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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.
The synthesis of TiO2 was studied in an original
hydrothermal process that uses triethanolamine titanium complex Ti(TeoaH)2 as a Ti precursor and triethanolamine (TeoaH3) as a shape controller to obtain bipyramidal anatase nanoparticles.
Backed-up by experimental evidence, i.e., time profiles for Ti(IV) species concentrations together with crystal shape and particle size distributions measured by dynamic light scattering and electron microscopy, a mathematical model was built. The model includes chemical reactions responsible for TiO2 generation in solution and the subsequent anatase nucleation and crystal growth. The oriented attachment mechanism was adopted to explain the build-up of crystals with equilibrium anatase structure (Wulff structure) and time-varying shape factor. This complex mathematical model was solved writing and validating an in-house
software using the Matlab (Natick, MA, USA) environment. The process was simulated for a batch time of 50 h, and the results, in terms of main species concentration and crystal size distributions, are in rather good agreement with the experimental measurements.