Machine learning-assisted accelerated research on piezoelectric response prediction of KNN-based ceramics-Reference-Cited by-同舟云学术

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Machine learning-assisted accelerated research on piezoelectric response prediction of KNN-based ceramics

Published:2024-10 Issue: Volume:1003 Page:175598
ISSN:0925-8388
Container-title:Journal of Alloys and Compounds
language:en
Short-container-title:Journal of Alloys and Compounds

Author:

Sun Ying,Hu Binbin,Zhang Yiting,Song Xilong,Feng Jiaqing,Xu Yong,Tao Hong,Ergu Daji

Funder

Sichuan Province Science and Technology Support Program

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Reference45 articles.

1. A comprehensive review on the state-of-the-art of piezoelectric energy harvesting;Sezer;Nano Energy,2021

2. Design of a prototype generator based on piezoelectric power generation for vibration energy harvesting;Nyamayoka;J. Energy South. Afr.,2017

3. Phase structure and properties of sodium bismuth titanate lead-free piezoelectric ceramics;Zhou;Prog. Mater. Sci.,2021

4. Modulation of defects and electrical behaviors of Cu-doped KNN ceramics by fluorine–oxygen substitution;Liao;Dalton Trans.,2020

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