Photoacoustic characterization of TiO2 thin-films deposited on Silicon substrate using neural networks

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.Comment: 21 pages, 5 figure

A combination of frequency photoacoustic and photoacoustic spectroscopy techniques for measurement of optical and thermal properties of macromolecular nanostructures

Macromolecular nanostructures represent a class of materials of considerable interest for application in nanooptics and nanoelectronics. The potential applications require understanding of the transport mechanisms in macromolecular nanostructures, and the recent theoretical studies indicated that the transport mechanisms of heat generated by absorption of IR and visible light are different. In this paper is proposed a combination of experimental techniques that would enable simultaneous measurement of optical and thermal properties of macromolecular structures excited by wide spectrum of light. The results of the experiments would enable credible testing of validity of the predictions of the theoretical studies, and further insight of the transport processes in macromolecular nanostructures