The effects of the finite size of the simulation box in equilibrium molecular dynamics simulations are investigated for prototypical superionic conductors of different types, namely the fluorite-structure materials PbF2, CaF2, and UO2 (type-II), and the α phase of AgI (type I). Largely validated empirical force-fields are employed to run ns-long simulations and extract general trends for several properties, at increasing size and in a wide temperature range. This work shows that, for the considered type-II superionic conductors, the diffusivity dramatically depends on the system size and that the superionic regime is shifted to larger temperatures in smaller cells. Furthermore, only simulations of several hundred atoms are able to capture the experimentally-observed, characteristic change in the activation energy of the diffusion process, occurring at the order-disorder transition to the superionic regime. Finite-size effects on ion diffusion are instead much weaker in α-AgI. The thermal conductivity is found generally smaller for smaller cells, where the temperature-independent (Allen-Feldman) regime is also reached at significantly lower temperatures. The finite-size effects on the thermal motion of the non-mobile ions composing the solid matrix follow the simple law which holds for solids.
Heat transport in superionic materials via machine-learned molecular dynamics
Peking University（北京大学）；Bohai University（渤海大学）；Università degli Studi di Modena e Reggio Emilia（摩德纳和雷焦艾米利亚大学）；CNRNanoS3（意大利国家研究委员会纳米科学研究所）；SISSA—Scuola Internazionale Superiore di Studi Avanzati（国际高等研究院）；CNR-IOM—Istituto Officina Materiali, DEMOCRITOS SISSA Unit（意大利国家研究委员会材料研究所DEMOCRITOS-SISSA分部）；National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Peking University（北京大学先进微纳制造技术国家重点实验室）
Deep Potential generation scheme and simulation protocol for the Li10GeP2S12-type superionic conductors
由于计算成本高，使用{ \it ab initio}分子动力学（AIMD）在室温下精确模拟锂离子在电池材料中的扩散过程一直是一个挑战。近年来，由于基于机器学习的原子间势的进步，这种情况发生了巨大变化。在这里，我们实现了深电位发生器计划，以\textit{automatically}产生LiGePS型固态电解质材料的原子间相互作用势。这增加了我们模拟这些材料的能力，在不牺牲{ \it ab initio}精度的情况下，提高了几个数量级。重要的技术方面，如统计误差和尺寸效应进行了仔细研究。我们进一步建立了一个可靠的协议，在实验条件下准确计算锂离子扩散过程，通过调查重要的技术方面，如统计误差和尺寸效应。这样的协议和自动化工作流程使我们能够以更高的效率筛选材料的相关属性。通过使用这里开发的协议和自动化的工作流程，我们得到的扩散系数数据和锂离子扩散的活化能，以及同意与实验。本文的工作为进一步研究锂离子扩散机理和优化固态电解质材料的锂离子导电性能奠定了基础。
Observation of hexagonal close-packed water ice at conditions in ice giant planetary interiors
CEA DAM DIF（法国原子能委员会达姆-迪费中心）；Université Paris-Saclay, CEA, Laboratoire Matière en Conditions Extrêmes（巴黎萨克雷大学、法国原子能委员会极端条件物质实验室）；Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Sorbonne Université, CNRS UMR 7590, MNHN（索邦大学矿物学、材料物理与宇宙化学研究所（IMPMC），CNRS UMR 7590，自然历史博物馆）；European Synchrotron Radiation Facility（欧洲同步辐射装置）
