The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Self-driving laboratory for accelerated discovery of thin-film materials
Open accessAbstract
An autonomous laboratory for thin film discovery is used to optimize the doping and annealing of organic semiconductors.
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Cites
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249
Functional genomic hypothesis generation and experimentation by a robot scientist
King, R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S. H., Kell, D. B., & Oliver, S. G. (2004) · Nature · doi:10.1038/nature02236 · Cited by 662
Next-Generation Experimentation with Self-Driving Laboratories
Häse, F., Roch, L. M., & Aspuru-Guzik, A. (2019) · Trends in Chemistry · doi:10.1016/j.trechm.2019.02.007 · Cited by 426
Self-citationPhoenics: A Bayesian Optimizer for Chemistry
Häse, F., Roch, L. M., Kreisbeck, C., & Aspuru-Guzik, A. (2018) · ACS Central Science · doi:10.1021/acscentsci.8b00307 · Cited by 379
Self-citationChimera: enabling hierarchy based multi-objective optimization for self-driving laboratories
Häse, F., Roch, L. M., & Aspuru-Guzik, A. (2018) · Chemical Science · doi:10.1039/c8sc02239a · Cited by 161
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Cited by
Burger, B., Maffettone, P. M., Gusev, V. V., Aitchison, C. M., Bai, Y., Wang, X., Li, X., Alston, B. M., Li, B., Clowes, R., et al. (2020) · Nature · doi:10.1038/s41586-020-2442-2 · Cited by 1,516
Recent advances and applications of deep learning methods in materials science
Choudhary, K., DeCost, B., Chen, C., Jain, A., Tavazza, F., Cohn, R., Park, C. W., Choudhary, A., Agrawal, A., Billinge, S. J. L., et al. (2022) · npj Computational Materials · doi:10.1038/s41524-022-00734-6 · Cited by 1,172
“Finally, we note an important technological challenge is to make a “closedloop” autonomous materials design and synthesis process [348, 349] that can include both machine learning and experimental components in a “self-driving laboratory” [350].”
BackgroundRenewed Prospects for Organic Photovoltaics
Zhang, G., Lin, F. R., Qi, F., Heumüller, T., Distler, A., Egelhaaf, H.-J., Li, N., Chow, P. C. Y., Brabec, C. J., Jen, A. K.-Y., et al. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00955 · Cited by 1,052
An autonomous laboratory for the accelerated synthesis of inorganic materials
Szymanski, N. J., Rendy, B., Fei, Y., Kumar, R. E., He, T., Milsted, D., McDermott, M. J., Gallant, M., Cubuk, E. D., Merchant, A., et al. (2023) · Nature · doi:10.1038/s41586-023-06734-w · Cited by 1,041
“Pioneering efforts have demonstrated autonomy in several aspects of materials research, including robotic and Bayesian-driven optimization of carbon nanotube yield 3,4 , photo-voltaic performance 5 and photocatalysis activity 6 .”
Self-Driving Laboratories for Chemistry and Materials Science
Tom, G., Schmid, S. P., Baird, S. G., Cao, Y., Darvish, K., Hao, H., Lo, S., Pablo-García, S., Rajaonson, E. M., Skreta, M., et al. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00055 · Cited by 707
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Metadata
- Authors
- 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.
- Venue
- Science Advances
- Published
- 2020-05-15
- Volume
- 6
- Issue
- 20
- Pages
- eaaz8867-eaaz8867
- ISSN
- 2375-2548 (ISSN-L)
- OpenAlex
- W2950629258
- Cited by
- 809
- References
- 5
- FWCI
- 30.86
- Type
- journal article
- Language
- en
- Open access
- gold
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- The paper
- 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. (2020). Self-driving laboratory for accelerated discovery of thin-film materials. Science Advances. https://doi.org/10.1126/sciadv.aaz8867
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
