XMatcher：用于X射线衍射相识别的开源框架
XMatcher: An Open-Source Framework for X-Ray Diffraction Phase Identification
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中文总结 AI 辅助
介绍开源框架XMatcher，用于X射线衍射相识别。它集成多种功能于便携工作流程，能生成理论库、检索候选相、校正匹配并报告指标证据，其AutoMix模块可处理多相模式，通过图形界面提供可解释且可重现的相识别平台。
中文摘要 AI 辅助
粉末X射线衍射（XRD）广泛用于晶体相识别，近期机器学习方法在加速衍射解释方面能力显著。但可靠的相分配仍需透明、基于证据的验证，尤其对于复杂样品。搜索匹配方法是有力补充策略，但很多实现是专有的。我们引入XMatcher，一个开源、证据驱动框架，集成衍射数据库、匹配算法和交互式可视化于便携工作流程。它能生成理论衍射库，通过化学和衍射约束检索候选相，应用全局角移校正和一对一峰匹配，并报告定量一致性指标及峰级证据。其AutoMix模块扩展到多相模式。通过本地图形界面，它实现候选检查、交互式模式比较等功能，提供了一个可解释和可重现的晶体相识别平台。
英文摘要
Powder X-ray diffraction (XRD) is widely used for crystalline phase identification, and recent machine learning approaches have demonstrated remarkable capabilities in accelerating diffraction interpretation. However, reliable phase assignment still requires transparent, evidence-based validation, particularly for complex samples where interpretability and expert assessment remain essential. Search-match methods provide a robust and complementary strategy, yet many implementations are proprietary, limiting accessibility and reproducibility. Here, we introduce XMatcher, an open-source, evidence-driven framework that integrates diffraction databases, matching algorithms, and interactive visualization into a portable workflow. XMatcher generates theoretical diffraction libraries from crystal structures, retrieves candidate phases through chemical and diffraction constraints, applies global angular-shift correction and one-to-one peak matching, and reports quantitative agreement metrics together with peak-level evidence. Its AutoMix module extends identification to multiphase patterns by evaluating candidate phase combinations, estimating non-negative diffraction contributions, and visualizing phase-specific peak distributions. Through a local graphical interface, XMatcher enables ranked candidate inspection, interactive pattern comparison, PDF/CIF-based whole-pattern validation, and reproducible analysis export. By exposing both supporting and conflicting evidence rather than relying on a single similarity score, XMatcher provides an interpretable and reproducible platform for crystalline phase identification.
