DiffraLab: an interactive dual-modeling platform for exploring neutron and x-ray diffraction principles in undergraduate education

Abstract This study presents DiffraLab, an interactive platform designed to help undergraduate students master the complex relationships between instrumental parameters, resolution, and diffraction patterns. Unlike research-grade software focused on automated data analysis, DiffraLab employs a pedagogical ‘glass-box’ design, enabling learners to manipulate hidden variables—such as collimator divergence and mosaic spread—within neutron and x-ray experiments. The platform integrates three modules: ResoFox (analytical resolution based on the Caglioti model), BraggIt (stochastic Monte Carlo simulation), and G-Fitter (data fitting). By comparing deterministic theory with stochastic simulations, students visualize the trade-offs between resolution and intensity. Pilot study results indicate that this dual-modeling approach helps novices construct robust physical models and appreciate the nature of experimental evidence, serving as an effective bridge for students before accessing large-scale facilities.