Article

VERID: A semantic digital twin infrastructure for agentic self-play in automated laboratories

The authors propose VERID, a persistent, high-fidelity semantic digital twin for automated laboratories that provides AI agents with four core services: queryable introspection, time-compressed simulation, comprehensive trajectory persistence, and a safe execution framework. Three case studies using mixtures of water-soluble dye and deionized water validated its optical and fluidic foundations, demonstrating pre-detection of critical protocol errors, in-run stateful error recovery, and post-hoc identification of subtle physical faults.

Part of the event: Authors propose laboratory semantic digital twin VERID

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