1. Data-driven design of carbon-based materials for high-performance flexible energy storage devices.
- Author
-
Wang, Yuxuan, Sha, Junwei, Zhu, Shan, Ma, Liying, He, Chunnian, Zhong, Cheng, Hu, Wenbin, and Zhao, Naiqin
- Subjects
- *
ENERGY storage , *ENERGY storage equipment , *CARBON nanofibers , *FLEXIBLE electronics , *ENERGY density , *MACHINE learning , *IONIC liquids - Abstract
With the rise of flexible electronics, the demand for advanced power sources has grown. Developing high-performance energy storage devices requires comprehensive consideration of various factors such as electrodes, electrolytes, and service conditions. Herein, a data-driven research framework is proposed to optimize the electrode-electrolyte system in supercapacitors. With the help of machine learning, we reveal the key factors affecting the capacitance performance of carbon-based materials. According to the algorithm analysis, a kind of 3D carbon network is prepared with controlled composition and structure, which is incorporated with a high-safety ionic liquid to obtain a supercapacitor device. This device with high energy density and impressive flexibility can maintain operational stability under extreme conditions such as humidity, shock, and localized damage. Overall, this work presents a typical pipeline for accelerating the design of energy-related devices. [Display omitted] • A data-driven design framework for energy storage devices is proposed. • Machine learning is used to investigate the key features of electrode materials. • An ultra-thin flexible supercapacitor device with high safety is fabricated. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF