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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
chemistry
Determination of early warning signs for photocatalytic degradation of titanium white oil paints by means of surface analysis
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy, Volume 172, Year 2017
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Description
Titanium white (TiO2) has been widely used as a pigment in the 20th century. However, its most photocatalytic form (anatase) can cause severe degradation of the oil paint in which it is contained. UV light initiates TiO2-photocatalyzed processes in the paint film, degrading the oil binder into volatile components resulting in chalking of the paint. This will eventually lead to severe changes in the appearance of a painting. To date, limited examples of degraded works of art containing titanium white are known due to the relatively short existence of the paintings in question and the slow progress of the degradation process. However, UV light will inevitably cause degradation of paint in works of art containing photocatalytic titanium white. In this work, a method to detect early warning signs of photocatalytic degradation of unvarnished oil paint is proposed, using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). Consequently, a four-stage degradation model was developed through in-depth study of TiO2-containing paint films in various stages of degradation. The XPS surface analysis proved very valuable for detecting early warning signs of paint degradation, whereas the AFM results provide additional confirmation and are in good agreement with bulk gloss reduction. © 2016 Elsevier B.V.
Authors & Co-Authors
Van Driel, Birgit A.
Netherlands, Delft
Delft University of Technology
Netherlands, Amsterdam
Cultural Heritage Agency of the Netherlands
Wezendonk, Tim A.
Netherlands, Delft
Delft University of Technology
van den Berg, Klaas Jan
Netherlands, Amsterdam
Cultural Heritage Agency of the Netherlands
Kooyman, Patricia J.
Netherlands, Delft
Delft University of Technology
Gascón, Jorge
Netherlands, Delft
Delft University of Technology
Dik, Joris
Netherlands, Delft
Delft University of Technology
Statistics
Citations: 28
Authors: 6
Affiliations: 2
Identifiers
Doi:
10.1016/j.saa.2016.04.026
ISSN:
13861425
Study Approach
Qualitative