No abstract

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 TiO 2 was studied in an original hydrothermal process that uses triethanolamine titanium complex Ti(TeoaH) 2 as a Ti precursor and triethanolamine (TeoaH 3 ) 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 TiO 2 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.

Engineered nanoparticles (NPs) are used as an active material in sensors, photovoltaics, photocatalysis, etc. Numerous publications have shown that particular facets of NPs dramatically influence their performance, e.g. in photocatalytic reactions with TiO 2 NPs [1, 2]. Therefore, information about the NP morphology expressed as area ratios of particular facets is highly demanded for the development of advanced nanomaterials. The accurate determination of the particle size distribution for spherical NPs is a task resolved rather easily by various techniques. However, measuring the morphology of individual NPs having complex 3D geometries like cubes, prisms or (bi)pyramids is challenging. Often, only time-consuming TEM and TEM-tomography experiments can resolve the 3D structure and facets of particles in the nanometer range accurately. We present new approaches based on i) top-view high resolution SEM and ii) in-depth view, transmission SEM (TSEM) for the determination of the full shape of facet-controlled NPs. From top-view high resolution SEM (approach i) we could identify the 3D geometry and the individual facet boundaries of NPs. A computer-generated 3D skeleton was manually matched to these facet boundaries, thereby yielding the necessary parameters for a full 3D description of the NP shape. The evaluation of the NP shape from TSEM (approach ii) relies on an automatic image analysis: The 2D projection of the particles on the image plane depends strongly on their orientation with respect to the incident electron beam. Taking only those particles into account for which the 2D projection coincides with an assumed silhouette for standing or lying NPs on the substrate, the size of the corresponding NP facet can be determined. Due to automated image analysis, statistically relevant amounts of data could be generated quickly and lead to reliable estimates of the NPs facet size. These general procedures to determine the NP shape is demonstrated on truncated bipyramidal TiO 2 anatase NPs. The TiO 2 NPs were synthesized by a ligand-assisted synthesis route, which provides a scalable model system with tuneable TiO 2 NP geometries [1, 2]. Figure 1 presents top-view SEM micrographs of TiO 2 anatase NPs. The truncated bipyramidal shape is clearly recognizable in Figure 1A. An enlarged part of A shows a single NP where individual facet boundaries can be identified ( Figure 1B). A computer-generated 3D skeleton was matched to the facet boundaries ( Figure 1C) which results in a full 3D description of the NP shape ( Figure 1D). Figure 2 consists of TSEM micrographs of the truncated bipyramidal TiO 2 NPs whereas A) shows the original micrograph and B) the same micrograph with NPs considered for the evaluation of the NPs shape. The NPs marked in red and yellow were identified as standing upright and flat-lying NPs on the support, respectively ( Figure 2B). Hence the corresponding NPs lengths and widths could be measured from the TSEM micrograph. In order to validate the new methods and estimate the associated measurement unce...