[ad_1]
Abolhasani, M. & Kumacheva, E. The rise of self-driving labs in chemical and materials sciences. Nat. Synth. 2, 483–492 (2023).
Seifrid, M. et al. Autonomous chemical experiments: challenges and perspectives on establishing a self-driving lab. Acc. Chem. Res. 55, 2454–2466 (2022).
Angelone, D. et al. Convergence of multiple synthetic paradigms in a universally programmable chemical synthesis machine. Nat. Chem. 13, 63–69 (2021).
Steiner, S. et al. Organic synthesis in a modular robotic system driven by a chemical programming language. Science 363, eaav2211 (2019).
Coley, C. W. et al. A robotic platform for flow synthesis of organic compounds informed by AI planning. Science 365, eaax1566 (2019).
Chatterjee, S., Guidi, M., Seeberger, P. H. & Gilmore, K. Automated radial synthesis of organic molecules. Nature 579, 379–384 (2020).
Bennett, J. A. et al. Autonomous reaction Pareto-front mapping with a self-driving catalysis laboratory. Nat. Chem. Eng. 1, 240–250 (2024).
Wang, J. Y. et al. Identifying general reaction conditions by bandit optimization. Nature 626, 1025–1033 (2024).
Szymanski, N. J. et al. An autonomous laboratory for the accelerated synthesis of novel materials. Nature 624, 86–91 (2023).
Ha, T. et al. AI-driven robotic chemist for autonomous synthesis of organic molecules. Sci. Adv. 9, eadj0461 (2023).
Burger, B. et al. A mobile robotic chemist. Nature 583, 237–241 (2020).
Zhu, Q. et al. An all-round AI-Chemist with a scientific mind. Natl Sci. Rev. 9, nwac190 (2022).
Zhu, Q. et al. Automated synthesis of oxygen-producing catalysts from Martian meteorites by a robotic AI chemist. Nat. Synth. 3, 319–328 (2023).
Koscher, B. A. et al. Autonomous, multiproperty-driven molecular discovery: from predictions to measurements and back. Science 382, eadi1407 (2023).
Bayley, O., Savino, E., Slattery, A. & Noël, T. Autonomous chemistry: navigating self-driving labs in chemical and material sciences. Matter 7, 2382–2398 (2024).
Caramelli, D. et al. Discovering new chemistry with an autonomous robotic platform driven by a reactivity-seeking neural network. ACS Cent. Sci. 7, 1821–1830 (2021).
Porwol, L. et al. An autonomous chemical robot discovers the rules of inorganic coordination chemistry without prior knowledge. Angew. Chem. Int. Ed. 59, 11256–11261 (2020).
Leeman, J. et al. Challenges in high-throughput inorganic materials prediction and autonomous synthesis. PRX Energy 3, 011002 (2024).
Blair, D. J. et al. Automated iterative Csp3–C bond formation. Nature 604, 92–97 (2022).
Angello, N. H. et al. Closed-loop optimization of general reaction conditions for heteroaryl Suzuki–Miyaura coupling. Science 378, 399–405 (2022).
MacLeod, B. P. et al. Self-driving laboratory for accelerated discovery of thin-film materials. Sci. Adv. 6, eaaz8867 (2020).
Jiang, Y. et al. An artificial intelligence enabled chemical synthesis robot for exploration and optimization of nanomaterials. Sci. Adv. 8, eabo2626 (2022).
Slattery, A. et al. Automated self-optimization, intensification, and scale-up of photocatalysis in flow. Science 383, eadj1817 (2024).
Christensen, M. et al. Data-science driven autonomous process optimization. Commun. Chem. 4, 112 (2021).
Basford, A. R. et al. Streamlining the automated discovery of porous organic cages. Chem. Sci. 15, 6331–6348 (2024).
Mennen, S. M. et al. The evolution of high-throughput experimentation in pharmaceutical development and perspectives on the future. Org. Process Res. Dev. 23, 1213–1242 (2019).
Ronchetti, R., Moroni, G., Carotti, A., Gioiello, A. & Camaioni, E. Recent advances in urea- and thiourea-containing compounds: focus on innovative approaches in medicinal chemistry and organic synthesis. RSC Med. Chem. 12, 1046–1064 (2021).
Brown, D. G. & Boström, J. Analysis of past and present synthetic methodologies on medicinal chemistry: where have all the new reactions gone?: Miniperspective. J. Med. Chem. 59, 4443–4458 (2016).
Zhang, D., Ronson, T. K., Zou, Y.-Q. & Nitschke, J. R. Metal–organic cages for molecular separations. Nat. Rev. Chem. 5, 168–182 (2021).
Bilbeisi, R. A. et al. Subcomponent self-assembly and guest-binding properties of face-capped Fe4L48+ capsules. J. Am. Chem. Soc. 134, 5110–5119 (2012).
Jiménez, A. et al. Selective encapsulation and sequential release of guests within a self-sorting mixture of three tetrahedral cages. Angew. Chem. Int. Ed. 53, 4556–4560 (2014).
Yoshida, N. & Ichikawa, K. Synthesis and structure of a dinuclear zinc(II) triple helix of an N,N-bis-bidentate Schiff base: new building blocks for the construction of helical structures. Chem. Commun. https://doi.org/10.1039/a701669g (1997).
Chu, L., Ohta, C., Zuo, Z. & MacMillan, D. W. C. Carboxylic acids as a traceless activation group for conjugate additions: a three-step synthesis of (±)-pregabalin. J. Am. Chem. Soc. 136, 10886–10889 (2014).
Vijayakrishnan, S., Ward, J. W. & Cooper, A. I. Discovery of a covalent triazine framework photocatalyst for visible-light-driven chemical synthesis using high-throughput screening. ACS Catal. 12, 10057–10064 (2022).
Thurow, K. et al. Multi-floor laboratory transportation technologies based on intelligent mobile robots. Transp. Saf. Environ. 1, 37–53 (2019).
Grau, A., Indri, M., Lo Bello, L. & Sauter, T. Robots in industry: the past, present, and future of a growing collaboration with humans. IEEE Ind. Electron. Mag. 15, 50–61 (2021).
Laveille, P. et al. Swiss CAT+, a data-driven infrastructure for accelerated catalysts discovery and optimization. CHIMIA 77, 154 (2023).
Boiko, D. A., MacKnight, R., Kline, B. & Gomes, G. Autonomous chemical research with large language models. Nature 624, 570–578 (2023).
Darvish, K. et al. ORGANA: a robotic assistant for automated chemistry experimentation and characterization. Preprint at https://arxiv.org/abs/2401.06949 (2024).
Giorgino, T. Computing and visualizing dynamic time warping alignments in R: the dtw package. J. Stat. Softw. 31, 1–24 (2009).
Dolomanov, O. V., Bourhis, L. J., Gildea, R. J., Howard, J. A. K. & Puschmann, H. OLEX2: a complete structure solution, refinement and analysis program. J. Appl. Crystallogr. 42, 339–341 (2009).
Sheldrick, G. M. SHELXT—integrated space-group and crystal-structure determination. Acta Crystallogr. 71, 3–8 (2015).
Sheldrick, G. M. Crystal structure refinement with SHELXL. Acta Crystallogr. C 71, 3–8 (2015).
Ayme, J.-F., Cooper, A. I., Szczypiński, F. T. & Vijayakrishnan, S. Data and code examples for: Twin cooperative mobile robots for autonomous synthetic chemistry. Zenodo https://doi.org/10.5281/zenodo.11209807 (2024).
[ad_2]
Source link
