BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Shen F, Li Z, Xin C, Guo H, Peng Y, Li K. Interface Defect Detection and Identification of Triboelectric Nanogenerators via Voltage Waveforms and Artificial Neural Network. ACS Appl Mater Interfaces 2022;14:3437-45. [PMID: 35001611 DOI: 10.1021/acsami.1c19718] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhang X, Zhang H. Triboelectric Nanogenerators for Information Security and Identification. Handbook of Triboelectric Nanogenerators 2023. [DOI: 10.1007/978-3-031-05722-9_21-1] [Reference Citation Analysis]
2 Li Z, Zhao L, Wang J, Yang Z, Peng Y, Xie S, Ding J. Piezoelectric energy harvesting from extremely low-frequency vibrations via gravity induced self-excited resonance. Renewable Energy 2023. [DOI: 10.1016/j.renene.2022.12.107] [Reference Citation Analysis]
3 Chen Z, Qian L, Cui R, Liu J, Zhang Q. Machining-induced residual stress analysis and multi-objective optimization for milling process of Mg–Li alloy. Measurement 2022;204:112127. [DOI: 10.1016/j.measurement.2022.112127] [Reference Citation Analysis]
4 Şanlıtürk E, Tekin AT, Çebi F. Defect Detection in Manufacturing via Machine Learning Algorithms. Encyclopedia of Data Science and Machine Learning 2022. [DOI: 10.4018/978-1-7998-9220-5.ch013] [Reference Citation Analysis]
5 Zhang Q, Liu Z, Jiang X, Peng Y, Zhu C, Li Z. Experimental investigation on performance improvement of cantilever piezoelectric energy harvesters via escapement mechanism from extremely Low-Frequency excitations. Sustainable Energy Technologies and Assessments 2022;53:102591. [DOI: 10.1016/j.seta.2022.102591] [Cited by in Crossref: 3] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
6 Shen F, Zhang D, Zhang Q, Li Z, Guo H, Gong Y, Peng Y. Influence of temperature difference on performance of solid-liquid triboelectric nanogenerators. Nano Energy 2022;99:107431. [DOI: 10.1016/j.nanoen.2022.107431] [Cited by in Crossref: 24] [Cited by in F6Publishing: 34] [Article Influence: 24.0] [Reference Citation Analysis]