 2023
This article is Open Access
Creative Commons BY license

RSC Adv., 2023,13, 16232-16240

Effect of defects on optical and electronic properties of graphene quantum dots: a density functional theory study

W. Liu, Y. Han, M. Liu, L. Chen and J. Xu, RSC Adv., 2023, 13, 16232 DOI: 10.1039/D3RA02564K

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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