Long timescale molecular dynamics simulations of carboxylic acid-modified anatase TiO2(101)-water interfaces using ab-initio deep neural network potentials
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引用次数: 0
Abstract
Carboxylic acid-modified anatase TiO-water interfaces are widely relevant, yet understanding of their molecular scale structure is limited. To help improve this understanding, we here construct a deep neural network potential (DP) that accurately represents the potential energy surface of the formic (FA) and acetic acid (AA)-covered anatase TiO(101) (A101) interfaces with water predicted by Density Functional Theory (DFT) with the SCAN exchange–correlation functional. Long time-scale (ns) Molecular Dynamics simulations employing such DP provide insight into the hydration structure at the interface, showing how the water density profile and radial distribution functions depend on the coverage and adsorption configurations of the acids. The developed model sets the stage for estimating the adsorption energetics of these small carboxylic acids on the A101 surface in an aqueous environment.
期刊介绍:
Surface Science is devoted to elucidating the fundamental aspects of chemistry and physics occurring at a wide range of surfaces and interfaces and to disseminating this knowledge fast. The journal welcomes a broad spectrum of topics, including but not limited to:
• model systems (e.g. in Ultra High Vacuum) under well-controlled reactive conditions
• nanoscale science and engineering, including manipulation of matter at the atomic/molecular scale and assembly phenomena
• reactivity of surfaces as related to various applied areas including heterogeneous catalysis, chemistry at electrified interfaces, and semiconductors functionalization
• phenomena at interfaces relevant to energy storage and conversion, and fuels production and utilization
• surface reactivity for environmental protection and pollution remediation
• interactions at surfaces of soft matter, including polymers and biomaterials.
Both experimental and theoretical work, including modeling, is within the scope of the journal. Work published in Surface Science reaches a wide readership, from chemistry and physics to biology and materials science and engineering, providing an excellent forum for cross-fertilization of ideas and broad dissemination of scientific discoveries.