2016
DOI: 10.1186/s40494-016-0105-2
|View full text |Cite
|
Sign up to set email alerts
|

Jackson Pollock’s Number 1A, 1948: a non-invasive study using macro-x-ray fluorescence mapping (MA-XRF) and multivariate curve resolution-alternating least squares (MCR-ALS) analysis

Abstract: Jackson Pollock's Number 1A, 1948 painting was investigated using in situ scanning macro-x-ray fluorescence mapping (MA-XRF) to help characterize the artist's materials and his creative process. A multivariate curve resolution-alternating least squares (MCR-ALS) approach was used to examine the hyperspectral data and obtain distribution maps and signature spectra for the paints he used. The composition of the paints was elucidated based on the chemical elements identified in the signature spectra and a tentati… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
18
0
1

Year Published

2016
2016
2023
2023

Publication Types

Select...
6
3

Relationship

1
8

Authors

Journals

citations
Cited by 40 publications
(19 citation statements)
references
References 36 publications
0
18
0
1
Order By: Relevance
“…The components are represented by the dyads of vectors composed of a concentration profile in the process direction and a pure spectrum in the direction of the multivariate response. This model can be extended to more complex data arrangements (i.e., augmented data matrices) for which Equation (2) would still hold, such as for spectroscopic images or for second-order data complying with the requirements described above [ 29 , 30 , 31 ]. In our study, non-negative values for the concentration and spectra profiles were used as constraints, to implement alternating least squares (ALS) [ 32 , 33 , 34 ].…”
Section: Methodsmentioning
confidence: 99%
“…The components are represented by the dyads of vectors composed of a concentration profile in the process direction and a pure spectrum in the direction of the multivariate response. This model can be extended to more complex data arrangements (i.e., augmented data matrices) for which Equation (2) would still hold, such as for spectroscopic images or for second-order data complying with the requirements described above [ 29 , 30 , 31 ]. In our study, non-negative values for the concentration and spectra profiles were used as constraints, to implement alternating least squares (ALS) [ 32 , 33 , 34 ].…”
Section: Methodsmentioning
confidence: 99%
“…instruments were developed that allowed performing scanning experiments in the museum or picture gallery where the works of art are normally on display or are conserved [26,149,150]. With these MA-XRF scanners, it was possible to examine a great variety of artworks by well-known artists such as Rubens [22], Rembrandt [151][152][153], Vermeer [154], Goya [155], Van Gogh [145,156], Magritte [157], Martins [158] and Pollock [159], and to discover new information on their artistic history and on their current state of conservation. Several X-ray instrumentation manufacturers and research institutions have recently described MA-XRF scanners of their own making [27,160].…”
Section: _####_ Page 6 Of 51mentioning
confidence: 99%
“…Hence, in this study, the applicability of PyMCA (Python MultiChannel Analyzer) [25] for deconvolution of these overlapping peaks is evaluated with self-made reference paints. As comparison of XRF spectra can be challenging, more and more accounts of additional multivariate data analysis are reported, mostly on processed data extracted from spectra (such as elemental concentrations) [26][27][28][29][30][31]. It is in this scope that, principal component analysis (PCA) has been used in this paper to enhance the interpretability of the pXRF dataset.…”
Section: Introductionmentioning
confidence: 99%