4.8 Review

Emerging artificial intelligence in piezoelectric and triboelectric nanogenerators

期刊

NANO ENERGY
卷 88, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.nanoen.2021.106227

关键词

Artificial intelligence (AI); Piezoelectric nanogenerators (PENG); Triboelectric nanogenerators (TENG)

资金

  1. Key Research and Development Program of Zhejiang, China [2021C03180, 2021C03181]
  2. Fundamental Research Funds for the Central Universities, China [2020-KYY-529112-0002]
  3. Hundred Talents Program at the Zhejiang University, China

向作者/读者索取更多资源

Piezoelectric nanogenerators and triboelectric nanogenerators are paving the way for sustainable energy harvesting, with recent advancements incorporating artificial intelligence to optimize their mechanical-to-electrical performance. This integration of AI in nanogenerators shows promising potential for future innovations in green energy solutions.
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.

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