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Self-driving laboratories promise to accelerate materials discovery.
Journal of The Electrochemical Society 131 , 469
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Science 363 , eaav2211
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Science Advances 6 , eaaz8867
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Energy & Environmental Science 13 , 1429–1461
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Science Advances 7 , eabg4930
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Chemistry of Materials 33 , 327–337
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Nature communications 13 , 995
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Advanced Functional Materials 32 , 2108805
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Science 378 , 1320–1324
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Nature 624 , 80–85
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Nature 624 , 86–91
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npj Computational Materials 9 , 133
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ACS Engineering Au 3 , 391–402
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Nature 624 , 570–578
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Nature Synthesis 3 , 606–614
ACS nano 19 , 9029–9041
Zaki, M., Prinz, C., and Ruehle, B. (2025). A self-driving lab for nano-and advanced materials synthesis · 2025
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Cell Reports Physical Science 6
Yik, J.T., Hvarfner, C., Sjölund, J., Berg, E.J., and Zhang, L. (2025). Accelerating aqueous electrolyte design with automated full-cell battery experimentation and bayesian optimization · 2025
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Nature Communications 16 , 9062
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Proceedings of the National Academy of Sciences 122 , e2414074122
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Journal of Materials Chemistry A
Ren, T., Chen, X., Zhang, H., Zhang, H., and Xia, W. (2025). Humidity stability of halide solid-state electrolytes · 2025
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Chen, J., Cross, S.R., Miara, L.J., Cho, J.J., Wang, Y., and Sun, W. (2024). Navigating phase diagram complexity to guide robotic inorganic materials synthesis · 2024
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Advanced Energy Materials 14 , 2302303
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Digital Discovery 3 , 1236–1246
Cakan, D.N., Kumar, R.E., Oberholtz, E., Kodur, M., Palmer, J.R., Gupta, A., Kaushal, K., Vossler, H.M., and Fenning, D.P. (2024). Pascal: the perovskite automated spin coat assembly line accelerates composition screening in triple-halide perovskite alloys · 2024
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Nature communications 15 , 10160
Ruan, Y., Lu, C., Xu, N., He, Y., Chen, Y., Zhang, J., Xuan, J., Pan, J., Fang, Q., Gao, H. et al. (2024). An automatic end-to-end chemical synthesis development platform powered by large language models · 2024
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Chemical Reviews 124 , 9633–9732
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Digital Discovery 3 , 842–868
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Nature Machine Intelligence 6 , 525–535
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Zimmermann, Y., Bazgir, A., Al-Feghali, A., Ansari, M., Bocarsly, J., Brinson, L.C., Chiang, Y., Circi, D., Chiu, M.H., Daelman, N. et al. (2025). 32 examples of llm applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery · 2025
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arXiv preprint arXiv:2509.25651
Panapitiya, G., Saldanha, E., Job, H., and Hess, O. (2025). Autolabs: Cognitive multi-agent systems with self-correction for autonomous chemical experimentation · 2025
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arXiv preprint arXiv:2509.21403
Gupta, R., Hartford, J., and Liu, B. (2025). Llms for bayesian optimization in scientific domains: Are we there yet? · 2025
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Patterns 6
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arXiv preprint arXiv:2512.23880
Huang, X., Chen, J., Fei, Y., Li, Z., Schwaller, P., and Ceder, G. (2025). Cascade: Cumulative agentic skill creation through autonomous development and evolution · 2025
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EES Batteries
Tang, X., Xie, F., Lu, Y., Rong, X., Chen, L., and Hu, Y.S. (2025). Halide-based solid electrolytes: opportunities and challenges in the synergistic development of all-solid-state li/na batteries · 2025
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ACS Energy Letters 10 , 1338–1346
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Nature pp. 1–8
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ACS Materials Letters 7 , 2482–2488
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Nature Materials pp. 1–17
Cheng, M., Fu, C.L., Okabe, R., Chotrattanapituk, A., Boonkird, A., Hung, N.T., and Li, M. (2026). Artificial intelligence-driven approaches for materials design and discovery · 2026
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Nature Synthesis pp. 1–10
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ACS Applied Energy Materials
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Chemistry of Materials 38 , 1364–1376. doi: 10.1021/acs.chemmater.5c02820
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