A chemical autonomous robotic platform for end-to-end synthesis of nanoparticles
Abstract Traditional nanomaterial development faces inefficiency and unstable results due to labor-intensive trial-and-error methods. To overcome these challenges, we developed a data-driven automated platform integrating artificial intelligence (AI) decision modules with automated experiments. Spec...
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| Main Authors: | Fan Gao, Hongqiang Li, Zhilong Chen, Yunai Yi, Shihao Nie, Zihao Cheng, Zeming Liu, Yuanfang Guo, Shumin Liu, Qizhen Qin, Zhengjian Li, Lisong Zhang, Han Hu, Cunjin Li, Liang Yang, Yunhong Wang, Guangxu Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-62994-2 |
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