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One of the crucial characteristics of functionalized thin films is their porosity (i.e., the ratio between the pore volume and the volume of the whole film). Due to the very low amount of material per coated area corresponding to thin films, it is a challenge for analytics to measure the film porosity. In this work, we present an Approach to determine the porosity of thin films by means of electron probe microanalysis (EPMA) either by wavelength-dispersive X-ray spectrometry (WDX) or by energy-dispersive X-ray spectrometry (EDX) with a scanning electron microscope (SEM). The procedure is based on the calculation of the film mass deposition from electron-excited X-ray spectra. The
mass deposition is converted into film density by division of measured film thickness.
Finally, the film porosity is calculated from the measured film density and the density of bulk, nonporous film material. The general applicability of the procedure to determine the
porosity is demonstrated on thin templated mesoporous TiO₂
films, dip-coated on silicon
wafer, with controlled porosity in the range of 15 to 50%. The high accuracy of the mass deposition as determined from X-ray spectra was validated with independent methods (ICP-OES and weighing). Furthermore, for the validation of the porosity results, ellipsometry, interference fringes method (IFM), and focused ion beam (FIB) cross sectioning were employed as independent techniques. Hence, the approach proposed
in the present study is proven to be suited as a new analytical tool for accurate and relatively fast determination of the porosity of thin films.
In the present work a series of design rules are developed in order to tune the morphology of TiO2 nanoparticles through hydrothermal process. Through a careful experimental design, the influence of relevant process parameters on the synthesis outcome are studied, reaching to the develop predictive models by using Machine Learning methods. The models, after the validation and training, are able to predict with high accuracy the synthesis outcome in terms of nanoparticle size, polydispersity and aspect ratio. Furthermore, they are implemented by reverse engineering approach to do the inverse process, i.e. obtain the optimal synthesis parameters given a specific product characteristic. For the first time, it is presented a synthesis method that allows continuous and precise control of NPs morphology with the possibility to tune the aspect ratio over a large range from 1.4 (perfect truncated bipyramids) to 6 (elongated nanoparticles) and the length from 20 to 140 nm.