On Boltzmann Averaging in Ab Initio Thermodynamics
arXiv:2506.23229 · doi:10.1063/5.0285752
Abstract
Ab initio thermodynamics is a widespread, computationally efficient approach to predict the stable configuration of a surface in contact with a surrounding (gas or liquid) environment. In a prevalent realization of this approach, this stable configuration is simply equated with the structure in a considered candidate pool that exhibits the lowest surface free energy. Here we discuss the possibility to consider the thermal accessibility of competing, higher-energy configurations through Boltzmann averaging when the extended surface configurations and their energetics are computed within periodic boundary condition supercells. We show analytically that fully converged averages can be obtained with a candidate pool derived from exhaustive sampling in a surface unit-cell exceeding the system's correlation length. In contrast, averaging over a small pool of ad hoc assembled structures is generally ill-defined. Enumerations of a lattice-gas Hamiltonian model for on-surface oxygen adsorption at Pd(100) are employed to illustrate these considerations in a practical context.
References in corpus (8)
- Composition, structure and stability of RuO_2(110) as a function of oxygen pressure
- First-principles, atomistic thermodynamics for oxidation catalysis
- icet - A Python library for constructing and sampling alloy cluster expansions
- On the accuracy of first-principles lateral interactions: Oxygen at Pd(100)
- Machine-learning-accelerated simulations to enable automatic surface reconstruction
- Determining Surface Phase Diagrams Including Anharmonic Effects
- Surface Phase Diagrams from Nested Sampling
- Ab initio approach for thermodynamic surface phases with full consideration of anharmonic effects -- the example of hydrogen at Si(100)