A self-learning scientific agent for X-ray diffraction

• 类型：arxiv
• 标识：2610.07862
• 链接：https://arxiv.org/abs/2610.07862
• 主分类：agent
• 形态：position
• TLDR：A central challenge for scientific agents is to turn analytical experience into reusable expertise grounded in physical evidence. Here we introduce Gan Jiang, a self-learning agent for powder X-ray diffraction built on a diffraction-analysis ecosystem we developed: XMatcher, XQueryer, XDecomposer and WPEM. Together, these engines span phase identification, multiphase decomposition and physics-constrained whole-pattern modelling. Gan Jiang converts analytical experience into executable skills by diagnosing failures, revising skill instructions and code, and validating revisions before reuse, wi
• 待LLM分类：否
• 标题中文：用于 X 射线衍射的自学习科学 Agent
• TLDR中文：科学 Agent 的核心挑战在于将分析经验转化为基于物理证据的可复用专业知识。本文介绍 Gan Jiang，一个基于我们自主开发的衍射分析生态系统（XMatcher、XQueryer、XDecomposer 与 WPEM）构建的面向粉末 X 射线衍射的自学习 Agent。这些引擎共同涵盖物相鉴定、多相分解以及物理约束的全谱建模。Gan Jiang 通过诊断失败、修订技能指令与代码，并在复用前验证修订，将分析经验转化为可执行的技能，伴随……
• 来源文件：
• /inbox/tom/_candidates/2026-10-08-agent-rag-longcontext-candidates.json