journal article·2025-08-06Open access

Neural network simulation of original colors in Friedrich’s Abbey Among Oak Trees featuring discoloured smalt

Clément de Mecquenem, Myriam Eveno, Matthias Alfeld, Thomas Calligaro, Eric Laval, Kristina Mösl, Ina Reiche

npj Heritage Science· Volume 13· Issue 1

Abstract

Artwork appearances change over time due to aging. Smalt, a blue cobalt-tinted glass pigment, deteriorates over time in oil paintings causing significant and irreversible color changes in many artworks. Virtual simulations can hypothesis original appearances while it remains a challenge for smalt-containing paintings. A novel procedure integrates non-invasive imaging methods, X-ray absorption near-edge structure (XANES), and machine learning to simulate the original colors of a smalt-containing discolored paintings. Macro-X-ray fluorescence provided elemental distribution, reflectance imaging spectroscopy captured color spectra of pigments and XANES informed cobalt speciation in cross sections. Friedrich’s Abbey Among Oak Trees (1808-1810) containing smalt and artificially aged model systems were studied. Machine learning predicted the original hues based on XANES. The procedure allowed us to simulate the original, cooler and more vibrant colors of the painting. The innovative approach visualizes a possible original state of the smalt-containing artwork that can be adapted to other alteration phenomena.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Cultural Heritage Materials Analysis · Spectroscopy and Chemometric Analyses · Wood and Agarwood Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (41)

Show source-provided references
1. van Loon, A., Noble, P. & Burnstock, A. Ageing and deterioration of traditional oil and tempera paints. In Conservation of easel paintings, Routledge series in conservation and museology, 216–243 (Routledge, 2020).10.4324/9780429399916-11 ↗
2. De Keyser, N. et al. Reviving degraded colors of yellow flowers in 17th century still life paintings with macro- and microscale chemical imaging. Sci. Adv. 8, eabn6344 (2022).10.1126/sciadv.abn6344 ↗
3. Dik, J. et al. Visualization of a Lost Painting by Vincent van Gogh Using Synchrotron Radiation Based X-ray Fluorescence Elemental Mapping. Anal. Chem. 80, 6436–6442 (2008).10.1021/ac800965g ↗
4. Monico, L. et al. Degradation Process of Lead Chromate in Paintings by Vincent van Gogh Studied by Means of Synchrotron X-ray Spectromicroscopy and Related Methods. 1. Artificially Aged Model Samples. Anal. Chem. 83, 1214–1223 (2011).10.1021/ac102424h ↗
5. Miliani, C. et al. Photochemistry of Artists’ Dyes and Pigments: Towards Better Understanding and Prevention of Colour Change in Works of Art. Angew. Chem. Int. Ed. 57, 7324–7334 (2018).10.1002/anie.201802801 ↗
6. De La Rie, E. R. Old master paintings: a study of the varnish problem. Anal. Chem. 61, 1228A–1240A (1989).10.1021/ac00196a740 ↗
7. Delamare, F. Aux origines des bleus de cobalt : les débuts de la fabrication du saffre et du smalt en Europe occidentale. Comptesrendus des. s.éances de. l ann.ée - Acad.émie des. Inscr. et. belles-Lett. 153, 297–315 (2009).
8. Stege, H. Out of the blue?. Z. für. Kunsttechnol. 18, 121–142 (2004).
9. Mühlethaler, B. & Thissen, J. SMALT. Stud. Conserv. 14, 47–61 (1969).10.1179/sic.1969.005 ↗
10. Cianchetta, I. et al. Discoloration of the smalt pigment: experimental studies and ab initio calculations. J. Anal. At. Spectrom. 27, 1941 (2012).10.1039/c2ja30132f ↗
11. Spring, M., Higgitt, C. & Saunders, D. Investigation of Pigment-Medium Interaction Processes in Oil Paint containing Degraded Smalt. Natl Gallery Tech. Bull. 26, 56–70 (2005).
12. Robinet, L., Spring, M. & Pag‚s-Camagna, S. Vibrational spectroscopy correlated with elemental analysis for the investigationof smalt pigment and its alteration in paintings. Anal. Methods 5, 4628 (2013).10.1039/c3ay40906f ↗
13. De Mecquenem, C. et al. Influence of the painting medium on the alteration process of smalt in oil paintings studied using combined K and Co K-edge XANES. Appl. Phys. A 130, 781 (2024).10.1007/s00339-024-07943-4 ↗
14. Langle, S. B. L’Éloge du doute en Restauration des œuvres d’art. CeROArt http://journals.openedition.org/ceroart/4627 (2015).10.4000/ceroart.4627 ↗
15. Parvathaneni, T. S. R., Pisarenco, M. & Onvlee, H. A Deep Learning Approach for Digital Color Reconstruction of Van Gogh’s Paintings Using Unpaired Areas Under the Frame. SN Computer Sci. 5, 498 (2024).10.1007/s42979-024-02823-3 ↗
16. Mol, V. R. & Maheswari, P. U. The digital reconstruction of degraded ancient temple murals using dynamic mask generation and an extended exemplar-based region-filling algorithm. Herit. Sci. 9, 1–18 (2021).10.1186/s40494-021-00604-2 ↗
17. Van Loon, A. et al. The role of smalt in complex pigment mixtures in Rembrandt’s Homer 1663: combining MA-XRF imaging, microanalysis, paint reconstructions and OCT. Herit. Sci. 8, 90 (2020).10.1186/s40494-020-00429-5 ↗
18. Carter, J., van Loon, A., Keune, K. & Froment, E. From purple to brown: Using degradation products in reconstructions of a complex smalt paint mixture in The Night Watch to study color change. In Working Towards a Sustainable Past. ed. J. Bridgland, Valencia (2023).
19. Geldof, M., Proaño Gaibor, A. N., Ligterink, F., Hendriks, E. & Kirchner, E. Reconstructing Van Gogh’s palette to determine the optical characteristics of his paints. Herit. Sci. 6, 1–20 (2018).10.1186/s40494-018-0181-6 ↗
20. Biever, C. St Luke’s new coat. Nature 417, 219–220 (2002).10.1038/417219a ↗
21. Robinet, L., Spring, M., Pagés-Camagna, S., Vantelon, D. & Trcera, N. Investigation of the Discoloration of Smalt Pigment in Historic Paintings by Micro-X-ray Absorption Spectroscopy at the Co K-Edge. Anal. Chem. 83, 5145–5152 (2011).10.1021/ac200184f ↗
22. Cotte, M. et al. The ID21 X-ray and infrared microscopy beamline at the ESRF: status and recent applications to artistic materials. J. Anal. At. Spectrom. 32, 477–493 (2017).10.1039/C6JA00356G ↗
23. Salomé, M. et al. The ID21 Scanning X-ray Microscope at ESRF. J. Phys.: Conf. Ser. 425, 182004 (2013).
24. Tack, P. et al. Investigation of (micro-)meteoritic materials at the new hard X-ray imaging PUMA beamline for heritage sciences. J. Synchrotron Radiat. 26, 2033–2039 (2019).10.1107/S160057751901230X ↗
25. Schöder, S. Heritage research at the PUMA beamline. Appl. Phys. A 130, 911 (2024).10.1007/s00339-024-08091-5 ↗
26. Solé, V., Papillon, E., Cotte, M., Walter, P. & Susini, J. A multiplatform code for the analysis of energy-dispersive X-ray fluorescence spectra. Spectrochimica Acta Part B: At. Spectrosc. 62, 63–68 (2007).10.1016/j.sab.2006.12.002 ↗
27. Ravaud, E. et al. Development of a versatile XRF scanner for the elemental imaging of paintworks. Appl. Phys. A 122, 17 (2016).10.1007/s00339-015-9522-4 ↗
28. Alfeld, Matthias. DataHandlerP. DataHandlerP, https://sourceforge.net/projects/datahandlerp/.
29. Pillay, R., Hardeberg, J. Y. & George, S. Hyperspectral imaging of art: Acquisition and calibration workflows. J. Am. Inst. Conserv. 58, 3–15 (2019).10.1080/01971360.2018.1549919 ↗
30. Duncan, D. R. The colour of pigment mixtures. Proc. Phys. Soc. 52, 390–401 (1940).10.1088/0959-5309/52/3/310 ↗
31. Kubelka, P. & Munk, F. Ein Beitrag zur Optik der Farbanstriche. Z. tech. Phys. 12, 593–601 (1931).
32. Kubelka, P. New Contributions to the Optics of Intensely Light-Scattering Materials. Part I. JOSA 38, 448–457 (1948).10.1364/JOSA.38.000448 ↗
33. Van Der Weerd, J., Van Veen, M. K., Heeren, R. M. A. & Boon, J. J. Identification of Pigments in Paint Cross Sections by Reflection Visible Light Imaging Microspectroscopy. Anal. Chem. 75, 716–722 (2003).10.1021/ac020282g ↗
34. Mösl, K.. Mönch am Meer und Abtei im Eichwald. Forschungen zur Maltechnik Caspar David Friedrichs. Ph.D. thesis, Univerity of Fine Arts Dresden, Dresden (2021).
35. Mösl, K. & Demandt, P. (eds) Der Mönch ist zurück. Die Restaurierung von Caspar David Friedrichs Mönch am Meer und Abtei im Eichwald, Nationalgalerie, Staatliche Museen zu Berlin, 32p. (2017).
36. Zlámalová Cílová, Z., Gelnar, M. & Randáková, S. Smalt production in the Ore Mountains: Characterization of samples related to the production of blue pigment in Bohemia. Archaeometry 62, 1202–1215 (2020).10.1111/arcm.12584 ↗
37. Gratuze, B., Soulier, I., Barrandon, J. & Foy, D. De l’origine du cobalt dans les verres. Rev. d'Archéométrie 16, 97–108 (1992).10.3406/arsci.1992.895 ↗
38. Janssens, K. et al. Rembrandt’s ‘Saul and David’ (c. 1652): Use of multiple types of smalt evidenced by means of non-destructive imaging. Microchemical J. 126, 515–523 (2016).10.1016/j.microc.2016.01.013 ↗
39. Abdi, H. & Williams, L. J. Principal component analysis. WIREs Computational Stat. 2, 433–459 (2010).10.1002/wics.101 ↗
40. Lloyd, S. Least squares quantization in PCM. IEEE Trans. Inf. Theory 28, 129–137 (1982).10.1109/TIT.1982.1056489 ↗
41. Arthur, D. & Vassilvitskii, S. K-Means++: The Advantages of Careful Seeding, In: Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans 8, 027–1035 (2007).