Eur. Phys. J. Plus (2020) 135:616 https://doi.org/10.1140/epjp/s13360-020-00607-1

Regular Article

New insights on the painting “Portrait of ”: a preliminary analytical study of Mario Nuzzi’s pictorial production and of his artistic collaborations

Lucilla Pronti1, Martina Romani1,a , Ombretta Tarquini2, Gianluca -Rinati3, Francesco Petrucci4, Marcello Colapietro2, Augusto Pifferi2, Marco Marinelli3, Mariangela Cestelli-Guidi1 1 INFN-Laboratori Nazionali di Frascati, Via Enrico Fermi 54, 00044 Frascati, RM, 2 C.N.R. Istituto di Cristallografia–Montelibretti, Via Salaria Km 29300, 00015 Monterotondo, RM, Italy 3 INFN-Dipartimento di Ingegneria Industriale, Università degli Studi di Roma Tor Vergata, Via del Politecnico 1, 00133 , Italy 4 Palazzo Chigi, Piazza di Corte, 14, 00040 Ariccia, RM, Italy

Received: 2 March 2020 / Accepted: 13 July 2020 © Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2020

Abstract The study and characterization of an art work carried out by two or more artists is always an interesting challenge since each painter, although belonging to the same artistic current, can introduce specific pictorial materials or peculiar aesthetic effects, which consti- tute the artist fingerprint. This work presents a preliminary analytical study of the “Portrait of Mario Nuzzi”, painted by Giovanni Maria Morandi and Mario Nuzzi. In particular, non- invasive investigations were conducted using UV–VIS–NIR–SWIR multispectral imaging, radiography and X-ray spectroscopy (XRF). Multivariate analyses (PCA) were performed on VIS–NIR multispectral imaging in order to highlight some details not clearly visible using a traditional univariate analysis. Such an approach could be useful for authentication pro- cesses. In particular, in this paper we propose the use of the score density plot to determine the artist’s “chiaroscuro” fingerprint. Finally, the artist’s palette was compared with that of the “Primavera” painting, painted by Mario Nuzzi and Filippo Lauri, by using XRF analy- ses. We discovered that “Portrait of Mario Nuzzi” has not been significantly changed since the final version. Furthermore, the elemental composition of the pigments revealed that the palette used in the two paintings does not completely overlap. This aspect encourages us to perform a more detailed analysis of the pigments with the aim of better discriminating the parts painted by Mario Nuzzi from those of each collaborator.

1 Introduction

It is known that paintings were often made with the contribution of several painters, who usually left their artistic “signature” in various details around the surface of the painting. This has been noted above all in artworks associated with a specific artist (i.e. Verrocchio’s workshop, Michelangelo’s workshop) [1] and/or in the retouching carried out for possible his-

a e-mail: [email protected] (corresponding author)

0123456789().: V,-vol 123 616 Page 2 of 14 Eur. Phys. J. Plus (2020) 135:616 torical–political purposes (for example the repainting of Siviero on Sironi’s fascist artworks) [2]. It must be said that it can be very difficult to establish which parts could have been painted by one artist rather than another, even after performing scientific analyses, since the materials and execution techniques can be very close and the artistic notions can be approximately the same. However, archaeometric investigations can be very useful for reconstructing the areas of intervention of an artist or for tracing the historical events of a work of art; in fact, some scientific research aims to develop databases of the artistic materials used by some artists [3–6] or to improve analytical techniques and data post-processing methods to support stylistic studies and support the authentication process [7]. Collaborations between artists can arise for several reasons. One of these may be the strong ability of a specific artist to make detailed motifs or figures, as the case of Mario Nuzzi, also called Mario de’ Fiori, who was the main specialist in the genre of flower still life in the XVII century [8]. Mario Nuzzi was a roman painter of Baroque style and made several paintings for Cardinal Flavio Chigi, one of the most important collectors of Nuzzi’s paintings. Among these, there are four paintings depicting the seasons and portrait of Mario Nuzzi which were painted in collaboration with other important artists of the time and are kept in Palazzo Chigi (Ariccia, Rome). In particular, it is known that Filippo Lauri painted the figures in “Primavera”, in “Summer”, in “Autumn” and Bernardino Mei in “Winter”, while Giovanni Maria Morandi posed Nuzzi intent on portraying a vase of flowers [9]. Mario Nuzzi is a painter not very known from the point of view of archaeometry, as well as other artists who worked at Palazzo Chigi. Therefore, the study of the artist’s palettes and the execution techniques of these artworks could be extremely important for reconstructing the operational phases of the artistic collaboration. In this paper, we report the results of non-destructive analyses performed on the portrait of Mario Nuzzi, which he performed in collaboration with Giovanni Maria Morandi. The presence of underdrawings and “pentimenti” was detected by NIR-SWIR reflectog- raphy and radiography. Furthermore, the VIS–NIR multispectral images were acquired and processed through principal component analysis (PCA) in order to highlight some details that are not clearly visible using a univariate approach (analysing single images). This approach has been well demonstrated on other scientific works, for both the identification of pictorial materials or degradation products [10–12] and to identify “pentimenti” [13, 14]. Although hyperspectral imaging associated with chemometric analysis is well-established approach in the field of cultural heritage due to the intrinsic need to “reduce” a large amount of data, its application on linked multispectral images is not yet widespread, especially for the identification of “pentimenti” and pictorial details useful for the authentication of the paintings. In the latter field, the potential value of multispectral imaging coupled with chemometric analysis has not been yet studied extensively. For example, this approach could be suitable for defining the “chiaroscuro” technique for each artist that could represent a method of authenticating the artworks [7]. PCA is useful for emphasizing the “chiaroscuro” method the considering not only the RGB spectral range (i.e. the photographic image) but also VIS–NIR multispectral ones. Furthermore, this approach shows even more advantages if we consider that white and brown/black pigments could show a specific spectral behaviour in the visible (i.e. zinc white, titanium white and lead white) [15] and infrared ranges (i.e. carbon- and iron-based pigments) [16].

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Fig. 1 The painting of “Portrait of Mario Nuzzi” (a) and the painting “Primavera” (b)

To support the results obtained from UV–VIS–NIR–SWIR imaging analyses, the use of complementary techniques with a high identification capacity of pigments and mixtures is often considered, such as X-ray fluorescence spectroscopy (XRF) [17, 18]. In this work, we present the analysis of inorganic pigments performed by X-ray fluores- cence spectroscopy on the portrait of Mario Nuzzi and on the “Primavera”, a painting created by Mario Nuzzi and Filippo Lauri, in order to compare the palettes.

2 Materials and methods

2.1 Materials

2.1.1 The “four seasons” paintings at Palazzo Chigi, Ariccia (Rome)

The painting represents one of the most emblematic works of the Roman Baroque style, both for the pictorial quality and for the fusion of two pictorial genres: still life and the portrait. The canvas belongs to a celebratory circle: “four seasons”, painted by Mario de’ Fiori himself in collaboration with Giacinto Brandi, Filippo Lauri, Carlo Maratti and Bernardino Mei, inaugurating the decorative genre in which figurative artists and still life painters collaborate for the same project, or “mixed painting”. The series was commissioned by the Cardinal Flavio Chigi between April 1658 and December 1659.

2.1.2 The “Portrait of Mario Nuzzi” at Palazzo Chigi, Ariccia (Rome)

The “Portrait of Mario Nuzzi” is an oil painting on canvas, 191×262 cm (Fig. 1a). It is a typ- ical example of a Baroque portrait in which the style joins Bernini’s theatricality: the painter turns suddenly as if he were called by an external interlocutor, interrupting the painting of the floral composition; a large curtain introduces us to the scene reproducing the effect of the theatrical act. The large canvas comes from the stitching of two different identical canvases, as revealed by the vertical trace in the centre of the painting; in this way, the two artists had the opportunity to work separately, even if the still life on the left, painted by Mario Nuzzi, was painted before the other one painted by Giovanni Maria Morandi, otherwise it would not have been possible to paint the floral composition on the painted canvas. 123 616 Page 4 of 14 Eur. Phys. J. Plus (2020) 135:616

2.1.3 The “Primavera” of Palazzo Chigi, Ariccia (Rome

“Primavera” is an oil painting on canvas, 150×250 cm (Fig. 1b). In this painting, the figure represents “Flora” and was painted by Filippo Lauri, while the floral composition was painted by Mario Nuzzi. Caravaggio’s style also emerges in this painting and the baroque and festive leaves/fruits make the scene rich in details.

2.2 Methods

2.2.1 VIS–NIR–SWIR multispectral imaging

VIS and NIR multispectral imaging were taken with a converted NIR camera (Nikon D7100). The camera is equipped with three band-pass filters centred at 370 nm, 440 nm, 526 nm (Edmund Optics) and five long pass filters above 600 nm, 695 nm, 780 nm, 830 nm and 1000 nm. The SWIR camera (XENICS “Xeva—1.7-640”) has an InGaAs sensor with the spectral range at 900–1700 nm. All multispectral images were suitably calibrated radiometrically with a reflectance stan- dard (Spectralon, Edmund Optics). To illuminate, we used two halogen bulbs (Uniflood 300 W, 3350 K, Cosmolight) positioned at 45° with respect to the normal of the painted surface. The working distance was about 2 m. The images were recorded using ImageJ (an open-source image processing software) and post-processed using MATLAB 2019b integrated by Hypertools (Free Graphical User Interface for Hyperspectral Image Analysis) [19]. We performed principal component analysis (PCA) on the hypercube, originated from the VIS–NIR multispectral images linked using MATLAB functions. PCA is a technique for reducing redundancy in multispectral images and for emphasizing in a few channels, called the “principal components”, the information contained in an original set of multispectral images [20, 21]. Each component explains a certain percentage of the variance: the first component (PC1) explains the maximum variance, the second component (PC2) another consistent part and so on, until reaching 100% of the explained variance. The algorithm chosen is the singular value decomposition (SVD) with mean centring as data pre-treatment.

2.2.2 UV fluorescence

The UV fluorescence image was acquired with a converted NIR camera (Nikon D7100) equipped with RGB filters. The lighting source used is two UV lamps with an excitation wavelength centred at 370 nm.

2.2.3 X-ray fluorescence spectroscopy

Energy-dispersive X-ray fluorescence (ED-XRF) is a non-invasive technique for identifying the elements present in a sample. The analyses were performed with a portable instrument with tungsten (W) X-ray source, a Peltier-cooled silicon drift detector complete with its amplifier- feeder and multi-channel (Amptek MCA 8000A). The detector resolution is 140 eV at 5.9 keV (Mn Kα). This apparatus is equipped with an optical triangulation system consisting of a digital microscope (PCE MM200) and a red laser pointer allowing to document the analysed point. The analyses were carried out by supplying the X generator with a voltage of 38 kV and a current of 350 μA. With this instrumentation, all the K lines for the elements with 1235 are revealed. A qualitative analysis 123 Eur. Phys. J. Plus (2020) 135:616 Page 5 of 14 616 was carried out in order to identify the elements in the points examined. The collected data were analysed with the PyMCA programme.

2.2.4 Radiography

The radiography was performed with a tungsten X-ray source and an image plate detector (IP) with reading system (Kodak CR7400) which allows to obtain digital image with dimension of 18×24 cm, grey scale at 16 bit and a 600 dpi resolution. The operating conditions were 38 kV and 1 MAS.

3 Results and discussion

The reflectographies of “Portrait of Mario Nuzzi”, performed selecting several infrared regions (NIR and SWIR), showed the presence of negligible pentimenti in the composi- tion of the work. In particular, we have detected hidden elements of the paintings, such as a frame and some details relating to the door in the background, as highlighted respectively by red arrows in Fig. 2a, b. The door was drawn under the drapes, and the double vertical lines (Fig. 2b) could be a real pentimento or a way to give the door three-dimensionality, which was covered in the final version. In these areas, the PCA performed on the VIS–NIR multispectral images showed the artist’s brushstrokes to paint the drapes: first he traced the boundaries and then filled the internal field with horizontal lines, as shown in PC1 and PC3 (Fig. 3). In addition, the score image of PC1 reveals the details of the brush strokes of the chair, which are not clearly distinguished in the visible image since they can be confused with the background. PC2 contains information on the distribution of diffused light, revealing the pictorial surface texture. PCA performed on the left side of the painting showed that the background is not a uniform black layer (Fig. 4), as seen in the InGaAs image (Fig. 2), but different vertical lines and shadows have been distinguished in PC1 and PC2. The reasons could be related to the presence of decorative lines on the wall or defects of the canvas, considering that multispectral NIR spectral features are included in the analysis. The image score of PC2 does not contain useful but detects the lines that determine the cor- ner of the room. This representation is probably attributed to the distribution of “chiaroscuro” effects and to the volumes achieved by the chromatic contrast. In this area of the painting, the radiography also showed the frame, detected in the NIR and InGaAs images, as a darker area, so this means that this detail was probably present in the original version of the drawing (Fig. 5). Moreover, in the lower part of the painting, reflectograms revealed some pentimenti or drawing details, shown in Fig. 6, in which the wood palette was painted over the painted canvas. As for the execution technique, the InGaAs image discovered the presence of a circum- scribed shape of the head that could correspond to a previous drawing of a headdress (Fig. 7a, b). Furthermore, it is possible to notice a halo around the head of Mario Nuzzi, which was not connected to any modern retouching, since it was not detected by the UV fluorescence image, as shown in Fig. 7c. No other drawings were detected by the radiographic image in Fig. 7d confirming that it could be a pictorial effect due to the shadow of the head or nuances of the background. The 123 616 Page 6 of 14 Eur. Phys. J. Plus (2020) 135:616

Fig. 2 InGaAs images of the frame (a) and the door (b) compared with the visible images

Fig. 3 Detail of the door in the “Portrait of Mario Nuzzi” (a). Intensity colour-coded images form principal component analysis (PCA); components are shown respectively as PC1 (b), PC2 (c)andPC3(d)

high radiographic contrast indicated the use of lead white as preparatory layer and for bright areas. 123 Eur. Phys. J. Plus (2020) 135:616 Page 7 of 14 616

Fig. 4 Detail of the frame in the “Portrait of Mario Nuzzi” (a). Intensity colour-coded images form principal component analysis (PCA); components are shown respectively as PC1 (b), PC2 (c)andPC3(d)

Fig. 5 Details of the frame in the “Portrait of Mario Nuzzi” (a) and radiography (b)

Fig. 6 Detail of the “Portrait of Mario Nuzzi” (a) and corresponding InGaAs image (b)

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Fig. 7 Details of the Mario Nuzzi’s face (a), InGaAs camera (b), UV fluorescence image (c), radiography (d)

In this area, the PCA performed on the VIS–NIR multispectral images, shown in Fig. 8, highlighted the distribution of the volumes given by light and shadows. In particular, PC1 showed the distribution of the high contrasted areas while the halftones are well defined in PC2 and PC3. Furthermore, the image score of PC2 describes the distribution of the scattered light revealing in particular the pictorial surface texture. The spectral behaviour of the pictorial surface texture, achieved by using PCA calculated by VIS–NIR multispectral images, depends on the preparatory layer, which could partially or completely cover the texture of the canvas and on the spectral response of the pigments used for the pictorial layers. These latter two characteristics could be attributed to a specific way of painting. The possibility to scientifically define the use of “chiaroscuro” for each artist could be considered a useful step during the authentication process and represents an interesting chal- lenge for the researchers. Therefore, the representation of the “scores density plot”, obtained 123 Eur. Phys. J. Plus (2020) 135:616 Page 9 of 14 616

Fig. 8 Detail of the frame in the “Portrait of Mario Nuzzi” (a). Intensity colour-coded images form principal component analysis (PCA); components are shown respectively as PC1 (b), PC2 (c)andPC3(d)

Fig. 9 Score density plot (PC1 vs PC2) and pixel distribution (in red) of selected scores values (1, 2, 3, 4, 5 areas of the score density plot) from the combination of PCA and VIS–NIR multispectral images, here discussed, could be useful to solve this problem. The scores density plot describes how the score values are distributed graphically in the new coordinate system (described, for example, by PC1 versus PC2). The scores density plot ofPC1versusPC2isreportedinFig.9. It shows the distribution of the scores values for each pixel of the spectral hypercube in the space of the components PC1 and PC2. False colours represent a density scale: from red (high amount of pixels with the same score values) to blue (few pixels with the same score values). For the portrait of Mario, most of the scores are distributed around the “zero” value of PC2, which means that PC2 does not explain a high percentage of variance and all the differences, in terms of “chiaroscuro”, could be observed as distribution of PC1 values. Indeed, a large quantity of “dark” pixels (Fig. 9, area 1) are localized at negative values of PC1, while the white pixels are correlated to high PC1 values (area 3). The areas 2, 4 and 5 are related to the half tones. As for the artist’s palette, the VIS–NIR multispectral acquisitions revealed that the blue and purple hues are characterized by an intense reflection in the infrared range. This aspect 123 616 Page 10 of 14 Eur. Phys. J. Plus (2020) 135:616

Fig. 10 Detail of the “Portrait of Mario Nuzzi” (a) and False colour image (b)

Fig. 11 Detail of the flowers in the “Portrait of Mario Nuzzi” (a). Intensity colour-coded images from principal component analysis (PCA); components are shown respectively as PC1 (b), PC2 (c)andPC3(d) is best highlighted by the false colour image in which these shades appear red, as shown in Fig. 10. Since the portrait area was realized by Giovanni Maria Morandi and the flowers by Mario Nuzzi, we performed a PCA on the VIS–NIR multispectral images in order to find any differences in the pigments used for the “real flowers” and the “painted flowers”. The PCA, in this case, was unable to find significant variations, as shown in Fig. 11. This could be related to a limitation of the technique used or to selection of filters or to the presence of mixtures. For this reason, we performed XRF spectroscopy in several areas of the painting and the results were compared with those obtained on the “Primavera” painting. A selection of the results was reported in Table 1. As for the two paintings, the presence of lead (Pb) and calcium (Ca) suggests the use of standard preparatory layers: a gypsum-based layer to cover the heterogeneities of the support (canvas) and a white lead pigment as a preparatory layer. In addition, all areas analysed were characterized by low copper (Cu) counts, indicating the use of a copper-based pigment as the background layer for both paintings. 123 Eur. Phys. J. Plus (2020) 135:616 Page 11 of 14 616 1.2 1.8 1.2 1.3 0.5 1.0 1.2 1.1 1.9 1.2 ± ± ± ± ± ± ± ± ± ± pparatus used 1.1 28.3 2.1 17.0 0.2 23.7 0.3 59.9 ± ± ± ± 0.4 – 74.5 ± 0.1 – 1.1 0.2 – – 53.2 0.2 – 1.7 ± ± ± 0.5 – – – 51.5 0.2 – – – 55.5 0.2 – – – 65.6 0.4 – 1.2 0.6 – – 21.1 0.3 – – – 94.3 ± ± ± ± ± ± 1.0 1.1 0.8 1.3 0.9 3.5 1.4 5.4 0.8 12.3 0.3 2.1 ± ± ± ± ± 0.2 – 0.3 ± ± 0.3 37.4 0.2 29.7 0.7 3.7 ± ± 0.3 – – 0.7 0.3 – – 1.8 0.5 – – – – 72.0 ± ± ± ± 0.2 0.5 ± 0.5 45.0 1.1 2.7 0.9 2.8 0.6 2.7 ± ± ± ± 0.2 0.5 ± 0.1 25.1 0.3 38.2 0.2 30.8 ± ± ± 0.4 – – – 19.2 0.2–––2.4 0.3 – –0.5 –0.2 2.3 0.8 –0.2 – – – 40.8 – 33.8 ± ± ± ± ± ± 0.1 0.2 0.4 –0.3 1.7 0.2 5.9 11 ± ± ± ± 0.1 0.9 0.1 3.3 0.2 4.0 0.1 1.2 0.1 1.7 ± ± ± ± ± 0.2 0.3 –2.5 0.5 0.4 0.7 0.1 0.6 ± K [K]–2.3 Ca [K]–3.6 Mn [K]–1.8 Fe [K]0.3 Cu [K] Zn [K] As [K] Sr [K] Sb [L] Hg [L] Pb [L] Analysed point K [K] Ca [K] Ti [K] Cr [K] Mn [K] Fe [K] Cu [K] Sr [K] Sn [L] Hg [L] Pb [L] Some representative XRF data. The XRF counts are reported as percentages after being normalized to W counts, which is introduced by the instrumental a Yellow Red Light green Red Red Brown Brown Green Table 1 Primavera White Portrait of Mario Nuzzi Red 123 616 Page 12 of 14 Eur. Phys. J. Plus (2020) 135:616 1.0 1.3 0.2 ± ± ± 0.4 49.1 ± t 0.2 Traces – 61.4 ± 0.7 Traces – – 2.7 ± 0.1 – 59.2 0.2 – – – Traces 7.5 0.3 – – 1.3 ± ± ± 0.5 0.7 0.8 1.3 0.9 3.3 ± ± ± 0.1 35.5 0.1 38.5 ± ± 0.1 0.8 0.3 0.4 0.4 Traces 26.8 ± ± ± 0.1 0.8 ± K [K]0.2 Ca [K]–3.0 Mn [K]–6.9 Fe [K] Cu [K] Zn [K] As [K] Sr [K] Sb [L] Hg [L] Pb [L] continued Yellow Light green Table 1 Portrait of Mario Nuzzi Yellow The elements not detected are labelled as “–”. In the second column, the red dot in the centre of images is the laser trace and indicates the analysed poin 123 Eur. Phys. J. Plus (2020) 135:616 Page 13 of 14 616

The white areas of the paintings are characterized by the presence of lead, probably attributed to lead white pigment, while the red parts were constituted by mercury (Hg) and iron (Fe), indicating a mixture of cinnabar and iron-based pigment, such as earth pigments. Other similarities in the elemental composition are relative to shadows, or generally to the brown areas, made up of manganese (Mn). This element is a marker of umber earth (iron and manganese oxides and hydroxides) widely used in paintings [22]. For yellow pigments, a high iron count has been detected which indicates the use of iron-based compounds; however, we also detected antimony (Sb) or arsenic (As) in some areas: arsenic was found in the darker areas, suggesting the use of orpiment, while antimony (detected in traces) could be related to lead antimonate yellow, called yellow. These two elements were not found in the painting “Primavera”, which instead showed the presence of tin (detected both in the figure and the flowers), generally linked to the use of lead tin oxide. Yellow pigments based on lead, tin and antimony are still an exciting field of research because these pigments seem to be used differently by the different pictorial circles of an artist or his workshop [23]. The presence of antimony could be very interesting due to the fact that during XVII century lead tin yellows, widely used between XIV and XVII centuries, gradually turned into lead antimonate (Naples) yellows [24]. From these preliminary results, it appears that Morandi preferred arsenic or antimony yellow pigments, while Nuzzi and Lauri used tin yellow pigments. Furthermore, the green areas of the “Portrait of Mario Nuzzi”, painted by Morandi, are characterized by the presence of copper and iron-based pigments. In some cases, we have found the presence of zinc which could suggest the use of verdigris [25]orrosasite[26]. In contrast, the “Primavera” painting did not show a significant amount of copper. In particular, in this painting the light green areas (i.e. Flora’s dress) showed the presence of chrome and iron. This aspect could suggest the use of Verona earth pigment [27].

4 Conclusions

A non-invasive approach has been adopted to analyse the painting of “Portrait of Mario Nuzzi” in order to gather information on the presence of regrets and the artist’s palettes. Some details of the execution technique have been revealed by conventional infrared reflectography and radiography, while others (i.e. the brush strokes directions and the effects of “chiaroscuro”) were discovered by PCA performed on VIS–NIR multispectral images. We have shown that this approach could represent a powerful method to improve the study of an artist’s “chiaroscuro”, through the use of different spectral ranges from the visible to the near infrared, making it possible to represent this stylistic element through measurable quantities. The graphical representation of the score density diagram from the PCA could be used as a painter’s fingerprint. Furthermore, since Mario Nuzzi has collaborated with other contemporary artists, the reconstruction of the areas he painted with respect to those made by his “collaborators” could be important information for art historians to support their stylistic observations. To this end, we have analysed the palette of two paintings (“Portrait of Mario Nuzzi” and “Primavera”) using XRF measurements. We found a similar elemental composition, except for the yellow and green hues. These differences suggest that it could be extremely important to carry out other analyses on Mario Nuzzi’s paintings located in Palazzo Chigi, in order to better understand this artist’s palettes and the execution techniques and to bring new insight on their collaboration.

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Acknowledgements We acknowledge the funding of Regione under the ADAMO Project No. B86C18001220002 of the Centre of Excellence at the Technological District for Cultural Heritage of Lazio (DTC). The authors want to acknowledge all the staff of Palazzo Chigi for their support during the mea- surement campaigns. We are grateful to A. Raco, G. Viviani, A. Grilli and M. Pietropaoli for the technical support. Finally, we acknowledge Dr. Roberta Fantoni responsible of the ADAMO project, and Professor Mauro Missori, WP leader.

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