Beilstein Journal of Nanotechnology (Sep 2024)

Quantum-to-classical modeling of monolayer Ge2Se2 and its application in photovoltaic devices

  • Anup Shrivastava,
  • Shivani Saini,
  • Dolly Kumari,
  • Sanjai Singh,
  • Jost Adam

DOI
https://doi.org/10.3762/bjnano.15.94
Journal volume & issue
Vol. 15, no. 1
pp. 1153 – 1169

Abstract

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Since the discovery of graphene in 2004, the unique properties of two-dimensional materials have sparked intense research interest regarding their use as alternative materials in various photonic applications. Transition metal dichalcogenide monolayers have been proposed as transport layers in photovoltaic cells, but the promising characteristics of group IV–VI dichalcogenides are yet to be thoroughly investigated. This manuscript reports on monolayer Ge2Se2 (a group IV–VI dichalcogenide), its optoelectronic behavior, and its potential application in photovoltaics. When employed as a hole transport layer, the material fosters an astonishing device performance. We use ab initio modeling for the material prediction, while classical drift–diffusion drives the device simulations. Hybrid functionals calculate electronic and optical properties to maintain high accuracy. The structural stability has been verified using phonon spectra. The E–k dispersion reveals the investigated material’s key electronic properties. The calculations reveal a direct bandgap of 1.12 eV for monolayer Ge2Se2. We further extract critical optical parameters using the Kubo–Greenwood formalism and Kramers–Kronig relations. A significantly large absorption coefficient and a high dielectric constant inspired the design of a monolayer Ge2Se2-based solar cell, exhibiting a high open circuit voltage of Voc = 1.11 V, a fill factor of 87.66%, and more than 28% power conversion efficiency at room temperature. Our findings advocate monolayer Ge2Se2 for various optoelectronic devices, including next-generation solar cells. The hybrid quantum-to-macroscopic methodology presented here applies to broader classes of 2D and 3D materials and structures, showing a path to the computational design of future photovoltaic materials.

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