Piet Mondrian’s Broadway Boogie Woogie: non invasive analysis using macro X-ray fluorescence mapping (MA-XRF) and multivariate curve resolution-alternating least square (MCR-ALS)

Piet Mondrian’s Broadway Boogie Woogie (1942–1943) was examined using Macro X-Ray Fluorescence mapping (MA-XRF) to help characterize the artist’s materials and understand his creative process as well as the current condition issues of the painting. The presence and distribution of key chemical elements was used to identify the main pigments in the different paint layers and under-layers, namely titanium white/barium sulfate, zinc white, bone black, cadmium yellow and/or cadmium-zinc yellow, cadmium red and/or cadmium-barium red and ultramarine. The XRF data was also examined using a multivariate curve resolution-alternating least square (MCR-ALS) approach to virtually separate and help characterize the different paint layers. Results suggest that Broadway Boogie Woogie was originally conceived as an asymmetrical grid of interlacing red and yellow bars. Mondrian then reworked the composition extensively breaking the bars by painting small squares in red, blue and gray and repainting them over and over again changing their size, color or tonality, and by adding and reworking large colored shapes in the background. Mondrian scraped off the paint in some areas before making adjustments to the composition but did not do it consistently throughout the painting. The yellow paint on the surface is severely cracked. Wherever red paint has been covered with yellow paint, it has oozed through the cracks in the top layer. The results illustrate how the MA-XRF / MCR-ALS approach can complement the examination of a painting and contribute to the understanding of the artist’s process and choice of materials in a non-invasive way.

[1]  Koen Janssens,et al.  A mobile instrument for in situ scanning macro-XRF investigation of historical paintings , 2013 .

[2]  Julian Morris,et al.  Curve resolution for multivariate images with applications to TOF-SIMS and Raman , 2004 .

[3]  Piet Mondrian,et al.  The New Art--the New Life: The Collected Writings Of Piet Mondrian , 1986 .

[4]  Koen Janssens,et al.  Optimization of mobile scanning macro-XRF systems for the in situ investigation of historical paintings , 2011 .

[5]  Piet Mondrian,et al.  Mondrian: The Transatlantic Paintings , 2001 .

[6]  Koen Janssens,et al.  Strategies for processing mega-pixel X-ray fluorescence hyperspectral data: a case study on a version of Caravaggio's painting Supper at Emmaus , 2015 .

[7]  Christian Bauckhage,et al.  Non-negative factor analysis supporting the interpretation of elemental distribution images acquired by XRF , 2014 .

[8]  Koen Janssens,et al.  Revealing hidden paint layers in oil paintings by means of scanning macro-XRF: a mock-up study based on Rembrandt's “An old man in military costume” , 2013 .

[9]  Koen Janssens,et al.  Rembrandt’s An Old Man in Military Costume: the underlying image re-examined , 2015 .

[10]  Jay W. Krueger,et al.  Issues in Contemporary Oil Paint , 2014 .

[11]  R Tauler,et al.  Resolution and segmentation of hyperspectral biomedical images by multivariate curve resolution-alternating least squares. , 2011, Analytica chimica acta.

[12]  E. de la Rie,et al.  Fluorescence of paint and varnish layers (Part II) , 1982 .

[13]  Paola Ricciardi,et al.  Mapping of egg yolk and animal skin glue paint binders in Early Renaissance paintings using near infrared reflectance imaging spectroscopy. , 2013, The Analyst.

[14]  I. Fiedler,et al.  Cadmium yellows, oranges and reds , 1986 .

[15]  M. D. de Jonge,et al.  High-definition X-ray fluorescence elemental mapping of paintings. , 2012, Analytical chemistry.

[16]  W. Windig,et al.  Interactive self-modeling mixture analysis , 1991 .

[17]  Koen Janssens,et al.  Exploring a Hidden Painting Below the Surface of René Magritte’s Le Portrait , 2016, Applied spectroscopy.

[18]  Mathieu Thoury,et al.  Visible and Infrared Imaging Spectroscopy of Picasso's Harlequin Musician: Mapping and Identification of Artist Materials in Situ , 2010, Applied spectroscopy.

[19]  Michael R. Keenan,et al.  Optimal scaling of TOF-SIMS spectrum-images prior to multivariate statistical analysis , 2004 .

[20]  Koen Janssens,et al.  Visualization of a lost painting by Vincent van Gogh using synchrotron radiation based X-ray fluorescence elemental mapping. , 2008, Analytical chemistry.

[21]  L. Pappalardo,et al.  Identification of forgeries in historical enamels by combining the non-destructive scanning XRF imaging and alpha-PIXE portable techniques , 2016 .

[22]  Gene H. Golub,et al.  Singular value decomposition and least squares solutions , 1970, Milestones in Matrix Computation.

[23]  Romà Tauler,et al.  Multivariate Curve Resolution: A Different Way To Examine Chemical Data , 2015 .

[24]  John Drennan,et al.  Metal Stearate Distributions in Modern Artists' Oil Paints: Surface and Cross-Sectional Investigation of Reference Paint Films Using Conventional and Synchrotron Infrared Microspectroscopy , 2012, Applied spectroscopy.

[25]  C. McGlinchey Handheld XRF for the examination of paintings:: proper use and limitations , 2013 .

[26]  Koen Janssens,et al.  Examination of historical paintings by state-of-the-art hyperspectral imaging methods: from scanning infra-red spectroscopy to computed X-ray laminography , 2014, Heritage Science.

[27]  D. Newbury,et al.  Maximum pixel spectrum: a new tool for detecting and recovering rare, unanticipated features from spectrum image data cubes , 2004, Journal of microscopy.

[28]  Norbert S. Baer,et al.  Advances in scientific instrumentation for conservation: an overview , 1982 .

[29]  K. Janssens,et al.  An intrusive portrait by Goya , 2011 .

[30]  Romà Tauler,et al.  Multivariate Curve Resolution (MCR). Solving the mixture analysis problem , 2014 .

[31]  E. Hendriks,et al.  Scanning XRF investigation of a Flower Still Life and its underlying composition from the collection of the Kröller–Müller Museum , 2013 .

[32]  Klaas Jan van den Berg,et al.  Water Sensitive Oil Paints in the Twentieth Century: A Study of the Distribution of Water-Soluble Degradation Products in Modern Oil Paint Films , 2014 .

[33]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[34]  Elisabetta Zendri,et al.  Modern Oil Paints – Formulations, Organic Additives and Degradation: Some Case Studies , 2014 .

[35]  P. Kotula,et al.  Multivariate statistical analysis of concatenated time-of-flight secondary ion mass spectrometry spectral images. Complete description of the sample with one analysis. , 2005, Analytical chemistry.

[36]  M. Keenan,et al.  Simplification of alternating least squares solutions with contrast enhancement , 2012 .

[37]  Romà Tauler,et al.  Vibrational spectroscopic image analysis of biological material using multivariate curve resolution–alternating least squares (MCR-ALS) , 2015, Nature Protocols.

[38]  M. Lankosz,et al.  New Approaches for Correction of Interlayer Absorption Effects in X-ray Fluorescence Imaging of Paintings. , 2016, Analytical chemistry.

[39]  Joyce Plesters,et al.  2. Ultramarine Blue, Natural and Artificial , 1966 .

[40]  V. A. Solé,et al.  A multiplatform code for the analysis of energy-dispersive X-ray fluorescence spectra , 2007 .

[41]  F. IAN G. RAWLINS,et al.  Painting Materials: a Short Encyclopedia , 1943, Nature.