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Digital imaging and modeling are essential tools for characterizing rock structures and understanding fluid flow behavior. These efforts often rely on X‐ray micro‐computed tomography (micro‐CT), which faces an inherent trade‐off between resolution and field‐of‐view (FOV). Deep learning super‐resolution (SR) methods have been developed to overcome this limitation, but their application to carbonate rocks is challenged by complex micro‐nanometer features. Due to the resolution limits, micro‐CT fails to capture sub‐micrometer features such as micropores in carbonates, and using such data as high‐resolution (HR) training images limits the SR model's ability to accurately reconstruct the micropore structures. We introduce a cascading SR pipeline designed to address these challenges and reveal sub‐micrometer features in carbonate rocks. The approach integrates multi‐stage 2D SR networks to progressively enhance low‐resolution (LR) images toward the HR domain, followed by a third‐plane SR network for 3D reconstruction. We evaluate this method on a three‐stage SR task: starting from a 3 μ${\\upmu }$ m resolution micro‐CT image, super‐resolving to an intermediate 1 μ${\\upmu }$ m resolution, and ultimately reaching 0.1 μ${\\upmu }$ m resolution based on scanning electron microscopy (SEM), achieving a 30×${\\times} $scale factor. Validation with unseen SEM demonstrates that the reconstructed domains retain essential structural and physical properties. This approach provides a practical solution to current imaging limitations and enables the integration of multi‐resolution modalities for improved rock characterization.

Understanding the reactive dissolution of carbonate rocks in CO2${\\text{CO}}_{2}$ ‐rich brine environments is critical for optimizing carbon capture and storage (CCS). This study integrates flow experiments with high‐resolution micro‐CT imaging and pore‐scale simulation to analyze the interplay between physical and chemical heterogeneity during reactive transport. By examining two carbonate samples comprised principally of dolomite and calcite with anhydrite also present, we quantify how the initial distribution of minerals and permeability variations influence flow patterns, dissolution dynamics, and the increase in permeability. The results show that reaction rates decrease with increasing flow heterogeneity due to enhanced mass transfer limitations. Furthermore, the proximity of minerals to fast‐flow channels impacts their effective reaction rates and alters their hierarchy, highlighting the interplay between transport processes, mineral spatial distribution and mineral dissolution. Both samples displayed dissolution patterns with localized channel widening and formation. The study provides key insights into mineral‐specific reaction behavior and flow‐dependent dissolution patterns, further evaluating a detailed framework for improving predictive models of subsurface CO2${\\text{CO}}_{2}$storage.

To avoid the negative consequences of climate change, there is an urgent need to remove carbon dioxide from the atmosphere. Carbon mineralization—the conversion of injected CO2 into stable carbonate minerals—offers a promising pathway for large‐scale, permanent geologic storage. While projects such as CarbFix have demonstrated its feasibility, optimizing and scaling in situ mineralization requires a deeper understanding of rock–fluid interactions and how carbonate precipitation alters rock properties. Previous studies have shown that elasticity, porosity, and permeability are all sensitive to mineral precipitation, but few have monitored their concurrent evolution. Here, we present flow‐through experiments on thermally cracked vesicular Iceland basalt in which permeability, porosity, ultrasonic velocity, and outlet fluid chemistry were tracked during carbonate precipitation from reactive fluids. Experiments were conducted with the apparatus inside an X‐ray micro‐computed tomography (μ\\upmu CT) scanner, which provided 3D whole‐rock data sets at 11.5 μ\\upmu m resolution every 20–40 min during flow. Results show that permeability decreases by one to two orders of magnitude within hours, while porosity declines by less than 4% over 24–90 hr. In contrast, ultrasonic velocity increases by up to 10% in step with permeability loss, demonstrating strong sensitivity to precipitation in critical flow pathways. Scanning electron microscope and μ\\upmu CT imaging reveal a transition from dendritic and sheet‐like morphologies at high flow and supersaturation to rhombic calcite crystals as permeability and flow decrease. These findings highlight the coupling between precipitation dynamics, pore‐scale heterogeneity, and bulk rock properties, and offer avenues for optimizing and monitoring carbon mineralization in the field. Plain Language Summary To avoid the worst consequences of global warming, there is an urgent need to remove and store large volumes of carbon dioxide (CO2). One promising method is to inject it into volcanic rocks such as basalt, where it reacts to form solid carbonate minerals. This process, called carbon mineralization, locks CO2 away safely for geologic timescales. The technology is not yet widely adopted, partly due to limited understanding of how it changes basalt properties. In our laboratory experiments, we flowed reactive fluids through basalt samples while monitoring their internal structure with X‐ray scans, their ability to transmit fluids, and their response to sound waves. We found that the flow rate dropped by a factor of 10–100, even though only a small fraction of pore space was filled with carbonates. At the same time, the speed of sound waves increased, showing they are sensitive to small amounts of mineral growth in critical flow pathways. These results reveal that where and how minerals grow inside rocks strongly controls how fast the process proceeds. They also suggest that seismic waves could be used in the field to monitor carbon mineralization underground, helping manage projects to safely store large volumes of CO2 in basalt. Key Points Integrated timelapse micro‐CT and multi‐parameter monitoring reveals how carbonate precipitation evolves in basalt at pore‐scale resolution Ultrasonic velocity rises sharply, showing sensitivity to precipitate location and flow pathway clogging Flow rate and pore geometry control crystal growth, providing potential levers to optimize mineralization efficiency and storage capacity

One of the main limitations of conventional absorption-based X-ray micro-computed tomography imaging of biological samples is the low inherent X-ray contrast of soft tissue. To overcome this limitation, the use of ethanol as contrast agent has been proposed to enhance image contrast of soft tissues through dehydration. Some authors have shown that ethanol shrinks and hardens the tissue too much, also causing small tissue ruptures due to fast dehydration. However, the local tissue deformation occurring as a consequence of tissue dehydration and whether tissue shrinkage can modify myocardial architecture has not been quantified yet. The aim of this paper is to quantify the local myocardial tissue deformation due to ethanol dehydration based on 3D non-rigid registration and perform a detailed characterization of its myocardial tissue organization, before and after ethanol dehydration. A rat adult heart was imaged with synchrotron-radiation-based X-ray phase contrast imaging (X-PCI) three times: before, 9 h after and 342 h after ethanol immersion. The total volume shrinkage as well as changes in the left ventricular myocardial thickness were computed. Then, to determine local deformation of the heart caused by ethanol dehydration, the related 3D tomographic datasets were registered by means of a non-rigid registration algorithm. Finally, changes on the orientation and organization of myocytes were assessed. Our results show that the use of ethanol in synchrotron X-PCI can improve image contrast, but the tissue shrinkage is not homogeneous thus changing the local myocardial organization.

We apply an accurate numerical scheme to solve for Stokes flow directly on binarized three-dimensional rock images, such as those obtained by micro-CT imaging. The method imposes no-flow conditions exactly at the solid boundaries and employs an algebraic multigrid method to solve for the resultant set of linear equations. We compute the permeability of a range of consolidated and unconsolidated porous rocks; the results are comparable with those obtained using the lattice Boltzmann method and agree with experimental measurements on larger core samples. We show that the Kozeny–Carman equation can over-estimate permeability by a factor of 10 or more, particularly for the more heterogeneous systems studied. We study the existence and size of the representative elementary volume (REV) at lamina scale. We demonstrate that the REV for permeability is larger than for static properties—porosity and specific surface area—since it needs to account for the tortuosity and connectedness of the flow paths. For the carbonate samples, the REV appeared to be larger than the image size. We also study the anisotropy of permeability at the pore scale. We show that the permeability of sandpacks varies by less than 10 % in different directions. For sandstones, permeability changes by 25 % on average. However, the anisotropy of permeability in carbonates can be up to 50 %, indicating the existence of connected pores in one direction which are not connected in another.

In the context of global efforts to transition toward renewable energy and reduce greenhouse gas emissions, geothermal energy is increasingly recognized as a viable and sustainable option. This paper presents a comprehensive assessment derived from a subset of a larger sample collection within the Dunántúli Group of the Pannonian Basin, Hungary, focusing on optimizing micro-computed tomography (µ-CT) resolution for analyzing pore structures in sandstone formations. By categorizing samples based on geological properties and selecting representatives from each group, the study integrates helium porosity and gas permeability measurements with µ-CT imaging at various resolutions (5 µm, 2 µm, and 1 µm). The findings reveal that µ-CT resolution significantly affects the discernibility and characterization of pore structures. Finer resolutions (2 µm and 1 µm) effectively uncovered interconnected pore networks in medium- to coarse-grained sandstones, suggesting favorable properties for geothermal applications. In contrast, fine-grained samples showed limitations in geothermal applicability at higher resolutions due to their compact nature and minimal pore connectivity, which could not be confidently imaged at 1 µm. Additionally, this study acknowledges the challenges in delineating the boundaries within the Dunántúli Group formations, which adds a layer of complexity to the characterization process. The research highlights the importance of aligning µ-CT findings with geological backgrounds and laboratory measurements for accurate pore structure interpretation in heterogeneous formations. By contributing vital petrophysical data for the Dunántúli Group and the Pannonian Basin, this study provides key insights for selecting appropriate µ-CT imaging resolutions to advance sustainable geothermal energy strategies in the region. The outcomes of this research form the basis for future studies aimed at developing experimental setups to investigate physical clogging and enhance geothermal exploitation methods, crucial for the sustainable development of geothermal resources in the Pannonian Basin.

Our understanding of metabolic interactions between small symbiotic animals and bacteria or parasitic eukaryotes that reside within their bodies is extremely limited. This gap in knowledge originates from a methodological challenge, namely to connect histological changes in host tissues induced by beneficial and parasitic (micro)organisms to the underlying metabolites. We addressed this challenge and developed chemo-histo-tomography (CHEMHIST), a culture-independent approach to connect anatomic structure and metabolic function in millimeter-sized symbiotic animals. CHEMHIST combines chemical imaging of metabolites based on mass spectrometry imaging (MSI) and microanatomy-based micro-computed X-ray tomography (micro-CT) on the same animal. Both high-resolution MSI and micro-CT allowed us to correlate the distribution of metabolites to the same animal’s three-dimensional (3D) histology down to submicrometer resolutions. Our protocol is compatible with tissue-specific DNA sequencing and fluorescence in situ hybridization for the taxonomic identification and localization of the associated micro(organisms). Building CHEMHIST upon in situ imaging, we sampled an earthworm from its natural habitat and created an interactive 3D model of its physical and chemical interactions with bacteria and parasitic nematodes in its tissues. Combining MSI and micro-CT, we present a methodological groundwork for connecting metabolic and anatomic phenotypes of small symbiotic animals that often represent keystone species for ecosystem functioning.

Bacteria-based self-healing concrete has emerged as a promising solution for enhancing structural durability by autonomously repairing cracks. However, the underlying transport mechanisms of healing agents and the efficiency of mineral precipitation remain inadequately modelled. This study presents a finite element modelling (FEM) approach to simulate the diffusion and reaction kinetics of self-healing bacterial agents in concrete microstructures. X-ray micro-computed tomography (Micro-CT) finite element meshes were utilized to accurately represent crack and pore geometries, while the diffusion-reaction equation governing calcium carbonate (CaCO 3 ) precipitation was numerically solved using FEniCS. Key input parameters, including diffusion coefficients, precipitation rates, and healing efficiencies, were extracted from literature to ensure model validation. Simulations reveal that healing agent concentration follows a nonlinear diffusion pattern, with efficiency influenced by crack geometry and bacterial metabolic activity. Heatmaps and contour plots highlight healing agent dispersion, while time-dependent analysis indicates a 65.5% crack closure efficiency under optimal bacterial conditions. The proposed model effectively replicates experimental trends, demonstrating its applicability for predicting healing performance in realistic structural conditions. This study provides a computational framework that can be extended to optimize bacteria encapsulation strategies, healing kinetics, and long-term durability assessments in self-healing concrete.

Understanding pore-scale oil-water two-phase flow dynamics in reservoir rocks is fundamental for optimizing petroleum exploitation. However, limitations in real-time observation have hindered comprehensive characterization of these processes. This study employs a novel three-dimensional visualization platform that integrates online micro-CT imaging (3.78 μm resolution) with oil-water displacement experiments in Berea sandstone. Experiments conducted at 20 °C and 50 °C across flow rates (0.10–0.35 mL/min) revealed distinct temperature-dependent saturation patterns: non-monotonic N-type behavior (initial increase, decrease, and then increase with flow rate) at 20 °C and V-type behavior (initial decrease followed by increase) at 50 °C, accounting for 76.0–94.3% of observed variations. Quantitative analysis demonstrated that these dominant patterns correlate with the evolution of maximum oil cluster volumes and their dynamic merging-splitting processes. Significantly, we identified temperature-sensitive preferential flow pathways that maintain stable oil phases independent of flow rate variations, occupying 17.1% and 13.6% of pore space at 20 °C and 50 °C, respectively. These findings advance our understanding of oil migration mechanisms by revealing temperature-dependent non-monotonic saturation patterns and quantifying the dynamics of preferential pathway formation, providing insights for optimizing reservoir development through enhanced characterization of fluid distribution patterns at varying depths and temperature conditions.

Bentonite is widely used as an engineering barrier in radioactive waste disposal. This study examined the hydromechanical behavior and microstructural evolution of a bentonite mixture under controlled hydration, utilizing real-time X-ray micro-CT imaging to capture transitions from granular to dense homogeneous states. The results demonstrated that, during the early stages of hydration, bentonite pellets experienced substantial swelling, filling inter-pellet voids and transforming from a loosely packed granular structure to a compact, homogeneous matrix. This transformation significantly reduced the porosity from an initial value of 20% to below 0.1% after 60 days, thereby substantially lowering the material’s permeability. Particle displacement analysis, employing digital image correlation techniques, revealed axial displacements of up to 2.6 mm and radial displacements of up to 0.9 mm, highlighting pronounced void closure and structural reorganization. The study also examined the influence of initial dry density heterogeneities on swelling pressure and permeability, providing insights for optimizing barrier design. The findings affirm that hydrated bentonite serves as a highly effective low-permeability barrier for sealing deep geological repositories. Its capacity for environmental adaptation, demonstrated through self-healing and densification, further reinforces its suitability for critical and long-term engineering applications.