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MacLeod BP, Parlane FGL, Morrissey TD, Häse F, Roch LM, Dettelbach KE, Moreira R, Yunker LPE, Rooney MB, Deeth JR, Lai V, Ng GJ, Situ H, Zhang RH, Elliott MS, Haley TH, Dvorak DJ, Aspuru-Guzik A, Hein JE, Berlinguette CP. Self-driving laboratory for accelerated discovery of thin-film materials. Sci Adv 2020; 6:eaaz8867. [PMID: 32426501 PMCID: PMC7220369 DOI: 10.1126/sciadv.aaz8867] [Citation(s) in RCA: 139] [Impact Index Per Article: 34.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 02/28/2020] [Indexed: 05/17/2023]
Abstract
Discovering and optimizing commercially viable materials for clean energy applications typically takes more than a decade. Self-driving laboratories that iteratively design, execute, and learn from materials science experiments in a fully autonomous loop present an opportunity to accelerate this research process. We report here a modular robotic platform driven by a model-based optimization algorithm capable of autonomously optimizing the optical and electronic properties of thin-film materials by modifying the film composition and processing conditions. We demonstrate the power of this platform by using it to maximize the hole mobility of organic hole transport materials commonly used in perovskite solar cells and consumer electronics. This demonstration highlights the possibilities of using autonomous laboratories to discover organic and inorganic materials relevant to materials sciences and clean energy technologies.
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Affiliation(s)
- B. P. MacLeod
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
- Stewart Blusson Quantum Matter Institute, The University of British Columbia, Vancouver, British Columbia, Canada
| | - F. G. L. Parlane
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
- Stewart Blusson Quantum Matter Institute, The University of British Columbia, Vancouver, British Columbia, Canada
| | - T. D. Morrissey
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
- Stewart Blusson Quantum Matter Institute, The University of British Columbia, Vancouver, British Columbia, Canada
| | - F. Häse
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, MaRS Centre, Toronto, Ontario, Canada
| | - L. M. Roch
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, MaRS Centre, Toronto, Ontario, Canada
| | - K. E. Dettelbach
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - R. Moreira
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - L. P. E. Yunker
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - M. B. Rooney
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - J. R. Deeth
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - V. Lai
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - G. J. Ng
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - H. Situ
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - R. H. Zhang
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - M. S. Elliott
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - T. H. Haley
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - D. J. Dvorak
- Stewart Blusson Quantum Matter Institute, The University of British Columbia, Vancouver, British Columbia, Canada
| | - A. Aspuru-Guzik
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Vector Institute for Artificial Intelligence, MaRS Centre, Toronto, Ontario, Canada
- Canadian Institute for Advanced Research (CIFAR), MaRS Centre, Toronto, Ontario, Canada
| | - J. E. Hein
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
| | - C. P. Berlinguette
- Department of Chemistry, The University of British Columbia, Vancouver, British Columbia, Canada
- Stewart Blusson Quantum Matter Institute, The University of British Columbia, Vancouver, British Columbia, Canada
- Canadian Institute for Advanced Research (CIFAR), MaRS Centre, Toronto, Ontario, Canada
- Department of Chemical and Biological Engineering, The University of British Columbia, Vancouver, British Columbia, Canada
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Onstott TC, Magnabosco C, Aubrey AD, Burton AS, Dworkin JP, Elsila JE, Grunsfeld S, Cao BH, Hein JE, Glavin DP, Kieft TL, Silver BJ, Phelps TJ, van Heerden E, Opperman DJ, Bada JL. Does aspartic acid racemization constrain the depth limit of the subsurface biosphere? Geobiology 2014; 12:1-19. [PMID: 24289240 DOI: 10.1111/gbi.12069] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Accepted: 11/06/2013] [Indexed: 06/02/2023]
Abstract
Previous studies of the subsurface biosphere have deduced average cellular doubling times of hundreds to thousands of years based upon geochemical models. We have directly constrained the in situ average cellular protein turnover or doubling times for metabolically active micro-organisms based on cellular amino acid abundances, D/L values of cellular aspartic acid, and the in vivo aspartic acid racemization rate. Application of this method to planktonic microbial communities collected from deep fractures in South Africa yielded maximum cellular amino acid turnover times of ~89 years for 1 km depth and 27 °C and 1-2 years for 3 km depth and 54 °C. The latter turnover times are much shorter than previously estimated cellular turnover times based upon geochemical arguments. The aspartic acid racemization rate at higher temperatures yields cellular protein doubling times that are consistent with the survival times of hyperthermophilic strains and predicts that at temperatures of 85 °C, cells must replace proteins every couple of days to maintain enzymatic activity. Such a high maintenance requirement may be the principal limit on the abundance of living micro-organisms in the deep, hot subsurface biosphere, as well as a potential limit on their activity. The measurement of the D/L of aspartic acid in biological samples is a potentially powerful tool for deep, fractured continental and oceanic crustal settings where geochemical models of carbon turnover times are poorly constrained. Experimental observations on the racemization rates of aspartic acid in living thermophiles and hyperthermophiles could test this hypothesis. The development of corrections for cell wall peptides and spores will be required, however, to improve the accuracy of these estimates for environmental samples.
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Affiliation(s)
- T C Onstott
- Department of Geosciences, Princeton University, Princeton, NJ, USA; Indiana Princeton Tennessee Astrobiology Initiative (IPTAI), NASA Astrobiology Institute, Indiana University, Bloomington, IN, USA
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