Machine Learning Accelerated Discovery of Functional MXenes with Giant Piezoelectric Coefficients-Reference-Cited by-同舟云学术

Machine Learning Accelerated Discovery of Functional MXenes with Giant Piezoelectric Coefficients

Published:2024-02-29 Issue:10 Volume:16 Page:12731-12743
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Li Xiaowen¹^ORCID,Qiu Jian¹^ORCID,Cui Heping²^ORCID,Chen Xianping¹³,Yu Jiabing¹^ORCID,Zheng Kai¹⁴

Affiliation:

1. College of Optoelectronic Engineering and Key Laboratory of Optoelectronic Technology & Systems Education Ministry of China, Chongqing University, 400044 Chongqing, China

2. The Institute of Materials in Electrical Engineering 1, RWTH Aachen University, 52074 Aachen, Germany

3. School of Electrical Engineering and State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, 400044 Chongqing, China

4. Department of Energy Conversion and Storage, Technical University of Denmark, 2800 Kongens Lyngby, Denmark

Funder

Central University Basic Research Fund of China

National Natural Science Foundation of China

Guangxi Key Laboratory of Optoelectronic Information Processing

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.3c14610

Reference76 articles.

1. Piezoelectric Materials for Energy Harvesting and Sensing Applications: Roadmap for Future Smart Materials

2. Stretchable piezoelectric energy harvesters and self-powered sensors for wearable and implantable devices

3. Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing

4. Piezoelectric Materials for Controlling Electro-Chemical Processes

5. Piezoelectric materials and systems for tissue engineering and implantable energy harvesting devices for biomedical applications

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