PowderLine: a programmatic powder diffraction analysis application

arXiv:2608.1700911.1h-index: 7
Predicted impact top 30% in MTRL-SCI · last 90 daysOriginality Incremental advance
AI Analysis

This tool addresses the challenge of applying whole-pattern fitting methods at scale for high-throughput experiments and autonomous laboratories, making complex analysis more accessible and programmatic for materials scientists.

PowderLine is a Python application designed to streamline powder diffraction analysis, particularly Rietveld refinement and single peak analysis. It encapsulates the entire refinement process into a single declarative recipe, which is then validated and executed to produce structured, machine-readable results.

Whole-pattern fitting methods, such as Rietveld refinement, excel at extracting detailed structural, chemical, and microstructural information from powder diffraction data. Obtaining reliable results requires both considerable expertise and software-specific knowledge, and applying these methods at scale typically relies on custom scripts written for each application. High-throughput experiments and autonomous self-driving laboratories increasingly utilize powder diffraction analysis to proceed programmatically and to return structured, machine-readable results. Here, we introduce PowderLine, a Python application that encapsulates a complete refinement into a single declarative recipe, validates that recipe against a versioned schema, and executes it through refinement software to return structured results. The refinement recipe is an all-inclusive, machine-readable and -writable description of either Rietveld or single peak analysis that users, scripts, and automated agents can specify and run in the same way. As a result of PowderLine's composability, it naturally fits into interactive, scripted, and autonomous workflows alike.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes