Shen Zhong-Hui, Wang Jian-Jun, Jiang Jian-Yong, Huang Sharon X, Lin Yuan-Hua, Nan Ce-Wen, Chen Long-Qing, Shen Yang
School of Materials Science and Engineering, State Key Lab of New Ceramics and Fine Processing, Tsinghua University, 100084, Beijing, China.
Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.
Nat Commun. 2019 Apr 23;10(1):1843. doi: 10.1038/s41467-019-09874-8.
Understanding the breakdown mechanisms of polymer-based dielectrics is critical to achieving high-density energy storage. Here a comprehensive phase-field model is developed to investigate the electric, thermal, and mechanical effects in the breakdown process of polymer-based dielectrics. High-throughput simulations are performed for the P(VDF-HFP)-based nanocomposites filled with nanoparticles of different properties. Machine learning is conducted on the database from the high-throughput simulations to produce an analytical expression for the breakdown strength, which is verified by targeted experimental measurements and can be used to semiquantitatively predict the breakdown strength of the P(VDF-HFP)-based nanocomposites. The present work provides fundamental insights to the breakdown mechanisms of polymer nanocomposite dielectrics and establishes a powerful theoretical framework of materials design for optimizing their breakdown strength and thus maximizing their energy storage by screening suitable nanofillers. It can potentially be extended to optimize the performances of other types of materials such as thermoelectrics and solid electrolytes.
了解聚合物基电介质的击穿机制对于实现高密度储能至关重要。在此，我们开发了一个综合相场模型，以研究聚合物基电介质击穿过程中的电学、热学和力学效应。对填充有不同性质纳米颗粒的聚（偏氟乙烯-六氟丙烯）基纳米复合材料进行了高通量模拟。基于高通量模拟数据库进行机器学习，以生成击穿强度的解析表达式，该表达式通过有针对性的实验测量得到验证，可用于半定量预测聚（偏氟乙烯-六氟丙烯）基纳米复合材料的击穿强度。本工作为聚合物纳米复合电介质的击穿机制提供了基本见解，并建立了一个强大的材料设计理论框架，通过筛选合适的纳米填料来优化其击穿强度，从而最大限度地提高其储能。它有可能被扩展用于优化其他类型材料的性能，如热电材料和固体电解质。
