National Institute of Optics-National Research Council (CNR-INO), Largo E. Fermi 6, 50125 Florence, Italy.
Biophotonics Platform, Champalimaud Clinical Centre, Champalimaud Foundation, Av. Brasilia, 1400-038 Lisbon, Portugal.
Molecules. 2022 Feb 22;27(5):1475. doi: 10.3390/molecules27051475.
The non-invasive analysis of fluorescence from binders and pigments employed in mixtures in artworks is a major challenge in cultural heritage science due to the broad overlapping emission of different fluorescent species causing difficulties in the data interpretation. To improve the specificity of fluorescence measurements, we went beyond steady-state fluorescence measurements by resolving the fluorescence decay dynamics of the emitting species through time-resolved fluorescence imaging (TRFI). In particular, we acquired the fluorescence decay features of different pigments and binders using a portable and compact fibre-based imaging setup. Fluorescence time-resolved data were analysed using the phasor method followed by a Gaussian mixture model (GMM) to automatically identify the populations of fluorescent species within the fluorescence decay maps. Our results demonstrate that this approach allows distinguishing different binders when mixed with the same pigment as well as discriminating different pigments dispersed in a common binder. The results obtained could establish a framework for the analysis of a broader range of pigments and binders to be then extended to several other materials used in art production. The obtained results, together with the compactness and portability of the instrument, pave the way for future in situ applications of the technology on paintings.
由于不同荧光物质的发射光谱存在广泛重叠，给艺术品混合物中结合剂和颜料的非侵入式荧光分析带来了巨大挑战，这给数据分析带来了困难。为了提高荧光测量的特异性，我们超越了稳态荧光测量，通过时间分辨荧光成像（TRFI）解析发射物质的荧光衰减动力学。具体来说，我们使用便携式紧凑型光纤成像装置获取了不同颜料和结合剂的荧光衰减特征。通过相位法和高斯混合模型（GMM）对荧光时间分辨数据进行分析，自动识别荧光衰减图谱中荧光物质的种群。研究结果表明，这种方法可以区分混合物中不同的结合剂，也可以区分分散在同一结合剂中的不同颜料。所获得的结果可以为分析更广泛范围的颜料和结合剂建立一个框架，然后将其扩展到艺术创作中使用的其他几种材料。该仪器的紧凑性和便携性为未来在绘画上进行该技术的原位应用铺平了道路。
