Stochastic surface walking method for crystal structure and phase transition pathway prediction
Literature Information
Cheng Shang, Xiao-Jie Zhang, Zhi-Pan Liu
The determination of crystal structures and the solid-to-solid phase transition mechanisms are two important and related subjects in material science. Here we develop an unbiased general-purpose potential energy surface (PES) searching method, namely, SSW-crystal method, for prediction of both the crystal structure and the crystal phase transition pathway. The SSW-crystal method features with stochastic surface walking (SSW) via repeated small structural perturbation by taking into account the second derivative information on both the lattice and the atom degrees of freedom. The SSW-crystal method is capable of overcoming the high barrier of phase transition and identifying the desirable phase transition reaction coordinates. By applying the SSW-crystal method to a set of examples, including SiO2 crystal up to 162 atoms per cell, Lennard-Jones model crystals up to 256 atoms, ternary SrTiO3 crystal of 50 atoms and the rutile-to-anatase TiO2 phase transition, we show that the SSW-crystal method can efficiently locate the global minimum (GM) from random initial structures without a priori knowledge of the system, and also allows for exhaustive sampling of the phase transition pathways, from which the lowest energy pathway can be obtained.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.














