Ultrasound-driven formation of defects and radicals in contact-electro-catalysis: a DFT and AIMD investigation
Year: 2025
Type: article
Abstract: This study reveals the critical chemical and physical roles of ultrasound in enhancing contact-electro-catalysis (CEC), using the methane (CH4) oxidation process as a model system. By integrating density functional theory (DFT), ab initio molecular dynamics (AIMD), and targeted experiments, we demonstrate for the first time that ultrasonic treatment significantly modifies the solid material’s (i.e. catalyst) surface chemistry and morphology, leading to enhanced catalytic performance. FTIR and Raman spectroscopy analyses reveal distinct molecular-level changes in the tested solid material (i.e. fluorinated ethylene propylene (FEP)) following ultrasonication, specifically the formation of C–H bonds, aligning closely with theoretical spectra predictions. Additionally, ultrasound induces substantial physical alterations, tripling the surface roughness of FEP, and significantly elevating fluoride ion concentrations in the surrounding solution, indicating pronounced C–F bond cleavage. AIMD simulations further elucidate that ultrasound-generated radicals initiate homogenous catalytic pathways by cleaving C–H bonds in CH4, identifying this as a critical mechanistic step previously unclarified. Those induced structural defects in FEP could also simultaneously enhance heterogeneous catalytic activity. Our findings establish a comprehensive mechanistic framework that resolves prior ambiguities in ultrasound-assisted CEC processes, offering robust theoretical and experimental foundations for advancing CEC catalytic efficiency and guiding future CEC catalyst development.
Source: Applied Surface Science
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,930
Awards: Solar up-draft tower to enable atmospheric photocatalysis for non-CO2 greenhouse gases removal: an emerging negative emission technology, Porous Materials as High Pressure Nano-Reactors: Machine Learning and Multi-Scale Simulation, G3372036332, G3542845438, Intelligent on-line lubricants condition monitoring enabled by durable liquid-solid triboelectric nanogenerator, G4937468798, G7670345361
OpenAlex ID: W4416416190
