影响因子IF>10的部分选取文章
[1]. J. X. Zhu*, S. Ji, Z. Ren, W. Wu, Z. Zhang, Z. Ni, L. Liu, Z. Zhang, A. Song*, C. Lee*. Triboelectric-induced ion mobility for artificial intelligence-enhanced mid-infrared gas spectroscopy. Nature Communications. 14 (2023):2524.
[2]. J. X. Zhu*, Y. Yang, H. Zhang, Z. Zhao, T. Hu*,L. Liu*, More than Energy Harvesting in Electret Electronics-Moving towardNext-generation Functional System. Advanced Functional Materials. 2023,2214859.
[3]. S. Ji, J. X. Zhu*, Z. Lyu, H. You, Y. Zhou, L.Gu, J. Qu, Z. Xia, Z. Zhang*, H. Dai* Deep learning enhanced lithium-ionbattery nonlinear fading prognosis. Journal of Energy Chemistry, 2023, 78,565-573.
[4]. J. X. Zhu*, H. Wen, H. Zhang, P. Huang*, L.Liu*, H. Hu. Recent advances in biodegradable electronics- from fundament tothe next-generation multi-functional, medical and environmental device.Sustainable Materials and Technologies, 35 (2023), e00530.
[5]. J. X. Zhu, S. Ji, J. Yu, H. Shao, H. Wen, H.Zhang, Z. Xia, Z. Zhang, C. Lee. Machine learning-augmented wearabletriboelectric human-machine interface in motion identification and virtualreality, Nano Energy, 103 (2022) 107766.
[6].J. X. Zhu, Z. Ren, C. Lee. Toward HealthcareDiagnoses by Machine Learning-Enabled Volatile Organic Compound Identification.ACS Nano, 2021, 15, 1, 894–903.
[7].J. X. Zhu, H. Wang, Z. Zhang, Z. Ren, Q. Shi, W.Liu, C. Lee. Continuous direct current by charge transportation fornext-generation IoT and real-time virtual reality applications. Nano Energy,73, 104760, 2020.
[8].J. X. Zhu#, M. Cho#, Y. Li, T. He, J. Ahn, J.Park, T. Ren, C. Lee*, I. Park,* Machine learning-enabled textile-basedgraphene gas sensing with energy harvesting-assisted IoT application, NanoEnergy, 86(2021), 106035.
[9].J. X. Zhu, M. Zhu, Q. Shi, W. Feng, L. Long, B.Dong, A. Haroun, Y. Yang, P. Vachon, X. Guo, T. He, C. Lee. Progress in TENGtechnology – a journey from energy harvesting to nanoenergy and nanosystem(NENS). Ecomat. 2: e12058. 1-45, 2020 (Wiley). Inside Cover.
[10].H. Wang*, J. X. Zhu*, T. He, Z. Zhang, C. Lee,Programmed-triboelectric nanogenerators—A multi-switch regulation methodology for energymanipulation. Nano Energy. 78 (2020) 105241 (共一).
[11].W. Song*, J. X. Zhu*, B. Gan, S. Zhao, H. Wang,C. Li, J. Wang, Flexible, Stretchable, and Transparent PlanarMicrosupercapacitors Based on 3D Porous Laser-Induced Graphene, Small, 2017,1702249. (共一)
[12].J. X. Zhu, M. Cho, Y. Li, J. Park, I. Cho, T-L.Ren, I. Park, Biomimetic Turbinate-like Artificial Nose for Hydrogen DetectionBased on 3D Porous Laser-induced Graphene, ACS Applied Materials &Interfaces, 2019, 11, 2724386-24394.
[13].J. X. Zhu, X. Guo, D. Meng, M. Choi, I. Park,R. Huang, W. Song, A flexible comb electrode triboelectric-electretnanogenerator with separated microfibers for self-powered position, motiondirection and acceleration tracking sensor, Journal of Materials Chemistry A,2018, 6, 16548-16555.
[14].S. Ji, J. X. Zhu*, Z. Zhang*, Z. Xia. Degradation Prognosis for Fast-Charging Batteries via Improved Domain Adaptation, IEEE Transactions on Industrial Informatics. Accepted
[15].S. Ji, Z. Zhang, Helge S. Stein, J. X. Zhu*, Flexible health prognosis of battery nonlinear aging using temporal transfer learning. Applied Energy. 377(2025), 124766.
[16].S. Ji, J. X. Zhu*, Y. Yang, G. Reis, Z. Zhang*, Data-driven Battery Characterization and Prognosis: Recent Progress, Challenges, and Prospects. Small Method. 2024, 2301021