Non-invasive characterization of polymeric materials in relation to art conservation using unilateral NMR combined with multivariate data analysis

Abstract

This article shows how to interpret data obtained by unilateral NMR for the characterization of works of art using multivariate analysis. Transverse 1H relaxation decays acquired by a Carr–Purcell–Meiboom–Gill pulse sequence are directly treated by Principal Component Analysis (PCA) and projection to latent structure by partial least square (PLS). The advantage of this procedure is the avoidance of any ambiguity in the model. The NMR signal is formed by a number of different hydrogen spins rendering the resulting relaxation decays multi-exponential. Therefore conventional approaches of fitting call for the use of mono-, bi-, or multi-exponential models yielding results depending on the choice of the model function. We demonstrate the technique on three examples: characterization of a set of resins representative for modern materials in art and design artefacts, mapping the state of degradation of an art work made of latex, and the analysis of a depth profile of an aged urethane rubber sample. In situ measurements often result in low signal-to-noise ratio data and the suggested technique does not only allow an unambiguous model-free approach, but is also robust against such low sensitivity data.