Effects of organic modifiers on the colloidal stability of TiO2 nanoparticles. A methodological approach for NPs categorization by multivariate statistical analysis

The considerable diversity and complexity of manufactured nanoparticles (NPs) have made their regulatory safety assessment challenging due to the need for excessive testing. Therefore, it is relevant to derive physicochemical and structural descriptors for in silico modelling that can help to develop strategies for “Safety by Design” (SbD) in the early stages of product development. This paper aims at informing such strategies by studying how surface modification by means of attaching organic ligands can affect the colloidal stability of nanoscale TiO2in different environmental media with changing electrolyte concentrations and pH levels. The functionalization was performed by using four catecholate derivatives (catechol, 3,4-dihydroxybenzaldehyde, 3,4-dihydroxybenzoic acid, dopamine hydrochloride), salicylic acid and polyethylene glycol (PEG) polymer. Surface charge, hydrodynamic diameter and sedimentation velocity were measured to assess the colloidal stability of each of the dispersions. Then, statistical clustering techniques and Principal Component Analysis (PCA) were applied to the obtained experimental data in order to identify physicochemical descriptors and classes of stability, which were used to classify the investigated surface modifications. In conclusion, the proposed approach, combining experimental results from simple and fast techniques with multivariate statistical methods has proven to be useful for supporting nanomaterials categorization for the purpose of developing SbD strategies.