AI 中文总结
本研究构建Wyckoff分辨氧化态图集及阴离子条件先验，提升材料氧化态分配覆盖度，为材料发现相关工作流提供可复现的先验支持。
AI 中文摘要
我们提出一种Wyckoff分辨氧化态图集及分配工具，可从组分或Wyckoff语法中按概率排序分配电荷中性的氧化态。该图集基于Materials Project（材料项目）2026年5月快照中的154879个衍生结构构建，通过对常见及已知非零氧化态进行分阶段精确中性枚举得到。所学先验在组分模式下可分配106053种材料，在Wyckoff模式下可分配114403种材料，而Materials Project全整数可能物种总数为108642种。匹配的Materials Project基线要求每种元素至少有一个电荷中性分配且恰好一个非零整数氧化态，包含89374种材料；相较于该基线，组分模式和Wyckoff模式的覆盖度分别提升18.7%和28.0%。在仅通过Wyckoff模式恢复的14665种材料中，99.98%的同元素在不同位点符号上呈现不同的形式氧化态。该CSV/Python工作流为结构修饰、生成式晶体模型及符号Wyckoff语法工作流提供可复现的先验。
英文摘要
We introduce a Wyckoff-resolved oxidation-state atlas and assignment utility for probabilityranked, charge-neutral assignment from compositions or Wyckoff grammars. The atlas is constructed from a May 2026 snapshot of 154,879 Materials Project-derived structures by staged exact-neutral enumeration over common and known nonzero oxidation states. The learned prior assigns 106,053 materials in composition mode and 114,403 in Wyckoff mode, compared with a broad MP all-integer possible species count of 108,642. A matched MP baseline requiring at least one charge-neutral assignment with exactly one nonzero integer oxidation state per element contains 89,374 materials; relative to this baseline, composition and Wyckoff modes increase coverage by 18.7% and 28.0%. Of the 14,665 materials recovered only in Wyckoff mode, 99.98% exhibit distinct formal oxidation states for the same element on different site tokens. The CSV/Python workflow provides a reproducible prior for structure decoration, generative crystal models, and symbolic Wyckoff-grammar workflows.
Comments19 pages (main & SI) and 5 figures
