In situ Raman mapping of art objects

Raman spectroscopy has grown to be one of the techniques of interest for the investigation of art objects. The approach has several advantageous properties, and the non-destructive character of the technique allowed it to be used for in situ investigations. However, compared with laboratory approaches, it would be useful to take advantage of the small spectral footprint of the technique, and use Raman spectroscopy to study the spatial distribution of different compounds. In this work, an in situ Raman mapping system is developed to be able to relate chemical information with its spatial distribution. Challenges for the development are discussed, including the need for stable positioning and proper data treatment. To avoid focusing problems, nineteenth century porcelain cards are used to test the system. This work focuses mainly on the post-processing of the large dataset which consists of four steps: (i) importing the data into the software; (ii) visualization of the dataset; (iii) extraction of the variables; and (iv) creation of a Raman image. It is shown that despite the challenging task of the development of the full in situ Raman mapping system, the first steps are very promising.Raman spectroscopy has grown to be one of the techniques of interest for the investigation of art objects. The approach has several advantageous properties, and the non-destructive character of the technique allowed it to be used for in situ investigations. However, compared with laboratory approaches, it would be useful to take advantage of the small spectral footprint of the technique, and use Raman spectroscopy to study the spatial distribution of different compounds. In this work, an in situ Raman mapping system is developed to be able to relate chemical information with its spatial distribution. Challenges for the development are discussed, including the need for stable positioning and proper data treatment. To avoid focusing problems, nineteenth century porcelain cards are used to test the system. This work focuses mainly on the post-processing of the large dataset which consists of four steps: (i) importing the data into the software; (ii) visualization of the dataset; (iii) extraction of the variables; and (iv) creation of a Raman image. It is shown that despite the challenging task of the development of the full in situ Raman mapping system, the first steps are very promising.A