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Figure 1. (A) Workflow of A-Lab for autonomous materials discovery, integrating ab initio target selection, ML-driven synthesis recipe generation, robotic solid-state synthesis, ML-driven phase identification, and active-learning optimization^[3]. Copyright 2023 Springer Nature; (B) Modular robotic workflow with mobile robots (digital images) transporting samples between a Chemspeed ISynth synthesizer, UPLC–MS and benchtop NMR, guided by a heuristic reaction planner^[1]. Copyright 2024 Springer Nature; (C) ChemAgents: a LLM-based hierarchical multi-agent system featuring a central Task Manager that coordinates four role-specific agents (Literature Reader, Experiment Designer, Computation Performer, Robot Operator) for on-demand autonomous chemical research^[4]. Copyright 2025 American Chemical Society. ML: Machine learning; UPLC–MS: ultraperformance liquid chromatography–mass spectrometry; NMR: nuclear magnetic resonance; LLM: large language model.