A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

We present a prototype implementation of a framework for hybrid workflows that integrates automated computation and analysis with manual experimental measurements. Leveraging the pyiron workflow engine, we introduce a lightweight, parameterized procedure description layer that can adjust instrument settings and orchestrate human interventions. Rather than replacing the existing execution engine, we add a minimal abstraction layer that translates procedure descriptions into executable steps for manual operations, enabling seamless handoffs between automated tasks and manual experimental tasks. We demonstrate the approach on a use case that combines manual tensile testing with subsequent analytical evaluation and result aggregation, illustrating how parameters and metadata propagate through the workflow and how instrument state changes and measurement results are captured. We also report a usability study that quantifies the ease with which lab scientists can create and modify workflows. Finally, we summarize lessons learned from this prototype, including improved provenance capture and streamlined experimental orchestration, as well as current limitations. We conclude that the proposed lightweight hybrid workflow description offers a promising path to bridging automation, computation and manual experimentation, and we outline directions for future work.