Physics-guided descriptors for prediction of structural polymorphs

Abstract

We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structural distortion modes. We systematically generate crystal structures utilizing the distortion modes and compute their energies with single-point DFT calculations. We then train a ML model to identify low-energy configurations on the material's high-dimensional potential energy surface. Here, we use BiFeO3 as a case study and explore its phase space by tuning the amplitudes of linear combinations of a finite set of distinct distortion modes. Our procedure is validated by rediscovering several known metastable phases of BiFeO3 with complex crystal structures, and its efficiency is proved by identifying 21 new low-energy polymorphs. This approach proposes a new avenue toward accelerating the prediction of low-energy polymorphs in solid-state materials.

References in corpus (14)

• Restoring the density-gradient expansion for exchange in solids and surfaces
• Generalized gradient approximation for solids and their surfaces
• Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
• Machine Learning Unifies the Modelling of Materials and Molecules
• Universal Fragment Descriptors for Predicting Electronic Properties of Inorganic Crystals
• Predicting the thermodynamic stability of perovskite oxides using machine learning models
• First-principles predictions of low-energy phases of multiferroic BiFeO3
• Data-driven learning of total and local energies in elemental boron
• Designing a robustly metallic noncenstrosymmetric ruthenate oxide with large thermopower anisotropy
• Interplay of octahedral rotations and breathing distortions in charge ordering perovskite oxides
• Domains and ferroelectric switching pathways in Ca${}_3$Ti${}_2$O${}_7$ from first principles
• A high-energy density antiferroelectric made by interfacial electrostatic engineering
• Polar and antipolar polymorphs of metastable perovskite BiFe0.5Sc0.5O3
• Prediction of new low-energy phases of BiFeO${}_3$ with large unit cell and complex tilts beyond Glazer notation