Search Results (81)

Enhanced Geothermal Systems (EGS) extend geothermal energy beyond conventional hydrothermal resources but face challenges in creating sustainable heat exchangers in low-permeability formations. This review synthesizes achievements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE), a field laboratory advancing EGS readiness in 175–230 °C granitic basement. From 2017 to 2025, drilling, multi-stage hydraulic stimulation, and monitoring established feasibility and operating parameters for engineered reservoirs. Hydraulic connectivity was created between highly deviated wells with ~300 ft vertical separation via hydraulic and natural fracture networks, validated by sustained circulation tests achieving 10 bpm injection at 2–3 km depth. Advanced monitoring (DAS, DTS, and microseismic arrays) delivered fracture propagation diagnostics with ~1 m spatial resolution and temporal sampling up to 10 kHz. A data infrastructure of 300+ datasets (>133 TB) supports reproducible ML. Geomechanical analyses showed minimum horizontal stress gradients of 0.74–0.78 psi/ft and N–S to NNE–SSW fractures aligned with maximum horizontal stress. Near-wellbore tortuosity, driving treating pressures to 10,000 psi, underscores completion design optimization, improved proppant transport in high-temperature conditions, and coupled thermos-hydro-mechanical models for long-term prediction, supported by AI platforms including an offline Small Language Model trained on Utah FORGE datasets. Full article

Faults and fractures play a critical role in subsurface systems; they may act as hydrocarbon traps, compartmentalize reservoirs, or serve as conduits for fluid migration across stratigraphic intervals. Consequently, fault delineation from seismic data plays a key role in reservoir characterization. This study presents a workflow for generating ant-tracking attribute volumes using multiple structural attributes to enhance fault/fracture delineation. Our results were thereafter validated with formation microimager (FMI) data. The workflow involves a sequential process comprising seismic data conditioning, structural attribute computation, and ant-tracking volume generation. Variance, curvature, and amplitude contrast attributes were calculated on conditioned 3D seismic data and subsequently used as input for the ant-tracking process. Parameter optimization was conducted through an iterative process of varying individual parameters and qualitatively assessing the results against key seismic features in both vertical sections and time slices. The ant-tracking volumes generated from individual attribute volumes were integrated to produce a composite volume, which served as input for automatic fault extraction. The resultant fault patch orientations were consistent with the formation microimager (FMI) log orientations. The integration of multiple structural attributes within the ant-tracking workflow significantly enhanced fault and fracture delineation by leveraging the complementary strengths of each attribute. Full article

Smartphone-based strain monitoring of structural components is an emerging approach to structural health monitoring. However, the existing techniques suffer from limited accuracy and poor cross-device adaptability. This study aims to optimize the smartphone-based Micro Image Strain Sensing (MISS) method by replacing the traditional Connected Component Labeling (CCL) algorithm with the arc-support line segments (ASLS) algorithm, thereby significantly enhancing the stability and adaptability of circle detection in micro-images captured by diverse smartphones. Additionally, this study evaluates the impact of lighting conditions and lens distortion on the optimized MISS method. The experimental results demonstrate that the ASLS algorithm outperforms CCL in terms of recognition accuracy (maximum error of 0.94%) and cross-device adaptability, exhibiting greater robustness against color temperature and focal length variations. Under fluctuating lighting conditions, the strain measurement noise remains within ±0.5 με and with a maximum error of 7.0 με compared to LVDT measurements, indicating the strong adaptability of the optimized MISS method to external light changes. Barrel distortion in microscopic images induces a maximum pixel error of 5.66%, yet the final optimized MISS method achieves highly accurate strain measurements. The optimized MISS method significantly improves measurement stability and engineering applicability, enabling effective large-scale implementation for strain monitoring of civil infrastructure. Full article

Accurate and robust calibration of multifocal plenoptic cameras is essential for high-precision 3D light field reconstruction. In this work, we propose a blur feature-guided cascaded calibration for the plenoptic camera. First, white images at different aperture values are used to estimate the high-confidence center point and radius of micro-images, and the defocus theory is used to estimate the initial values of the intrinsic parameters. Second, the gradient value is introduced to quantify the degree of blurring of the corner points, which are then divided into three types: clear, semi-clear, and blurred. Furthermore, a joint geometric constraint model of epipolar lines and virtual depth is constructed, and the coordinates of the semi-clear and blurred corner points are optimized in a step-by-step manner by using the clear corner point coordinates. The micro-image center ray projection equation is then devised to assist in the optimization of the microlens array core parameters and establish blur-adaptive credibility weights, thereby constructing a global nonlinear optimization. Finally, the proposed method is tested on both simulated and captured datasets, and the results exhibit superior performance when compared with the established methods described by Labussière, Nousias, and Liu. The proposed method excels in corner feature extraction, calibration accuracy of both internal and external parameters, and calibration sensitivity when applied to multifocal-length light field cameras, highlighting its advantages and robustness. Full article

To improve the accuracy of three-dimensional (3D) reconstruction under microscopic conditions for laser-induced breakdown spectroscopy (LIBS), this study developed a novel visual platform by integrating an industrial CCD camera with a microscope. A customized microscale calibration target was designed to calibrate intrinsic and extrinsic camera parameters accurately. Based on the pinhole imaging model, disparity maps were obtained via pixel matching to reconstruct high-precision 3D ablation morphology. A mathematical model was established to analyze how key imaging parameters—baseline distance, focal length, and depth of field—affect reconstruction accuracy in micro-imaging environments. Focusing on trace element detection in WC-Co alloy samples, the reconstructed ablation craters enabled the precise calculation of ablation volumes and revealed their correlations with laser parameters (energy, wavelength, pulse duration) and the physical-chemical properties of the samples. Multivariate regression analysis was employed to investigate how ablation morphology and plasma evolution jointly influence LIBS quantification. A nonlinear calibration model was proposed, significantly suppressing matrix effects, achieving R² = 0.987, and reducing RMSE to 0.1. This approach enhances micro-scale LIBS accuracy and provides a methodological reference for high-precision spectral analysis in environmental and materials applications. Full article

The neurobiology of chronic pain is complex and multifaceted, intertwining with the mesocorticolimbic system to regulate the behavioral and perceptional response to adverse stimuli. Specifically, the ventral tegmental area (VTA), the dopaminergic hub of the reward pathways located deep within the midbrain, is crucial for regulating the release of dopamine (DA) throughout the central nervous system (CNS). To better understand the nuances among chronic pain, VTA response, and therapeutics, implementing progressive approaches for mapping and visualizing the deep brain in real time during nociceptive stimulation is crucial. In this study, we utilize a fluorescence imaging platform with a genetically encoded calcium indicator (GCaMP6s) to directly visualize activity in the VTA during acute nociceptive stimulation in both healthy adult mice and adult mice with partial nerve ligation (PNL)-induced neuropathic pain. We also investigate the visualization of the analgesic properties of morphine. Deep brain imaging using our self-fabricated µ-complementary metal–oxide–semiconductor (CMOS) imaging device allows the tracking of the VTA’s response to adverse stimuli. Our findings show that nociceptive stimulation is associated with a reduction in VTA fluorescence activity, supporting the potential of this platform for visualizing pain-related responses in the central nervous system. Additionally, treatment with morphine significantly reduces the neuronal response caused by mechanical stimuli and is observable using the CMOS imaging platform, demonstrating a novel way to potentially assess and treat neuropathic pain. Full article

The aim of this work was to design a coil for magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to analyze the morphology of cells in vitro. This newly developed hardware, due to compatibility to the 1.5-Tesla MRI scanner (GE Healthcare, Boston, MA, USA), allows for the characterization of cell cultures in vitro. To adapt a designed coil on the 1.5-Tesla MRI scanner, some changes in hardware and software were carried out. The advantage of the designed receiving circuit is the ability to perform MRI with a resolution of 80 μm × 80 μm pixel size. Additionally, this coil can be used to visualize cell cultures and tissue sections, which, due to their small dimensions, could not be imaged on standard MRS and MRI coils at 1.5 Tesla. Full article

Addressing the issue of lifespan prediction for electronic packages under thermal loading, this paper proposes a method for predicting the lifespan of electronic packages based on ultrasonic microimaging. Firstly, experimental samples equipped with flip-chip packages were designed and fabricated and subjected to aging through thermal cycle acceleration tests. Ultrasonic microscopy was utilized to periodically acquire ultrasonic image data for monitoring solder joint degradation. Secondly, the internal ultrasonic wave propagation mechanism within electronic packages was investigated, establishing a qualitative relationship between the intensity in the central region of the solder joint’s ultrasonic image and internal defects within the joint. Image processing techniques were applied to enhance the quality of the solder joint images, and the mean intensity in the central region of the solder joint image was extracted as a failure feature. Finally, based on the extracted failure feature, a data-driven failure model for solder joints was developed, which predicts the lifespan of the solder joints based on cumulative failure probability. The research results indicate that the proposed model accurately describes the failure process of solder joints and effectively differentiates the lifespan variations among solder joints at different locations on the chip. This provides theoretical support for the reliability assessment of electronic package solder joints and holds practical value for enhancing the overall reliability of electronic packaging components. Full article

Light field camera depth estimation is a core technology for high-precision three-dimensional reconstruction and realistic scene reproduction. We propose a depth estimation algorithm that fuses blurry features and planar geometric structure priors, aimed at overcoming the limitations of traditional methods in neighborhood selection and mismatching in weak texture regions. First, by constructing a multi-constraint adaptive neighborhood microimage set, the microimages with the lowest blur degree are selected to calculate matching costs, and sparse feature correspondence relationships are used to propagate depth information. Second, planar prior knowledge is introduced to optimize pixel matching costs in weak texture regions, and weights are dynamically adjusted and pixel matching costs are updated during the iterative propagation process within microimages based on matching window completeness. Then, potential mismatched points are eliminated using epipolar geometric relationships. Finally, experiments were conducted using public and real-world datasets for verification and analysis. Compared with famous depth estimation algorithms, such as Zeller and BLADE, the Our method demonstrates superior performance in quantitative depth estimation metrics, scene reconstruction completeness, object edge clarity, and depth scene coverage, providing richer and more accurate depth information. Full article

Underground reservoir technology in coal mines enables the effective storage and utilization of water resources disturbed by mining activities. Owing to the effects of mining operations and water extraction/injection activities, the water head in underground reservoirs fluctuates dynamically. The total bearing capacity of a coal pillar dam is significantly reduced due to the combined effects of overlying rock stress, dynamic and static water pressures, and mining-induced stresses, which are critical for ensuring the safe operation of underground reservoirs. Based on the correlation between different water head heights and the corresponding water pressures on the coal pillar dam, a custom-made coal rock pressure water immersion test device was used to saturate the coal samples under various water pressure conditions. The mechanical deformation and failure characteristics of the samples and fracture propagation patterns under different water pressure conditions were studied using uniaxial compression, acoustic emission (AE), and three-dimensional X-ray microimaging. The results indicated that, compared with the dry state, the peak strain of the water-immersed coal samples increased to varying degrees with increasing water pressure. Additionally, the average porosity and the number of pores with diameters in the range of 0 to 150 μm significantly increased in water-immersed coal samples. Under the combined influence of water immersion pressure and uniaxial stress, loading the water-saturated coal samples to the fracture damage threshold significantly intensified deformation, failure, and fracture propagation within the samples, and the failure mode changed from tension to a composite tensile–shear failure. Full article

Characterizing the fractal nature of shale pores is critical for understanding their heterogeneity, which significantly impacts hydrocarbon mobility. A critical technique in this analysis involves the digital evaluation of scanning electron microscopy (SEM) images. While the cumulative size distribution model is a viable method in SEM fractal analysis, its accurate application necessitates exhaustive microimaging of entire sample cross-sections, rendering it impractical. To address this challenge, we propose an innovative approach that develops a universal equation for this model, along with numerical solving methods. This approach expands the model’s applicability, enabling accurate fractal analysis of entire samples using only randomly selected microscopic fields. It enhances the existing framework for fractal modeling and potentially serves as a valuable tool for studying fractal structures. Using this method, we investigated the fractal characteristics of various macropore types across different lithological units in the Chang-7 shale of the Ordos Basin. Our findings indicate that macropore heterogeneity is influenced by variations in pore type composition, their response under compaction, and organic acid dissolution, all of which are driven by differences in lithology. These findings provide new insights into the mechanisms driving macropore heterogeneity from the perspective of lithological and pore-type variations, potentially yielding valuable implications for the exploration and development of Chang-7 shale oil. Full article

Polyethylene terephthalate (PET) is one of the most produced plastic materials in the world. The emergence of microplastics and nanoplastics (MPs/NPs) as a significant environmental contaminant has become a matter of increasing concern. While the toxicological effects of PET NPs have been widely researched, there is a lack of methodologies for studying their accumulation. The present study introduces a novel method to monitor the distribution of PET NPs in germinating wheat (Triticum aestivum L.) seeds. This involves the functionalization of superparamagnetic iron oxide nanoparticles (SPIONs) with PET NPs (PET–fSPIONs) coupled with magnetic resonance microimaging (µMRI) to provide insight into their distribution within the seed. The present study has demonstrated that PET–fSPIONs accumulate in specific regions of germinating wheat seeds, including the shoot apical meristem, the radicle, the coleoptile, the plumule, and the scutellum. Furthermore, the accumulation of PET–fSPIONs has been shown to exert a discernible effect on spin–spin relaxation (T₂), as observed via MRI and quantitative T₂ relaxation time analysis. The accumulation of PET NPs in embryo regions was also confirmed by SEM. Diffusion-weighted magnetic resonance imaging (DW-MRI) and non-invasive chemical shift imaging analyses demonstrated that PET NPs resulted in restricted diffusion within the highlighted areas, as well as an impact on lipid content. Our study reveals that using µMRI with fSPIONs provides a non-invasive method to monitor the biodistribution of PET nanoparticles in wheat seeds. Additionally, it offers valuable insights into the microstructural interactions of PET. Full article

The aim of the presented research is to evaluate the potential performance of a new bending magnet X-ray beamline—PolyX, designed for microimaging and microspectroscopy at the National Synchrotron Radiation Centre SOLARIS in Krakow. Due to the short beamline length (<15 m), PolyX uses compact polycapillary and single-bounce monocapillary optics for X-ray focusing in the 4–15 keV energy range. Polycapillary optics require a dedicated approach for an efficient simulation of X-ray propagation in multiple capillary channels. Therefore, the PolyX beamline was ray traced by combining XRT (XRayTracer) and polycap libraries. In addition, to estimate the X-ray fluorescence spectra excited by focused beams, Monte Carlo simulations were conducted using XMI-MSIM. All simulations were aimed to estimate the crucial X-ray beam properties, i.e., the flux, the spot size, and the energy spectrum, for monochromatic and polychromatic X-ray beams. Full article

Background: Intraoperative frozen sections (FS) are frequently used to establish the diagnosis of lung cancer when preoperative examinations are not conclusive. The downside of FS is its resource-intensive nature and the risk of tissue depletion when small lesions are assessed. Ex vivo fluorescence confocal microscopy (FCM) is a novel microimaging method for loss-free examinations of native materials. We tested its suitability for the intraoperative diagnosis of lung tumors. Methods: Samples from 59 lung resection specimens containing 45 carcinomas were examined in the FCM. The diagnostic performance in the evaluation of malignancy and histological typing of lung tumors was evaluated in comparison with FS and the final diagnosis. Results: A total of 44/45 (98%) carcinomas were correctly identified as malignant in the FCM. A total of 33/44 (75%) carcinomas were correctly subtyped, which was comparable with the results of FS and conventional histology. Our tests documented the excellent visualization of cytological features of normal tissues and tumors. Compared to FS, FCM was technically less demanding and less personnel intensive. Conclusions: The ex vivo FCM is a fast, effective, and safe method for diagnosing and subtyping lung cancer and is, therefore, a promising alternative to FS. The method preserves the tissue without loss for subsequent examinations, which is an advantage in the diagnosis of small tumors and for biobanking. Full article

Glass fiber-reinforced polymer (GFRP) laminates are used in many applications because of their availability, high mechanical properties, and cost-effectiveness. Fiber defects in the form of waviness or wrinkles can occur during the production of multilayered laminates. When curved laminates of significant thickness are produced, the likelihood of such defects increases. Studies have confirmed that fiber deformation during manufacture leads to a reduction in the mechanical properties of laminates. Therefore, early detection of such defects is essential. The main part of this paper deals with research into the possibility of using active infrared thermography to detect wrinkles in curved multilayered GFRP laminates. The size of the artificial wrinkles was assessed by analyzing scans and microimages. The shape deformations of the samples were evaluated by comparing the samples with the mold and the assumed nominal shape. The influence of the out-of-autoclave manufacturing process on the reduction in wrinkles formed without significantly affecting the internal structure of the laminate is presented in this work. This research demonstrated the ability to detect wrinkles in thick curved laminates using active infrared thermography. However, it also showed how the interpretation of the thermographic results is affected by the curvature of the structure, the lack of uniform heating, and the configuration of the thermographic setup. Full article