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MADSci¶

Modular Autonomous Discovery for Science — an open-source Python framework for building modular, autonomous scientific laboratories.

What is MADSci?¶

MADSci makes it easier to build self-driving labs (SDLs) — laboratories that close the loop between experiment design, execution, and analysis so that AI and optimization algorithms can drive discovery with minimal human intervention.

Standing up an SDL usually means integrating a zoo of heterogeneous instruments, robots, and data systems — a large and repetitive systems-engineering burden. MADSci lowers that barrier by providing a common standard for wrapping any instrument or robot as a Node, plus a suite of independent manager services you can use on their own or compose into a full autonomous lab:

• Instrument automation & integration — wrap any device as a MADSci Node behind a common (REST) interface, in any language.

• Workflow management — define and run flexible workflows across one or more nodes.

• Experiment management — run closed-loop autonomous experiments combining workflows, compute, decision-making, and analysis.

• Resource management — track labware, consumables, equipment, samples, and assets.

• Event & data management — distributed logging and data capture across the whole lab.

• Location management — coordinate physical locations and their node/resource representations.

• Observability — built-in OpenTelemetry tracing, metrics, and log correlation.

How to cite¶

If you use MADSci in your work, please cite our paper in the Journal of Open Source Software:

Lewis, R. D., Ginsburg, T. S., Ozgulbas, D., Stone, C., Stroka, A., Cleary, A., Foster, I. T., & Paulson, N. (2026). MADSci: A modular Python-based framework to enable autonomous science. Journal of Open Source Software, 11(119), 9416. Lewis et al. (2026)

@article{Lewis2026MADSci,
  title     = {{MADSci}: A modular {Python}-based framework to enable autonomous science},
  author    = {Lewis, Ryan D. and Ginsburg, Tobias S. and Ozgulbas, Doga and Stone, Casey and Stroka, Abraham and Cleary, Aileen and Foster, Ian T. and Paulson, Noah},
  journal   = {Journal of Open Source Software},
  publisher = {Open Journals},
  year      = {2026},
  volume    = {11},
  number    = {119},
  pages     = {9416},
  doi       = {10.21105/joss.09416},
  url       = {https://doi.org/10.21105/joss.09416}
}

Instruments & robots¶

MADSci drives 36 instruments, robots and controllers today: Opentrons and Hudson liquid handlers, Universal Robots and PreciseFlex arms, plate readers, an SEM, a battery cycler, humanoid platforms, a 3D printer and beamline temperature control. Each one is a reusable module you can pick up and run against your own hardware.

See MADSci Node Modules for the full list, grouped by function and linked to every module, or the Equipment Integrator Guide to build a module for hardware that is not there yet.

Contributors¶

MADSci is developed by the Rapid Prototyping Lab at Argonne National Laboratory and a growing community. The paper authors and core contributors are Ryan D. Lewis, Tobias S. Ginsburg, Doga Ozgulbas, Casey Stone, Abraham Stroka, Aileen Cleary, Ian T. Foster, and Noah Paulson.

See the full list of everyone who has contributed on the contributors graph. Contributions are welcome — see the Contributing Guide to get involved.

Developed by the Rapid Prototyping Lab at Argonne National Laboratory.
Argonne is a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC.