Fold Commons

MoleculeFlow

How a self-driving lab actually runs a discovery campaign — as a loop, not a straight line. Each landmark run below is broken into the same five stages an autonomous system cycles through (plan → synthesize → measure → analyze → decide), and every one is cited to its primary paper. Nothing is installed; nothing about you is collected.

This is the tool — a deliberately small curated starter set of published runs, not a comprehensive index — see the coverage gauge below. Editorial is CC BY 4.0; each run links its primary paper by DOI. A native version, when it ships, adds offline use; it never gates the web.

The closed loop

1 Plan 2 Synthesize 3 Measure 4 Analyze 5 Decide
  1. 1Plan — Propose the next experiment
  2. 2Synthesize — Run it on the robotic platform
  3. 3Measure — Read the instruments
  4. 4Analyze — Interpret the result
  5. 5Decide — Accept, reject, or iterate

A curated starter set — not a comprehensive index

This edition tracks 3 landmark runs — an estimated ≈15% of the published autonomous / self-driving-lab campaigns in the field. We show what we curate and name what we omit, so you can calibrate. As of 2026-06-10.

What’s covered

  • Landmark autonomous / self-driving-lab campaigns published in peer-reviewed venues or arXiv
  • Closed-loop runs with a legible plan → synthesize → measure → analyze → decide cycle
  • Runs whose primary paper is openly citable by DOI

Known gaps

  • Most published self-driving-lab campaigns (ChemOS / Gryffin / Phoenics, Ada, RoboRXN, Emerald Cloud Lab, Berkeley A-Lab follow-ups) not yet curated here
  • Materials-acceleration-platform (MAP) runs beyond the single A-Lab example
  • Industrial closed-loop pipelines that publish no methods paper
  • Negative or aborted campaigns (survivorship bias toward headline successes)
  • Per-step raw instrument data — this corpus curates the loop structure, not the underlying datasets
Lab
Year

3 of 3 runs

  1. A-Lab 2023

    A-Lab discovers new inorganic compounds

    An autonomous synthesis platform produced novel, ICSD-absent inorganic materials over 17 days of largely unattended operation.

    1. 1. Plan DFT-screen candidate stoichiometries; rank by predicted stability.
    2. 2. Synthesize Robot weighs precursors, mixes, and fires them in a tube furnace.
    3. 3. Measure Run XRD on the quenched powder; cluster phases against the ICSD.
    4. 4. Analyze Refine cell parameters; flag novel phases.
    5. 5. Decide Promote the phase to the catalogue; queue follow-up characterisation.

    Primary paper Szymanski et al., Nature (2023) doi:10.1038/s41586-023-06734-w

  2. Coscientist 2023

    Autonomous Suzuki–Miyaura coupling planning

    A GPT-4-driven planner ("Coscientist") proposed and executed a Pd-catalysed Suzuki–Miyaura cross-coupling end-to-end with minimal human steering.

    1. 1. Plan Propose a Suzuki–Miyaura coupling between an aryl halide and a boronic acid.
    2. 2. Synthesize Issue liquid-handler instructions; run the reaction in a heated vial.
    3. 3. Measure Read the crude HPLC trace; compute conversion.
    4. 4. Analyze Compare observed product mass against the prediction.
    5. 5. Decide Accept the route; archive the successful protocol.

    Primary paper Boiko et al., Nature (2023) doi:10.1038/s41586-023-06792-0

  3. ORGANA 2024

    ORGANA runs heterogeneous chemistry with a modular agent

    A composable planning + execution graph drives wet chemistry across multiple instrument backends without per-task retooling.

    1. 1. Plan Compose a plan over the reagent + instrument graph.
    2. 2. Synthesize Route subtasks to the liquid handler / glovebox / electrochemistry rig.
    3. 3. Measure Stream sensor readings into a central state store.
    4. 4. Analyze Apply a per-task analysis tool; emit a structured outcome.
    5. 5. Decide Update the plan; loop until the success criterion is met.

    Primary paper Darvish et al., arXiv (2024) doi:10.48550/arXiv.2401.06949