Artificial intelligence can rapidly propose candidate phases and structures from X-ray diffraction (XRD), but these hypotheses often fail in downstream refinement because peak intensities cannot be stably assigned under severe overlap and diffraction consistency is enforced only weakly. Here we introduce WPEM, a physics-constrained whole-pattern decomposition and refinement workflow that turns Bragg's law into an explicit constraint within a batch expectation--maximization framework. WPEM models the full profile as a probabilistic mixture density and iteratively infers component-resolved intensities while keeping peak centres Bragg-consistent, producing a continuous, physically admissible intensity representation that remains stable in heavily overlapped regions and in the presence of mixed radiation or multiple phases. We benchmark WPEM on standard reference patterns (\ce{PbSO4} and \ce{Tb2BaCoO5}), where it yields lower $R_{\mathrm{p}}$/$R_{\mathrm{wp}}$ than widely used packages (FullProf and TOPAS) under matched refinement conditions. We further demonstrate generality across realistic experimental scenarios, including phase-resolved decomposition of a multiphase Ti--15Nb thin film, quantitative recovery of \ce{NaCl}--\ce{Li2CO3} mixture compositions, separation of crystalline peaks from amorphous halos in semicrystalline polymers, high-throughput operando lattice tracking in layered cathodes, automated refinement of a compositionally disordered Ru--Mn oxide solid solution (CCDC 2530452), and quantitative phase-resolved deciphering of an ancient Egyptian make-up sample from synchrotron powder XRD. By providing Bragg-consistent, uncertainty-aware intensity partitioning as a refinement-ready interface, WPEM closes the gap between AI-generated hypotheses and diffraction-admissible structure refinement on challenging XRD data.

翻译：人工智能能够从X射线衍射数据中快速提出候选物相和结构假设，但这些假设在下游精修阶段常因峰强度在严重重叠区域无法稳定归属、且衍射一致性约束薄弱而失效。本文提出WPEM——一种物理约束的全谱分解与精修工作流，该框架将布拉格定律转化为批处理期望最大化算法中的显式约束。WPEM将完整衍射谱建模为概率混合密度模型，在保持峰位满足布拉格一致性的前提下迭代推断各组分强度，从而生成连续且物理可接受的强度表征，该表征在严重重叠区域、混合辐射或多相共存条件下仍保持稳定。我们在标准参考谱（\ce{PbSO4}与\ce{Tb2BaCoO5}）上对WPEM进行基准测试，在相同精修条件下其$R_{\mathrm{p}}$/$R_{\mathrm{wp}}$值均低于主流软件包（FullProf与TOPAS）。我们进一步展示了该方法在真实实验场景中的普适性，包括：多相Ti-15Nb薄膜的物相解析分解、\ce{NaCl}–\ce{Li2CO3}混合物成分的定量重构、半结晶聚合物中晶态峰与非晶晕的分离、层状正极材料的高通量原位晶格追踪、成分无序Ru-Mn氧化物固溶体（CCDC 2530452）的自动化精修，以及基于同步辐射粉末X射线衍射对古埃及化妆样品的定量物相解析。通过提供布拉格一致且具有不确定度评估的强度划分方案作为精修就绪接口，WPEM弥合了人工智能生成假设与衍射可容结构精修在处理挑战性X射线衍射数据之间的鸿沟。