Fenech, A; Fearn, T; Strlic, M; (2012) Use of Design-of-Experiment principles to develop a dose-response function for colour photographs. Polymer Degradation and Stability , 97 (4) pp. 621-625. 10.1016/j.polymdegradstab.2012.01.012.
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Colour photographs are very vulnerable to the environmental conditions they are stored in. Although ideal conditions of storage have been identified, these conditions are often not appropriate in archival collections. Therefore, it is essential to understand how these environmental conditions affect degradation in order to optimise material lifetime. Such information is typically obtained using accelerated degradation experiments following ‘one-factor-at-a-time’ methodologies. However, when planned using ‘Design-of-Experiment’ principles, such experiments provide more information with fewer experimental runs, while information is provided not only on factor effects but also on interactions between factors. This study employed a central composite experimental design plan to develop a dose–response function relating the rate of degradation of dyes in colour photographs to temperature (T), relative humidity (RH) and acetic acid concentrations (c(AA)), which had been identified as the environmental parameters of greatest concern for colour photographs in archival collections: View the MathML sourceln(ΔERGBt)=32+0.0002(c(AA))+0.01(RH)−11(1000T). This function now allows managers to appraise various options of environmental management within their collections.
|Title:||Use of Design-of-Experiment principles to develop a dose-response function for colour photographs|
|Open access status:||An open access version is available from UCL Discovery|
|Additional information:||This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
|UCL classification:||UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science|
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