Hybrid Modeling of Molecular Sensing and Catalysis in Low-dimensional Nanomaterials. (2016) - Baskin, Artem; Král, Petr
Abstract: We use hybrid quantum and classical modeling to describe recently observed molecular sensing at graphene grain boundaries and electrochemical reduction of carbon dioxide (CO2 ) on molybdenum disulphide (MoS2 ) flakes. In the sensing studies, classical and quantum molecular dynamics simulations are used to relax graphene with grain boundaries deposited on amorphous SiO2 . Electronic structure calculations show how this graphene is locally doped by the substrate and adsorbed molecules, while electronic transport modelling reveals that the doping can lead to synchronous opening and closing of local electron transport channels, resulting in a very large observed sensitivity. In the catalysis studies, electronic structure calculations combined with ab initio molecular dynamics uncover that the metallic character and high d-electron density of molybdenum-terminated MoS2 edges and EMIM-ion delivery are responsible for the observed superior CO2 reduction performance, with a high current density and low ∼54 mV overpotential. The described mechanisms open up new pathways for the design of nanometer-scale highly sensitive chemical detectors and the development of inexpensive systems of CO2 conversion to energy-rich products. These studies illustrate how hybrid modeling techniques can explain complex transport phenomena in nanostructures.