Advanced Mapping of Inorganic Treatments on Porous Carbonate Stones by Combined Synchrotron Radiation High Lateral μXRPD and μXRF

Advanced Mapping of Inorganic Treatments on Porous Carbonate Stones by Combined Synchrotron Radiation High Lateral μXRPD and μXRF | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Advanced Mapping of Inorganic Treatments on Porous Carbonate Stones by Combined Synchrotron Radiation High Lateral μXRPD and μXRF Giulia Massinelli, Nicoletta Marinoni, Chiara Colombo, Giacomo Diego Gatta, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3921021/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Apr, 2024 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Understanding the effects of consolidating inorganic mineral treatments on carbonate stones of cultural heritage, on the nature and distribution of newly formed products within the matrix, poses a significant challenge in Heritage Science and Conservation Science. Existing analytical methods often fail to deliver spatial and compositional insights into the newly formed crystalline phases with the appropriate high lateral resolution. In this study, we explore the capabilities and limitations of synchrotron radiation (SR) micro-X-ray powder diffraction (µXRPD) mapping combined with micro-X-ray fluorescence (µXRF) to give insight into compounds formed following the application of ammonium oxalate (AmOx) and diammonium phosphate-based (DAP) solutions on porous carbonate stone. Ultimately, the integration of µXRPD mapping and µXRF analysis proved itself a powerful asset in providing precise qualitative and quantitative data on the newly formed phases, in the case of both calcium oxalates (CaOxs) and calcium phosphates (CaPs), and their complex stratigraphic distribution, thus opening a new route for applications to a more comprehensive study of inorganic treatments applied to carbonate substrates. Physical sciences/Materials science Physical sciences/Nanoscience and technology/Techniques and instrumentation/Characterization and analytical techniques Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Stone consolidation is one of the major challenges when dealing with buildings and stone artifacts belonging to Cultural Heritage (CH), which usually suffer from the decohesion of materials due to the decay process [ 1 ]. Since the mid-1990s, several inorganic treatments have been developed to address this issue, aiming at restoring adhesion and cohesion to damaged carbonate stones [ 2 ], and partially transforming the original matrix minerals into newly formed crystalline phases [ 3 , 4 ]. In such context, over the past two decades, inorganic mineral treatments based on ammonium oxalate ((NH 4 ) 2 C 2 O 4 , AmOx) and di-ammonium phosphate ((NH 4 ) 2 HPO 4 , DAP) solutions have gained prominence for carbonate stones [ 5 – 7 ]. These water-soluble salts react with the carbonate matrix of the stone substrate to produce sub-micrometric reaction products [ 8 ]. Specifically, AmOx primarily produces Ca-oxalate (CaOxs) while DAP's reaction should ideally yield calcium phosphate phases (CaPs). Oxalate phases exhibit limited penetration into the stone (~ 1 mm) whereas DAP-based treatments offer greater consolidating capabilities in terms of treatment penetration (2–8 mm, depending on the stone substrate) [ 9 , 10 ]. However, inorganic mineral treatments exhibit significant variability in terms of the newly formed phases within the treated stone materials and their effect on the stone microstructure. Factors such as their crystal-chemical composition, crystallinity, penetration, and distribution are influenced by a series of interrelated variables playing during the solution reaction with the calcite matrix (i.e., solution molarity, treatment methodology, etc.) [ 10 , 12 ]. Consequently, studying the outcome of the reaction process, specifically the new "reaction products-calcite matrix" system, presents a significant challenge. Despite this complexity, understanding the modifications induced by inorganic treatments is crucial, given that the physical, chemical, and microstructural properties of the new system significantly impact the macroscopic interaction of the building stone with the agents of decay. The complexity of studying these transformations becomes particularly pronounced in the case of reaction products that share a similar elemental composition to those of the carbonate stone substrate, like in the case of CaOxs formed by AmOx solutions, or in the case of complex reaction kinetics in the presence of carbonate ions that result in not stoichiometric reaction. Examples of this last scenario are CaPs phases formed with DAP solutions, which ideally should yield crystalline hydroxyapatite (HAP, Ca 10 (PO 4 ) 6 (OH) 2 ), however, the result is complex mixtures of crystalline and poorly crystalline phosphate phases [ 11 ]. In accordance, a range of analytical techniques has been employed tailored to characterize carbonate stone treated with inorganic mineral treatments and gain insights into the composition and penetration depth of the newly formed phases to assert their performance. Conventional methods such as SEM-EDX, XRD, and FT-IR have been widely used but lack the specificity and lateral resolution required for characterizing phases with different degrees of crystallinity, in addition to being invasive (as many of their experimental setups require a sample) or, in some cases destructive (i.e., with a complex sample preparation) [ 13 – 15 ]. High lateral resolution micro-spectroscopy techniques, like µ-ATR-FTIR and µ-Raman mapping or spectroscopic imaging, have proven valuable for probing the spatial distribution of consolidants, providing complementary structural and compositional insights on the newly formed phases [ 16 – 19 ]. However, these techniques may face challenges in distinguishing the newly formed phases within the microstructure due to overlapping vibrational bands. More recently, synchrotron radiation (SR) facilities have experienced a remarkable rise in the study of Cultural Heritage materials [ 20 – 23 ]. Advanced radiation imaging techniques, such as SR-based X-ray micro-computed tomography (µ-CT), have been employed to non-invasively determine the effects of the new product crystallization on the 3D stone’s microstructure at a maximum voxel size of 1 µm 3 . However, no chemical information is provided [ 24 – 27 ]. Moreover, micro-X-ray powder diffraction tomography (XRDCT) measurements allow structural characterization and 3D localization of the reaction products, but the highly heterogeneous systems may result in very big and complex XRDCT datasets and data interpretation [ 28 ]. Lastly, more, recently, SR-based spectroscopy techniques such as Ca K-edge 2D X-ray absorption near-edge structure (XANES) with µ-XRF mapping have been successfully employed to spatially distinguish among amorphous calcium carbonate with a micrometric lateral resolution [ 29 ]. Despite the advancements in analytical techniques, it is still challenging to achieve comprehensive spatially resolved insights into the "reaction products-calcite matrix" system. Synchrotron radiation (SR) micro-X-ray powder diffraction (µXRPD) mapping stands out as a powerful asset, as it can provide spatially resolved information about the crystallographic properties of the reaction products at a lateral resolution down to the submicrometric scales. This technique, when complemented with the elemental information of micro-X-ray fluorescence (µXRF) mapping, becomes particularly well-suited for the micro-analysis of highly heterogeneous systems, especially when the new phases are present in minor fractions if compared to the substrate's minerals or are poorly crystalline. This integrated approach, although common in CH materials, is predominant in the examination of oil paintings [ 23 , 30 – 32 ] and wall paintings [ 33 , 34 ], ceramics [ 35 – 37 ], paper [ 38 ], and metals [ 39 , 40 ], but, to the best of our knowledge, has not been employed yet to study the reaction products of inorganic consolidation solutions on porous carbonate stones in CH. In this paper, by building on what others have done in this field, we're also bringing something new to the table by addressing the challenges of dealing with more complicated systems. We explore the capabilities and limitations of this methodology approach combining SR-µXRPD and µXRF mapping in collecting comprehensive qualitative and quantitative information about the crystal-chemical compositions and spatial distribution of the newly formed phases (CaPs and CaOxs), resulting from the reaction of AmOx and DAP solutions on porous carbonate stones, to test its applicability and contribution in the ongoing knowledge related to stone conservation in Cultural Heritage. 2. Materials and Methods 2.1 Sample selection and preparation Noto Yellowish Limestone was selected as the primary substrate for our investigation. This type of porous limestone gained significance as a building material for the construction of Baroque monuments in the Val di Noto (south-eastern Sicily). Its composition predominantly consists of calcite, accompanied by minor fractions of clay minerals, quartz, and iron hydroxides. This stone offers an ideal context to investigate the reactions of carbonate components in a relatively straightforward system while still accounting for some degree of chemical heterogeneity. Notably, the stone exhibits a considerable open porosity ranging between 25% and 35%, making it even more susceptible to decay and enhancing capillarity ensuring feedback in the event of microstructural variations during the treatments. A tailored preparation method was devised to preserve crystalline phases and microstructural information. A thin section, of approximately 30 µm thickness, was prepared traversal (from the treated surface to the bulk) from each 5×5×2 cm³ treated limestone specimen. Embedding the sample in resin and adding a piece of polycarbonate to the section were essential steps to stabilize the thin section, during the follow-up cutting procedure. The thin sections were resized to a final size of 2 x 4 mm, to optimize the mounting space on the sample holders. Such preparation is compatible with the ID13 set-up allowing for optimal transmission of X-rays and a controlled and uniform probed voxel across the two-dimensional surface. To obtain a more objective assessment of the capabilities and limitations of the techniques employed, we subjected the limestone samples to various treatment protocols. This systematic approach allows us to assess the performance of our methodologies under different conditions. Two protocols encompassed the application of just one solution (either AmOx or DAP). Another one adopted the application of a sequential treatment (DAP followed by AmOx solution). The diverse treatments aim to replicate real-world situations encountered in the conservation of CH materials. Concentrations for DAP and AmOx as well as application methodology and condition were determined based on precedent experiments and established practices from conservation worksites. 2.2 Combined Micro X‑ray Fluorescence (µXRF) and Micro X‑ray Powder Diffraction (µXRPD) The combined Micro X‑ray fluorescence (µXRF) and Micro X‑ray Powder diffraction (µXRPD) investigations were conducted at the ID13 beamline at the European Synchrotron Radiation Facility (ESRF) in Grenoble (Fig. 1 a). The samples were mounted together on a 4mm diameter 12-hole holder as shown in Fig. 1 b. As illustrated in Fig. 1 c, the multi-hole sample holder was then mounted vertically, perpendicular to the X-ray beam. The µXRPD branch performed crystalline phase mapping using a 2.5×2.5 µm 2 beam with an energy of 13 keV. Throughout the thin section, regions of interest (ROIs) were systematically collected, commencing from the sample surface, and extending to approximately 1.2 mm (as illustrated in Fig. 1 d). Each ROI corresponds to a map of approximately 400 µm (horizontal) by 400 µm (vertical). This specific ROI size was chosen to strike a balance between achieving sufficient spatial detail and maintaining manageable data acquisition times. Considering the characteristics of the limestone samples, including potential variations in crystalline phases or microstructural features, the 400 µm by 400 µm ROI was deemed apt for capturing relevant information without the pitfalls of oversampling or undersampling. Two-dimensional (2D) diffraction patterns were acquired in transmission mode at every pixel of 2D maps using the graphical user interface (GUI) Daiquiri. These x-ray diffraction patterns were subsequently transformed into one-dimensional (1D) diffractograms through azimuthal integration, facilitated by Jupyter Notebooks based on the PyFAI software package [ 40 ]. Simultaneously, Micro X-ray Fluorescence (µXRF) spectra were obtained for the same map (Fig. 1 e), using a Vortex EM detector mounted orthogonally to the beam. 2.3 Data processing Data processing was an essential step in our study as the “reaction products - stone matrix” system exhibited Ca-baring elemental composition but with diverse crystalline phases in different locations and degrees of crystallinity. To investigate this complexity, we relied on the PyMca ROI imaging software [ 42 ], which enables simultaneous visualization of µXRPD and µXRF imaging data. This parallel processing workflow maximized the synergy of the two techniques, allowing us to not only visualize elemental composition but also directly identify crystalline phases and their location. The initial data processing step involved I/I 0 normalization of the intensity map pixels to rectify variations induced by the incoming X-ray beam. Figure 2 a shows an example of the false color appearance of the µXRF map before normalization, emphasizing the importance of this step to produce an accurate representation of elemental intensity ( in Fig. 2 b the elemental map after the normalization is shown). Afterward, the normalized µXRF map underwent a fitting process for specific elements composing our "reaction products-calcite matrix" system. The fitting process generated distribution maps for these elements, enabling effective comparisons of their presence and distribution. An illustrative example Fig. 2 c displays the elemental distribution map for calcium in one of the samples. Regarding the µXRPD imaging, the software displayed a correlated µXRPD pattern representing the averaged profile of all acquired patterns across the 2D map. Raw data preprocessing involved 1D background correction, addressing signals contributed by the amorphous polycarbonate layer in the sample preparation, which can make it more challenging to identify and analyze the diffraction peaks associated with the limestone system. This improvement in peak-to-background ratio facilitates more reliable peak identification, especially for weak or overlapping peaks, like in the case of the new crystalline phases. The exclusion of low-angle regions was done accurately to not result in the loss of important information associated with low angles, like some amorphous or poorly crystalline phases of CaPs and CaOxs. In Figs. 2 d and 2 e, the effect on µXRPD maps of the background correction process is shown. In the post-preprocessing, the identification of crystalline phases within µXRPD patterns, exported from PyMca, employed the HighScore Plus software. The analysis complemented the data processing using PyMca. Leveraging the strengths of PyMca, we conducted tailored data post-processing to address the diverse analytical inquiries arising in the study of the effects of inorganic treatments on carbonate stones. The subsequent post-processing methodologies will be described in the upcoming sections. PyMca's "RGB Correlator" tool was mainly used as it visually highlights distribution patterns of elements alongside crystalline phases, creating µXRPD and µXRF correlation maps. This capability proved indispensable in unraveling relationships between element distribution and identifying correlations or anticorrelations in calcium-based crystalline phases within a predominantly calcite matrix. Lastly, Image analysis, to obtain quantitative data, was done via the software Fiji Studio by thresholding techniques on phase-specific maps. This extracts quantitative measurements on the phase % distribution within a given area. Averages percentages and standard deviations were calculated to ensure meaningful results. 3 Results and Discussion Qualitative phase characterization of the "reaction products-calcite matrix" system First, the capability of combined µXRPD and µXRF imaging to characterize the different reaction products (CaOxs and CaPs), within the newly formed system in all treatment methodologies (single treatment and sequential treatments), was studied. Analysis of the maps’ average µXRPD patterns for all Noto Limestone samples analyzed, untreated, and treated were first conducted. The average diffraction patterns of the untreated limestone samples show predominantly the peaks associated with calcite, with occasional quartz. This trend remains consistent across treated samples' diffraction patterns, as illustrated in Fig. 3 . In these patterns, the main peaks of the reaction products were weak. This result aligns with prior literature and reflects how the reaction products of both solutions are in a low wt% fraction if compared to the abundant calcite matrix [ 47 ]. Focusing specifically on the reaction products from the AmOx solution (Fig. 4 a and b ), the CaOxs, low-intensity peaks appear in some surface-proximate diffraction patterns (as shown in Fig. 4 c), where the highest crystallization activity for these phases usually occurs, indicating their presence without definitive identification. The challenge in their identification arises due to the nano-crystalline nature of the main CaOx phases— whewellite (CaOx monohydrate) and weddellite (CaOx dihydrate)—together with their low fractions if compared to the calcite matrix [ 44 ]. Even with our high-resolution XRPD patterns, discerning these CaOxs in all patterns remains difficult. The sole examination of µXRF imaging does not facilitate their identification either, as CaOxs share a similar elemental composition to the calcite matrix (Ca, C, O). However, in the case of the AmOx-treated samples, the high-resolution µXRF Ca maps have shown, as seen in Fig. 4 d, low-intensity (~ 70–100 in the scale bar) and high-intensity areas (corresponding to ~ 170–250 in the scale bar). An unusually big gap in the intensity of Ca through the elemental map was here registered. These intensity variations throughout the Ca maps could, therefore, be correlated with different calcium contents in crystalline phases within our "reaction products-calcite matrix" system. Given that CaOxs contain less calcium (around 38% CaO) than calcite (approximately 55% CaO) [ 48 ], these intensity fluctuations in the elemental map could suggest a different distribution of oxalate and calcite phases within the stone system, corresponding respectively to the low and high-intensity area. Combining the µXRF maps with µXRPD data, we could generate area-specific average diffraction patterns by selecting pixels from areas exhibiting these calcium intensity variations. These patterns reveal peaks attributed to CaOxs with good resolution, as shown in Fig. 4 e. The area-specific diffraction pattern exhibited a high signal-to-noise ratio and a consistently flat baseline, which helps us confirm not only the crystallization but also facilitates the unambiguous identification of whewellite and weddellite. The situation becomes even more complex in the case of DAP-treatment samples (Fig. 4 f and g ). Like CaOxs, CaPs are nanometric-sized products and low in concentration [ 43 ]. Additionally, the complex reaction of DAP solutions with calcite does not yield only hydroxyapatite (HAP) but results in a mixture of by-products with varying Ca/P ratios in concentration distributed within the matrix based on reaction conditions [ 45 ]. These by-product phases share similarities in elemental composition and crystalline structure [ 46 ], making their phase identification even more complex. Consequently, map average diffraction patterns of DAP-treated samples lack identifiable peaks even in our diffraction patterns, as shown in Fig. 4 h, which hinders the confirmation of the presence of CaPs. Moving on to µXRF imaging, a situation like the AmOx-treated sample was observed in the elemental maps of calcium distribution in samples treated with DAP. This is coupled with localized high phosphorus intensities (Fig. 4 i). Given the known high Ca/P ratio in HAP (around 1.76), correlating calcium intensity variations with areas of high phosphorus concentration implies the potential CaP presence. Confirming this involves associating the µXRF imaging with the µXRPD data, generating area-specific diffraction patterns for pixels showing Ca/P elemental correlation. By generating specific diffraction patterns for these correlated areas, the identification of CaPs was achievable. The resulting diffraction patterns showed well-resolved HAP peaks that supported its visualization and identification. These patterns exhibit also good resolution at the low angular range where by-products of the reaction reside. The result is that this combined technique aids in identifying traditionally difficult-to-characterize [ 21 ] by-products such as octacalcium phosphate (OCP) and other CaP phases associated with HAP crystallization, such as Ammonium Dihydrogen Phosphate ADP, and carbonate-substituted HAP (C-HAP), as shown in Fig. 4 l, providing crucial information about the composition of the DAP "reaction products-calcite matrix" system. The combination of techniques proves effective for qualitative phase analysis of both CaOxs (whewellite and weddellite) and CaP (HAP and by-products), even in the more complex scenario of sequential treatment samples (DAP + AmOx). Despite the additional challenges posed here because of the simultaneous presence of CaOxs and CaPs, this approach facilitated the visualization and characterization of the newly crystallized phases (oxalate and phosphate) within the complex systems generated by these treatments, as shown in Fig. 5 . In the end, focusing solely on the average µXRPD pattern, the identification of reaction products was limited mainly because of their low concentration compared to the dominant calcite matrix. In contrast, examining µXRF data alone resulted challenging in samples lacking elemental markers for identifying CaOxs and could only hint at the crystallization of CaPs when the markers were present. Integrating both techniques enabled the production of area-specific diffraction patterns associated with those zones exhibiting calcium intensity variations or high Ca/P correlation, allowing for the identification of specific crystalline phases characteristic of the newly formed “reaction products-calcite matrix" system. Phases’ penetration depth and spatial distribution of the reaction products The combination of techniques used in this study yields an invaluable advantage in generating comprehensive µXRPD maps. Phase-specific distribution maps were generated by isolating distinct peaks associated with the identified crystalline phases in the diffraction patterns, providing detailed insight into the spatial distribution of each phase. SR-µXRPD mapping allows micrometric individual mapping of each reaction product distribution within the "reaction products-calcite matrix" systems, offering exceptional spatial resolution. Such data not only visualizes the penetration depth of the crystallization but also localizes where the chemical reactions take place. Our analysis consistently reveals phase-specific color maps accurately depicting the areal distribution of CaOxs and CaPs crystalline phases across all examined samples, without artifacts. In the context of AmOx-treated samples, the areal distribution data through RGB correlation maps reveals a distinct distribution pattern of CaOx phases: a gradient from the surface, with weddellite (WED) overlaying whewellite (WHE). This observation underscores the spatial relationship between these phases shown in Fig. 6 a. The data underscored a crystalline network following the solution diffusion path within the stone's microstructure, originating from the surface interface. These findings highlight the CaOx areal arrangement given by the treatment. Such data offer, for the first time, an opportunity to establish correlations between the phases of CaOx formed and their spatial distribution, allowing interpretations of the consolidation effect. Currently, literature only suggests that the distribution and penetration of distinct CaOxs significantly affect resultant system properties [ 49 ]. The application of µXRPD mapping of DAP reaction products has revealed unprecedented details regarding the areal distribution of CaP phases within the stone, particularly highlighting hydroxyapatite (HAP) and its associated by-products (ADP, OCP, and C-HAP). As shown in Fig. 6 b, HAP distribution follows a gradient from the surface, less homogeneous than the CaOxs network. The by-products, less identified in prior studies, exhibit a distribution pattern linked to HAP, extending to similar depths within the stone and localized in spots within its porous network. It is important to acknowledge that the representation of these CaP phases in the color maps might be subject to potential inaccuracies (either underestimated or overestimated) because of the mixture of phases within our systems. CaP peaks are collocated in the diffraction pattern close to the peaks of other phases complicating their isolation and mapping. Despite this, the ability to pinpoint the spatial distribution of both HAP and its by-products remains crucial. The literature already suggests correlations between the presence of these by-products, such as ADP indicating acidification, and changes in the stone's condition [ 10 ]. Therefore, having data on CaP distribution allows for a deeper exploration of these correlations, facilitating a better understanding of the localized effects of CaP phases on the stone's chemical changes and conditions. In the case of sequential treatment, the mapping of CaOxs and CaP phases, and the examination of phase coexistence through RGB correlation maps, highlight distinct variations in both penetration depth and areal distribution compared to single treatments. The data (Fig. 6 c) showed that, in sequential treatments, HAP and by-products are dispersed throughout the stone bulk rather than follow a gradient from the stone surface. CaOxs seemly exhibit different penetration depths compared to single treatments, although they are still primarily located on the surface. Additionally, the maps illustrate sparse areas of coexistence between CaOxs and CaPs. These observations strongly indicate interactions between the solutions’ reactions. The significance of obtaining these data lies in its capacity to shed light on these interactions, thereby enhancing our understanding of combining treatment effects on stone microstructures absent in the literature. Quantitative phase analysis and Orientation of the reaction products The high resolution of µXRPD maps also enables us to obtain information on quantitative phase concentration and orientation at the scale of the studied area (ROI = 400 x 400 µm²). Acquiring such data at this scale, with a clear view of the phases’ distribution, provides essential insights for assessing localized effects and evaluating treatment performance. Table 1 Quantitative Assessment of the Reaction Products Areal Amounts (Mean % ± Standard Deviation) on Surface Maps for Various Treatment Methodologies. Reaction Products WHE WED HAP C-HAP OCP ADP AmOx- treated 25.4 ∓ 2.71 1.54 ∓ 0.47 - - - - DAP-treated - - 22.2 ∓ 3.91 1.48 ∓ 0.61 7.62 ∓ 1.39 0.26 ∓ 0.13 DAP + AmOx treated 21.5 ∓ 3.47 2.76 ∓ 0.59 16.2 ∓ 2.17 1.16 ∓ 0.45 5.38 ∓ 1.72 0.51 ∓ 0.18 For quantitative assessment of newly crystallized reaction products, image analysis of phase-specific µXRPD maps was used to quantify the areal fraction of reaction product observed in the 2D map (shown in Table 1 ). In the case of AmOx-treated samples, this quantification confirmed existing literature by highlighting predominant whewellite crystallization, while uncovering unexpectedly high content of weddellite in some surface areas. Similarly, in samples treated with DAP solution, through quantitative evaluation, we categorized the main reaction products (HAP and OCP, 22.2% and 7.6%, respectively) as well as reaction by-products into minor (between 1% and 0.1%) and trace (less than 0.1%) products, based on their concentrations. The localized quantitative data derived from µXRPD map image analysis, of the sequentially treated samples, revealed that the % of crystallization of the reaction compounds is, generally, in line with the one in the single treatments. Additionally, µXRPD distribution maps are generated by selecting Bragg peaks of the crystalline phase. As each peak on the diffraction pattern corresponds to a specific set of crystallographic planes within the crystalline material, mapping a peak shows the areal distribution of a specific crystal plane. Correlation through RGB correlation of maps associated with different peaks of a single phase is here used to reveal the crystal orientation of the reaction products. Indeed, the lack of merging colors in the RGB correlation maps in specific areas was used to detect the crystal orientation of a selected crystalline plane. For instance, in the case of CaOxs (both whewellite and weddellite), they exhibit randomly distributed crystallites within the stone matrix, showing up as a single cohesive yellow color on the maps (Fig. 7 a). On the other hand, CaPs, primarily HAP, in DAP-treated samples show preferential orientations in some areas, as distinct green (HAP d 310 ) and red (HAP d 002 ) color distributions show up on the correlation maps (Fig. 7 b). This observation becomes particularly intriguing when studying sequential treatments where no significant orientation of CaPs can be detected (Fig. 7 c). Here the data show how CaPs crystallized differently. This proves an interaction between the solutions (the DAP-stone system is disturbed by the crystallization of CaOxs,) and the reactivity of the CaPs phases to be disturbed by the interaction. Overall, our experimental setup prioritized high spatial resolution and simultaneous µXRF and µXRPD acquisition, but this compromised the features of the collected X-ray diffraction patterns hindering, for example, a proper Rietveld analysis. The preclusion of Rietveld’s full-profile fit hinders any structural analysis of the crystalline phases, along with a phase quantification (in a multi-phase system) based on the refined scale factor of each crystalline component. However, this limitation is here efficiently overcome, as 1) the crystal structure of the co-present crystalline phases, in the system under investigation, is already well known and 2) the relative (areal) fraction of the crystalline components can be obtained through the µXRPD map analysis, along with their average crystallites orientation. In this light, the lack of the Rietveld full-profile fit does not diminish the description of the complex polycrystalline system under investigation and opens a new route for other scenarios in which the application of full-profile fit analysis is precluded. 4 Conclusion Our research effectively demonstrates how the synergy of µXRF and µXRPD at high resolution leads to an efficient characterization of the newly formed conservation products (CaOxs and CaPs), overcoming the analytical challenge of their low wt% concentration compared to the dominant calcite matrix. While µXRPD alone struggled, due to their low abundance, µXRF provided elemental data, leading to area-specific diffraction patterns, and ultimately enabling phase identification in complex multiphase mixtures. Moreover, these techniques provide invaluable insights into the penetration depth and spatial distribution of reaction products, enhancing our understanding of the treated stone system. The data derived from µXRPD mapping proved, for the first time, to be crucial in assessing reaction product concentrations. Additionally, orientation analysis of crystalline phases on the µXRPD maps offered a deeper understanding of phase formation and preferential orientations within the treated samples, and of the phase interaction in the case of sequential treatment. While acknowledging some limitations, mainly due to the need for micro-sampling, the combination of the techniques provided high-quality data on CH stone consolidation. Moreover, the obtained positive outcomes not only contribute to our fundamental understanding of these complex systems and inorganic mineral treatments but also underline their potential applications in further studies. In conclusion, this study underscores the significance of combining advanced synchrotron-based X-rays 2D mapping techniques for comprehensive and spatially resolved analyses of complex CH multiphase which broadens the applicability of these advanced synchrotron-based approaches in the study of inorganic mineral treatments in Conservation Science and Heritage Science. Declarations Competing interests The authors declare no competing interests. Correspondence and requests for materials should be addressed to G.M. Author Contribution All authors reviewed the manuscript. G.M., E.P., and N.M. wrote the main manuscript text. G.M. and M.B. performed the analysis and G.M., E.P., N.M., and C.C. interpreted the results. Preparation of Figures: N.M. and G.M. All authors (G.M., E.P., C.C., D.G., M.R., M.B., N.M.) assisted in the revision of the submitted manuscript. Acknowledgments For the beamtime received, thanks are expressed to the European Synchrotron Radiation Facility ID13 beamline ( https://doi.org/10.15151/ESRF-ES-981402187 ). The authors also acknowledge the TS Lab & Geoservice snc (Pisa, Italy) for developing an ad hoc effective protocol to prepare polished thin sections suitable for the investigations. Funding for this research was provided by the Italian Ministry of Education (MIUR) (PRIN2017 - Mineral reactivity, a key to understand large-scale processes: award No. 2017 L83S77) and "Dipartimenti di Eccellenza 2023–2027 – “Le Georisorse per la transizione ecologica e lo sviluppo territoriale" References Sena da Fonseca, B. (2023). Current Trends in Stone Consolidation Research: An Overview and Discussion. Buildings, 13(2), 403. Giorgi, R., Baglioni, M., Berti, D. & Baglioni, P. New methodologies for the conservation of cultural heritage: Micellar solutions, microemulsions, and hydroxide nanoparticles. Acc. Chem. 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Investigation of Calcium and Magnesium Phosphate Crystals in Stones Treated with Diammonium Hydrogen Phosphate Conservation Product: Potential of Micro-Raman Spectroscopy. Crystals, 13(8), 1212. Calore, N., Botteon, A., Colombo, C., Comunian, A., Possenti, E., Realini, M., … Conti,C. (2018). High Resolution ATR µ-FTIR to map the diffusion of conservation treatments applied to painted plasters.Vibrational Spectroscopy, 98, 105–110. Cotte, M.; Genty-Vincent, A.; Janssens, K.; Susini, J. Applications of synchrotron X-ray nano-probes in the field of cultural heritage. Cr. Phys. 2018, 19, 575–588. Bertrand, L., Cotte, M., Stampanoni, M., Thoury, M., Marone, F., & Schöder, S. (2012). Development and trends in synchrotron studies of ancient and historical materials. Physics Reports, 519(2), 51–96. Janssens, K., Van der Snickt, G., Vanmeert, F., Legrand, S., Nuyts, G., Alfeld, M.,… De Wael, K. (2017). 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Construction and Building Materials, 397, 132348. Conti, C., Colombo, C., Festa, G., Hovind, J., Cippo, E. P., Possenti, E., & Realini, M. (2016). Investigation of ammonium oxalate diffusion in carbonatic substrates by neutron tomography. Journal of Cultural Heritage, 19, 463–466. Realini, M., Colombo, C., Conti, C., Grazzi, F., Perelli Cippo, E., & Hovind, J. (2017). Development of neutron imaging quantitative data treatment to assess conservation products in cultural heritage. Analytical and bioanalytical chemistry, 409, 6133–6139. Possenti, E., Conti, C., Gatta, G. D., Marinoni, N., Merlini, M., Realini, M., … Colombo,C. (2022). Synchrotron X-ray diffraction computed tomography to non-destructively study inorganic treatments for stone conservation. Iscience, 25(10). Monico, L., Cartechini, L., Rosi, F., De Nolf, W., Cotte, M., Vivani, R., … Miliani,C. (2020). Synchrotron radiation Ca K-edge 2D-XANES spectroscopy for studying the stratigraphic distribution of calcium-based consolidants applied in limestones. Scientific Reports, 10(1), 14337. Ghirardello, Marta, et al. "Application of Synchrotron Radiation-Based Micro-Analysis on Cadmium Yellows in Pablo Picasso's Femme." Microscopy and Microanalysis 28.5 (2022): 1504–1513. de Mecquenem, C., Eveno, M., Alfeld, M., Pillay, R., Laval, E., Ravaud, E., & Reiche, I. (2023). A multimodal study of smalt preservation and degradation on the painting "Woman doing a Libation or Artemisia" from an anonymous painter of the Fontainebleau School. The European Physical Journal Plus, 138(2), 1–8. Gonzalez, V., Fazlic, I., Cotte, M., Vanmeert, F., Gestels, A., De Meyer, S., … Keune,K. (2023). Lead (II) Formate in Rembrandt's Night Watch: Detection and Distribution from the Macro‚Äêto the Micro‚Äêscale. Angewandte Chemie, 135(16), e202216478. Avranovich Clerici, E., de Meyer, S., Vanmeert, F., Legrand, S., Monico, L., Miliani, C., & Janssens, K. (2023). Multi-Scale X-ray Imaging of the Pigment Discoloration Processes Triggered by Chlorine Compounds in the Upper Basilica of Saint Francis of Assisi. Molecules, 28(16), 6106. Oriols, N., Salvadó, N., Pradell, T., Jiménez, N., Cotte, M., Gonzalez, V., & Butí, S. (2022). Carbonation of fresco mural paintings with a dolomitic mortar. Cement and Concrete Research, 157, 106828. Sciau, P., Goudeau, P., Tamura, N., & Dooryhee, E. (2006). Micro scanning X-ray diffraction study of Gallo-Roman Terra Sigillata ceramics. Applied Physics A, 83, 219–224. Leon, Y., Sciau, P., Goudeau, P., Tamura, N., Webb, S., & Mehta, A. (2010). The nature of marbled Terra Sigillata slips a combined µXRF and µXRD investigation. Applied Physics A, 99, 419–425 Wang, T., Zhu, T. Q., Feng, Z. Y., Fayard, B., Pouyet, E., Cotte, M., … Sciau, P.(2016). Synchrotron radiation-based multi-analytical approach for studying underglaze color: The microstructure of Chinese Qinghua blue decors (Ming dynasty). Analytica Chimica Acta, 928, 20–31. Guarnieri, N., Ghirardello, M., Goidanich, S., Comelli, D., Dellasega, D., Cotte,M., … Toniolo, L. (2023). Imaging and micro-invasive analyses of black stains on the passepartout of Codex Atlanticus Folio 843 by Leonardo da Vinci. Scientific Reports,13(1), 4902. Kergourlay, Florian, et al. "Stabilization treatment of cultural heritage artifacts: In situ monitoring of marine iron objects dechlorinated in alkali solution." Corrosion Science 132 (2018): 21–34. Grousset, Sophie, et al. "In situ monitoring of corrosion processes by coupled micro-XRF/micro-XRD mapping to understand the degradation mechanisms of reinforcing bars in hydraulic binders from historic monuments." Journal of Analytical Atomic Spectrometry 30.3 (2015): 721–729. Ševčík, R., Viani, A., Machová, D., Lanzafame, G., Mancini, L., & Appavou, M. S. (2019). Synthetic calcium carbonate improves the effectiveness of treatments with nanolime to contrast decay in highly porous limestone. Scientific reports, 9(1), 15278. Kieffer, J.; Valls, V.; Blanc, N.; Hennig, C. New tools for calibrating diffraction setups. J. Synchrotron Radiat. 2020, 27, 558–566. Possenti, E., Conti, C., Gatta, G. D., Realini, M., & Colombo, C. (2019). Diammonium hydrogenphosphate treatment on dolostone: the role of Mg in the crystallization process. Coatings, 9(3), 169. Conti, C., Colombo, C., Dellasega, D., Matteini, M., Realini, M., & Zerbi, G. (2011). Ammonium oxalate treatment: evaluation by µ-Raman mapping of the penetration depth in different plasters. Journal of cultural heritage, 12(4), 372–379. Suzuki, O., Shiwaku, Y., & Hamai, R. (2020). Octacalcium phosphate bone substitute materials: Comparison between properties of biomaterials and other calcium phosphate materials. Dental materials journal, 39(2), 187–199. Dorozhkin, S. V. (2007). Calcium orthophosphates. Journal of materials science, 42(4), 1061–1095. Conti, C., Cutard, L., Botteon, A., Brambilla, L., Marinoni, N., Realini, M., … Colombo,C. (2023). Investigation of Calcium and Magnesium Phosphate Crystals in Stones Treated with Diammonium Hydrogen Phosphate Conservation Product: Potential of Micro-Raman Spectroscopy. Crystals, 13(8), 1212. Conti, C., Casati, M., Colombo, C., Possenti, E., Realini, M., Gatta, G. D., … Zerbi,G. (2015). Synthesis of calcium oxalate trihydrate: New data by vibrational spectroscopy and synchrotron X-ray diffraction. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 150, 721–730. Possenti, E., Conti, C., Gatta, G. D., Realini, M., & Colombo, C. (2019). Diammonium hydrogenphosphate treatment on dolostone: the role of Mg in the crystallization process. Coatings, 9(3), 169. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Apr, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 Feb, 2024 Reviews received at journal 22 Feb, 2024 Reviewers agreed at journal 19 Feb, 2024 Reviewers agreed at journal 15 Feb, 2024 Reviewers invited by journal 15 Feb, 2024 Editor assigned by journal 15 Feb, 2024 Editor invited by journal 12 Feb, 2024 Submission checks completed at journal 12 Feb, 2024 First submitted to journal 02 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3921021","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":272454808,"identity":"acd1d6a8-4921-488f-a428-cde61399bfa4","order_by":0,"name":"Giulia Massinelli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIie3QMUsDMRTA8ScHcXlX13cozVdIl9qhux/CJbc4XaCTOBQJFOpm1076FexycyDQWwpdO97h6iaILsVcbUXopV0d8p/CJb/LuwMIhf5jEZwYuV0bgN4FO9UAEgiYn8BfQsjQbInXbE7+Rgi0e4OH8CsUphzC9dmkqOzgjrCVvHXLKutBi+tG0rGOyDmo6SoTdrpwg51nlyLN/YN1RjVhoPQKwcbjDenScbIG9bwsShuvHUkWhwmPHEnHoF6MFDbWjhAeJiJiA5M+kprV34Lz+iff3NYEGZONhE/srPr86KunZfH6jsN+mz/YPPnK79t8ZJpv+XlM+zvYPJa7Rft2QqFQKLTrG/lZUyFb8PfuAAAAAElFTkSuQmCC","orcid":"","institution":"Università degli Studi di Milano","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Massinelli","suffix":""},{"id":272454809,"identity":"ace3ebdf-f8e1-4e35-b937-bbc07541b7a5","order_by":1,"name":"Nicoletta Marinoni","email":"","orcid":"","institution":"Università degli Studi di Milano","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nicoletta","middleName":"","lastName":"Marinoni","suffix":""},{"id":272454810,"identity":"3f69ea64-c73c-4361-adaf-83f405f2d0c9","order_by":2,"name":"Chiara Colombo","email":"","orcid":"","institution":"Istituto di Scienze del Patrimonio Culturale (ISPC), Consiglio Nazionale delle Ricerche (CNR)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chiara","middleName":"","lastName":"Colombo","suffix":""},{"id":272454811,"identity":"cc22af33-1be5-4097-b00d-c1239097a8b8","order_by":3,"name":"Giacomo Diego Gatta","email":"","orcid":"","institution":"Università degli Studi di Milano","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Giacomo","middleName":"Diego","lastName":"Gatta","suffix":""},{"id":272454812,"identity":"4c107cd0-4bf8-4f69-95d3-3b1c65bd11eb","order_by":4,"name":"Marco Realini","email":"","orcid":"","institution":"Istituto di Scienze del Patrimonio Culturale (ISPC), Consiglio Nazionale delle Ricerche (CNR)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marco","middleName":"","lastName":"Realini","suffix":""},{"id":272454813,"identity":"d84c3724-5807-4ccf-93d4-4cf84fd9b246","order_by":5,"name":"Manfred Burghammer","email":"","orcid":"","institution":"European Synchtron Radiation Facility","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Manfred","middleName":"","lastName":"Burghammer","suffix":""},{"id":272454814,"identity":"6227cd13-c823-4707-a738-ba73ed412d83","order_by":6,"name":"Elena Possenti","email":"","orcid":"","institution":"Istituto di Scienze del Patrimonio Culturale (ISPC), Consiglio Nazionale delle Ricerche (CNR)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Elena","middleName":"","lastName":"Possenti","suffix":""}],"badges":[],"createdAt":"2024-02-02 13:30:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3921021/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3921021/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-58718-z","type":"published","date":"2024-04-20T22:39:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":51135383,"identity":"dec0adbd-4e33-4c1f-9ca1-88101e885f34","added_by":"auto","created_at":"2024-02-14 18:29:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5970780,"visible":true,"origin":"","legend":"\u003cp\u003e(a) SR-µXRPD scanning and µXRF set-up at ID13 beamline, ESRF, (b) focus of the sample holder, (c) some of the analyzed thin section (2 x 4 mm) mounted on the 4mm diameter 12-hole holder and (d) Schematic illustration of μXRPD mapping and μXRF experiment on Noto limestone thin section. (e) µXRD patterns and µXRF spectra were acquired at each pixel of an area of 400 μm (horizontal) by 400 μm (vertical) defined over the sample surface.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/c4a406de82d2842743250524.jpg"},{"id":51135368,"identity":"365704f0-5148-4d93-b081-bf2ac990d388","added_by":"auto","created_at":"2024-02-14 18:29:16","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7990634,"visible":true,"origin":"","legend":"\u003cp\u003eData processing on the PyMca ROI imaging software of one of the samples. (a) Original μXRF map of an ROI; (b) I/I\u003csub\u003e0\u003c/sub\u003e normalization of the μXRF map; (c) RGB correlation of the elemental distribution maps of calcium, iron, and magnesium; (d) Original μXRPD map of the same ROI and (e) μXRPD map after the 1D background correction.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/96be07e100ac79b6b16e7788.jpg"},{"id":51135378,"identity":"bdfd2801-0252-464c-bb97-122c2cc291f7","added_by":"auto","created_at":"2024-02-14 18:29:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4137541,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Average μXRPD patterns extracted from representative surface maps of an untreated Noto limestone sample (NT) and three samples treated by AmOx, DAP, and DAP+AmOx; (b) A zoom (position ~ 8-20 2Theta) to highlight the marker peaks of calcite (CAL) and quartz (QTZ).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/63ad04b5da8f4520d02f9625.jpg"},{"id":51135379,"identity":"232442f3-c4f3-449a-a759-0edeacfd1ccf","added_by":"auto","created_at":"2024-02-14 18:29:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4918609,"visible":true,"origin":"","legend":"\u003cp\u003eComparison between single treated samples. For the AmOx treated: (a) Optical image of the cross-section. Selection of the investigated ROI (green) and the investigated pixels (red);(b) Representative average surface μXRF map of the ROI; (c) Map average μXRPD pattern extracted from the ROI; (d) Elemental map of calcium showing variation in intensity; (e) Area-specific average μXRPD pattern for the red area exhibiting low Ca intensity. A zoom of the diffraction patterns (position ~ 8-20 2Theta) is shown to highlight the marker peaks whewellite (WHE) and weddellite (WED). For the DAP treated: (e) Optical image of the cross-section. Selection of the investigated ROI (green) and the investigated pixels (red); (b) Representative surface μXRF map of the ROI; (c) Map average μXRPD pattern extracted from the ROI (d) RGB correlation map of the elemental distribution of calcium (blue) and phosphorous (red); (e) Area-specific average μXRPD pattern for the red area exhibiting correlation Ca/P. The patterns are presented in a zoom (position ~ 16-25 2Theta) to highlight the marker peaks hydroxyapatite (HAP), Ammonium Hydrogen Phosphate (ADP), and carbonate-substituted HAP (C-HAP).\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/9cf4f34773ea62d2b3cf72f4.jpg"},{"id":51135380,"identity":"0787465a-fdb9-4cd6-ac71-ceaa8e3e7529","added_by":"auto","created_at":"2024-02-14 18:29:19","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5001468,"visible":true,"origin":"","legend":"\u003cp\u003eDAP+AmOx treated Noto Limestone sample (a) Optical image of the cross-section. Selection of the investigated ROI (blue) and the investigated pixels (red); (b) Area-specific average μXRPD pattern for the red area and a zoom (position ~ 8-21 2Theta) to highlight the marker peaks hydroxyapatite (HAP), whewellite (WHE), and weddellite (WED).\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/0d60c7931299e80a7bad8100.jpg"},{"id":51135375,"identity":"d71a36a9-634f-4804-8952-18d7d068f8fc","added_by":"auto","created_at":"2024-02-14 18:29:18","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":6139632,"visible":true,"origin":"","legend":"\u003cp\u003e(a) RGB correlation of the μXRPD areal distribution maps of whewellite (WHE) and weddellite (WED) in an AmOx-treated sample; (b) RGB correlation of the μXRPD areal distribution maps of the marker peaks of identified HAP and by-products (ADP and OCP) in a DAP-treated sample; (c) RGB correlation of the μXRPD areal distribution maps the main CaOxs (whewellite and weddellite) and CaPs (hydroxyapatite) in a DAP+AmOx treated sample. All three figures are an ROI of 400 x 400 μm² taken from the surface of the samples.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/35d046b8806edbecbfcc780f.jpg"},{"id":51135374,"identity":"2a837b6a-4a7b-4fad-bdea-edfeef4ef1e6","added_by":"auto","created_at":"2024-02-14 18:29:17","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":6188564,"visible":true,"origin":"","legend":"\u003cp\u003e(a) RGB correlation of the μXRPD areal distribution maps of two marker peaks of whewellite in an AmOx-treated sample; (b) RGB correlation of the μXRPD areal distribution maps of two marker peaks of hydroxyapatite in a DAP-treated sample; (c) RGB correlation of the μXRPD areal distribution maps of two marker peaks of hydroxyapatite in a DAP+AmOx treated sample.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/a38ca50b1a5dc0f81d3ca086.jpg"},{"id":55690379,"identity":"03c805c3-a6b0-4aea-b188-8eb4fcd8ddaa","added_by":"auto","created_at":"2024-05-01 22:39:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1206184,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3921021/v1/5ebc5fd5-69ed-40d9-9b13-2db689cac18f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAdvanced Mapping of Inorganic Treatments on Porous Carbonate Stones by Combined Synchrotron Radiation High Lateral μXRPD and μXRF\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStone consolidation is one of the major challenges when dealing with buildings and stone artifacts belonging to Cultural Heritage (CH), which usually suffer from the decohesion of materials due to the decay process [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Since the mid-1990s, several inorganic treatments have been developed to address this issue, aiming at restoring adhesion and cohesion to damaged carbonate stones [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and partially transforming the original matrix minerals into newly formed crystalline phases [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn such context, over the past two decades, inorganic mineral treatments based on ammonium oxalate ((NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e, AmOx) and di-ammonium phosphate ((NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, DAP) solutions have gained prominence for carbonate stones [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These water-soluble salts react with the carbonate matrix of the stone substrate to produce sub-micrometric reaction products [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Specifically, AmOx primarily produces Ca-oxalate (CaOxs) while DAP's reaction should ideally yield calcium phosphate phases (CaPs). Oxalate phases exhibit limited penetration into the stone (~\u0026thinsp;1 mm) whereas DAP-based treatments offer greater consolidating capabilities in terms of treatment penetration (2\u0026ndash;8 mm, depending on the stone substrate) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, inorganic mineral treatments exhibit significant variability in terms of the newly formed phases within the treated stone materials and their effect on the stone microstructure. Factors such as their crystal-chemical composition, crystallinity, penetration, and distribution are influenced by a series of interrelated variables playing during the solution reaction with the calcite matrix (i.e., solution molarity, treatment methodology, etc.) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Consequently, studying the outcome of the reaction process, specifically the new \"reaction products-calcite matrix\" system, presents a significant challenge. Despite this complexity, understanding the modifications induced by inorganic treatments is crucial, given that the physical, chemical, and microstructural properties of the new system significantly impact the macroscopic interaction of the building stone with the agents of decay. The complexity of studying these transformations becomes particularly pronounced in the case of reaction products that share a similar elemental composition to those of the carbonate stone substrate, like in the case of CaOxs formed by AmOx solutions, or in the case of complex reaction kinetics in the presence of carbonate ions that result in not stoichiometric reaction. Examples of this last scenario are CaPs phases formed with DAP solutions, which ideally should yield crystalline hydroxyapatite (HAP, Ca\u003csub\u003e10\u003c/sub\u003e(PO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e6\u003c/sub\u003e(OH)\u003csub\u003e2\u003c/sub\u003e), however, the result is complex mixtures of crystalline and poorly crystalline phosphate phases [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn accordance, a range of analytical techniques has been employed tailored to characterize carbonate stone treated with inorganic mineral treatments and gain insights into the composition and penetration depth of the newly formed phases to assert their performance. Conventional methods such as SEM-EDX, XRD, and FT-IR have been widely used but lack the specificity and lateral resolution required for characterizing phases with different degrees of crystallinity, in addition to being invasive (as many of their experimental setups require a sample) or, in some cases destructive (i.e., with a complex sample preparation) [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. High lateral resolution micro-spectroscopy techniques, like \u0026micro;-ATR-FTIR and \u0026micro;-Raman mapping or spectroscopic imaging, have proven valuable for probing the spatial distribution of consolidants, providing complementary structural and compositional insights on the newly formed phases [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, these techniques may face challenges in distinguishing the newly formed phases within the microstructure due to overlapping vibrational bands. More recently, synchrotron radiation (SR) facilities have experienced a remarkable rise in the study of Cultural Heritage materials [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Advanced radiation imaging techniques, such as SR-based X-ray micro-computed tomography (\u0026micro;-CT), have been employed to non-invasively determine the effects of the new product crystallization on the 3D stone\u0026rsquo;s microstructure at a maximum voxel size of 1 \u0026micro;m\u003csup\u003e3\u003c/sup\u003e. However, no chemical information is provided [\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Moreover, micro-X-ray powder diffraction tomography (XRDCT) measurements allow structural characterization and 3D localization of the reaction products, but the highly heterogeneous systems may result in very big and complex XRDCT datasets and data interpretation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Lastly, more, recently, SR-based spectroscopy techniques such as Ca K-edge 2D X-ray absorption near-edge structure (XANES) with \u0026micro;-XRF mapping have been successfully employed to spatially distinguish among amorphous calcium carbonate with a micrometric lateral resolution [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDespite the advancements in analytical techniques, it is still challenging to achieve comprehensive spatially resolved insights into the \"reaction products-calcite matrix\" system. Synchrotron radiation (SR) micro-X-ray powder diffraction (\u0026micro;XRPD) mapping stands out as a powerful asset, as it can provide spatially resolved information about the crystallographic properties of the reaction products at a lateral resolution down to the submicrometric scales. This technique, when complemented with the elemental information of micro-X-ray fluorescence (\u0026micro;XRF) mapping, becomes particularly well-suited for the micro-analysis of highly heterogeneous systems, especially when the new phases are present in minor fractions if compared to the substrate's minerals or are poorly crystalline. This integrated approach, although common in CH materials, is predominant in the examination of oil paintings [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and wall paintings [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], ceramics [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], paper [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and metals [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], but, to the best of our knowledge, has not been employed yet to study the reaction products of inorganic consolidation solutions on porous carbonate stones in CH.\u003c/p\u003e\u003cp\u003eIn this paper, by building on what others have done in this field, we're also bringing something new to the table by addressing the challenges of dealing with more complicated systems. We explore the capabilities and limitations of this methodology approach combining SR-\u0026micro;XRPD and \u0026micro;XRF mapping in collecting comprehensive qualitative and quantitative information about the crystal-chemical compositions and spatial distribution of the newly formed phases (CaPs and CaOxs), resulting from the reaction of AmOx and DAP solutions on porous carbonate stones, to test its applicability and contribution in the ongoing knowledge related to stone conservation in Cultural Heritage.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Sample selection and preparation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eNoto Yellowish Limestone was selected as the primary substrate for our investigation. This type of porous limestone gained significance as a building material for the construction of Baroque monuments in the Val di Noto (south-eastern Sicily). Its composition predominantly consists of calcite, accompanied by minor fractions of clay minerals, quartz, and iron hydroxides. This stone offers an ideal context to investigate the reactions of carbonate components in a relatively straightforward system while still accounting for some degree of chemical heterogeneity. Notably, the stone exhibits a considerable open porosity ranging between 25% and 35%, making it even more susceptible to decay and enhancing capillarity ensuring feedback in the event of microstructural variations during the treatments.\u003c/p\u003e \u003cp\u003eA tailored preparation method was devised to preserve crystalline phases and microstructural information. A thin section, of approximately 30 \u0026micro;m thickness, was prepared traversal (from the treated surface to the bulk) from each 5\u0026times;5\u0026times;2 cm\u0026sup3; treated limestone specimen. Embedding the sample in resin and adding a piece of polycarbonate to the section were essential steps to stabilize the thin section, during the follow-up cutting procedure. The thin sections were resized to a final size of 2 x 4 mm, to optimize the mounting space on the sample holders. Such preparation is compatible with the ID13 set-up allowing for optimal transmission of X-rays and a controlled and uniform probed voxel across the two-dimensional surface.\u003c/p\u003e \u003cp\u003eTo obtain a more objective assessment of the capabilities and limitations of the techniques employed, we subjected the limestone samples to various treatment protocols. This systematic approach allows us to assess the performance of our methodologies under different conditions. Two protocols encompassed the application of just one solution (either AmOx or DAP). Another one adopted the application of a sequential treatment (DAP followed by AmOx solution). The diverse treatments aim to replicate real-world situations encountered in the conservation of CH materials. Concentrations for DAP and AmOx as well as application methodology and condition were determined based on precedent experiments and established practices from conservation worksites.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Combined Micro X‑ray Fluorescence (\u0026micro;XRF) and Micro X‑ray Powder Diffraction (\u0026micro;XRPD)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe combined Micro X‑ray fluorescence (\u0026micro;XRF) and Micro X‑ray Powder diffraction (\u0026micro;XRPD) investigations were conducted at the ID13 beamline at the European Synchrotron Radiation Facility (ESRF) in Grenoble (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The samples were mounted together on a 4mm diameter 12-hole holder as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, the multi-hole sample holder was then mounted vertically, perpendicular to the X-ray beam. The \u0026micro;XRPD branch performed crystalline phase mapping using a 2.5\u0026times;2.5 \u0026micro;m\u003csup\u003e2\u003c/sup\u003e beam with an energy of 13 keV. Throughout the thin section, regions of interest (ROIs) were systematically collected, commencing from the sample surface, and extending to approximately 1.2 mm (as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Each ROI corresponds to a map of approximately 400 \u0026micro;m (horizontal) by 400 \u0026micro;m (vertical). This specific ROI size was chosen to strike a balance between achieving sufficient spatial detail and maintaining manageable data acquisition times. Considering the characteristics of the limestone samples, including potential variations in crystalline phases or microstructural features, the 400 \u0026micro;m by 400 \u0026micro;m ROI was deemed apt for capturing relevant information without the pitfalls of oversampling or undersampling. Two-dimensional (2D) diffraction patterns were acquired in transmission mode at every pixel of 2D maps using the graphical user interface (GUI) Daiquiri. These x-ray diffraction patterns were subsequently transformed into one-dimensional (1D) diffractograms through azimuthal integration, facilitated by Jupyter Notebooks based on the PyFAI software package [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Simultaneously, Micro X-ray Fluorescence (\u0026micro;XRF) spectra were obtained for the same map (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee), using a Vortex EM detector mounted orthogonally to the beam.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data processing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eData processing was an essential step in our study as the \u0026ldquo;reaction products - stone matrix\u0026rdquo; system exhibited Ca-baring elemental composition but with diverse crystalline phases in different locations and degrees of crystallinity. To investigate this complexity, we relied on the PyMca ROI imaging software [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], which enables simultaneous visualization of \u0026micro;XRPD and \u0026micro;XRF imaging data. This parallel processing workflow maximized the synergy of the two techniques, allowing us to not only visualize elemental composition but also directly identify crystalline phases and their location.\u003c/p\u003e \u003cp\u003eThe initial data processing step involved I/I\u003csub\u003e0\u003c/sub\u003e normalization of the intensity map pixels to rectify variations induced by the incoming X-ray beam. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea shows an example of the false color appearance of the \u0026micro;XRF map before normalization, emphasizing the importance of this step to produce an accurate representation of elemental intensity (\u003cem\u003ein\u003c/em\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb the elemental map after the normalization is shown).\u003c/p\u003e \u003cp\u003eAfterward, the normalized \u0026micro;XRF map underwent a fitting process for specific elements composing our \"reaction products-calcite matrix\" system. The fitting process generated distribution maps for these elements, enabling effective comparisons of their presence and distribution. An illustrative example Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec displays the elemental distribution map for calcium in one of the samples.\u003c/p\u003e \u003cp\u003eRegarding the \u0026micro;XRPD imaging, the software displayed a correlated \u0026micro;XRPD pattern representing the averaged profile of all acquired patterns across the 2D map. Raw data preprocessing involved 1D background correction, addressing signals contributed by the amorphous polycarbonate layer in the sample preparation, which can make it more challenging to identify and analyze the diffraction peaks associated with the limestone system. This improvement in peak-to-background ratio facilitates more reliable peak identification, especially for weak or overlapping peaks, like in the case of the new crystalline phases. The exclusion of low-angle regions was done accurately to not result in the loss of important information associated with low angles, like some amorphous or poorly crystalline phases of CaPs and CaOxs. In Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, the effect on \u0026micro;XRPD maps of the background correction process is shown.\u003c/p\u003e \u003cp\u003eIn the post-preprocessing, the identification of crystalline phases within \u0026micro;XRPD patterns, exported from PyMca, employed the HighScore Plus software. The analysis complemented the data processing using PyMca. Leveraging the strengths of PyMca, we conducted tailored data post-processing to address the diverse analytical inquiries arising in the study of the effects of inorganic treatments on carbonate stones. The subsequent post-processing methodologies will be described in the upcoming sections.\u003c/p\u003e \u003cp\u003ePyMca's \"RGB Correlator\" tool was mainly used as it visually highlights distribution patterns of elements alongside crystalline phases, creating \u0026micro;XRPD and \u0026micro;XRF correlation maps. This capability proved indispensable in unraveling relationships between element distribution and identifying correlations or anticorrelations in calcium-based crystalline phases within a predominantly calcite matrix.\u003c/p\u003e \u003cp\u003eLastly, Image analysis, to obtain quantitative data, was done via the software Fiji Studio by thresholding techniques on \u003cem\u003ephase-specific\u003c/em\u003e maps. This extracts quantitative measurements on the phase % distribution within a given area. Averages percentages and standard deviations were calculated to ensure meaningful results.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results and Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eQualitative phase characterization of the \"reaction products-calcite matrix\" system\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFirst, the capability of combined \u0026micro;XRPD and \u0026micro;XRF imaging to characterize the different reaction products (CaOxs and CaPs), within the newly formed system in all treatment methodologies (single treatment and sequential treatments), was studied.\u003c/p\u003e \u003cp\u003eAnalysis of the maps\u0026rsquo; average \u0026micro;XRPD patterns for all Noto Limestone samples analyzed, untreated, and treated were first conducted. The average diffraction patterns of the untreated limestone samples show predominantly the peaks associated with calcite, with occasional quartz. This trend remains consistent across treated samples' diffraction patterns, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In these patterns, the main peaks of the reaction products were weak. This result aligns with prior literature and reflects how the reaction products of both solutions are in a low wt% fraction if compared to the abundant calcite matrix [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFocusing specifically on the reaction products from the AmOx solution (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea \u003cem\u003eand b\u003c/em\u003e), the CaOxs, low-intensity peaks appear in some surface-proximate diffraction patterns (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), where the highest crystallization activity for these phases usually occurs, indicating their presence without definitive identification. The challenge in their identification arises due to the nano-crystalline nature of the main CaOx phases\u0026mdash; whewellite (CaOx monohydrate) and weddellite (CaOx dihydrate)\u0026mdash;together with their low fractions if compared to the calcite matrix [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Even with our high-resolution XRPD patterns, discerning these CaOxs in all patterns remains difficult.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe sole examination of \u0026micro;XRF imaging does not facilitate their identification either, as CaOxs share a similar elemental composition to the calcite matrix (Ca, C, O). However, in the case of the AmOx-treated samples, the high-resolution \u0026micro;XRF Ca maps have shown, as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, low-intensity (~\u0026thinsp;70\u0026ndash;100 in the scale bar) and high-intensity areas (corresponding to ~\u0026thinsp;170\u0026ndash;250 in the scale bar). An unusually big gap in the intensity of Ca through the elemental map was here registered. These intensity variations throughout the Ca maps could, therefore, be correlated with different calcium contents in crystalline phases within our \"reaction products-calcite matrix\" system. Given that CaOxs contain less calcium (around 38% CaO) than calcite (approximately 55% CaO) [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], these intensity fluctuations in the elemental map could suggest a different distribution of oxalate and calcite phases within the stone system, corresponding respectively to the low and high-intensity area.\u003c/p\u003e \u003cp\u003eCombining the \u0026micro;XRF maps with \u0026micro;XRPD data, we could generate \u003cem\u003earea-specific\u003c/em\u003e average diffraction patterns by selecting pixels from areas exhibiting these calcium intensity variations. These patterns reveal peaks attributed to CaOxs with good resolution, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee. The \u003cem\u003earea-specific\u003c/em\u003e diffraction pattern exhibited a high signal-to-noise ratio and a consistently flat baseline, which helps us confirm not only the crystallization but also facilitates the unambiguous identification of whewellite and weddellite.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe situation becomes even more complex in the case of DAP-treatment samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef \u003cem\u003eand g\u003c/em\u003e). Like CaOxs, CaPs are nanometric-sized products and low in concentration [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Additionally, the complex reaction of DAP solutions with calcite does not yield only hydroxyapatite (HAP) but results in a mixture of by-products with varying Ca/P ratios in concentration distributed within the matrix based on reaction conditions [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. These by-product phases share similarities in elemental composition and crystalline structure [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], making their phase identification even more complex. Consequently, map average diffraction patterns of DAP-treated samples lack identifiable peaks even in our diffraction patterns, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eh, which hinders the confirmation of the presence of CaPs.\u003c/p\u003e \u003cp\u003eMoving on to \u0026micro;XRF imaging, a situation like the AmOx-treated sample was observed in the elemental maps of calcium distribution in samples treated with DAP. This is coupled with localized high phosphorus intensities (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei). Given the known high Ca/P ratio in HAP (around 1.76), correlating calcium intensity variations with areas of high phosphorus concentration implies the potential CaP presence. Confirming this involves associating the \u0026micro;XRF imaging with the \u0026micro;XRPD data, generating \u003cem\u003earea-specific\u003c/em\u003e diffraction patterns for pixels showing Ca/P elemental correlation. By generating specific diffraction patterns for these correlated areas, the identification of CaPs was achievable. The resulting diffraction patterns showed well-resolved HAP peaks that supported its visualization and identification. These patterns exhibit also good resolution at the low angular range where by-products of the reaction reside. The result is that this combined technique aids in identifying traditionally difficult-to-characterize [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] by-products such as octacalcium phosphate (OCP) and other CaP phases associated with HAP crystallization, such as Ammonium Dihydrogen Phosphate ADP, and carbonate-substituted HAP (C-HAP), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003el, providing crucial information about the composition of the DAP \"reaction products-calcite matrix\" system.\u003c/p\u003e \u003cp\u003eThe combination of techniques proves effective for qualitative phase analysis of both CaOxs (whewellite and weddellite) and CaP (HAP and by-products), even in the more complex scenario of sequential treatment samples (DAP\u0026thinsp;+\u0026thinsp;AmOx). Despite the additional challenges posed here because of the simultaneous presence of CaOxs and CaPs, this approach facilitated the visualization and characterization of the newly crystallized phases (oxalate and phosphate) within the complex systems generated by these treatments, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eIn the end, focusing solely on the average \u0026micro;XRPD pattern, the identification of reaction products was limited mainly because of their low concentration compared to the dominant calcite matrix. In contrast, examining \u0026micro;XRF data alone resulted challenging in samples lacking elemental markers for identifying CaOxs and could only hint at the crystallization of CaPs when the markers were present. Integrating both techniques enabled the production of \u003cem\u003earea-specific\u003c/em\u003e diffraction patterns associated with those zones exhibiting calcium intensity variations or high Ca/P correlation, allowing for the identification of specific crystalline phases characteristic of the newly formed \u0026ldquo;reaction products-calcite matrix\" system.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003ePhases\u0026rsquo; penetration depth and spatial distribution of the reaction products\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe combination of techniques used in this study yields an invaluable advantage in generating comprehensive \u0026micro;XRPD maps. \u003cem\u003ePhase-specific\u003c/em\u003e distribution maps were generated by isolating distinct peaks associated with the identified crystalline phases in the diffraction patterns, providing detailed insight into the spatial distribution of each phase. SR-\u0026micro;XRPD mapping allows micrometric individual mapping of each reaction product distribution within the \"reaction products-calcite matrix\" systems, offering exceptional spatial resolution. Such data not only visualizes the penetration depth of the crystallization but also localizes where the chemical reactions take place.\u003c/p\u003e \u003cp\u003eOur analysis consistently reveals \u003cem\u003ephase-specific\u003c/em\u003e color maps accurately depicting the areal distribution of CaOxs and CaPs crystalline phases across all examined samples, without artifacts.\u003c/p\u003e \u003cp\u003eIn the context of AmOx-treated samples, the areal distribution data through RGB correlation maps reveals a distinct distribution pattern of CaOx phases: a gradient from the surface, with weddellite (WED) overlaying whewellite (WHE). This observation underscores the spatial relationship between these phases shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea. The data underscored a crystalline network following the solution diffusion path within the stone's microstructure, originating from the surface interface. These findings highlight the CaOx areal arrangement given by the treatment. Such data offer, for the first time, an opportunity to establish correlations between the phases of CaOx formed and their spatial distribution, allowing interpretations of the consolidation effect. Currently, literature only suggests that the distribution and penetration of distinct CaOxs significantly affect resultant system properties [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe application of \u0026micro;XRPD mapping of DAP reaction products has revealed unprecedented details regarding the areal distribution of CaP phases within the stone, particularly highlighting hydroxyapatite (HAP) and its associated by-products (ADP, OCP, and C-HAP). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb, HAP distribution follows a gradient from the surface, less homogeneous than the CaOxs network. The by-products, less identified in prior studies, exhibit a distribution pattern linked to HAP, extending to similar depths within the stone and localized in spots within its porous network. It is important to acknowledge that the representation of these CaP phases in the color maps might be subject to potential inaccuracies (either underestimated or overestimated) because of the mixture of phases within our systems. CaP peaks are collocated in the diffraction pattern close to the peaks of other phases complicating their isolation and mapping. Despite this, the ability to pinpoint the spatial distribution of both HAP and its by-products remains crucial. The literature already suggests correlations between the presence of these by-products, such as ADP indicating acidification, and changes in the stone's condition [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, having data on CaP distribution allows for a deeper exploration of these correlations, facilitating a better understanding of the localized effects of CaP phases on the stone's chemical changes and conditions.\u003c/p\u003e \u003cp\u003eIn the case of sequential treatment, the mapping of CaOxs and CaP phases, and the examination of phase coexistence through RGB correlation maps, highlight distinct variations in both penetration depth and areal distribution compared to single treatments. The data (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec) showed that, in sequential treatments, HAP and by-products are dispersed throughout the stone bulk rather than follow a gradient from the stone surface. CaOxs seemly exhibit different penetration depths compared to single treatments, although they are still primarily located on the surface. Additionally, the maps illustrate sparse areas of coexistence between CaOxs and CaPs. These observations strongly indicate interactions between the solutions\u0026rsquo; reactions. The significance of obtaining these data lies in its capacity to shed light on these interactions, thereby enhancing our understanding of combining treatment effects on stone microstructures absent in the literature.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eQuantitative phase analysis and Orientation of the reaction products\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe high resolution of \u0026micro;XRPD maps also enables us to obtain information on quantitative phase concentration and orientation at the scale of the studied area (ROI\u0026thinsp;=\u0026thinsp;400 x 400 \u0026micro;m\u0026sup2;). Acquiring such data at this scale, with a clear view of the phases\u0026rsquo; distribution, provides essential insights for assessing localized effects and evaluating treatment performance.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuantitative Assessment of the Reaction Products Areal Amounts (Mean % \u0026plusmn; Standard Deviation) on Surface Maps for Various Treatment Methodologies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eReaction Products\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWHE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWED\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eHAP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eC-HAP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOCP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eADP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmOx- treated\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.4\u0026thinsp;∓\u0026thinsp;2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54\u0026thinsp;∓\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDAP-treated\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.2\u0026thinsp;∓\u0026thinsp;3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u0026thinsp;∓\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.62\u0026thinsp;∓\u0026thinsp;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.26\u0026thinsp;∓\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDAP\u0026thinsp;+\u0026thinsp;AmOx treated\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.5\u0026thinsp;∓\u0026thinsp;3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76\u0026thinsp;∓\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.2\u0026thinsp;∓\u0026thinsp;2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16\u0026thinsp;∓\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.38\u0026thinsp;∓\u0026thinsp;1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u0026thinsp;∓\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFor quantitative assessment of newly crystallized reaction products, image analysis of phase-specific \u0026micro;XRPD maps was used to quantify the areal fraction of reaction product observed in the 2D map (shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the case of AmOx-treated samples, this quantification confirmed existing literature by highlighting predominant whewellite crystallization, while uncovering unexpectedly high content of weddellite in some surface areas. Similarly, in samples treated with DAP solution, through quantitative evaluation, we categorized the main reaction products (HAP and OCP, 22.2% and 7.6%, respectively) as well as reaction by-products into minor (between 1% and 0.1%) and trace (less than 0.1%) products, based on their concentrations. The localized quantitative data derived from \u0026micro;XRPD map image analysis, of the sequentially treated samples, revealed that the % of crystallization of the reaction compounds is, generally, in line with the one in the single treatments.\u003c/p\u003e \u003cp\u003eAdditionally, \u0026micro;XRPD distribution maps are generated by selecting Bragg peaks of the crystalline phase. As each peak on the diffraction pattern corresponds to a specific set of crystallographic planes within the crystalline material, mapping a peak shows the areal distribution of a specific crystal plane. Correlation through RGB correlation of maps associated with different peaks of a single phase is here used to reveal the crystal orientation of the reaction products. Indeed, the lack of merging colors in the RGB correlation maps in specific areas was used to detect the crystal orientation of a selected crystalline plane. For instance, in the case of CaOxs (both whewellite and weddellite), they exhibit randomly distributed crystallites within the stone matrix, showing up as a single cohesive yellow color on the maps (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). On the other hand, CaPs, primarily HAP, in DAP-treated samples show preferential orientations in some areas, as distinct green (HAP d\u003csub\u003e310\u003c/sub\u003e) and red (HAP d\u003csub\u003e002\u003c/sub\u003e) color distributions show up on the correlation maps (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). This observation becomes particularly intriguing when studying sequential treatments where no significant orientation of CaPs can be detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec). Here the data show how CaPs crystallized differently. This proves an interaction between the solutions (the DAP-stone system is disturbed by the crystallization of CaOxs,) and the reactivity of the CaPs phases to be disturbed by the interaction.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOverall, our experimental setup prioritized high spatial resolution and simultaneous \u0026micro;XRF and \u0026micro;XRPD acquisition, but this compromised the features of the collected X-ray diffraction patterns hindering, for example, a proper Rietveld analysis. The preclusion of Rietveld\u0026rsquo;s full-profile fit hinders any structural analysis of the crystalline phases, along with a phase quantification (in a multi-phase system) based on the refined scale factor of each crystalline component. However, this limitation is here efficiently overcome, as 1) the crystal structure of the co-present crystalline phases, in the system under investigation, is already well known and 2) the relative (areal) fraction of the crystalline components can be obtained through the \u0026micro;XRPD map analysis, along with their average crystallites orientation. In this light, the lack of the Rietveld full-profile fit does not diminish the description of the complex polycrystalline system under investigation and opens a new route for other scenarios in which the application of full-profile fit analysis is precluded.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur research effectively demonstrates how the synergy of \u0026micro;XRF and \u0026micro;XRPD at high resolution leads to an efficient characterization of the newly formed conservation products (CaOxs and CaPs), overcoming the analytical challenge of their low wt% concentration compared to the dominant calcite matrix. While \u0026micro;XRPD alone struggled, due to their low abundance, \u0026micro;XRF provided elemental data, leading to \u003cem\u003earea-specific\u003c/em\u003e diffraction patterns, and ultimately enabling phase identification in complex multiphase mixtures.\u003c/p\u003e \u003cp\u003eMoreover, these techniques provide invaluable insights into the penetration depth and spatial distribution of reaction products, enhancing our understanding of the treated stone system. The data derived from \u0026micro;XRPD mapping proved, for the first time, to be crucial in assessing reaction product concentrations. Additionally, orientation analysis of crystalline phases on the \u0026micro;XRPD maps offered a deeper understanding of phase formation and preferential orientations within the treated samples, and of the phase interaction in the case of sequential treatment.\u003c/p\u003e \u003cp\u003eWhile acknowledging some limitations, mainly due to the need for micro-sampling, the combination of the techniques provided high-quality data on CH stone consolidation. Moreover, the obtained positive outcomes not only contribute to our fundamental understanding of these complex systems and inorganic mineral treatments but also underline their potential applications in further studies.\u003c/p\u003e \u003cp\u003eIn conclusion, this study underscores the significance of combining advanced synchrotron-based X-rays 2D mapping techniques for comprehensive and spatially resolved analyses of complex CH multiphase which broadens the applicability of these advanced synchrotron-based approaches in the study of inorganic mineral treatments in Conservation Science and Heritage Science.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCorrespondence and requests for materials\u003c/h2\u003e \u003cp\u003e \u003cem\u003eshould be addressed to G.M.\u003c/em\u003e\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors reviewed the manuscript. G.M., E.P., and N.M. wrote the main manuscript text. G.M. and M.B. performed the analysis and G.M., E.P., N.M., and C.C. interpreted the results. Preparation of Figures: N.M. and G.M. All authors (G.M., E.P., C.C., D.G., M.R., M.B., N.M.) assisted in the revision of the submitted manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eFor the beamtime received, thanks are expressed to the European Synchrotron Radiation Facility ID13 beamline (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15151/ESRF-ES-981402187\u003c/span\u003e\u003cspan address=\"10.15151/ESRF-ES-981402187\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The authors also acknowledge the TS Lab \u0026amp; Geoservice snc (Pisa, Italy) for developing an ad hoc effective protocol to prepare polished thin sections suitable for the investigations. Funding for this research was provided by the Italian Ministry of Education (MIUR) (PRIN2017 - Mineral reactivity, a key to understand large-scale processes: award No. 2017 L83S77) and \"Dipartimenti di Eccellenza 2023\u0026ndash;2027 \u0026ndash; \u0026ldquo;Le Georisorse per la transizione ecologica e lo sviluppo territoriale\"\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSena da Fonseca, B. (2023). Current Trends in Stone Consolidation Research: An Overview and Discussion. Buildings, 13(2), 403.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiorgi, R., Baglioni, M., Berti, D. \u0026amp; Baglioni, P. New methodologies for the conservation of cultural heritage: Micellar solutions, microemulsions, and hydroxide nanoparticles. Acc. Chem. 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Laboratory and field study on consolidation of a byzantine marble sarcophagus. Construction and Building Materials, 262, 120784.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePossenti, E., Colombo, C., Conti, C., Gigli, L., Merlini, M., Plaisier, J.R., Realini, M., and Gatta, G.D. (2018b). Grazing incidence synchrotron X-ray diffraction of marbles consolidated with diammonium hydrogen phosphate treatments: non-destructive probing of buried minerals. Appl. Phys. A 124, 383.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePossenti, E., Colombo, C., Realini, M., Song, C. L., \u0026amp; Kazarian, S. G. (2021). Time-resolved ATR\u0026ndash;FTIR spectroscopy and macro-ATR\u0026ndash;FTIR spectroscopic imaging of inorganic treatments for stone conservation. Analytical Chemistry, 93(44), 14635\u0026ndash;14642.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOsticioli, I., Botticelli, G., Matteini, P., Siano, S., Pini, R., \u0026amp; Matteini, M. 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Synthesis of calcium oxalate trihydrate: New data by vibrational spectroscopy and synchrotron X-ray diffraction. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 150, 721\u0026ndash;730.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePossenti, E., Conti, C., Gatta, G. D., Realini, M., \u0026amp; Colombo, C. (2019). Diammonium hydrogenphosphate treatment on dolostone: the role of Mg in the crystallization process. Coatings, 9(3), 169.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3921021/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3921021/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding the effects of consolidating inorganic mineral treatments on carbonate stones of cultural heritage, on the nature and distribution of newly formed products within the matrix, poses a significant challenge in Heritage Science and Conservation Science. Existing analytical methods often fail to deliver spatial and compositional insights into the newly formed crystalline phases with the appropriate high lateral resolution. In this study, we explore the capabilities and limitations of synchrotron radiation (SR) micro-X-ray powder diffraction (\u0026micro;XRPD) mapping combined with micro-X-ray fluorescence (\u0026micro;XRF) to give insight into compounds formed following the application of ammonium oxalate (AmOx) and diammonium phosphate-based (DAP) solutions on porous carbonate stone. Ultimately, the integration of \u0026micro;XRPD mapping and \u0026micro;XRF analysis proved itself a powerful asset in providing precise qualitative and quantitative data on the newly formed phases, in the case of both calcium oxalates (CaOxs) and calcium phosphates (CaPs), and their complex stratigraphic distribution, thus opening a new route for applications to a more comprehensive study of inorganic treatments applied to carbonate substrates.\u003c/p\u003e","manuscriptTitle":"Advanced Mapping of Inorganic Treatments on Porous Carbonate Stones by Combined Synchrotron Radiation High Lateral μXRPD and μXRF","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-14 18:29:07","doi":"10.21203/rs.3.rs-3921021/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-02-28T05:22:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-22T09:02:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16f6d3a2-1a2a-4871-afef-81ca4e391766","date":"2024-02-19T17:32:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"f4985550-15eb-45cf-b4e8-e0794f46f23a","date":"2024-02-15T19:46:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-15T19:36:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-15T14:50:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-02-12T14:47:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-02-12T14:44:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-02-02T13:25:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10f1833d-76e6-4c2b-9efb-1730650773c8","owner":[],"postedDate":"February 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28751427,"name":"Physical sciences/Materials science"},{"id":28751428,"name":"Physical sciences/Nanoscience and technology/Techniques and instrumentation/Characterization and analytical techniques"}],"tags":[],"updatedAt":"2024-05-01T22:39:02+00:00","versionOfRecord":{"articleIdentity":"rs-3921021","link":"https://doi.org/10.1038/s41598-024-58718-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-04-20 22:39:02","publishedOnDateReadable":"April 20th, 2024"},"versionCreatedAt":"2024-02-14 18:29:07","video":"","vorDoi":"10.1038/s41598-024-58718-z","vorDoiUrl":"https://doi.org/10.1038/s41598-024-58718-z","workflowStages":[]},"version":"v1","identity":"rs-3921021","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3921021","identity":"rs-3921021","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}