PMID- 36007144 OWN - NLM STAT- MEDLINE DCOM- 20221017 LR - 20221017 IS - 1521-4095 (Electronic) IS - 0935-9648 (Linking) VI - 34 IP - 41 DP - 2022 Oct TI - A Machine-Learning-Enhanced Simultaneous and Multimodal Sensor Based on Moist-Electric Powered Graphene Oxide. PG - e2205249 LID - 10.1002/adma.202205249 [doi] AB - Simultaneous multimodal monitoring can greatly perceive intricately multiple stimuli, which is important for the understanding and development of a future human-machine fusion world. However, the integrated multisensor networks with cumbersome structure, huge power consumption, and complex preparation process have heavily restricted practical applications. Herein, a graphene oxide single-component multimodal sensor (GO-MS) is developed, which enables simultaneous monitoring of multiple environmental stimuli by a single unit with unique moist-electric self-power supply. This GO-MS can generate a sustainable moist-electric potential by spontaneously adsorbing water molecules in air, which has a characteristic response behavior when exposed to different stimuli. As a result, the simultaneous monitoring and decoupling of the changes of temperature, humidity, pressure, and light intensity are achieved by this single GO-MS with machine-learning (ML) assistance. Of practical importance, a moist-electric-powered human-machine interaction wristband based on GO-MS is constructed to monitor pulse signals, body temperature, and sweating in a multidimensional manner, as well as gestures and sign language commanding communication. This ML-empowered moist-electric GO-MS provides a new platform for the development of self-powered single-component multimodal sensors, showing great potential for applications in the fields of health detection, artificial electronic skin, and the Internet-of-Things. CI - (c) 2022 Wiley-VCH GmbH. FAU - Yang, Ce AU - Yang C AUID- ORCID: 0000-0002-6432-443X AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Wang, Haiyan AU - Wang H AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Yang, Jiawei AU - Yang J AD - Tsien Excellence in Engineering Program, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Yao, Houze AU - Yao H AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - He, Tiancheng AU - He T AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Bai, Jiaxin AU - Bai J AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Guang, Tianlei AU - Guang T AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Cheng, Huhu AU - Cheng H AUID- ORCID: 0000-0003-1170-8218 AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Yan, Jianfeng AU - Yan J AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. FAU - Qu, Liangti AU - Qu L AUID- ORCID: 0000-0002-0161-3816 AD - Key Laboratory of Organic Optoelectronics & Molecular Engineering, Ministry of Education, Department of Chemistry & State Key Laboratory of Tribology in Advanced Equipment (SKLT), Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, P. R. China. LA - eng GR - 22035005/National Science Foundation of China/ GR - 52022051/National Science Foundation of China/ GR - 22075165/National Science Foundation of China/ GR - 52073159/National Science Foundation of China/ GR - 52090032/National Science Foundation of China/ GR - 21911530143/NSFC-STINT/ GR - SKLT2021B03/State Key Laboratory of Tribology/ GR - 2020THFS0501/Tsinghua-Foshan Innovation Special Fund/ GR - KZ202110017026/Scientific Research Project of Beijing Educational Committee/ PT - Journal Article DEP - 20220912 PL - Germany TA - Adv Mater JT - Advanced materials (Deerfield Beach, Fla.) JID - 9885358 RN - 0 (graphene oxide) RN - 059QF0KO0R (Water) RN - 7782-42-5 (Graphite) SB - IM MH - *Graphite/chemistry MH - Humans MH - Machine Learning MH - Water MH - *Wearable Electronic Devices OTO - NOTNLM OT - moist-electric OT - multimodal sensor OT - self-powered sensors OT - simultaneous monitoring EDAT- 2022/08/26 06:00 MHDA- 2022/10/18 06:00 CRDT- 2022/08/25 15:02 PHST- 2022/08/07 00:00 [revised] PHST- 2022/06/10 00:00 [received] PHST- 2022/08/26 06:00 [pubmed] PHST- 2022/10/18 06:00 [medline] PHST- 2022/08/25 15:02 [entrez] AID - 10.1002/adma.202205249 [doi] PST - ppublish SO - Adv Mater. 2022 Oct;34(41):e2205249. doi: 10.1002/adma.202205249. Epub 2022 Sep 12.