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awesome-self-driving-labs
A community-curated list of resources related to self-driving labs which combine hardware automation and artificial intelligence to accelerate scientific discovery.
https://github.com/AccelerationConsortium/awesome-self-driving-labs
Last synced: 1 day ago
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Review Papers
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2023 <!-- omit from toc -->
- Role of AI in Experimental Materials Science
- Next-Generation Intelligent Laboratories for Materials Design and Manufacturing
- Toward Autonomous Laboratories: Convergence of Artificial Intelligence and Experimental Automation
- The Rise of Self-Driving Labs in Chemical and Materials Sciences
- The Digital Lab Framework as part of The World Avatar
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2022 <!-- omit from toc -->
- Linking Scientific Instruments and Computation: Patterns, Technologies, and Experiences
- Autonomous (AI-Driven) Materials Science
- Autonomous Chemical Experiments: Challenges and Perspectives on Establishing a Self-Driving Lab - Granda, A.; Morgan Chan, Z.; Hotta, K.; Ser, C. T.; Vestfrid, J.; Wu, T. C.; Aspuru-Guzik, A. *Acc. Chem. Res.* 2022, acs.accounts.2c00220.
- Cloud Labs: Where Robots Do the Research
- Reaching Critical MASS: Crowdsourcing Designs for the next Generation of Materials Acceleration Platforms - Simpers, J.; Aspuru-Guzik, A.; Kalil, T.; Cranford, S. *Matter* 2022, 5 (7), 1972–1976.
- Defining Levels of Automated Chemical Design
- Toward Autonomous Materials Research: Recent Progress and Future Challenges - K.; Schweigert, D.; Sun, S.; Suram, S. K.; Torrisi, S. B.; Trewartha, A.; Storey, B. D. *Applied Physics Reviews* 2022, 9 (1), 011405.
- From Platform to Knowledge Graph: Evolution of Laboratory Automation
- Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery - Licona, F.; Abolhasani, M. *Advanced Intelligent Systems* 2022, 2200331.
- Artificial Intelligence for Materials Research at Extremes - Simpers, J.; Musinski, W.; Graham-Brady, L.; Li, K.; Hollenbach, J.; Singh, A.; Taheri, M. L. *MRS Bulletin* 2022, 47 (11), 1154–1164.
- Autonomous (AI-Driven) Materials Science
- Toward Autonomous Materials Research: Recent Progress and Future Challenges - K.; Schweigert, D.; Sun, S.; Suram, S. K.; Torrisi, S. B.; Trewartha, A.; Storey, B. D. *Applied Physics Reviews* 2022, 9 (1), 011405.
- Autonomous (AI-Driven) Materials Science
- Toward Autonomous Materials Research: Recent Progress and Future Challenges - K.; Schweigert, D.; Sun, S.; Suram, S. K.; Torrisi, S. B.; Trewartha, A.; Storey, B. D. *Applied Physics Reviews* 2022, 9 (1), 011405.
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2021 <!-- omit from toc -->
- Enabling Modular Autonomous Feedback-Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration
- Flexible Automation Accelerates Materials Discovery
- Autonomous Experimentation Systems for Materials Development: A Community Perspective - Simpers, J.; Brown, K. A.; Reyes, K. G.; Schrier, J.; Billinge, S.; Buonassisi, T.; Foster, I.; Gomes, C. P.; Gregoire, J. M.; Mehta, A.; Montoya, J.; Olivetti, E.; Park, C.; Rotenberg, E.; Saikin, S. K.; Smullin, S.; Stanev, V.; Maruyama, B. *Matter* 2021, 4 (9), 2702–2726.
- The Role of Machine Learning Algorithms in Materials Science: A State of Art Review on Industry 4.0
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2020 <!-- omit from toc -->
- Autonomous Discovery in the Chemical Sciences Part II: Outlook
- Autonomous Discovery in the Chemical Sciences Part I: Progress
- Materials Acceleration Platforms: On the Way to Autonomous Experimentation - Leonar, M. M.; Mejía-Mendoza, L. M.; Aguilar-Granda, A.; Sanchez-Lengeling, B.; Tribukait, H.; Amador-Bedolla, C.; Aspuru-Guzik, A. *Current Opinion in Green and Sustainable Chemistry* 2020, 25, 100370.
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2019 <!-- omit from toc -->
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2017 <!-- omit from toc -->
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2024 <!-- omit from toc -->
- Self-Driving Laboratories for Chemistry and Materials Science - Garcia, S.; Rajaonson, E. M.; Skreta, M.; Yoshikawa, N.; Corapi, S.; Akkoc, G. D.; Strieth-Kalthoff, F.; Seifrid, M.; Aspuru-Guzik, A. *Chemical Reviews* 2024.
- Review of Low-Cost Self-Driving Laboratories in Chemistry and Materials Science: The "Frugal Twin" Concept - Granda, A.; V. Kalinin, S.; Maruyama, B.; Politi, M.; Tran, H.; D. Sparks, T.; Aspuru-Guzik, A. _Digital Discovery_ 2024.
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SDL Examples
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Emoji Key
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Academic Research
- Powder-Bot: A Modular Autonomous Multi-Robot Workflow for Powder X-Ray Diffraction
- A Robotic Platform for the Synthesis of Colloidal Nanocrystals - F. *Nat. Synth* 2023.
- Self-driving laboratories to autonomously navigate the protein fitness landscape
- NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science
- A Self-Driving Laboratory Designed to Accelerate the Discovery of Adhesive Materials
- A self-driving laboratory advances the Pareto front for material properties
- Autonomous retrosynthesis of gold nanoparticles via spectral shape matching
- Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy
- Autonomous Materials Synthesis via Hierarchical Active Learning of Nonequilibrium Phase Diagrams - C.; Guevarra, D.; Connolly, A. B.; Gregoire, J. M.; Thompson, M. O.; Gomes, C. P.; van Dover, R. B. *Sci. Adv.* 2021, 7 (51), eabg4930.
- Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy
- Realization of closed-loop optimization of epitaxial titanium nitride thin-film growth via machine learning
- Toward Autonomous Additive Manufacturing: Bayesian Optimization on a 3D Printer
- Using simulation to accelerate autonomous experimentation: A case study using mechanics
- Autonomous Discovery of Battery Electrolytes with Robotic Experimentation and Machine Learning
- Self-Driving Laboratory for Accelerated Discovery of Thin-Film Materials - Guzik, A.; Hein, J. E.; Berlinguette, C. P. *Sci. Adv.* 2020, 6 (20), eaaz8867.
- Autonomous materials synthesis by machine learning and robotics
- A Bayesian experimental autonomous researcher for mechanical design
- Networking Chemical Robots for Reaction Multitasking
- Autonomy in Materials Research: A Case Study in Carbon Nanotube Growth
- Evolution of Oil Droplets in a Chemorobotic Platform
- A Self-Driving Laboratory Designed to Accelerate the Discovery of Adhesive Materials
- Autonomous retrosynthesis of gold nanoparticles via spectral shape matching
- A dynamic knowledge graph approach to distributed self-driving laboratories
- Autonomous materials synthesis by machine learning and robotics
- Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems
- Accelerate Synthesis of Metal–Organic Frameworks by a Robotic Platform and Bayesian Optimization - W.; Shutt, K.; Lin, J. *ACS Appl. Mater. Interfaces* 2021, 13 (45), 53485–53491.
- Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back - C.; Jaakkola, T. S.; Barzilay, R.; Gómez-Bombarelli, R.; Green, W. H.; & Jensen, K. F. *Science* 2023.
- Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters - Kalthoff, F.; Hao, H.; Rathore, V.; Derasp, J.; Gaudin, T.; Angello, N. H.; Seifrid, M.; Trushina, E.; Guy, M.; Liu, J.; Tang, X.; Mamada, M.; Wang, W.; Tsagaantsooj, T.; Lavigne, C.; Pollice, R.; Wu, T. C.; Hotta, K.; Bodo, L.; Li, S.; Haddadnia, M.; Wołos, A.; Roszak, R.; Ser, C. T.; Bozal-Ginesta, C.; Hickman, R. J.; Vestfrid, J.; Aguilar-Granda, A.; Klimareva, E. L.; Sigerson, R. C.; Hou, W.; Gahler, D.; Lach, S.; Warzybok, A.; Borodin, O.; Rohrbach, S.; Sanchez-Lengeling, B.; Adachi, C.; Grzybowski, B. A.; Cronin, L.; Hein, J. E.; Burke, M. D.; Aspuru-Guzik, A. _Science_ 2024, 384 (6697).
- Navigating phase diagram complexity to guide robotic inorganic materials synthesis - J.; Wang, Y.; Sun, W. *Nat. Synth* 2024.
- An autonomous laboratory for the accelerated synthesis of novel materials
- Autonomous materials synthesis by machine learning and robotics
- Functional genomic hypothesis generation and experimentation by a robot scientist
- Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations
- Brokering between tenants for an international materials acceleration platform
- Self-driving laboratories to autonomously navigate the protein fitness landscape
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Education
- Automated PH Adjustment Driven by Robotic Workflows and Active Machine Learning - Bischof, P.; Lapkin, A. A. *Chemical Engineering Journal* 2023, 451, 139099.
- Build Instructions for Closed-Loop Spectroscopy Lab: Light-Mixing Demo
- Driving school for self-driving labs
- What Is a Minimal Working Example for a Self-Driving Laboratory?
- The LEGOLAS Kit: A Low-Cost Robot Science Kit for Education with Symbolic Regression for Hypothesis Discovery and Validation
- Augmented Titration Setup for Future Teaching Laboratories
- ChemOS: An Orchestration Software to Democratize Autonomous Discovery - Mendoza, T.; Yunker, L. P. E.; Hein, J. E.; Aspuru-Guzik, A. *PLoS ONE* 2020, 15 (4), e0229862.
- Autonomous Titration for Chemistry Classrooms: Preparing Students for Digitized Chemistry Laboratories - Mendoza, T.; Boixo, C.; Romero, J.; Roch, L.; Aspuru-Guzik, A. *ChemRxiv* 2020.
- Rethinking a Timeless Titration Experimental Setup through Automation and Open-Source Robotic Technology: Making Titration Accessible for Students of All Abilities
- Driving school for self-driving labs
- ChemOS: An Orchestration Software to Democratize Autonomous Discovery - Mendoza, T.; Yunker, L. P. E.; Hein, J. E.; Aspuru-Guzik, A. *PLoS ONE* 2020, 15 (4), e0229862.
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Industry
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Prospective
- Reproducible Sorbent Materials Foundry for Carbon Capture at Scale - Ng, W.; Allen, A. J.; Stafford, C. M.; Ortiz-Montalvo, D. L. CR-PHYS-SC 2022, 3 (10).
- An Object-Oriented Framework to Enable Workflow Evolution across Materials Acceleration Platforms - Gomez, J.; Quijano Velasco, P.; Vissol-Gaudin, E.; Tan, J. D.; Ramalingam, B.; I Made, R.; Pethe, S. D.; Sebastian, S.; Lim, Y.-F.; Khoo, Z. H. J.; Bai, Y.; Cheng, J. J. W.; Hippalgaonkar, K. *Matter* 2022, 5 (10), 3124–3134.
- Designing Workflows for Materials Characterization
- Delivering Real-Time Multi-Modal Materials Analysis with Enterprise Beamlines - PHYS-SC 2022, 3 (11).
- An Automated Biomateriomics Platform for Sustainable Programmable Materials Discovery - --->
- An Automated Biomateriomics Platform for Sustainable Programmable Materials Discovery - --->
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Software
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Optimization
- Adaptive Experimentation Platform (Ax) - friendly, modular, and actively developed general-purpose Bayesian optimization platform with support for simple and advanced optimization tasks such as noisy, multi-objective, multi-task, multi-fidelity, batch, high-dimensional, linearly constrained, nonlinearly constrained, mixed continuous/discrete/categorical, and contextual Bayesian optimization.
- BoTorch - averse Bayesian optimization and constraint active search.
- RayTune
- ChemOS
- The Citrine Platform
- Deep Search
- Dragonfly - objective and multi-fidelity support.
- Atlas - world experimental science problems: mixed parameters, multi-objective, noisy, constrained, multi-fidelity, and meta-learning optimization along with search space expansion/contraction. [WIP]
- Chimera - based multi-objective optimization scalarizing function.
- Gryffin
- Gemini - fidelity Bayesian optimization technique and is supported by Gryffin.
- Golem
- Phoenics - scaling Bayesian optimization algorithm with support for batch and periodic parameter optimization.
- Anubis
- BoFire
- BLOX
- PHYSBO
- SLAMD - A web app leveraging data-driven design for cementitious materials via a digital lab twin, complemented by a (materials-agnostic) AI optimization feature. Features UI to interactively explore design spaces. The web app uses Python and Javascript.
- Summit
- GPax - based Gaussian processes (GPs) built on top of NumPyro and JAX that take advantage of prior physical knowledge and different data modalities for active learning and Bayesian optimization. It supports "deep kernel learning", structured probabilistic mean functions, hypothesis learning workflows, multitask, multifidelity, heteroscedastic, and vector BO and emphasizes user friendliness.
- Bayesian Back End (BayBE) - source toolbox by [Merck KGaA](https://www.merckgroup.com/) for Bayesian optimization, featuring custom encodings, chemical knowledge integration, hybrid spaces, transfer learning, simulation tools, and robust, serializable code for real-world experimental campaigns.
- Simulation Toolkit For Scientific Discovery (ST4SD)
- Generative Toolkit for Scientific Discovery
- NIMS-OS
- Honegumi - nay-goo-mee"), which means “skeletal framework” in Japanese, is a package for interactively creating minimal working examples for advanced Bayesian optimization topics.
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Other
- autophasemap - like data.
- Olympus - driving lab setups.
- Amplitude-Phase-Distance
- [code - details/65d39af766c13817290035c1)] is a Python API for the Chemspeed AutoSuite software.
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Workflow Orchestration
- [code - management.readthedocs.io/en/latest/)]
- [code
- [code
- [code
- [code
- [code - 021-00051-1)]
- [code
- [code
- [code - driving-lab-demo.readthedocs.io/)]
- [code
- [code
- [code
- [code (Python interface)
- [code (Python interface) - standard.com/standards/)]
- [code (Python interface) - technologies/opc-ua/)]
- [code - -->
- @sgbaird's lab-automation list - workflow-engines/).
- [code - cares/TheWorldAvatar/blob/main/JPS_BASE_LIB/python_derivation_agent/README.md)] [[paper](https://doi.org/10.1016/j.future.2023.10.008)]
- [code
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Research Data Management
- list of solutions by Labii - finder.ulb.tu-darmstadt.de/home).
- NOMAD Oasis
- eLabFTW
- SciNote
- Uncountable
- Labii
- Scispot
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Media
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Hardware
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Open-source
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Programming Languages
Categories
Sub Categories
Academic Research
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Optimization
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Workflow Orchestration
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Industry
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2022 <!-- omit from toc -->
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Education
11
Research Data Management
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Prospective
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2023 <!-- omit from toc -->
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Open-source
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2021 <!-- omit from toc -->
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Other
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2020 <!-- omit from toc -->
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2024 <!-- omit from toc -->
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2019 <!-- omit from toc -->
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Emoji Key
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2017 <!-- omit from toc -->
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Forums
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Keywords
machine-learning
9
python
7
bayesian-optimization
7
experimental-design
4
optimization
4
automation
3
active-learning
3
data-science
2
chemistry
2
workflow
2
materials-science
2
orchestration
2
deep-learning
2
data-ops
1
data-engineering
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data
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smart-lab
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self-driving-lab
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rpi-pico
1
raspberry-pi
1
infrastructure
1
ml-ops
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observability
1
pipeline
1
prefect
1
workflow-engine
1
flow-based-programming
1
javascript
1
low-code
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node-red
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openjs-foundation
1
visual-programming
1
bluesky
1
dataacquisition
1
chemyx
1
harvard-apparatus
1
high-throughput-screening
1
iot
1
laboratory
1
modbus
1
omega
1
pump-control
1
science
1
syringe-pump
1
adaptive-design
1
as7341
1
circuitpython
1
closed-loop
1
internet-of-laboratory-things
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materials-informatics
1