First principle analysis of interfacial structure effect on optoelectronic properties of molybdenum disulfide-transition metal oxide nanocomposites

Abstract

To thoroughly investigate and understand the structural, optical, and electrical effects of incorporating transition metal oxides (TMOs) such as, Co3O4 and CuOinto molybdenum disulfide (MoS2), density functional theory (DFT) calculations with appropriate corrections were performed and impact of these changes on energy storage and catalysis applications were studied. According to calculations the incorporation of Co3O4 into MoS2 leads to Mo-4d and Co-3d orbital interactions, resulting in a decrease in the band gap. Additionally, a charge redistribution occurred at the MoS2 and Co3O4 interface, creating more active sites for electro- and opto-catalytic reactions. One of the most notable findings was the red shift of the optical absorbance spectra, which enables the nanocomposites to absorb in the near-infrared range. Additionally, theoretical calculations showed that CuO prevents the restacking of MoS2 layers, increasing its active surface area. Hybridization between Mo and O orbitals results in increased states close the fermi level, leading to higher conductivity, specific capacitance, and lower optical band gap. The transfer of charge from MoS2 to CuO creates a strong intrinsic electric field that improves electron transfer and can result in longer charging and discharging times, leading to improved electrochemical performance. Furthermore, a new catalyst model system is proposed using CuO-MoS2 heterostructure.The active surface is CuO nanosheet with exposed {001} facet and MoS2 nanosheet is the supporting layer. The heterostructure active sites provide a suitable chemical environment for selective production of multicarbon products from CO2 electrocatalytic reduction. The model exhibits good electrical conductivity, efficient electron transport to active surface sites, and less interfacial resistance. A photo-enhanced electrocatalysis mechanism is proposed due to the photoactive nature of MoS2. Machine learning is used to predict selected properties and compared with the DFT results. In summary, incorporation of TMOs have an overall positive effect and can enhance electrochemical and catalytic performance of MoS2based nanocomposites.