nanoCT Data Research Articles

Dual U-Net based feature map algorithm for automatic projection alignment of synchrotron nano-CT

Synchrotron radiation-based nano-CT is a non-destructive imaging technique used to study the internal structure of matter. The efficient and automatic correction of errors in nano-CT imaging has proven challenging. Accordingly, different projection alignment techniques have been employed to address these issues. However, these techniques have their limitations. Herein, we propose a novel error correction model, a U-Net, that combines an experimentally informed mathematical model, optimized deep learning algorithm, and efficient projection matching model. The results show that the generation of feature maps based on our model is effective for improving the quality of 3D reconstructions while remaining highly robust. We further propose an optimized feature map generation method, a dual U-Net. Applying it yields an almost negligible alignment error rate for low random error-shift nano-CT data and a stable decrease in errors of one order of magnitude for high random error-shift nano-CT data. This study demonstrates the feasibility of the proposed feature map replacement projection alignment method, which may prove crucial to maximizing the efficiency and generalization of automatic projection alignment tasks.

Laminar structure differences and heterogeneities in reservoirs in continental organic-rich shales: The Cretaceous Nenjiang Formation in the Songliao Basin

Shale has a unique laminar structure that is currently the focus of considerable interest and a great deal of research in the academic community and industry. Studies have focused primarily on the differences among laminar combinations, whereas only a few have investigated the structure of individual lamina. In this study, we use typical organic-rich shale from the Cretaceous Nenjiang Formation in the Songliao Basin as an example and analyze each individual lamina of the shale on a millimeter scale. We have investigated heterogeneities among the different laminae by using X-ray fluorescence analysis, rock slicing, laser scanning confocal microscopy, field emission scanning electron microscopy, total organic carbon (TOC), rock pyrolysis, X-ray diffraction mineral analysis, electronic computer tomography (nano-CT), nitrogen adsorption, and other experimental methods. Four laminar units — composed of clay minerals, feldspar-quartz, and calcite — are distinguished based on their different levels of Ca, K, and Fe. We designate these units as UA, UB, UC, and UD (from the top to bottom in the formation). The palaeoenvironment, organic geochemical parameters, and mineral compositions of the different laminar structures are “two-stage” in character. From UD to UA, TOC values indicate a slightly decreasing trend, whereas the calcite content indicates a substantial increase, which is related to gradual reduction in the paleodepth, increasing aridity of the climate, increase of salinity, and decrease of reducibility during the sedimentary period. Different laminae correspond to different pore structures. The pore types in units UC and UD are mainly clay mineral-related pores and pyrite intergranular pores. In contrast, calcite dissolution pores are common in units UA and UB. Nitrogen adsorption and nano-CT data indicate that the pore development degree and pore size of organic matter in units UC and UD are better than those of units UA and UB. The porosity of UD is 2.6 times higher than that of UA. Laminae have an important influence on shale quality. The traditional approach to shale evaluation takes laminar combinations in shale strata as the research unit. Switching the focus to the heterogeneity of individual lamina could help in the selection of “sweet spots” and identification of optimal locations for shale oil exploration and development.

Feature detection network-based correction method for accurate nano-tomography reconstruction.

Driven by the development of advanced x-ray optics such as Fresnel zone plates, nano-resolution full-field transmission x-ray microscopy (Nano-CT) has become a powerful technique for the non-destructive volumetric inspection of objects and has long been developed at different synchrotron radiation facilities. However, Nano-CT data are often associated with random sample jitter because of the drift or radial/axial error motion of the rotation stage during measurement. Without a proper sample jitter correction process prior to reconstruction, the use of Nano-CT in providing accurate 3D structure information for samples is almost impossible. In this paper, to realize accurate 3D reconstruction for Nano-CT, a correction method based on a feature detection neural network, which can automatically extract target features from a projective image and precisely correct sample jitter errors, is proposed, thereby resulting in high-quality nanoscale 3D reconstruction. Compared with other feature detection methods, even if the target feature is overlapped by other high-density materials or impurities, the proposed Nano-CT correction method still acquires sub-pixel accuracy in geometrical correction and is more suitable for Nano-CT reconstruction because of its universal and faster correction speed. The simulated and experimental datasets demonstrated the reliability and validity of the proposed Nano-CT correction method.

Integration of Multiscale Imaging of Nanoscale Pore Microstructures in Gas Shales

Quantification of the microstructures of shales is difficult due to their complexity which extends across many orders of magnitude of scale. Nevertheless, shale microstructures are extremely important, not only as shale gas resources but also as cap rocks in CCS resources, in geothermal reservoirs, and as a host to the long-term storage of radioactive materials. In this work, we have performed ultrahigh-resolution CT imaging (nano-CT), mercury injection porosimetry (MIP), and nitrogen adsorption experiments on a sample of gas shale for which we already have focused ion beam scanning electron microscopy (FIB-SEM) and high-resolution CT (micro-CT) data sets. The combination of these data sets has allowed us to examine the microstructure of the shale in unprecedented depth across a wide range of scales (from about 20 nm to 0.5 mm). Overall, the sample shows a porosity of 0.67 ± 0.009% from the nano-CT data, 0.0235 ± 0.003% from nitrogen adsorption, and 0.60 ± 0.07% from MIP, which compare with 0.10 ± 0.01%, 0.52 ± 0.05%, and 0.94 ± 0.09% from three FIB-SEM measurements and 0.06 ± 0.008% from one micro-CT measurement. The data vary due to the different scales at which each technique interrogates the rock and whether the pores are openly accessible (especially in the case of the nitrogen adsorption value). The measured kerogen fraction is 32.4 ± 1.45% from nano-CT compared with 34.8 ± 1.74%, 38.2 ± 1.91%, 41.4 ± 2.07%, and 44.5 ± 2.22% for three FIB-SEM and one micro-CT measurement. The pore size imaged by nano-CT ranged between 100 and 5000 nm, while the corresponding ranges were between 3 and 2000 nm for MIP analysis and between 2 and 90 nm for N2 adsorption. The distribution of pore aspect ratio and scale-invariant pore surface area to volume ratio (σ) as well as the calculated permeability shows the sample to have a high shale gas potential. Aspect ratios indicate that most of the pores that contribute significantly to pore volume are oblate, which is confirmed by the range of σ (3–13). Oblate pores have greater potential for interacting with other pores compared to equant and needle-shaped prolate pores as well optimizing surface area for gas to desorb from the kerogen into the pores. Permeability essays provide 2.61 ± 0.42 nD from the nano-CT data, 2.65 ± 0.45 nD from MIP, and (5.07 ± 0.02) × 10–4 nD from nitrogen adsorption, which are consistent with expectations for generic gas shales (i.e., tens of nD) and the measurements made previously on the same sample using FIB-SEM and micro-CT imaging techniques.

Direct three-dimensional imaging for morphological analysis of electrospun fibers with laboratory-based Zernike X-ray phase-contrast computed tomography.

Electrospinning is a well-established and widely used method for the production of protein-based fibrous biomaterials. The visualization of the morphology and the characterization of sample features related to the three-dimensional (3D) structure, like the porosity and fibers thickness, is crucial for the design and fabrication of tailor-made and application-optimized materials. Here, we evaluated the benefits of using 3D X-ray imaging in a laboratory setup with a resolution in the sub-micrometer range for the characterization of electrospun gelatin fibrous mats. We used phase-contrast X-ray computed tomography at the nanoscale (nano-CT) for the evaluation of the time-course morphological changes of the mats induced by chemical cross-linking of the gelatin fibers. We present an image processing protocol that enables the segmentation of the fibers and quantification of the mats porosity, the analysis of the shape and size of the pores, and of the fibers thickness and orientation. We compared the results obtained from the processed nano-CT data with those obtained with the conventional methods used for the characterization of electrospun fibrous materials, and we discuss the advantages and limitations of each method when applied to gelatin electrospun samples. Our results reveal that the use of phase-contrast nano-CT provides quick additional and relevant information for the characterization of fibrous mats and, thus, provides beneficial insights for the design and fabrication of novel fibrous materials.

Scalable double regularization for 3D Nano-CT reconstruction

Nano-CT (computerized tomography) has emerged as a non-destructive high-resolution cross-sectional imaging technique to effectively study the sub-μm pore structure of shale, which is of fundamental importance to the evaluation and development of shale oil and gas. Nano-CT poses unique challenges to the inverse problem of reconstructing the 3D structure due to the lower signal-to-noise ratio (than Micro-CT) at the nano-scale, increased sensitivity to the misaligned geometry caused by the movement of object manipulator, limited sample size, and a larger volume of data at higher resolution. We propose a scalable double regularization (SDR) method to utilize the entire dataset for simultaneous 3D structural reconstruction across slices through total variation regularization within slices and L1 regularization between adjacent slices. SDR allows information borrowing both within and between slices, contrasting with the traditional methods that usually build on slice by slice reconstruction. We develop a scalable and memory-efficient algorithm by exploiting the systematic sparsity and consistent geometry induced by such Nano-CT data. We illustrate the proposed method using synthetic data and two Nano-CT imaging datasets of Jiulaodong (JLD) shale and Longmaxi (LMX) shale acquired in the Sichuan Basin. These numerical experiments show that the proposed method substantially outperforms selected alternatives both visually and quantitatively.

Nanoscopic X-ray tomography for correlative microscopy of a small meiofaunal sea-cucumber

In the field of correlative microscopy, light and electron microscopy form a powerful combination for morphological analyses in zoology. Due to sample thickness limitations, these imaging techniques often require sectioning to investigate small animals and thereby suffer from various artefacts. A recently introduced nanoscopic X-ray computed tomography (NanoCT) setup has been used to image several biological objects, none that were, however, embedded into resin, which is prerequisite for a multitude of correlative applications. In this study, we assess the value of this NanoCT for correlative microscopy. For this purpose, we imaged a resin-embedded, meiofaunal sea cucumber with an approximate length of 1 mm, where microCT would yield only little information about the internal anatomy. The resulting NanoCT data exhibits isotropic 3D resolution, offers deeper insights into the 3D microstructure, and thereby allows for a complete morphological characterization. For comparative purposes, the specimen was sectioned subsequently to evaluate the NanoCT data versus serial sectioning light microscopy (ss-LM). To correct for mechanical instabilities and drift artefacts, we applied an alternative alignment procedure for CT reconstruction. We thereby achieve a level of detail on the subcellular scale comparable to ss-LM images in the sectioning plane.

Effects of Porous Carbon Morphology, Agglomerate Structure and Relative Humidity on Local Oxygen Transport Resistance

The morphology and ionomer distribution in the polymer electrolyte membrane fuel cell (PEMFC) cathode electrode (used in Toyota Mirai) are quantified with nano-scale resolution X-ray computed tomography (nano-CT). Using the nano-CT data, different shapes, sizes and compositions of agglomerates are extracted. Statistical information from multiple techniques, including transmission electron microscopy (TEM), ultra-small angle X-ray scattering (USAXS), and Brunauer-Emmett-Teller (BET) gas adsorption porosimetry are combined to reconstruct the high surface-area porous carbon (HSC) support, exterior (on the surface of carbon) and interior (inside carbon pores) catalysts, ionomer, and primary pores in the extracted agglomerates. Application of capillary condensation theory to the reconstructed agglomerate structure is shown to accurately represent the experimentally-observed relative humidity (RH) dependence of the electrochemically-active surface area (ECA). Direct numerical simulations (DNS) show that the high local O2 transport resistance () under dry conditions is mainly associated with the reduced ECA. We demonstrate that the agglomerate shape and size affect only if the primary pores are poorly accessible (i.e., capillary-condensed water filled primary pores result in lower for lower aspect ratio agglomerates). We also estimate associated with the location of catalyst (whether inside or on the surface of HSC).

Visualizing the Carbon Binder Phase of Battery Electrodes in Three Dimensions

This study presents a technique to directly characterize the carbon and binder domain (CBD) in lithium-ion (Li-ion) battery electrodes in three dimensions and use it to determine the effective transport properties of a LiNi0.33Mn0.33Co0.33O2 (NMC) electrode. X-ray nanocomputed tomography (nano-CT) is used to image an electrode composed solely of carbon and binder, whereas focused ion beam–scanning electron microscopy is used to analyze cross-sections of a NMC electrode to gain morphological information regarding the electrode and CBD porosity. Combining the information gathered from these techniques reduces the uncertainty inherent in segmenting the nano-CT CBD data set and enables effective diffusivity of its porous network to be determined. X-ray microcomputed tomography (micro-CT) is then used to collect a NMC data set that is subsequently segmented into three phases, comprised of active material, pore, and CBD. The effective diffusivity calculated for the nano-CT data set is incorporated for the CBD present in the micro-CT data set to estimate the ensemble tortuosity factor for the NMC electrode. The tortuosity factor greatly increases when compared to the same data set segmented without considering the CBD. The porous network of the NMC electrode is studied with a continuous pore size distribution approach that highlights median radii of 180 nm and 1 μm for the CBD and NMC pores, respectively, and with a pore throat size distribution calculation that highlights median equivalent radii of 350 and 700 nm.

Evaluation of phase retrieval approaches in magnified X-ray phase nano computerized tomography applied to bone tissue.

X-ray phase contrast imaging offers higher sensitivity compared to conventional X-ray attenuation imaging and can be simply implemented by propagation when using a partially coherent synchrotron beam. We address the phase retrieval in in-line phase nano-CT using multiple propagation distances. We derive a method which extends Paganin's single distance method and compare it to the contrast transfer function (CTF) approach in the case of a homogeneous object. The methods are applied to phase nano-CT data acquired at the voxel size of 30 nm (ID16A, ESRF, Grenoble, France). Our results show a gain in image quality in terms of the signal-to-noise ratio and spatial resolution when using four distances instead of one. The extended Paganin's method followed by an iterative refinement step provides the best reconstructions while the homogeneous CTF method delivers quasi comparable results for our data, even without refinement step.

(Invited) Direct Observations of Liquid Water Formation at Nano- and Micro-Scale in Platinum Group Metal-Free Electrodes By Operando X-Ray Computed Tomography

Platinum group metal (PGM)-free catalyst materials are promising alternatives to Pt-based catalysts for use in polymer electrolyte fuel cells (PEFCs) providing for reduced cost and potentially broadening technology footprint because of sources availability. Optimizing the morphology of these PGM-free catalyst layers for enhanced transport properties is critical for reaching high power-density targets. Unfortunately, the current understandings of both morphology and transport processes are very limited due to the novelty of the materials and the challenges in designing operando characterization techniques. In order to bridge these gaps in understanding, we used operando synchrotron X-ray computed tomography to visualize water transport in operating PEFCs. In this study, we present a non-destructive observation of operando morphology and water transport processes for PGM-free PEFCs. Our previous studies highlighted some of the morphological features of PGM-free electrodes on nano and micro-scale (1, 2). Ex-situ nano-CT data complements operando micro-CT observation by providing water distribution in smaller macropores (< 1 µm). Figure 1 shows grey-scale cross-section four stitched FOVs along one of the channels for OCV and 50 % RH (Figure 1a) and 40 mAcm-2 at 100 % RH (Figure 1b) operando conditions. The anode, cathode layers, as well, as membrane are clearly seen from this cross-section view. No liquid water was observed at 50 % RH condition, whereas for 100 % RH and under applied current density large water droplets are seen in the cathode channel and within the cathode PGM-free layer. Figure 1b and c show zoom-in locations within the MEA. Tree-like agglomerates were observed within the cathode PGM-free GDE that were compressed against 50 µm membrane. Under applied current density of 40 mAcm-2 liquid water was clearly observed within both large and small voids of the GDE and membrane swelling to 72 µm was also measured. From Figure 1d and b membrane expands into the GDE voids upon humidification resulting in several locations in loss of contact with the anode GDE. In this presentation we demonstrate that (1) gas-diffusion electrodes (GDEs) form highly non-uniform interfaces with the membrane and under constant current operation, liquid water formed in electrochemical reactions fills the larger macropores within the PGM-free electrode and at the electrode-membrane interface; (2) from nano-CT data ionomer swelling in macropores is 16 % going from 50 % RH to 100 % RH but no notable structural changes occur within CL at nano-scale; (3) water is removed into the cathode channel and is also observed under location of the land-area (which is cooler but also has larger voids); and (4) water preferentially fills larger voids, that are lower capillary pressure locations, due to hydrophobic nature of the catalyst. Figure 1. Along-the-channel cross-section tomographs for temperature 60oC a) 50 % RH OCV and b) 100 % RH 40 mAcm-2, where c and d) are corresponding zoom-in locations from a and b. Locations for liquid water are marked, as well as membrane thicknesses. References A. Serov, A. D. Shum, X. Xiao, V. De Andrade, K. Artyushkova, I. V. Zenyuk and P. Atanassov, Applied Catalysis B: Environmental (2017).S. Kabir, K. Lemire, K. Artyushkova, A. Roy, M. Odgaard, D. Schlueter, A. Oshchepkov, A. Bonnefont, E. Savinova, D. C. Sabarirajan, P. Mandal, E. J. Crumlin, I. Zenyuk, P. Atanassov and A. Serov, Journal of Materials Chemistry A (2017). Figure 1

Agglomerates in Polymer Electrolyte Fuel Cell Electrodes: Part I. Structural Characterization

This two-part study characterizes the structural and transport properties of polymer electrolyte fuel cell (PEFC) cathode catalyst electrode. The agglomerates comprising the electrode are characterized with nano scale resolution X-ray computed tomography (nano-CT). A hybrid reconstruction technique is used to further refine the 3-D agglomerate microstructure and obtain 1-nm voxel resolution of the constituent catalyst, ionomer, carbon support and primary and secondary pore phases. Our analysis of nano-CT data shows that the electrode composition is heterogeneous and the agglomerates have structural heterogeneities in terms of size and composition. There is a strong correlation between the ionomer to carbon weight ratio (I/C) and agglomerate microstructure, suggesting that ionomer plays role in formation of larger agglomerates. With the hybrid reconstructions, we show that ionomer film thickness is spatially non-uniform inside the agglomerate and is strongly dependent on the I/C. Smaller agglomerate size and high I/C are shown to favor the ionomer impregnation. We demonstrate that the majority of the primary pores are smaller than 15 nm for I/C = 0.8 and higher I/C reduces the primary pore size. We also characterize the uniformity of the catalyst distribution and show that the majority of the catalyst is located away from the agglomerate surface.

Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography

X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli, a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.

PGM-Free Electrode Microstructure Analysis and Transport Modeling

The dependence of proton exchange membrane fuel cell (PEMFC) systems on platinum group metal (PGM) catalysts is a major barrier to these systems meeting the cost-performance targets required to be competitive with the internal combustion engines (ICEs) in the market. In the past decade, oxygen reduction reaction (ORR) catalysts derived from earth abundant materials have gained increasing interest as low cost alternatives to replace platinum catalysts. To date the most promising PGM-free catalyst candidate are the pyrolyzed transition metal (such as Fe, Co), nitrogen and carbon (M-N-C) complexes [1]. While there have been significant improvements in the ORR activity of these materials through innovative synthesis and treatment techniques, the volumetric activity (ORR activity per cm3of electrode, measured at high cell voltage where the only limiting factor is the electro-catalytic process) of these PGM-free catalysts is low relative to the incumbent carbon-supported platinum catalysts. Achieving comparable activity requires almost 10 times thicker electrodes with respect to Pt-based counterparts [2]. While the majority of the PGM-free electrode studies focus on the volumetric activity, thicker electrodes lead to increased mass and charge transport resistances especially for air cathode gas utilized for automotive applications. In this study, performance and transport properties of electrodes based on the cyanamide-polyaniline-iron (CM-PANI-Fe) catalyst developed by Los Alamos National Laboratory were investigated. The electrode microstructure was characterized by use of the nano-scale X-ray tomography (nano-CT) technique. After ion exchanging the protons in Nafion® with cesium (Cs+), the samples were scanned in absorption contrast mode to visualize Cs+intensity, and thus the ionomer, while pore morphology was obtained using Zernike phase contrast scans, as in [2]. Ionomer volume fraction distribution and pores larger than the nano-CT resolution (~20 nm) were obtained as shown in Fig. 1. By running transport simulations, the effective transport properties were calculated for various sub-volumes extracted from the nano-CT data, as illustrated in Fig. 1. Using the effective ion conductivities in a simple performance model, ORR kinetic parameters () were calculated and sources of voltage losses were identified depending on the experimental polarization data. Finally, the mass transport resistances were quantified by using the calculated kinetic ORR and effective transport parameters within a detailed cathode model that accounts for the charge, reactant and liquid water transport. It was concluded that the flooded pores are the major source of mass transport resistances for the thick PGM-free electrodes whereas the film resistance becomes dominant for thinner electrodes, as shown in Figs. 2a and 2b.

A Method for Quantitative 3D Mesoscale Analysis of Solid Oxide Fuel Cell Microstructures Using Xe-plasma Focused Ion Beam (PFIB) Coupled with SEM

Three-dimensional (3D) distributions of microstructural features in electrodes of solid oxide fuel cells (SOFCs) directly influence their electrochemical performance. Commercial grade SOFCs produced in cost-constrained environments can be expected to exhibit variations on the mesoscale (≈ hundreds of µm) of the microscale features (≈ tens of µm) that determine the local electrochemical activity. We are interested in quantitatively determining the mesoscale distributions of microscale properties in SOFC electrodes, especially quantifying the tails of distributions to establish correlations between such outliers and long-term performance. In this talk, we describe a new method that allows for the fast reconstruction of incredibly large volumes while maintaining a resolution on the order of tens of nm, allowing for fine-scale features to be accurately quantified. We use a Xe plasma focused ion beam (FIB) for slicing and a scanning electron microscope (SEM) for imaging. The pFIB allows for an increase in material removal rates by a factor of ≈ 100 compared to Ga ion FIBs, while the SEM resolution remains very high (herein ≈ 50nm), comparable to nano-CTs. In the same time as required for collecting Ga-FIB or nano-CT data sets, we collected a pFIB volume that is ≈ 70-80 times larger than attainable with Ga-FIB-SEM and ≈15-20 times larger than with nano-CT. From this data, we quantified the mesoscale distributions, containing both the mean and the variance, of key microscale features including volume fraction, average particle size, tortuosity, and triple phase boundary density. The commercial SOFC electrodes investigated were found to exhibit significant variations in the mesoscale distributions of their local microstructural features, which will be discussed. Importantly, these mesoscsale variations in microstructural features are expected to result in significant variations in electrochemical activity throughout the electrode. Using an effective medium theory model of polarization resistance, we quantified the distribution of microscale polarization resistance and mapped it spatially. Though the average value of polarization resistance is within range of expectation, the measoscale distribution of the microscale/local value of polarization resistance around the average indicates that several local areas are well outside the average, and potentially operating in regions expected to impact long-term cell performance.

A novel multimodular methodology to investigate external cervical tooth resorption

To introduce a multimodular combination of techniques as a novel minimal invasive approach to investigate efficiently and accurately external cervical resorption (ECR). One case of a central incisor with extensive external cervical resorption was selected to demonstrate the potential of a comparative novel study methodology. ECR diagnosis was based on clinical inspection, digital radiography and cone-beam computed tomography (CBCT). After extraction, the tooth was investigated using microfocus computed tomography (micro-CT), nano-CT and hard tissue histology. These techniques were compared for their accuracy and applicability to highlight their advantages and disadvantages. Nano-CT was more effective than micro-CT and CBCT for detailed ex vivo exploration of ECR. The reparative tissue, pericanalar resorption resistant sheet (PRRS), pulp tissue reactions, resorption channels and their interconnection with the periodontal ligament space were accurately visualized by detailed processing and analysis of the nano-CT data set with Dataviewer and CTAn software. Nano-CT analysis provided better insight in the true extent of the resorption, based on quantitative measurements and 3D visualization of the tooth structure. Nano-CT imaging results were similar to hard tissue histology at the mineralized tissue level. To clarify the dynamic phenomenon of reparative tissue formation and substitution of the resorbed tissues, nano-CT needed to be associated with hard tissue histology. Nano-CT is a fast and minimal invasive technique for the ex vivo analysis and understanding of ECR and is complementary with hard tissue histology. A combined approach of clinical and CBCT examination, with nano-CT and histological mapping measurements, can provide an ideal platform for future ECR imaging and exploration studies.