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Updated: Sep 15, 2025

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基于深度神经网络的NBT基陶的压电特性预测

Xin Zhang1, Yalong Liang2, Jiachen Wang1

  • 1Henan International Joint Laboratory of Structural Mechanics and Computational Simulation, College of Architectural and Civil Engineering, Huanghuai University, Zhumadian, China.

Science progress
|July 17, 2025
PubMed
概括

深度神经网络 (DNN) 可以通过分析组成和处理条件来预测压电材料的特性. 这种方法通过理解局部极异质性来加速发现新的压电材料.

关键词:
机器学习是机器学习.深度神经网络是一个神经网络.当地的极地异质性.压电陶材料 - 压电陶压电电的属性是压电的.预测方法 预测方法的方法.

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