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Spectroscopic evaluation of painted layer structural changes induced by gamma radiation in experimental models Mihaela M. Manea,a Ioan V. Moise,a Marian Virgolici,a Constantin D. Negut,a Olimpia-Hinamatsuri Barbu,c Mihalis Cutrubinis,a Viorel Fugaru,a Ioana R. Stanculescu,a,b,* and Corneliu C. Pontaa a Centre of Technological Irradiations IRASM, Horia Hulubei National Institute for Physics and Nuclear Engineering, P.O.B. MG-6, 077125 Magurele, Romania b Department of Physical Chemistry, Faculty of Chemistry, University of Bucharest, 4-12 Regina Elisabeta Bd., 030018 Bucharest, Romania c Department of Conservation–Restoration, National University of Arts Bucharest, 19 General Budisteanu Street, 010773 Bucharest, Romania. * Corresponding author: Tel./ Fax +40213159249, E-mail address: istanculescu@nipne.ro Abstract The degradation of cultural heritage objects by insects and microorganisms is an important issue for conservators, art specialists and humankind in general. Gamma irradiation is an efficient method of polychrome wooden artifacts disinfestation. Color changes and other modifications in the physical chemical properties of materials induced by gamma irradiation are feared by cultural heritage responsible committees and they have to be evaluated objectively and precisely. In this paper FTIR and FT-Raman spectroscopy methods were used to investigate the structural changes in some experimental models of tempera paint layers on wood following 11 kGy gamma irradiation at two dose rates. Radiation chemistry depends on the particular pigment, matrix formed by protein, resin (in case of varnished samples) and water presence. For the majority of painted layer in experimental models very small spectral variations were observed. Small changes in the FTIR spectra were observed for the raw Sienna experimental model: for the higher dose rate the egg yolk protein oxidation peaks and the CH stretching bands due to lipids degradation products increased. Keywords: gamma irradiation; FTIR; FT-Raman; painted layer; dammar varnish; tempera 1. Introduction From ancient times pigments were used in human fundamental expression forms like painting and writing. Identification of pigments and dyes in artworks and historical textiles is crucial for the study of their manufacturing technology, for their restoration and long-term preservation (Brosseau et al., 2009; Aykuz et al., 2009; Maier et al., 2010; Bacci et al., 2003; Breitman et al., 2007). Main methods of pigments characterization are X-ray Fluorescence analysis (XRF), Scanning Electron Microscopy with Energy-dispersive X-ray detection (SEM-EDX), X-ray diffraction (XRD), Particle induced X-ray emission (PIXE) and vibrational spectroscopy (Desnica et al., 2008; De Nolf et al., 2006; Darchuk et al., 2010; Webera et al, 1998). FT-IR and FT-Raman analysis are well known methods of structural study of pure and multicomponent samples providing information on chemical bonds via the characteristic vibration frequencies and bands intensities (Smith and Dent, 2005, Colthup et al. 1990, Stanculescu et al., 2003). The applications of vibrational spectroscopic techniques to art are numerous. FT-IR and FT-Raman may be used to characterize genuine and fake artefacts, to obtain information for art restorers and museum conservation scientists, to quantify effects of environmental degradation on exposed artwork and to identify pigments (Deneckere et al., 2010; Edwards et al., 2000; Edwards, 2009; Kaminska et al, 2006; Saverwyns, 2010). The use of Raman spectroscopy and microscopy is a developing trend in art objects analysis due to the nondistructive investigation and sensibility (Boon and Ferreira, 2006; Coupry 2000; Vandenabeele et al. 2008; Mathieson and Nugent, 1996). To our knowledge no vibrational spectroscopy study was performed on gamma irradiated wood painted layers. This may be due to the last twenty years emergence of the art-science interface

*Manuscript accepted for publication. Cite this article as: Mihaela M. Manea, Ioan V. Moise, Marian Virgolici, Constantin D. Negut, Olimpia-Hinamatsuri Barbu, Mihalis Cutrubinis, Viorel Fugaru, Ioana R. Stanculescu, Corneliu C. Ponta, Spectroscopic evaluation of painted layer structural changes induced by gamma radiation in experimental models, Radiation Physics and Chemistry, Volume 81, Issue 2, February 2012, Pages 160-167, ISSN 0969-806X, 10.1016/j.radphyschem.2011.09.015.

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research or to the scarcely available irradiation facilities. The effect of gamma rays on canvas oil painting was studied with thermal analysis and colorimetry (Rizzo et al., 2002; Brainard, 2003). The most important species involved in the biological decay of polychrome wooden objects are fungi and insects. Gamma irradiation is a treatment aiming in prevention from these biodeteriorating organisms and remediation (curing) of infected objects (Dorge and Howlett, 1994; Tiano, 2009). Applied absorbed doses are chosen according to radio-resistance of the species involved in biodeterioration, ranging from 500 Gy, enough to kill larvae and prevent the emergence of adult insects, to about 10 kGy, at which most of the fungi are killed (Katusin-Razem et al., 2003). The effects on wooden material at these doses are known to be acceptable for the community involved in conservation of cultural heritage artifacts. Important advantages may be mentioned in its favor: no toxic or radioactive residues remained in the treated item, large amount of objects can be treated quickly, excellent reliability and attractive cost. In case of emergency, radiation treatment in industrial facilities is probably the only method that can be used. The potential side-effect is due to the interaction of gamma rays with the matter that may change its chemical and physical properties. The modification of the physical-chemical properties depends on the dose. Such an approach actually establishes irradiation treatment limitations. Color changes are to be expected in minerals due to the population of localized, metastable electron traps at lattice imperfections, by free electrons, resulting from ionizations (Smithsonian's Museum Conservation Institute, 2001). The case of painted wooden artifacts has to be studied step by step or let‟s say layer by layer. Polychrome layers are subdivided in a preparation layer and a paint layer, the chemical composition of which varies according to the mode and the period of painting. For the European regions, the preparation layer is usually made with lime or gypsum with addition of animal or vegetal glue. On this smooth surface several layers of color are present, which consist of pigments mixed with binders of oil or distemper (egg or glue). The painted surfaces could be covered with a thin, translucent protective varnish, usually dammar, a triterpenic resin which contains primarily dammarolic acid. Our group developed a color analysis study before and after the radiation treatment of the powder pigments/painted wood panels using a portable integrating sphere spectrophotometer for color measurements (Negut et al, 2007, Negut et al., 2010). One aim of the work was to evaluate the colour stability over one year for a set of un- and irradiated painted wooden panels. It was found that colour shift in time is insignificant for experimental models prepared with mars red and chrome yellow. The colour of varnished samples prepared with red lead and raw Sienna was the most unstable. Irradiated samples were less stable than unirradiated ones, except unvarnished raw Sienna and mars red. Colour shift over time increased with the dose rate. Varnish did not had an effect on the colour stability over time except the samples prepared with raw Sienna where the colour shift was higher for varnished samples. The purpose of the present work is to evaluate by vibrational spectroscopy the gamma irradiation induced changes in the chemical/supramolecular structure of the painting layer of the same painted wooden experimental models. 2. Experimental 2.1. Experimental models Experimental models (see Fig. 1) prepared by Conservation-Restoration Department of Bucharest National University of Arts (Romania), consisted of small rectangular (3x10 cm) pieces of wood covered by a ground layer (chalk in mixture with bone glue) and pigments : ultramarine (Na8-

10Al6S6O24S2-4), red lead (Pb3O4), chrome yellow (PbCrO4), mars red (synthetic Fe2O3), raw sienna (iron oxidesH2O), lead white (PbCO3)2Pb(OH)2 mixed with tempera (18% aqueous solution of yolk egg). The sources of pigments were: Maimeri, Italy (raw Sienna, mars red, chrome yellow and ultramarine), Schmincke, Germany (lead white) and unknown, Greece (red lead). The proportion between chalk and glue aqueous solutions was 1:1 in volume. Egg yolk, traditionally used as binder in tempera painting is composed of approximately 49% of water, 33% of lipids, 16.5% of proteins

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and 1% of carbohydrates (glucose). The lipids are made up of triglycerides (65%), phospholipids (29%) and cholesterol (5%) (Gaspard et al., 2008). The ratio of pigment to yolk egg emulsion was 1:2 in weight. Half of every sample was additionally varnished with dammar. Fig 1. 2.2. Gamma irradiation A SVST Co-60/B gamma irradiator was used for irradiation. Irradiation was carried out in the presence of air at room temperature. An ECB dosimetric system was used for dose measurements. All values of dose are expressed as absorbed dose in water. The dosimetric system has traceability to High Dose Reference Laboratory – RISØ – Denmark. Samples were prepared in three series: one unirradiated, used as a reference, and two irradiated at 11 kGy but using two dose rates: 35 Gy/min (d) and 245 Gy/min (D). 2.3. FTIR and FT-Raman measurements Bruker Vertex 70 FT-IR/Raman spectrometer equipped with a mobile optic fiber RAMPROBE attached to RAM II module (LN2 Ge detector) was used. FT-IR spectra were recorded in KBr pellets from 1 mg sample and 300 mg KBr (Brosseau et al., 2009). All the spectra were manipulated and analysed with the OPUS software. Atmospheric compensation, vector normalization of whole spectra and baseline correction using straight lines and one iteration additional concave rubberband correction were applied to the spectra. FT-Raman spectra were recorded between 50 and 3500 cm–1 using Nd:YAG laser excitation of 1064 nm, and between 1 and 500 mW source power. Spectral acquisition was made with 100 scans at 4 cm–1 resolution, in situ. 3. Results and discussion The ability of FTIR and FT-Raman spectroscopy to identify multicomponent painted layers was checked using the experimental models. The comparison of our spectra with the spectra of the pigments ultramarine, lead white, chrome yellow, raw sienna, red lead, red mars, of egg yolk and of dammar from literature and databases e-VISART, e-VISARCH, IRUG was used to confirm the picture layer composition and to evaluate the gamma rays effects (Burgio and Clark, 2001; Castro et al., 2005; Infrared and Raman Users Group, 2011).

For analysis of the gamma irradiation effect, the FTIR data were a better source because FT-Raman spectra were perturbed by the strong fluorescence of the irradiated samples. The fluorescence observed in the irradiated probes may be attributed to trapped electrons. It is known that obtaining a good FT-Raman spectrum requires fulfillment of many conditions: low absorbing material, lack of impurities and a skilful operator for acquisition optimization. 3.1. FT-IR analysis For every type of pigment six samples were analysed: unirradiated and irradiated with d and with D dose rates, with and without varnish. For the preparation of KBr pellet one milligram of paint layer was obtained with a scalpel under an optical microscope. In the Fig. 2 is given the FTIR spectra of unirradiated, unvarnished raw sienna and red lead paint layers and egg yolk. This representation is used to prove the ability of FTIR spectroscopy to analyze multicomponent samples. One may observe that paint layers spectra are the sums of egg yolk and pigment spectra contributions. Only the example of raw sienna and red lead paint layers are given to have a clear picture. The peaks of egg yolk at 2925, 2854, 1746, 1650, 1547, 1465, 1379, 1094, 1238 973 and 722 cm-1 superpose well on the painted layer FTIR peaks. In the fingerprint region (1800-600 cm-1) small shifts in band position of about 5 cm-1 are observed due to egg yolk interaction with

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pigments. Comparison of the spectra of egg yolk and paint layers reveals fine changes in amide I (1650 cm-1) and amide III (1200 cm-1) protein bands due to physical interactions. Fig. 2 One of the successes of the FTIR analysis was the identification of varnished samples although a very low quantity of dammar resin was used (about 5% in weight). Fig. 3 shows the pure dammar resin, raw sienna and yellow chrome painted layer FTIR spectra Analysis of the spectra allowed the identification of dammar treated experimental models by the band of 1705 cm-1 of dammar which is observed only in the varnished samples. Only the case of raw sienna samples is shown to avoid the many spectra superposition. Fig. 3. Fig 4. shows the FTIR spectra of raw Sienna paint layer experimental model before and after gamma irradiation at two dose rates: d-35 Gy/min and D- 245 Gy/min. To save printing space only the case of raw Sienna experimental model is illustrated. Instead, the spectra of all samples are summarized in table 1. Fig. 4. The shape of OH band has some displacements but this may be due to the use of KBr pellets which are highly hygroscopic and therefore can change their water content according to time elapsed from the preparation. Egg yolk losses water at room temperature and its spectrum changes, especially in the OH range. In the case of painting layers it was observed that Raman spectrum gives more information on the pigment while the FTIR spectrum gives more information on the polymeric content (Zieba-Palus and Borusiewicz, 2006). FTIR bands position and assignment are given in the Table 1 for the organic component of all experimental model pictorial layers. Table 1. In general, very small band variations are observable in the FTIR spectra of tempera paints “organic

content”, supposed the most susceptible to gamma induced modifications. The most important changes in the FTIR spectra of irradiated experimental models were observed for raw Sienna samples: for the higher dose rate the egg yolk protein oxidation peaks and the CH stretching bands due to lipids degradation products increase. For every set of paint layer experimental model the average spectrum, the standard deviation (stdev) and mean distance (md) were calculated with the OPUS software. The Averaging command generates a new spectrum from a set of original spectra of the same type. The intensities of this new spectrum are calculated by averaging the intensities of the original spectra. The following stdev, md values were obtained: chrome yellow 0.169, 0.149; mars red 0.126, 0.112; raw sienna 0.128, 0.114; red lead 0.173, 0.149; lead white 0.295, 0.239; ultramarine 0.098, 0.084. Lead white has the biggest deviations and this is consistent with the observed colour non-uniformity of the samples. Chrome yellow and red lead have comparable next biggest values. It is interesting that this approach groups gives near values of stdev and md for Pb based pigments (lead white, chrome yellow and red lead) and Fe based pigments (mars red and raw sienna). Ultramarine painted layer presents the smallest deviations in the spectra with the exception of peak at 1465 cm-1 which increase visibly for the D dose rate (Fig. 5). Fig. 5. The ultramarine painted layer has two bands at 3695 and 3620 cm-1 that may indicate the presence of free hydroxyl grops. Loss of color of ultramarine observed in aged samples may be due to liberation

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of S from small sulphur species S3- and S2

-, which are trapped in the oxide lattice and formation of H2S (Smith and Dent, 2005). The same mechanism may interfere in gamma radiation response but such changes could not be detected in the FTIR spectrum. 3.2. FT-Raman analysis FT–Raman spectra were acquired using the traditional acquisition mode, in the sample compartment of the Bruker Vertex 70 instrument and with a mobile probe adequate for in-situ measurements with the aim to compare the sensibility of the two techniques. Thus, the intensity of the spectrum acquired in the sample compartment is higher than that of the spectrum acquired with the mobile probe but a good signal pigment is obtained in each case. Since we were looking for small changes induced by irradiation we decided to use the sample compartment acquisition mode. Pigments peaks were assigned using internet and literature databases as follows: chrome yellow 141w, 339w, 361s, 378m, 405w, 842s, lead white 415w (br), 681w, 1051s, 1055s, mars red 294vw, red lead 551m, 148s, 123ms, ultramarine 1097m, 549vs, raw Sienna 418 w (strong; m, medium; w, weak; v, very; sh, shoulder; br, broad) (Burgio and Clark, 2001; Infrared and Raman Users Group, 2011; K. Castro et al., 2005). Examples of FT-Raman paint layer experimental models spectra are given in the Fig. 6.

Fig. 6.

The FT-Raman spectra of irradiated sample showed strong fluorescence which increased with the dose rate. The spectra showed intense bands of vibration of pigment and weak bands of the egg yolk and dammar resin components. In the Fig. 6a and 6b the band at 2900 cm-1, attributed to the CH stretching vibrations is more intense for the vernis treated samples. There are no significant differences in the FT-Raman spectra for unirradiated and irradiated experimental models with the exception of fluorescence due to trapped electrons resulted from the gamma ray ionizations. 4. Conclusions The FTIR spectra analysis permitted, in the case of raw sienna and chrome yellow paint layers experimental models, the rapid identification of dammar varnished and unvarnished samples by the most intense band of dammar from 1705 cm-1. Mineral pigments used in the historical paintings proved to be stable at irradiation. As expected, FT-Raman spectroscopy showed lower sensibility than the FTIR spectroscopy in the analysis of the gamma irradiation effect on polymeric component of wooden artifacts picture layers. The most important changes in the FTIR spectra were observed for raw Sienna samples: for the higher dose rate the egg yolk protein oxidation peaks and the CH stretching bands due to lipids degradation products increase in intensity. FTIR and FT-Raman spectra of chrome yellow and ultramarine paint layers are very similar for unvarnished, varnished, unirradiated and irradiated samples. The FT-Raman spectra of irradiated samples show strong fluorescence which increases with the dose rate. Previous finding that a small color shift appears for 11 kGy gamma treated samples may be attributable to a complex radiation chemistry involving the organic polymer matrix of the experimental models paint layer. The small structural changes observed recommend the use of gamma irradiation in the disinfection of painted wood artefacts, at small dose rate. Further investigations are envisaged on the gamma irradiation behavior of different pigments, painting media and varnishes. The use of nuclear techniques for the preservation of cultural heritage artifacts is still in its infancy despite of roaring success stories like the disinfection of Ramses II mummy (France, 1977) and the mass sterilization of artifacts from Majdanek Nazi Camp (Poland, 2011). Acknowledgements

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This work was funded by the ANCS, DELCROM project, contract no. 92-086/2008 and PN II, Human Resources, PD project no. 27/2010, Fourier Transform Vibrational Spectroscopy Used in Characterization of Painting Pigments: An Authentification Chance for Roumanian Paintings. Authors wish to thanks to Dr. Caruso Francesco from Dipartmento de Chimica Fisica “F.

ACCASCINA”, Universita Degli Studi Di Palermo, Palermo, Italy for providing dammar reference sample. References Akyuz, S., Akyuz, T., Basaran, S., Kocabas, I., Gulec, A., Cesmeli, H., Ucar, B., 2009. FT-IR and EDXRF analysis of wall paintings of ancient Ainos Hagia Sophia Church. J. Mol. Struct. 924-926, 400-403. Bacci, M., Casini, A., Cucci, C., Picollo, M., Radicati, B., Vervat, M., 2003. Non-invasive spectroscopic measurements on the Il ritratto della figliastra by Giovanni Fattori: identification of pigments and colourimetric analysis. J. Cult. Herit., 4, 329-336. Brainard, D.H., 2003. Color Appearance and Color Difference Specification, in Shevell, S.K. (Ed.), The Science of Color 2nd edition, Optical Society of America, Washington D.C., 191-216. Breitman, M., Ruiz-Moreno, S., López Gil, A., 2007. Experimental problems in Raman spectroscopy applied to pigment identification in mixtures. Spectroch. Acta A: Mol. Biomol. Spectrosc. 68, 1114-1119. Brosseau, C.L., Rayner, K.S., Casadio, F., Grzywacz, C.M., Van Duyne, R.P., 2009. Surface-enhanced Raman spectroscopy: a direct method to identify colorants in various artist media Anal. Chem. 81, 7443-7447. Burgio, L., Clark, R.J.H., 2001. Library of FT-Raman spectra of pigments, minerals, pigment media and varnishes, and supplement to existing library of Raman spectra of pigments with visible excitation. Spectroch. Acta A 57, 1491-1521. Castro, K., Perez-Alonso, M., Rodrıguez-Laso, M. D., Fernandez, L.A., Madariaga, J.M., 2005. On-line FT-Raman and dispersive Raman spectra database of artists‟ materials (e-VISART database). Anal. Bioanal. Chem. 382, 248-258. Colthup, N.B., Daly, L.H., Wiberly, S.E., 1990. Introduction to Infrared and Raman Spectroscopy, Academic Press, San Diego. Coupry, C.I. 2000. Application of Raman microspectrometry to arts objects. Analusis 28, 39-45. Darchuk, L., Tsybrii, Z., Worobiec, A., Vázquez, C., Palacios, O.M., Stefaniak, E.A., Gatto Rotondo, G., Sizov, F., Van Grieken, R., 2010. Argentinean prehistoric pigments' study by combined SEM/EDX and molecular spectroscopy. Spectrochim. Acta A Mol. Biomol. Spectrosc. 75, 1398-1402. De Nolf, W., Vekemans, B., Janssens, K., Falkenberg, G., 2006. Pigment identification by scanning μ-XRF/μ-XRD. http://hasyweb.desy.de/science/annual_reports/2006_report/part1/contrib/48/17879.pdf (last accesed September 23, 2011) Deneckere, A., Hocquet, F.-Ph., Born, A., Klein, P., Rakkaa, S., Lycke, S., De Langhe, K., Martens, M.P.J., Strivay, D., Vandenabeelee, P., Moens, L., 2010. Direct analysis of the central panel of the so-called Wyts triptych after Jan van Eyck. J. Raman Spectroscopy 41, 1210–1219. Desnica, V., Škarić, K., Jembrih-Simbuerger, D., Fazinić, S., Jakšić, M., Mudronja, D., Pavličić, M.,

Peranić, I., Schreiner, M., 2008. Portable XRF as a valuable device for preliminary in situ pigment

investigation of wooden inventory in the Trski Vrh Church in Croatia. Applied Physics A: Materials Science Processing, 92, 19-23. Dorge, V., Howlett, F. C., 11–14 November 1994. Proc. Symp. organized by the Wooden Artifacts Group of the American Institute, for Conservation of Historic and Artistic Works and the Foundation of the AIC, Williamsburg, Virginia. Edwards, H.G.M., Farwell, D.W., Newton, E.M., Rull Perez, F., Jorge Villar, S., 2000. Raman spectroscopic studies of a 13th century polychrome statue: identification of a „forgotten‟ pigment. J.

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Edwards, H.G.M., 2009. Art Works Studied Using IR and Raman Spectroscopy in Lindon, J., Tranter, G., Koppenaal, D. (Eds.) Encyclopedia of Spectroscopy and Spectrometry, Academic Press, pp. 12-17. Gaspard, S., Oujja, M., Moreno, P., Mendez, C., Garcia, A., Domingo, C., Castillejo, M., Interaction of Femtosecond Laser Pulses with Tempera Paints. Applied Surface Science 255 (2008) 2675-2681. Infrared and Raman Users Group, www.irug.org (last accessed September 23, 2011) Kaminska, A., Sawczak, M., Oujja, M., Domingo, C., Castillejo, M., Sliwinski, G., 2006. Pigment identification of a XIV/XV c. wooden crucifix by means of the Raman spectroscopic technique. J. Raman Spectrosc. 37, 1125–1130. Katusin-Razem, B., Mihaljevic, B., Razem, D., Microbial decontamination of cosmetic raw materials and personal care products by irradiation, 2003. Rad. Phys. Chem. 66. 309-316. Maier, M.S., Gómez, B.A., Parera, S.D., Elkin, D., De Rosa, H., Ciarlo, N.C., Svoboda, H., 2010. Characterization of cultural remains associated to a human skeleton found at the site HMS Swift (1770). J. Mol. Struct. 978, 191-193. Mathieson, L., Nugent K.W., 1996. Raman Laser Microprobe Spectroscopy and the Analysis of Materials from Oil Paintings, AICCM Bull. 21, 3-11. Negut, D.C., Ponta, C.C., Georgescu, R.M., Moise, I.V., Niculescu, Gh., Lupu, A.I.M., 2007. Effects of gamma irradiation on the colour of pigments. Proc. SPIE, Vol. 6618, O3A: Optics for Arts, Architecture and Archaeology, R1-10. Negut, C.D., Cortella, L., Cutrubinis, M., Tran, K., Ponta, C.C., 2010. Inter-comparison of colour measurements of poly-chromed wooden objects which were irradiated for disinfection reasons, - Braga 2008 : Proceedings of the International Conference Wood Science for Conservation of Cultural Heritage held by COST Action IE0601 (Braga - Portugal, 5-7 November 2008, Gril J. (Ed)), Firenze, Firenze University Press (2010) 230-235. Rizzo, M.M., Machado, L.D.B., Borrely, S.I., Sampa, M.H.O., Rela, P.R., Farah, J.P.S., Schumacher, R.I., 2002. Effects of gamma rays on a restored painting from the XVIIth century. Rad. Phys. Chem. 63, 259-252. Saverwyns, S., 2010. Russian avant-garde… or not? A micro-Raman spectroscopy study of six paintings attributed to Liubov Popova. J. Raman Spectroscopy 41, 1235–1242. Smith, E., Dent, G., 2005. Modern Raman spectroscopy a practical approach, John Wiley & Sons, Chichester. Smithsonian's Museum Conservation Institute, 2001. http://si.edu/mci/english/research/consulting/ mail_irradiation.html (last accessed September 23, 2011) Stanculescu, I., Mandravel, C., Delattre, F., Landy, D., Woisel, P., Surpateanu, G., 2003. Complexation of tetrandrine with calcium ion probed by various spectroscopic methods and molecular modeling. J. Mol. Struct., 655, 81-87. Tiano, P., 2009. Biodegradation of Cultural Heritage: Decay Mechanisms and Control Methods, http://www.arcchip.cz/w09/w09_tiano.pdf (last accessed September 23, 2011) Boon, J.J., Ferreira, E.S.B. (Eds), 2006. MOLAR Reports, Reporting Highlights of the De Mayerne Programme, NWO, The Hague, Vandenabeele, P., De Paepe, P., Moens, L., 2008. Study of the 19th century porcelain cards with direct Raman analysis. J. Raman Spectroscopy 39, 1099-1103. Zieba-Palus, J., Borusiewicz, R., 2006. Examination of multilayer paint coats by the use of infrared, Raman and XRF spectroscopy for forensic purposes. J. Mol. Struct. 792–793, 286–292. Webera, G., Delbroucka, J. M., Strivaya, D., Kerffa, F., Martinot, L., 1998. Use of a variable incidence angle PIXE arrangement for studying pigment multilayers. Nuclear Instruments Methods Phys. Res. B: Beam Interactions with Materials and Atoms 139, 196-201. Figures legends Fig.1. Experimental models of tempera painted wooden panels: from left to right top row: ultramarine, lead white, chrome yellow bottom row: raw sienna, red lead, red mars; Notations: +V -

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varnished paint layer side; d- 35 Gy/min dose rate irradiated experimental models; D - 245 Gy/min dose rate irradiated experimental models; u - unirradiated experimental models. Fig. 2. FTIR spectra of unirradiated, unvarnished raw sienna (orange) and red lead (red) paint layers and egg yolk (black). Fig. 3. FTIR spectra of dammar varnish (black), unvarnished (red) and varnished (orange) raw sienna painted layer. Fig. 4. FTIR spectra of raw Sienna experimental model paint layer: unirradiated (black), d irradiated (orange) and D irradiated (red). There are two curves for each color because the spectra of varnished and unvarnished regions are shown. Fig. 5. FTIR spectra of ultramarine paint layer: unirradiated (black), d irradiated (orange) and D irradiated (red). There are two curves for each color because the spectra of varnished and unvarnished regions are shown. Fig. 6. FT-Raman spectra of a) ultramarine b) chrome yellow c) red mars; unirradiated (black), d irradiated (orange) and D irradiated (red); There are two curves for each color because the spectra of varnished and unvarnished regions are shown.

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Table 1. Main organic component FTIR bands position (cm-1) and assignment of red lead (rl) ultramarine (u), lead white (lw), chrome yellow (cy) raw sienna (rs), red mars (rm) pictorial layer experimental models; Notations: v-varnished; d-35 Gy/min dose rate irradiated; D-245 Gy/min dose rate irradiated

Sample C–H asym stretching C–H sym stretching C=O stretching Amide I CH2 lipids rl rl v rl d rl d v rl D rl D v u u v u d u d v u D u D v lw lw v lw d lw d v lw D lw D v cy cy v cy d cy d v cy D cy D v rs rs v rs d rs d v rs D rs D v rm rm v rm d rm d v rm D rm D v

2925 2925 2925 2926 2925 2926 2925 2926 2925 2926 2926 2926 2926 2926 2925 2926 2926 2926 2925 2925 2925 2925 2925 2925 2925 2925 2926 2925 2925 2925 2924 2924 2924 2923 2924 2924

2854 2854 2854 2854 2854 2854 2854 2855 2854 2855 2854 2855 2854 2854 2854 2854 2854 2855 2854 2854 2854 2854 2854 2854 2854 2854 2854 2854 2854 2854 2853 2853 2853 2853 2853 2853

1743 1744 1745 1744 1744 1745 1743 1743 1744 1743 1744 1743 1744 1744 1744 1744 1743 1742 1744 1741 1743 1742 1743 1742 1743 1742 1744 1741 1743 1741 1743 1740 1741 1739 1742 1739

1656 1655 1656 1655 1655 1656 1657 1658 1657 1658 1657 1658 1657 1656 1653 1656 1654 1655 1649 1649 1650 1649 1649 1650 1655 1654 1652 1650 1653 1654 1649 1649 1649 1649 1649 1649

1459 1458 1460 1457 1458 1458 1463 1463 1465 1464 1465 1443 1456 * * * * * 1455 1454 1463 1461 1463 1461 1461 1458 1463 1457 1463 1458 1463 1454 1462 1452 1463 1452

*-could not be determined due to bands superposition

Table

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49

Figure 1Click here to download high resolution image

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

500100015002000250030003500

Wavenumber cm-1

0.00

0.02

0.04

0.06

0.08

0.10

Abs

orba

nce

Uni

ts

Fig. 2.

Figure 2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

500100015002000250030003500

Wavenumber cm-1

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Abs

orba

nce

Uni

ts

Fig. 3.

Figure 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

500100015002000250030003500

Wavenumber cm-1

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Abs

orba

nce

Uni

ts

Fig. 4.

Figure 4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

I:\RAMAN\FTIR_PIGMENTI\ultramarin\ultramarin_D_max.0 ultramarin_D_max KBR pellet I:\RAMAN\FTIR_PIGMENTI\ultramarin\ultr_d.0 ultr_d KBr I:\RAMAN\FTIR_PIGMENTI\ultramarin\ultr_d_v.0 ultr_d_v KBr I:\RAMAN\FTIR_PIGMENTI\ultramarin\ultr_D_v.1 ultr_D_v KBr I:\RAMAN\FTIR_PIGMENTI\ultramarin\ultr_umiditate_10%.0 ultr_umiditate_10% KBr I:\RAMAN\FTIR_PIGMENTI\ultramarin\ultr_v.0 ultr_v KBr

01/08/200922/07/200922/07/200922/07/200922/07/200922/07/2009

500100015002000250030003500

Wavenumber cm-1

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Abs

orba

nce

Uni

ts

Page 1/1

Fig. 5.

Figure 5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

I:\RAMAN\raman compartment\ultramarine\ultramarine Dmax 1 mW.0 ultramarine Dmax 1 mW lemn pictat I:\RAMAN\raman compartment\ultramarine\ultramarine Dmax verni 1 mW.2 ultramarine Dmax verni 1 mW lemn pictat I:\RAMAN\raman compartment\ultramarine\ultramarine Dmin 1mW.0 ultramarine Dmin 1mW lemn pictat I:\RAMAN\raman compartment\ultramarine\ultramarine Dmin vernis 1 mW.0 ultramarine Dmin vernis 1 mW lemn pictat I:\RAMAN\raman compartment\ultramarine\ultramarine non irradiated 50 mW.0 ultramarine non irradiated 50 mW painted wood I:\RAMAN\raman compartment\ultramarine\ultramarine non irradiated vernis 50 mW.0 ultramarine non irradiated vernis 50 mW painted wood

25/05/200925/05/200925/05/200925/05/200912/05/200912/05/2009

1087

.22

713.

07

549.

05

358.

63

282.

46

155.

70

500100015002000250030003500

Wavenumber cm-1

0.0

00

.02

0.0

40

.06

0.0

8

Ra

ma

n I

nte

nsi

ty

Page 1/1

Fig. 6. a

I:\RAMAN\raman compartment\chrome yellow\chrome yellow iradiated Dmax 16 mW.0 chrome yellow iradiated Dmax 16 mW painted wood I:\RAMAN\raman compartment\chrome yellow\chrome yellow non iradiated 150 mW.0 chrome yellow non iradiated 150 mW painted wood I:\RAMAN\raman compartment\chrome yellow\yellow chrome Dmax vernis 16 mW.2 yellow chrome Dmax vernis 16 mW lemn pictat I:\RAMAN\raman compartment\chrome yellow\yellow chrome vernis 16 mW.0 yellow chrome vernis 16 mW lemn pictat I:\RAMAN\raman compartment\chrome yellow\chrome yellow iradiated Dmin 16 mW.0 chrome yellow non iradiated 16 mW painted wood I:\RAMAN\raman compartment\chrome yellow\chrome yellow_d vernis.0 chrome yellow_d vernis painted wooden panel

12/05/200912/05/200929/05/200929/05/200912/05/200908/09/2009

1087

.49

843.

96

345.

77

283.

16

156.

44

500100015002000250030003500

Wavenumber cm-1

0.0

00

.05

0.1

00

.15

0.2

0

Ra

ma

n I

nte

nsi

ty

Page 1/1

Fig. 6. b

Figure 6

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

I:\RAMAN\raman compartment\mars red\mars red D v.0 mars red D v painted wooden panel I:\RAMAN\raman compartment\mars red\mars red iradiated Dmax 4 mW.0 mars red iradiated Dmax 4 mW painted wood I:\RAMAN\raman compartment\mars red\mars red irradiated D min 4mW.0 mars red irradiated D min 4mW painted wooden panel I:\RAMAN\raman compartment\mars red\mars red non iradiated 4 mW.0 mars red non iradiated 4 mW painted wood I:\RAMAN\raman compartment\mars red\mars_red_d_v.0 mars_red_d_v painted wooden panel I:\RAMAN\raman compartment\mars red\mars_red_v.0 mars_red_v painted wooden panel

08/09/200912/05/200908/09/200912/05/200908/09/200908/09/2009

412.

37

293.

93

227.

92

100200300400500600700800900

Wavenumber cm-1

0.0

10

.03

0.0

50

.07

Ra

ma

n I

nte

nsi

ty

Page 1/1

Fig. 6. c