实现领域特定的原子级模型：固态酸家族的机器学习势
Enabling Domain-Specific Atomistic Models: A Machine Learning Potential for the Solid Acid Family
- Technische Universität Ilmenau（伊尔梅瑙工业大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究提出一个针对固态酸家族的通用机器学习势，基于440万构型数据库，超越通用模型，恢复输运性质，并引入紧凑变体支持大规模模拟。
AI中文摘要：
在周期表上训练的机器学习原子间势使原子模拟得以广泛使用，并且将势专门化到单一化合物类别被广泛预期能提高精度。然而，这样的例子仍然稀少，更少有在速度上超越通用模型或达到更高水平的电子结构理论的势。在此，我们提出一个势，它在无水的固态氢键网络介导的质子导体类别内是通用的，而非跨化学领域通用，并基于一个包含440万个第一性原理构型、覆盖55种材料的数据库。该势在该领域内超越了领先的通用势，恢复了那些模型未能捕捉到的实测活化能和阴离子旋转动力学的排序；静态结构上的一致并不意味着输运性质上的一致。对于远离训练集的组成，精度会下降，但对于结构近亲仍保持竞争力，并且通过每个材料额外增加几百个构型即可达到更高水平的电子结构理论。我们还引入了一个紧凑变体，其参数仅为五分之一，速度更快，且比所有测试过的通用模型更准确。它在单个图形处理器上可维持超过25万个原子，使晶界和向高导电相的转变触手可及，并使质子的量子处理变得可负担。参考精度和可访问的系统大小因此变得基本独立，为其他化合物类别提供了模板。
英文摘要：
Machine-learned interatomic potentials trained across the periodic table have made atomistic simulation broadly accessible, and specializing them to a single compound class is widely expected to improve accuracy. Yet examples remain scarce, and fewer still surpass universal models in speed or reach a higher level of electronic-structure theory. Here we present a potential that is universal within the class of water-free solid-state hydrogen-bond network mediated proton conductors rather than across chemistry and a database of 4.4 million first-principles configurations spanning 55 materials. It surpasses leading general-purpose potentials across this domain, recovering measured activation energies and the ordering of anion rotational dynamics that those models miss; agreement on static structure does not imply agreement on transport. Accuracy falls for compositions far from the training set but stays competitive for close structural relatives, and a higher level of electronic-structure theory is reached with a few hundred additional configurations per material. We further introduce a compact variant carrying a fifth of the parameters, faster still and yet more accurate than every general-purpose model tested. It sustains more than a quarter of a million atoms on a single graphics processor, placing grain boundaries and the transition into the highly conducting phase within reach, and making a quantum treatment of the protons affordable. Reference accuracy and accessible system size thus become largely independent, offering a template for other compound classes.
