Degradation predictive modelling of aged CdxZn1-xS paints

CdxZn1-xS pigments have been used since the 1840s, but being efficient catalysts, they unfortunately aggravate the ageing process of the polymeric network of oil paintings in which they are used. It is important to understand how the evolving molecular composition of CdxZn1-xS -oil paints can affect an artwork durability and assess the risk that these formulations can pose to the paint. The aim of this work is to achieve better insight on the historical production of Cd/Zn pigments, follow their change during ageing, correlate each degradation pathway to a set of optical and elemental properties, develop a strategy for optimizing the conservation conditions of different oil-paint systems, and model the evolution of degradation markers. CdxZn1-xS nanocrystals with different features were synthesized according to historical recipes. Samples were artificially aged for two months and analysed after two additional years of natural ageing. A complete material characterization was carried out. A Principal Component Analysis (PCA) and Design of Experiment (DoE) joint approach was used to model and study the effects and interactions of intrinsic and environmental parameters on the ageing process. PCA was performed to identify degradation patterns and define their dependence based on the type of pigment involved. Additionally, it allowed to individuate and classify degradation markers. A series of indexes was computed to evaluate the severity of the degradation and quantify the amount of each secondary product formed. The obtained values, referred to as Alteration Indexes, were extrapolated from Fourier- Transform Infrared Spectroscopy in Attenuated Total Reflectance (FTIR-ATR) spectra. A D-Optimal (D-Opt) DoE was implemented using the Indexes as a Response and applied for a statistical study of the parameters (both intrinsic and environmental) involved in the deterioration process, asses their statistical relevance in the system, and build prediction models.