SDL Examples

SDL Examples¶

Examples of SDLs for academic research, education, and industry.

Emoji Key¶

The following emoji are used to help represent full autonomy vs. manual intervention for various categories.

| Category | Emoji |

| ---- | ---- |

| Synthesis |🧪|

| Characterization | 🔬|

| Sample transfer |🏗️|

| Experiment planning |💻|

| Manual intervention |✖️|

Academic Research¶

Examples of SDLs which are used primarily in academic research settings.

2024 ¶

🧪🔬🏗️💻 | A dynamic knowledge graph approach to distributed self-driving laboratories. Bai, J.; Mosbach, S.; Taylor, C. J.; Karan, D.; Lee, K. F.; Rihm, S. D.; Akroyd, J.; Lapkin, A. A.; Kraft, M. Nat. Commun. 2024, 15, 462.

2023 ¶

🧪🔬🏗️✖️ | Powder-Bot: A Modular Autonomous Multi-Robot Workflow for Powder X-Ray Diffraction. Lunt, A. M.; Fakhruldeen, H.; Pizzuto, G.; Longley, L.; White, A.; Rankin, N.; Clowes, R.; Alston, B. M.; Cooper, A. I.; Chong, S. Y. arXiv 2023.
🧪🔬🏗️💻 | A Robotic Platform for the Synthesis of Colloidal Nanocrystals. Zhao, H.; Chen, W.; Huang, H.; Sun, Z.; Chen, Z.; Wu, L.; Zhang, B.; Lai, F.; Wang, Z.; Adam, M. L.; Pang, C. H.; Chu, P. K.; Lu, Y.; Wu, T.; Jiang, J.; Yin, Z.; Yu, X.-F. Nat. Synth 2023.
🧪🔬🏗️💻 | Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back. Koscher, B.; Canty, R. B.; McDonald, M. A.; Greenman, K. P.; McGill, C. J.; Bilodeau, C. L.; Jin, W.; Wu, H.; Vermeire, F. H.; Jin, B.; Hart, T.; Kulesza, T.; Li, S.-C.; Jaakkola, T. S.; Barzilay, R.; Gómez-Bombarelli, R.; Green, W. H.; & Jensen, K. F. Science 2023.
🧪🔬🏗️💻 | Self-driving laboratories to autonomously navigate the protein fitness landscape. Rapp, J. T.; Bremer, B. J.; Romero, P. A. bioRxiv 2023.
🧪🔬🏗️💻 | NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science. Tamura, R.; Tsuda, K.; Matsuda, S. arXiv 2023.

2022 ¶

🧪🔬🏗️💻 | A Self-Driving Laboratory Designed to Accelerate the Discovery of Adhesive Materials. Rooney, M. B.; MacLeod, B. P.; Oldford, R.; Thompson, Z. J.; White, K. L.; Tungjunyatham, J.; Stankiewicz, B. J.; Berlinguette, C. P. Digital Discovery 2022, 10.1039.D2DD00029F.
🧪🔬🏗️💻 | A self-driving laboratory advances the Pareto front for material properties. MacLeod, B. P., Parlane, F. G. L., Rupnow, C. C., Dettelbach, K. E., Elliott, M. S., Morrissey, T. D., Haley, T. H., Proskurin, O., Rooney, M. B., Taherimakhsousi, N., Dvorak, D. J., Chiu, H. N., Waizenegger, C. E. B., Ocean, K., Mokhtari, M. & Berlinguette, C. P. Nat Commun. 2022, 13, 995.
🧪🔬✖️💻 | Autonomous retrosynthesis of gold nanoparticles via spectral shape matching. Vaddi, Kiran; Huat Thart Chiang; and Lilo D. Pozzo. Digital Discovery 2022, 10.1039/D2DD00025C.
🧪🔬🏗️💻 | Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy. Roccapriore, K. M., Kalinin, S. V., Ziatdinov, M. Adv. Sci. 2022, 9, 2203422.

2021 ¶

🧪🔬🏗️💻 | Autonomous Materials Synthesis via Hierarchical Active Learning of Nonequilibrium Phase Diagrams. Ament, S.; Amsler, M.; Sutherland, D. R.; Chang, M.-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.
🧪🔬🏗️💻 | Accelerate Synthesis of Metal–Organic Frameworks by a Robotic Platform and Bayesian Optimization. Xie, Y.; Zhang, C.; Deng, H.; Zheng, B.; Su, J.-W.; Shutt, K.; Lin, J. ACS Appl. Mater. Interfaces 2021, 13 (45), 53485–53491.
🧪🔬🏗️💻 | Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy. Kalinin, S. V.; Ziatdinov, M.; Hinkle, J.; Jesse, S.; Ghosh, A.; Kelley, K. P.; Lupini, A. R.; Sumpter, B. G.; Vasudevan, R. K. ACS Nano 2021, 15 (8), 12604–12627.
🧪🔬✖️💻 | Realization of closed-loop optimization of epitaxial titanium nitride thin-film growth via machine learning. Ohkubo, I.; Hou, Z.; Lee, J. N.; Aizawa, T.' Lippmaa, M.; Chikyow, T.; Mori, T. Materials Today Physics 2021, 16, 100296.
🧪🔬🏗️💻 | Toward Autonomous Additive Manufacturing: Bayesian Optimization on a 3D Printer. Deneault, J. R.; Chang, J.; Myung, J.; Hooper, D.; Armstrong, A.; Pitt, M.; Maruyama, B. MRS Bulletin 2021, 46 (7), 566–575.
🧪🔬🏗️💻 | Using simulation to accelerate autonomous experimentation: A case study using mechanics. Gongora, A. E.; Snapp, K. L.; Whiting, E.; Riley, P.; Reyes, K. G.; Morgan, E. F.; Brown, K. A., Iscience 2021, 24(4).

2020 ¶

🧪🔬🏗️💻 | Autonomous Discovery of Battery Electrolytes with Robotic Experimentation and Machine Learning. Dave, A.; Mitchell, J.; Kandasamy, K.; Wang, H.; Burke, S.; Paria, B.; Póczos, B.; Whitacre, J.; Viswanathan, V. Cell Reports Physical Science 2020, 1 (12), 100264.
🧪🔬🏗️💻 | Self-Driving Laboratory for Accelerated Discovery of Thin-Film Materials. MacLeod, B. P.; Parlane, F. G. L.; Morrissey, T. D.; Häse, F.; Roch, L. M.; Dettelbach, K. E.; Moreira, R.; Yunker, L. P. E.; Rooney, M. B.; Deeth, J. R.; Lai, V.; Ng, G. J.; Situ, H.; Zhang, R. H.; Elliott, M. S.; Haley, T. H.; Dvorak, D. J.; Aspuru-Guzik, A.; Hein, J. E.; Berlinguette, C. P. Sci. Adv. 2020, 6 (20), eaaz8867.
🧪🔬🏗️💻 | ChemOS: An Orchestration Software to Democratize Autonomous Discovery. Roch, L. M.; Häse, F.; Kreisbeck, C.; Tamayo-Mendoza, T.; Yunker, L. P. E.; Hein, J. E.; Aspuru-Guzik, A. PLoS ONE 2020, 15 (4), e0229862.
🧪🔬🏗️💻 | Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems. Langner, S.; Häse, F.; Perea, J. D.; Stubhan, T.; Hauch, J.; Roch, L. M.; Heumueller, T.; Aspuru‐Guzik, A.; Brabec, C. J. Adv. Mater. 2020, 32 (14), 1907801.
🧪🔬🏗️💻 | Autonomous materials synthesis by machine learning and robotics. Shimizu, R.; Kobayashi, S.; Watanabe, Y.; Ando, Y.; Hitosugi, T. APL Mater. 2020, 8 (11), 111110.
🧪🔬🏗️💻 | A Bayesian experimental autonomous researcher for mechanical design. Gongora, A. E.; Xu, B.; Perry, W.; Okoye, C.; Riley, P.; Reyes, K. G.; Morgan, E. F.; Brown, K. A. Sci. Adv. 2020, 6 (15), eaaz1708.

2018 ¶

🧪🔬🏗️💻 | Networking Chemical Robots for Reaction Multitasking. Caramelli, D.; Salley, D.; Henson, A.; Camarasa, G. A.; Sharabi, S.; Keenan, G.; Cronin, L. Nat Commun 2018, 9 (1), 3406.

2016 ¶

🧪🔬🏗️💻 | Autonomy in Materials Research: A Case Study in Carbon Nanotube Growth. Nikolaev, P.; Hooper, D.; Webber, F.; Rao, R.; Decker, K.; Krein, M.; Poleski, J.; Barto, R.; Maruyama, B. npj Comput Mater 2016, 2 (1), 16031.

2014 ¶

🧪🔬🏗️💻 | Evolution of Oil Droplets in a Chemorobotic Platform. Gutierrez, J. M. P.; Hinkley, T.; Taylor, J. W.; Yanev, K.; Cronin, L. Nat Commun 2014, 5 (1), 5571.

Education¶

Examples of SDLs which are used primarily in educational settings.

2023 ¶

🧪🔬🏗️💻 | Automated PH Adjustment Driven by Robotic Workflows and Active Machine Learning. Pomberger, A.; Jose, N.; Walz, D.; Meissner, J.; Holze, C.; Kopczynski, M.; Müller-Bischof, P.; Lapkin, A. A. Chemical Engineering Journal 2023, 451, 139099.
🧪🔬🏗️💻 | Build Instructions for Closed-Loop Spectroscopy Lab: Light-Mixing Demo. Baird, S. G.; Sparks, T. D. ChemRxiv January 9, 2023.
🧪🔬🏗️💻 | Driving school for self-driving labs. Snapp, K. L.; Brown, K. A. Digital Discovery 2023, 10.1039/D3DD00150D.

2022 ¶

🧪🔬🏗️💻 | What Is a Minimal Working Example for a Self-Driving Laboratory?. Baird, S. G.; Sparks, T. D. Matter 2022, 5 (12), 4170–4178.
🧪🔬🏗️💻 | The LEGOLAS Kit: A Low-Cost Robot Science Kit for Education with Symbolic Regression for Hypothesis Discovery and Validation. Saar, L.; Liang, H.; Wang, A.; McDannald, A.; Rodriguez, E.; Takeuchi, I.; Kusne, A. G. MRS Bulletin 2022, 47 (9), 881–885.

2021 ¶

🧪🔬🏗️💻 | Augmented Titration Setup for Future Teaching Laboratories. Yang, F.; Lai, V.; Legard, K.; Kozdras, S.; Prieto, P. L.; Grunert, S.; Hein, J. E. J. Chem. Educ. 2021, 98 (3), 876–881.

2020 ¶

🧪🔬🏗️💻 | ChemOS: An Orchestration Software to Democratize Autonomous Discovery. Roch, L. M.; Häse, F.; Kreisbeck, C.; Tamayo-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. Häse, F.; Tamayo-Mendoza, T.; Boixo, C.; Romero, J.; Roch, L.; Aspuru-Guzik, A. ChemRxiv 2020.

2019 ¶

🧪🔬🏗️💻 | Rethinking a Timeless Titration Experimental Setup through Automation and Open-Source Robotic Technology: Making Titration Accessible for Students of All Abilities. Soong, R.; Agmata, K.; Doyle, T.; Jenne, A.; Adamo, A.; Simpson, A. J. J. Chem. Educ. 2019, 96 (7), 1497–1501.

Industry¶

Industry examples involving SDLs.

Cloud-based Labs¶

Software-as-a-Service (SaaS)¶

Prospective¶

Ideas for SDLs.

Reproducible Sorbent Materials Foundry for Carbon Capture at Scale. McDannald, A.; Joress, H.; DeCost, B.; Baumann, A. E.; Kusne, A. G.; Choudhary, K.; Yildirim, T.; Siderius, D. W.; Wong-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. Leong, C. J.; Low, K. Y. A.; Recatala-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. Kalinin, S. V., Ziatdinov, M., Ahmadi, M., Ghosh, A., Roccapriore, K., Liu, Y., & Vasudevan, R. K. (2023). arXiv:2302.04397.