Emerging artificial intelligence in piezoelectric and triboelectric nanogenerators

被引:115
作者
Jiao, Pengcheng [1 ,2 ]
机构
[1] Zhejiang Univ, Inst Port Coastal & Offshore Engn, Ocean Coll, Zhoushan 316021, Zhejiang, Peoples R China
[2] Zhejiang Univ, Engn Res Ctr Ocean Sensing Technol & Equipment, Minist Educ, Zhoushan, Zhejiang, Peoples R China
关键词
Artificial intelligence (AI); Piezoelectric nanogenerators (PENG); Triboelectric nanogenerators (TENG); WATER-WAVE ENERGY; BROAD FREQUENCY BAND; SELF-POWERED SENSOR; MECHANICAL-ENERGY; BLUE ENERGY; MATERIALS DISCOVERY; GIANT PIEZOELECTRICITY; BIOMECHANICAL ENERGY; KEYSTROKE DYNAMICS; ROTATION ENERGY;
D O I
10.1016/j.nanoen.2021.106227
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG) have opened an exciting venue to sustainably harvest electrical energy from the environments, which have led to multifunctional applications in different fields. More recently, a paradigm shift has directed to the emerging artificial intelligence (AI) in PENG and TENG, aiming to address the challenges of the nanogenerators in analysis, design, fabrication, and appli-cation. AI-PENG and AI-TENG are envisioned to enhance and optimize the mechanical-to-electrical performance of the nanogenerators to a favorable behavior. However, an overview on the topic of AI-PENG and AI-TENG has not yet been exploited in the literature. In this review article, we showcase the recent progress of PENG and TENG and discuss the future trends of AI-enhanced nanogenerators with desirable electrical performance, i.e., using AI-enabled design models as a viable tool to design, predict, and optimize the structures and materials of PENG and TENG. This topical review explains why the nanogenerators are extensively considered as one of the promising energy solutions and are especially suitable for certain applications in engineering and life science, how to surpass the limitations of PENG and TENG by AI-based structural design and material discovery, and what technological avenues that AI-PENG and AI-TENG may provide for green energy in future innovations.
引用
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页数:21
相关论文
共 307 条
[1]   Perspective: Materials informatics and big data: Realization of the "fourth paradigm" of science in materials science [J].
Agrawal, Ankit ;
Choudhary, Alok .
APL MATERIALS, 2016, 4 (05)
[2]  
Ahmadian M., 2008, ACT PASSIV SMART STR, V2008
[3]   A review on energy harvesting approaches for renewable energies from ambient vibrations and acoustic waves using piezoelectricity [J].
Ahmed, Riaz ;
Mir, Fariha ;
Banerjee, Sourav .
SMART MATERIALS AND STRUCTURES, 2017, 26 (08)
[4]   Quantifying Uncertainty in Internet of Medical Things and Big-Data Services Using Intelligence and Deep Learning [J].
Al-Turjman, Fadi ;
Zahmatkesh, Hadi ;
Mostarda, Leonardo .
IEEE ACCESS, 2019, 7 :115749-115759
[5]   Aloe vera: A tropical desert plant to harness the mechanical energy by triboelectric and piezoelectric approaches [J].
Alluri, Nagamalleswara Rao ;
Raj, Nirmal Prashanth Maria Joseph ;
Khandelwal, Gaurav ;
Vivekananthan, Venkateswaran ;
Kim, Sang-Jae .
NANO ENERGY, 2020, 73
[6]  
[Anonymous], 2018, ADV ENERGY MATER, DOI [10.1002/aenm.201802159, DOI 10.1002/aenm.201802159]
[7]  
[Anonymous], 1983, MACHINE LEARNING ART
[8]   Piezoelectric and triboelectric nanogenerators: Trends and impacts [J].
Askari, Hassan ;
Khajepour, Amir ;
Khamesee, Mir Behrad ;
Saadatnia, Zia ;
Wang, Zhong Lin .
NANO TODAY, 2018, 22 :10-13
[9]   Giant piezoelectricity in PMN-PT thin films: Beyond PZT [J].
Baek, Seung-Hyub ;
Rzchowski, Mark S. ;
Aksyuk, Vladimir A. .
MRS BULLETIN, 2012, 37 (11) :1022-1029
[10]   Boosting Photovoltaic Output of Ferroelectric Ceramics by Optoelectric Control of Domains [J].
Bai, Yang ;
Vats, Gaurav ;
Seidel, Jan ;
Jantunen, Heli ;
Juuti, Jari .
ADVANCED MATERIALS, 2018, 30 (43)