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A multi-process model for the photocatalytic reduction of CO 2 .

Chen SunYimin XuanKai Zhang
Published in: Physical chemistry chemical physics : PCCP (2022)
The photocatalytic conversion of CO 2 to fuel and valuable carbon compounds is a feasible method for the large-scale reuse of CO 2 . However, it involves complex multi-processes and physical phenomena, limiting the enhanced performance of photocatalysis. Consequently, building a comprehensive model is necessary. Herein, we present a multi-process computational framework for simulating the whole photocatalytic CO 2 reduction process. In this work, the physical and chemical properties of the catalysts were determined by density functional theory (DFT). Specifically, we employed a framework consisting of an optical absorption and carrier transport model to simulate the conversion process from photons to carriers, a micro-kinetic model to describe the surface catalytic reaction process, and a continuum transport model to calculate the mass transfer process between the solution and surface. Using this multiscale model, we simulated and analyzed the photocatalytic processes of rGO-MoS 2 /PPy (MoS 2 and polymer polypyrrole on reduced graphene oxide). The simulation clarified the key factors affecting the catalyst activity and selectivity. Moreover, the energy loss in different processes was also clarified, which showed that the model can be a theoretical analysis tool for analyzing and improving the photocatalytic performance of materials.
Keyphrases
  • reduced graphene oxide
  • visible light
  • gold nanoparticles
  • density functional theory
  • highly efficient
  • molecular dynamics
  • mental health
  • high speed
  • carbon dioxide
  • tandem mass spectrometry
  • electron transfer