Issue 18, 2024

Surface phase diagrams from nested sampling

Abstract

Studies in atomic-scale modeling of surface phase equilibria often focus on temperatures near zero Kelvin due to the challenges in calculating the free energy of surfaces at finite temperatures. The Bayesian-inference-based nested sampling (NS) algorithm allows for modeling phase equilibria at arbitrary temperatures by directly and efficiently calculating the partition function, whose relationship with free energy is well known. This work extends NS to calculate adsorbate phase diagrams, incorporating all relevant configurational contributions to the free energy. We apply NS to the adsorption of Lennard-Jones (LJ) gas particles on low-index and vicinal LJ solid surfaces and construct the canonical partition function from these recorded energies to calculate ensemble averages of thermodynamic properties, such as the constant-volume heat capacity and order parameters that characterize the structure of adsorbate phases. Key results include determining the nature of phase transitions of adsorbed LJ particles on flat and stepped LJ surfaces, which typically feature an enthalpy-driven condensation at higher temperatures and an entropy-driven reordering process at lower temperatures, and the effect of surface geometry on the presence of triple points in the phase diagrams. Overall, we demonstrate the ability and potential of NS for surface modeling.

Graphical abstract: Surface phase diagrams from nested sampling

Supplementary files

Article information

Article type
Paper
Submitted
04 Jan 2024
Accepted
11 Apr 2024
First published
17 Apr 2024
This article is Open Access
Creative Commons BY-NC license

Phys. Chem. Chem. Phys., 2024,26, 13862-13874

Surface phase diagrams from nested sampling

M. Yang, L. B. Pártay and R. B. Wexler, Phys. Chem. Chem. Phys., 2024, 26, 13862 DOI: 10.1039/D4CP00050A

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