Efficient Bayesian Inference of Atomistic Structure in Complex Functional Materials

TL;DR

This paper introduces BOSS, a Bayesian optimization method that efficiently predicts atomistic structures in complex materials, demonstrated on molecular adsorption on TiO2 surfaces, aligning well with experimental data.

Contribution

The paper presents a novel Bayesian optimization approach for atomistic structure prediction in large systems, enabling high-accuracy inference with reduced computational cost.

Findings

Successfully identified favorable molecular adsorption configurations

Achieved structures consistent with experimental images

Demonstrated applicability to large-scale surface studies

Abstract

Tailoring the functional properties of advanced organic/inorganic heterogeonous devices to their intended technological applications requires knowledge and control of the microscopic structure inside the device. Atomistic quantum mechanical simulation methods deliver accurate energies and properties for individual configurations, however, finding the most favourable configurations remains computationally prohibitive. We propose a 'building block'-based Bayesian Optimisation Structure Search (BOSS) approach for addressing extended organic/inorganic interface problems and demonstrate its feasibility in a molecular surface adsorption study. In BOSS, a likelihood-free Bayesian scheme accelerates the identification of material energy landscapes with the number of sampled configurations during active learning, enabling structural inference with high chemical accuracy and featuring large simulation cells. This allowed us to identify several most favourable molecular adsorption configurations for $\mathrm{C}_{60}$ on the (101) surface of $\mathrm{TiO}_2$ anatase and clarify the key molecule-surface interactions governing structural assembly. Inferred structures were in good agreement with detailed experimental images of this surface adsorbate, demonstrating good predictive power of BOSS and opening the route towards large-scale surface adsorption studies of molecular aggregates and films.