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Updated: Feb 11, 2026

Fabrication and Design of Wood-Based High-Performance Composites
08:08

Fabrication and Design of Wood-Based High-Performance Composites

Published on: November 9, 2019

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由机器学习实现的优越储能性能,为无抗铁电材料的加速组合设计提供了优越的储能性能

Feng Li1, Liang Sun1, Zongyuan Zhang1

  • 1Information Materials and Intelligent Sensing Laboratory of Anhui Province, Leibniz International Joint Research Center of Materials Sciences of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University, Hefei, China.

Small (Weinheim an der Bergstrasse, Germany)
|February 10, 2026
PubMed
概括

机器学习加速了无AgNbO3基反铁电的发现,用于储能. 一个新的框架预测了具有超高能量储存密度和效率的组合,优于传统方法.

关键词:
抗铁电气制品 抗铁电气制品介电电容器的介电电容器储能密度 储能密度 储能密度没有的无材料.机器学习是机器学习.

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