Dr Dario Caramelli
- Affiliate (School of Chemistry)
email:
Dario.Caramelli@glasgow.ac.uk
School of Chemistry, The ARC, University of Glasgow, Glasgow, G12 8QQ
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email:
Dario.Caramelli@glasgow.ac.uk
School of Chemistry, The ARC, University of Glasgow, Glasgow, G12 8QQ
Leonov, A. I. et al. (2024) An integrated self-optimizing programmable chemical synthesis and reaction engine. Nature Communications, 15, 1240. (doi: 10.1038/s41467-024-45444-3) (PMID:38336880) (PMCID:PMC10858227)
M. Mehr, S. H. , Caramelli, D. and Cronin, L. (2023) Digitizing chemical discovery with a Bayesian explorer for interpreting reactivity data. Proceedings of the National Academy of Sciences of the United States of America, 120(17), e2220045120. (doi: 10.1073/pnas.2220045120) (PMID:37068251)
Caramelli, D., Granda, J. M., Mehr, S. H. M. , Cambie, D. , Henson, A. B. and Cronin, L. (2021) Discovering new chemistry with an autonomous robotic platform driven by a reactivity-seeking neural network. ACS Central Science, 7(11), pp. 1821-1830. (doi: 10.1021/acscentsci.1c00435)
Caramelli, D., Henson, A. , Aragon Camarasa, G. , Sharabi, S., Keenan, G. and Cronin, L. (2018) Networking chemical robots for reaction multitasking. Nature Communications, 9, 3406. (doi: 10.1038/s41467-018-05828-8) (PMID:30143646) (PMCID:PMC6109044)
Turk-MacLeod, R., Henson, A. , Rodriguez-Garcia, M., Gibson, G. M. , Aragon Camarasa, G. , Caramelli, D., Padgett, M. J. and Cronin, L. (2018) Approach to classify, separate, and enrich objects in groups using ensemble sorting. Proceedings of the National Academy of Sciences of the United States of America, 115(22), pp. 5681-5685. (doi: 10.1073/pnas.1721929115) (PMID:29760051) (PMCID:PMC5984510)
Leonov, A. I. et al. (2024) An integrated self-optimizing programmable chemical synthesis and reaction engine. Nature Communications, 15, 1240. (doi: 10.1038/s41467-024-45444-3) (PMID:38336880) (PMCID:PMC10858227)
M. Mehr, S. H. , Caramelli, D. and Cronin, L. (2023) Digitizing chemical discovery with a Bayesian explorer for interpreting reactivity data. Proceedings of the National Academy of Sciences of the United States of America, 120(17), e2220045120. (doi: 10.1073/pnas.2220045120) (PMID:37068251)
Caramelli, D., Granda, J. M., Mehr, S. H. M. , Cambie, D. , Henson, A. B. and Cronin, L. (2021) Discovering new chemistry with an autonomous robotic platform driven by a reactivity-seeking neural network. ACS Central Science, 7(11), pp. 1821-1830. (doi: 10.1021/acscentsci.1c00435)
Caramelli, D., Henson, A. , Aragon Camarasa, G. , Sharabi, S., Keenan, G. and Cronin, L. (2018) Networking chemical robots for reaction multitasking. Nature Communications, 9, 3406. (doi: 10.1038/s41467-018-05828-8) (PMID:30143646) (PMCID:PMC6109044)
Turk-MacLeod, R., Henson, A. , Rodriguez-Garcia, M., Gibson, G. M. , Aragon Camarasa, G. , Caramelli, D., Padgett, M. J. and Cronin, L. (2018) Approach to classify, separate, and enrich objects in groups using ensemble sorting. Proceedings of the National Academy of Sciences of the United States of America, 115(22), pp. 5681-5685. (doi: 10.1073/pnas.1721929115) (PMID:29760051) (PMCID:PMC5984510)
Mehr, H. , Caramelli, D. and Cronin, L. (2022) Digitizing Chemical Discovery with a Bayesian Explorer for Interpreting Reactivity Data. [Data Collection]
Cronin, L. , Caramelli, D., Granda, J. M., Cambie, D., Mehr, H. and Henson, A. (2020) Dataset for A Reactivity First Approach to Autonomous Discovery of New Chemistry. [Data Collection]