论文标题
使用神经网络沉积在硅底物上的TiO2薄膜的光声表征
Photoacoustic characterization of TiO2 thin-films deposited on Silicon substrate using neural networks
论文作者
论文摘要
在本文中，分析了通过神经网络分析了在20至20 kHz的频率范围内确定沉积在硅基板上的薄TIO2膜的热，弹性和几何特性的可能性。为此，在两层模型和纳米层薄膜参数中，底物参数仍然是已知和常数的：厚度，膨胀和热扩散率。用三个神经网络分别分析了这三个参数的预测，所有这些都通过第四个神经网络共同分析。结果表明，同时分析所有三个参数的神经网络达到了最高的准确性，因此使用仅提供一个参数预测的网络的使用较少。
In this paper, the possibility of determining the thermal, elastic and geometric characteristics of a thin TiO2 film deposited on a silicon substrate, thickness 30 mikrons, in the frequency range of 20 to 20 kHz with neural networks was analyzed. For this purpose, the substrate parameters remained the known and constant in the two-layer model and nano layer thin-film parameters were changed: thickness, expansion and thermal diffusivity. Prediction of these three parameters was analyzed separately with three neural networks and all of these together by fourth neural network. It was shown that neural network, which analyzed all three parameters at the same time, achieved the highest accuracy, so the use of networks that provide predictions for only one parameter is less reliable.
