Multivariate analysis studies of the ageing effect for artist's oil paints containing modern organic pigments

2014 ◽  
Vol 46 (10-11) ◽  
pp. 786-790 ◽  
Author(s):  
Naoko Sano ◽  
Peter J. Cumpson ◽  
Elke Cwiertnia ◽  
Justin J. Perry ◽  
Brian W. Singer
Keyword(s):  
Multivariate Analysis ◽  
Ageing Effect ◽  
Organic Pigments ◽  
Oil Paints

Sensitivity of Modern Oil Paints to Solvents. Effects on Synthetic Organic Pigments

2014 ◽  
pp. 351-362 ◽  
Author(s):  
Diana Blumenroth ◽  
Stefan Zumbühl ◽  
Nadim C. Scherrer ◽  
Wolfgang Müller
Keyword(s):  
Organic Pigments ◽  
Oil Paints

scholarly journals Identification of Pre-1950 Synthetic Organic Pigments in Artists’ Paints. A Non-Invasive Approach Using Handheld Raman Spectroscopy

Heritage ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1348-1365
Author(s):  
Rika Pause ◽  
Inez Dorothé van der van der Werf ◽  
Klaas Jan van den van den Berg
Keyword(s):  
Raman Spectroscopy ◽  
Chemical Composition ◽  
Invasive Approach ◽  
Organic Pigments ◽  
Non Invasive ◽  
Art Objects ◽  
Time Period ◽  
Actual Use ◽  
Oil Paints

There is little information on the actual use of early synthetic organic pigments (SOPs) in art objects, especially those from before 1950. Their presence can, however, pose a challenge to conservation because their chemical composition, as well as their lightfastness and sensitivity to solvents, are often unknown. Here, a study on the non-invasive identification of SOPs in historic pre-1950 varnished paint-outs from artists’ materials manufacturer Royal Talens is presented. The paints were analysed using a handheld Raman device. Spectra were evaluated by recording the spectra of the same samples with a benchtop instrument. This study demonstrated that the identification of SOPs in varnished oil paints with a non-invasive approach is possible and rather straightforward. The handheld Raman device allowed us to identify fourteen SOPs from eight pigment classes. Besides the occurrence of expected and the known SOPs of this time period, there were also some surprising results, like the detection of the triarylcarbonium pigments PG2 and PB8, and the monoazo Mordant Yellow 1.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

1118: The Incidence and Duration of Postoperative Ileus in Patients Undergoing Radical Cystectomy. A Multivariate Analysis of Contributing Factors

2005 ◽  
Vol 173 (4S) ◽  
pp. 303-303
Author(s):  
Diana Wiessner ◽  
Rainer J. Litz ◽  
Axel R. Heller ◽  
Mitko Georgiev ◽  
Oliver W. Hakenberg ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Radical Cystectomy ◽  
Postoperative Ileus ◽  
Contributing Factors
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