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SuSMoST: Surface Science Modeling and Simulation Toolkit.

Sergey S Akimenko1, Galina D Anisimova1, Anastasiya I Fadeeva1

  • 1Department of Chemical Engineering, Omsk State Technical University, Omsk, Russia.

Journal of Computational Chemistry
|July 4, 2020
PubMed
Summary
This summary is machine-generated.

The Surface Science Modeling and Simulation Toolkit (SuSMoST) predicts adsorption layer properties using statistical physics. This tool aids in understanding surface phenomena and designing new materials.

Keywords:
Metropolis Monte Carlolattice modelmolecular modelingself-assembled monolayerstensor networks

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Area of Science:

  • Surface Science
  • Computational Chemistry
  • Statistical Physics

Background:

  • Understanding adsorption layers is crucial for materials science and catalysis.
  • Predicting thermodynamic properties and structures of adsorption systems is computationally challenging.

Purpose of the Study:

  • Introduce the Surface Science Modeling and Simulation Toolkit (SuSMoST).
  • Provide a tool for predicting and explaining adsorption layer structure and thermodynamic properties.
  • Facilitate ab initio calculations of interactions between adsorbed species.

Main Methods:

  • SuSMoST utilizes statistical physics algorithms and models.
  • It automatically builds graph and tensor-network models from atomic descriptions.
  • Generates representative adsorption layer samples and computes thermodynamic quantities.

Main Results:

  • SuSMoST enables prediction of adsorption layer structure and thermodynamic properties.
  • Facilitates ab initio calculations for adsorbed species interactions.
  • Allows plotting of phase diagrams, assessment of thermal stability, and simulation of desorption spectra.

Conclusions:

  • SuSMoST is a valuable toolkit for surface science research.
  • It simplifies complex modeling and simulation of adsorption systems.
  • Empowers researchers to analyze and design surface-based materials and processes.