In-silico color prediction process for natural dyes in Madder

Abstract

In the field of cultural heritage, accurately identifying the colors produced by madder root dyes without alteration is critical. In fact, textile dyeing using extracts from their roots has been performed for centuries. Many examples of madder dye remain today in museum and conservation collections. Madder is an interesting natural source of dye because it contains up to 68 different colorants. However, many of these dyes are extremely sensitive to hydrolysis, decarboxylation, and degradation from enzymes, extraction chemicals, and processing temperatures. The valuable chemical information embedded in the dye structure may be lost if extraction and analysis are too harsh, resulting in inaccurate color prediction with large color differences. Thus, they are often overlooked as colorants in historical textiles. Over the past decades, traditional extraction techniques have been used to analyze textiles but they are invasive and destructive. As a result, this method is expensive, time-consuming, and in some cases is not suited for the analysis of artwork. But in the last decades, computer techniques have been presented as a powerful tool that enables the prediction of UV–VIS signature spectra and color coordinates with high accuracy using Time-Dependent Density Functional Theory. The aim of this study is to elaborate an efficient color prediction process of madder's root without any chemical degradation of dyes. It will enable the creation of a robust analytical database to identify madder colors in heritage objects. Here, we provide a rapid method to obtain a complete database of predicted UV–VIS spectra and color of anthraquinone derivatives found in Madder. In the context of historical textiles, the detailed color of natural colorants present in the artwork is of paramount importance for conservation and restoration purposes.