Search Results (1,939)

Hydrogen is widely recognized as a key enabler of the clean energy transition, but the lack of safe, efficient, and scalable storage technologies continues to hinder its broad deployment. Conventional hydrogen storage approaches, such as compressed hydrogen storage, cryo-compressed hydrogen storage, and liquid hydrogen storage, face limitations, including high energy consumption, elevated cost, weight, and safety concerns. In contrast, solid-state hydrogen storage using carbon-based adsorbents has gained growing attention due to their chemical tunability, low cost, and potential for modular integration into energy systems. This review provides a comprehensive evaluation of hydrogen storage using carbon-based materials, covering fundamental adsorption mechanisms, classical materials, emerging architectures, and recent advances in computationally AI-guided material design. We first discuss the physicochemical principles driving hydrogen physisorption, chemisorption, Kubas interaction, and spillover effects on carbon surfaces. Classical adsorbents, such as activated carbon, carbon nanotubes, graphene, carbon dots, and biochar, are evaluated in terms of pore structure, dopant effects, and uptake capacity. The review then highlights recent progress in advanced carbon architectures, such as MXenes, three-dimensional architectures, and 3D-printed carbon platforms, with emphasis on their gravimetric and volumetric performance under practical conditions. Importantly, this review introduces a forward-looking perspective on the application of artificial intelligence and machine learning tools for data-driven sorbent design. These methods enable high-throughput screening of materials, prediction of performance metrics, and identification of structure–property relationships. By combining experimental insights with computational advances, carbon-based hydrogen storage platforms are expected to play a pivotal role in the next generation of energy storage systems. The paper concludes with a discussion on remaining challenges, utilization scenarios, and the need for interdisciplinary efforts to realize practical applications. Full article

Porous ceramics have been widely used in various fields. In this paper, porous ceramics with through-hole structures were prepared using a novel and eco-friendly gel casting method with carrageenan as the gelling agent. Especially, the idea of large size particle stacking is introduced into the gel casting process. By introducing large size alumina aggregates as raw materials, and small size micropowders as filling materials, micropores were directly formed after the green body was sintered. To tune the pore size, pore structure, gas permeability, the strength of the final porous ceramics, the components of the raw materials including the alumina aggregates, the filling materials, and sintering additives in the slurry were precisely designed. Porous Al₂O₃-based ceramics with high gas permeability, high flexural strength, and moderate porosity were finally obtained. Full article

The evaluation of the wave-induced seabed stability such as liquefaction and shear failure is one of the factors that must be considered in the design of marine infrastructures. Due to the transformation within the porous medium, the wave-induced soil response manifests itself as a phase delay in the dynamic wave pressure on the seabed surface, which is referred to as “phase-lag”. In this study, the analytical solutions of wave-induced soil response in an infinite porous seabed are further examined to clarify the effects of phase-lags. Based on the coefficient of relative rigidity of the soil skeleton to the pore fluid ($R_k$), a simplified approximation is derived. The expressions of the phase-lags for wave-induced soil response are presented for various cases. Moreover, the phase-lag effects on instantaneous liquefaction and shear failure are analysed. Based on the parametric study, it is concluded the extreme phase-lag for wave-induced pore pressure increases with increasing $R_k$, the extreme phase-lag for horizontal effective stress and shear stress decrease with increasing $R_k$. Furthermore, the liquefaction zone and shear failure zone increase with increasing $R_k$. Full article

One of the hottest topics in current research is the creation of scaffolds for bone tissue restoration that are both biocompatible and tissue inducible. The aim of this work is to develop a numerical model to study the effects of temperature, velocity, and scaffold structure on flow and biomechanical properties, as well as to optimize design parameters to improve tissue engineering outcomes. The results show that the fluid transport properties of cylindrical unit cell architectures are superior. For effective mass transfer, pore diameters > 4 mm and porosity > 60% are ideal design parameters. With important clinical and financial implications, these discoveries offer theoretical direction and economical methods for developing bone tissue engineering. Full article

Sustainable deepwater drilling for oil and gas offers significant potential. In this work, we synthesized a nanoscale collapse-prevention agent by grafting didecyldimethylammonium chloride onto spherical nano-silica and characterized it using Fourier-transform infrared spectroscopy, thermogravimetric analysis, zeta-potential, and particle-size measurements, as well as SEM and TEM. Adding 1 wt% of this agent to a bentonite slurry only marginally alters its rheology and maintains acceptable low-temperature flow properties. Microporous-membrane tests show filtrate passing through 200 nm pores drops to 55 mL, demonstrating excellent plugging. Core-immersion studies reveal that shale cores retain integrity with minimal spalling after prolonged exposure. Rolling recovery assays increase shale-cutting recovery to 68%. Wettability tests indicate the water contact angle rises from 17.1° to 90.1°, and capillary rise height falls by roughly 50%, reversing suction to repulsion. Together, these findings support a synergistic plugging–adsorption–hydrophobization mechanism that significantly enhances wellbore stability without compromising low-temperature rheology. This work may guide the design of high-performance collapse-prevention additives for safe, efficient deepwater drilling. Full article

Immunoassays relying on highly specific antigen–antibody recognition are important tools for effectively measuring the levels of various targets. Efforts have been made in the development of various methods to improve the detection sensitivity and stability of immunoassays. Covalent organic frameworks (COFs), as an emerging class of novel crystalline porous materials, have unique advantages such as flexible designability, high surface area, excellent stability, tunable pore sizes, and multiple functionalities. They have great potential as novel sensory materials. Herein, we summarize the advances of COFs in electrochemical and optical immunoassays serving as electrode modifiers, signal indicators, enzyme or probe carriers, etc. Meanwhile, the design and application of typical COFs-based immunoassays in the determination of different targets are discussed in detail. Finally, challenges and future perspectives are presented. Full article

As 3D concrete printing emerges as a transformative construction method, its structural safety remains hindered by unresolved issues of mechanical anisotropy and interlayer defects. To address this, we systematically investigate the failure mechanisms and mechanical performance of basalt fiber-reinforced 3D-printed magnesite concrete. A total of 30 cube specimens (50 mm × 50 mm × 50 mm)—comprising three types (Corner, Stripe, and R-a-p)—were fabricated and tested under compressive and splitting tensile loading along three orthogonal directions using a 2000 kN electro-hydraulic testing machine. The results indicate that 3D-printed concrete exhibits significantly lower strength than cast-in-place concrete, which is attributed to weak interfacial bonds and interlayer pores. Notably, the R-a-p specimen’s Z-direction compressive strength is 38.7% lower than its Y-direction counterpart. To complement the mechanical tests, DIC, CT scanning, and SEM analyses were conducted to explore crack development, internal defect morphology, and microstructure. A finite element model based on the experimental data successfully reproduced the observed failure processes. This study not only enhances our understanding of anisotropic behavior in 3D-printed concrete but also offers practical insights for print-path optimization and sustainable structural design. Full article

This study conducted uniaxial creep tests on coal samples under both natural and water-saturated conditions for durations of about 180 days per sample to study the stability of coal pillar dams of the Daliuta Coal Mine underground reservoir. Combined with synchronized acoustic emission (AE) monitoring, the research systematically revealed the time-dependent deformation mechanisms and damage evolution laws of coal under prolonged water immersion and natural conditions. The results indicate that water-immersed coal exhibits a unique negative creep phenomenon at the initial stage, with the strain rate down to −0.00086%/d, attributed to non-uniform pore compaction and elastic rebound effects. During the steady-state creep phase, the creep rates under water-immersed and natural conditions were comparable. However, water immersion led to an 11.4% attenuation in elastic modulus, decreasing from 2300 MPa to 2037 MPa. Water immersion would also suppress AE activity, leading to the average daily AE events of 128, which is only 25% of that under natural conditions. In the accelerating creep stage, the AE event rate surged abruptly, validating its potential as an early warning indicator for coal pillar instability. Based on the identified long-term strength of the coal sample, it is recommended to maintain operational loads below the threshold of 9 MPa. This research provides crucial theoretical foundations and experimental data for optimizing the design and safety monitoring of coal pillar dams in CMURs. Full article

In order to improve the durability of loess-based composite coal gangue porous planting concrete (LCPC), the effects of fly ash and slag powder content on the durability and microstructure of LCPC were studied. In this paper, fly ash and slag powder were mixed into LCPC, and freeze-thaw cycle and dry-wet cycle tests were carried out. The compressive strength, dynamic elastic modulus, and mass change were used as evaluation indices to determine the optimal mix ratio for LCPC durability. Scanning electron microscopy (SEM) was performed, and the experimental design was carried out with the water–cement ratio, fly ash, and slag powder content as variables. The microstructure characteristics of LCPC were analyzed. The results show that the maximum number of freeze-thaw cycles can reach 35 times and the maximum number of dry-wet cycles can reach 50 when 5% fly ash and 20% slag powder are used. With an increase in the water-cement ratio, the skeleton of the loess gradually became complete, and its structure became more compact. In the micro-morphology diagram, the mixed fly ash and slag powder particles are not obvious, but with an increase in dosage, the size of the cracks and pores gradually decreases. The incorporation of fly ash and slag powder can play a positive role in the durability of LCPC and improvement of its microstructure. The results of this study are crucial for improving the application performance of ecological restoration, soil improvement, and long-term stability of structures, and can provide a scientific basis for the sustainable development of environmentally friendly building materials. Full article

China has abundant shale oil and gas resources, which have become a critical pillar for future energy substitution. However, due to the highly heterogeneous nature and complex pore structures of shale reservoirs, traditional plugging agents face significant limitations in enhancing plugging efficiency and adapting to extreme wellbore environments. In response to the technical demands of nanoparticle-based plugging in shale reservoirs, this study systematically investigated the microscopic interaction mechanisms of nano-plugging agent shell polymers (Ployk) with various reservoir minerals under different temperature and salinity conditions using molecular simulation methods. Key parameters, including interfacial interaction energy, mean square displacement, and system density distribution, were calculated to thoroughly analyze the effects of temperature and salinity variations on adsorption stability and structural evolution. The results indicate that nano-plugging agent shell polymers exhibit pronounced mineral selectivity in their adsorption behavior, with particularly strong adsorption performance on SiO₂ surfaces. Both elevated temperature and increased salinity were found to reduce the interaction strength between the shell polymers and mineral surfaces and significantly alter the spatial distribution and structural ordering of water molecules near the interface. These findings not only elucidate the fundamental interfacial mechanisms of nano-plugging agents in shale reservoirs but also provide theoretical guidance for the precise design of advanced nano-plugging agent materials, laying a scientific foundation for improving the engineering application performance of shale oil and gas wellbore-plugging technologies. Full article

As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. In response to these challenges, this article proposes a defect detection and classification method for laser welding seams of automotive brake joints based on machine vision inspection technology. Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. This article first analyzes the common types of weld defects in laser welding of automotive brake joints, including craters, holes, and nibbling, and explores the causes and characteristics of these defects. Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. The results show that the system can accurately identify and distinguish pits, holes, and undercutting defects in welds, with an average classification accuracy of over 90%. The detection and recognition rate of pit defects reaches 100%, and the detection accuracy of undercutting defects is 92.6%. And the overall missed detection rate is less than 3%, with both the missed detection rate and false detection rate for pit defects being 0%. The average detection time for each image is 0.24 s, meeting the real-time requirements of industrial automation. Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints. Full article

Fully printable carbon-based multiporous layered electrode perovskite solar cells (MPLE−PSCs) are close to being commercialized due to their excellent stability, their ability to easily be scaled up, and their amenability to mass production via non-vacuum fabrication processes. To improve their efficiency, it is important that detailed studies of the morphologies of mesoporous electrodes be carried out. In this study, we prepared five types of ZrO₂ spacer layers for MPLE−PSCs, and the morphology of ZrO₂ and device performance were evaluated using a scanning electron microscope, nitrogen adsorption/desorption measurements, electrode resistance measurements, UV-visible light reflectance measurements, and current density–voltage measurements. The results reveal that the adequate specific surface area and pore size distribution of mesoporous ZrO₂ provided high insulation ability when used as spacers between electrodes and light absorbance, resulting in a 10.92% photoelectric conversion efficiency with a 23.22 mA cm⁻² short-circuit current density. This information can serve as a guideline for designing morphologies useful for producing high-efficiency devices. Full article

Accurate pre-drilling mud weight window (MWW) prediction is crucial for drilling fluid design and wellbore stability in complex geological formations. Traditional physics-based approaches suffer from subjective parameter selection and inadequate handling of multi-mechanism over-pressured formations, while machine learning methods lack physical constraints and interpretability. This study develops a novel physics-guided deep learning framework integrating rock mechanics theory with deep neural networks for enhanced MWW prediction. The framework incorporates three key components: first, a physics-driven layer synthesizing intermediate variables from rock physics calculations to embed domain knowledge while preserving interpretability; second, a geological sequence-matching algorithm enabling precise stratigraphic correlation between offset and target wells, compensating for lateral geological heterogeneity; third, a long short-term memory network capturing sequential drilling characteristics and geological structure continuity. Case study results from 12 wells in northwestern China demonstrate significant improvements over traditional methods: collapse pressure prediction error reduced by 40.96%, pore pressure error decreased by 30.43%, and fracture pressure error diminished by 39.02%. The proposed method successfully captures meter-scale pressure variations undetectable by conventional approaches, providing critical technical support for wellbore design optimization, drilling fluid formulation, and operational safety enhancement in challenging geological environments. Full article

Currently, the visual study of the structure of building materials and products is gradually supplemented by intelligent algorithms based on computer vision technologies. These algorithms are powerful tools for the visual diagnostic analysis of materials and are of great importance in analyzing the quality of production processes and predicting their mechanical properties. This paper considers the process of analyzing the visual structure of non-autoclaved aerated concrete products, namely their porosity, using the YOLOv11 convolutional neural network, with a subsequent prediction of one of the most important properties—thermal conductivity. The object of this study is a database of images of aerated concrete samples obtained under laboratory conditions and under the same photography conditions, supplemented by using the author’s augmentation algorithm (up to 100 photographs). The results of the porosity analysis, obtained in the form of a log-normal distribution of pore sizes, show that the developed computer vision model has a high accuracy of analyzing the porous structure of the material under study: Precision = 0.86 and Recall = 0.88 for detection; precision = 0.86 and recall = 0.91 for segmentation. The Hellinger and Kolmogorov–Smirnov statistical criteria, for determining the belonging of the real distribution and the one obtained using the intelligent algorithm to the same general population show high significance. Subsequent modeling of the material using the ANSYS 2024 R2 Material Designer module, taking into account the stochastic nature of the pore size, allowed us to predict the main characteristics—thermal conductivity and density. Comparison of the predicted results with real data showed an error less than 7%. Full article

Multi-layer cell constructs produced in vitro are an innovative treatment option to support the growing demand for therapy in regenerative medicine. Our research introduces a novel construct integrating organ-derived decellularised extracellular matrix (dECM) hydrogels and 3D-printed biodegradable polymer meshes composed of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and poly(3-hydroxybutyrate-co-4-hydroxybutyrate) (P34HB) to support and maintain multiple layers of different cell types. We achieved that by integrating the mechanical stability of PHBV+P34HB, commonly used in the food storage industry, with a dECM hydrogel, which replicates organ stiffness and supports cellular survival and function. The construct was customised by adjusting the fibre arrangement and pore sizes, making it a suitable candidate for a personalised design. We showed that the polymer is degradable after precoating it with PHB depolymerase (PhaZ), with complete degradation achieved in 3–5 days and delayed by adding the hydrogel to 10 days, enabling tuneable degradation for regenerative medicine applications. Finally, as a proof of concept, we composed a three-layered tissue in vitro; each layer represented a different tissue type: epidermal, vascular, and subcutaneous layers. Possible future applications include wound healing and diabetic ulcer paths, personalised drug delivery systems, and personalised tissue implants. Full article