Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li7La3Zr2O12 solid electrolytes.

Batteries based on solid-state electrolytes, including Li7La3Zr2O12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. These examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.

Impacts of vacancy-induced polarization and distortion on diffusion in solid electrolyte Li3OCl.

Lithium-rich oxychloride antiperovskites are promising solid electrolytes for enabling next-generation batteries. Here, we report a comprehensive study varying Li+ concentrations in [Formula: see text] using ab initio molecular dynamics simulations. The simulations accurately capture the complex interactions between Li+ vacancies ([Formula: see text]), the dominant mobile species in [Formula: see text]. The [Formula: see text] polarize and distort the host lattice, inducing additional non-vacancy-mediated diffusion mechanisms and correlated diffusion events that reduce the activation energy barrier at concentrations as low as 1.5% [Formula: see text]. Our analyses of discretized diffusion events in both space and time illustrate the critical interplay between correlated dynamics, polarization and local distortion in promoting ionic conductivity in [Formula: see text]. This article is part of the Theo Murphy meeting issue 'Understanding fast-ion conduction in solid electrolytes'.

Paradigms of frustration in superionic solid electrolytes.

Superionic solid electrolytes have widespread use in energy devices, but the fundamental motivations for fast ion conduction are often elusive. In this Perspective, we draw upon atomistic simulations of a wide range of superionic conductors to illustrate some ways frustration can lower diffusion cation barriers in solids. Based on our studies of halides, oxides, sulfides and hydroborates and a survey of published reports, we classify three types of frustration that create competition between different local atomic preferences, thereby flattening the diffusive energy landscape. These include chemical frustration, which derives from competing factors in the anion-cation interaction; structural frustration, which arises from lattice arrangements that induce site distortion or prevent cation ordering; and dynamical frustration, which is associated with temporary fluctuations in the energy landscape due to anion reorientation or cation reconfiguration. For each class of frustration, we provide detailed simulation analyses of various materials to show how ion mobility is facilitated, resulting in stabilizing factors that are both entropic and enthalpic in origin. We propose the use of these categories as a general construct for classifying frustration in superionic conductors and discuss implications for future development of suitable descriptors and improvement strategies. This article is part of the Theo Murphy meeting issue 'Understanding fast-ion conduction in solid electrolytes'.

The impacts of dopants on the small polaron mobility and conductivity in hematite - the role of disorder.

Hematite (α-Fe2O3) is a promising transition metal oxide for various energy conversion and storage applications due to its advantages of low cost, high abundance, and good chemical stability. However, its low carrier mobility and electrical conductivity have hindered the wide application of hematite-based devices. Fundamentally, this is mainly caused by the formation of small polarons, which show conduction through thermally activated hopping. Atomic doping is one of the most promising approaches for improving the electrical conductivity in hematite. However, its impact on the carrier mobility and electrical conductivity of hematite at the atomic level remains to be illusive. In this work, through a kinetic Monte-Carlo sampling approach for diffusion coefficients combined with carrier concentrations computed under charge neutrality conditions, we obtained the electrical conductivity of the doped hematite. We considered the contributions from individual Fe-O layers, given that the in-plane carrier transport dominates. We then studied how different dopants impact the carrier mobility in hematite using Sn, Ti, and Nb as prototypical examples. We found that the carrier mobility change is closely correlated with the local distortion of Fe-Fe pairs, i.e. the more stretched the Fe-Fe pairs are compared to the pristine systems, the lower the carrier mobility will be. Therefore, elements which limit the distortion of Fe-Fe pair distances from pristine are more desired for higher carrier mobility in hematite. The calculated local structure and pair distribution functions of the doped systems have remarkable agreement with the experimental EXAFS measurements on hematite nanowires, which further validates our first-principles predictions. Our work revealed how dopants impact the carrier mobility and electrical conductivity of hematite and provided practical guidelines to experimentalists on the choice of dopants for the optimal electrical conductivity of hematite and the performance of hematite-based devices.