This study established an integrated cement sheath integrity experimental device and proposed a strain equivalence method to quantitatively reproduce the cement sheath deformation under downhole conditions in the laboratory to evaluate the effect of cyclic differential pressure (CDP) in underground energy storage wells (UESWs) on cement sheath integrity (CSI). The results indicate that when the cement sheath used for UESWs was cured for 7 and 28 d at 90 °C and 21 MPa, its elasticity moduli were 7.31 GPa and 7.38 GPa and its maximum deviatoric stresses were 35.2 MPa and 39.2 MPa, respectively. Combining the above mechanical parameters, the casing–cement sheath–formation mechanical models were used to calculate the stress and strain of the cement sheath. It can be found that at a differential pressure of 18 MPa, the cement sheath under downhole conditions was undergoing elastic deformation, and its first interface strain reached 0.0378%. In addition, when the cement sheath under experimental conditions reached the same strain, the equivalent differential pressure was 12.2 MPa. Furthermore, the CSI was measured. When the cement sheath was cured for 7, 14, and 21 days, an equivalent CDP of 12.2 MPa was applied to the cement sheath for a total of 90 cycles, and the cement sheath maintained good integrity. On the other hand, when the cement sheath was continuously cured for 28 d, the equivalent CDP was applied only 5 times (for a total of 95 cycles), gas channeling was recorded, and its integrity failed. Comparing the calculated and experimental results, under CDP, the cement sheath did not undergo real elastic deformation; instead, CDP caused strain accumulation and interfacial bonding degradation in the cement sheath with a skeleton pore structure, rather than elastic deformation.
IntroductionWeathered sandstone at the Dazu Rock Carvings is susceptible to progressive loss of intergranular cohesion under repeated moisture fluctuations and salt crystallization. This study evaluated a compatible nanolime treatment designed to enhance the mechanical resistance of weathered sandstone while preserving its visual appearance and pore connectivity.MethodsHigh-purity calcium hydroxide nanoparticles were synthesized via a one-step anion-exchange route. The synthesized nanolime and treated sandstone were characterized and evaluated using X-ray diffraction (XRD), transmission electron microscopy coupled with energy-dispersive spectroscopy (TEM/EDS), colorimetry, porosity and permeability measurements, uniaxial compressive strength (UCS) testing, nanoindentation mapping, accelerated wetting-drying and hygrothermal-salt aging tests, and in situ Leeb hardness monitoring.ResultsThe synthesized nanolime consisted predominantly of hexagonal portlandite platelets approximately 50–100 nm in size, with no detectable chloride-containing crystalline by-products under the applied characterization conditions. Nanolime treatment increased the mean UCS from 37.35 to 47.00 MPa while causing negligible changes in color, porosity, and permeability. Following accelerated aging, nanolime-treated specimens retained higher hardness and elastic modulus than both untreated specimens and those treated with traditional lime water. Field monitoring further showed rapid recovery of surface hardness within 24 h after treatment, followed by continued strengthening over 100 days in selected weathered zones.DiscussionThese results demonstrate that anion-exchange-derived nanolime provides mineral-compatible reinforcement while maintaining the visual and hydro-physical characteristics of weathered sandstone. Longer-term field monitoring and direct assessment of carbonation depth are still required to establish its long-term durability and service-life performance.
The use of agricultural waste materials and hybrid fiber reinforcement in concrete offers a sustainable approach for producing high-performance construction materials with improved mechanical properties and durability. This study investigated the mechanical, chemical durability, thermal, and microstructural performance of high-strength concrete incorporating 15% pyrolyzed coffee grounds (PCG) produced at 350 °C as a partial fine-aggregate replacement. Hooked-end steel fibers and alkali-treated banana fibers were used as hybrid reinforcements, while Response Surface Methodology (RSM) based on Central Composite Design (CCD) was employed to optimize the effects of fiber dosage and steel–banana hybridization ratio. Mechanical performance was evaluated through compressive, splitting tensile, and flexural strength tests, while durability was assessed under 10% NaCl, 5% HCl, and 5% HNO3 exposure. Microstructural characterization was conducted using SEM/EDX, XRD, and TGA/DTG analyses. The results showed that the combined incorporation of PCG and hybrid fibers enhanced concrete performance through improved crack-bridging, matrix densification, and pore refinement. The optimum mixture, containing 1.25%–1.50% total fiber dosage and a steel-to-banana fiber ratio of 80:20, achieved a compressive strength of 69.6 MPa, splitting tensile strength of 9.0 MPa, and flexural strength of 14.0 MPa. The same mixture exhibited superior chemical durability, with minimum mass losses of 2.45%, 3.90%, and 4.40% under NaCl, HCl, and HNO3 exposure, respectively. Microstructural analyses confirmed a denser matrix, stronger fiber–matrix bonding, reduced pore connectivity, and enhanced hydration-product formation, while TGA/DTG results indicated improved thermal stability. Validation experiments closely matched model predictions, confirming the reliability of the CCD-RSM models. Overall, the synergistic use of pyrolyzed coffee grounds and hybrid steel–banana fibers produced a durable, high-strength, and environmentally sustainable concrete suitable for structural applications in aggressive environments while promoting the valorization of coffee-processing waste within a circular economy framework.
Driven by recent advances in machine learning, steel rolling is transitioning toward intelligent, data-centric operation. This study presents a unified machine learning framework for predictive, closed-loop quality control of steel strips across hot and cold rolling processes. The model explicitly quantifies the complex, nonlinear effects of key operational parameters, such as rolling force and gap settings, on final product quality. The proposed framework enables real-time monitoring and dynamic compensation of dimensional deviations and shape defects, thereby improving dimensional consistency and process stability. Additionally, a multimodal perception-based system is introduced for early anomaly detection and coordinated parameter optimization, facilitating adaptive setpoint adjustment and proactive defect mitigation. Collectively, these machine learning-driven approaches enhance product uniformity and rolling efficiency while offering a scalable pathway toward more autonomous, resource-efficient, and sustainable rolling operations, aligning with the paradigm of AI-driven sustainable manufacturing.
Glass transition (Tg) and melting (Tm) temperatures set the processing window, service range, and end-use performance of polymers, making their rapid prediction central to accelerated materials design. Experiments and simulations are accurate but costly, while classical structure–property models depend on hand-crafted descriptors; machine learning instead maps chemical structure to thermal transitions end to end. This review organizes machine-learning prediction of Tg and Tm around three pillars—molecular representation, model architecture, and interpretability—and foregrounds the features that separate polymer informatics from generic molecular machine learning: repeat-unit periodicity, chain-length-invariant encoding, copolymer sequence, and stereoregularity. We compare descriptors, fingerprints, graph neural networks, and coarse-grained schemes; traditional, deep, transfer, and multi-task models under data scarcity; and methods for quantifying predictive uncertainty and delimiting applicability domains. We treat Tg and Tm as physically distinct targets, since Tm additionally reflects crystal packing, hydrogen bonding, and chain symmetry. A recurring theme is label quality: calorimetric, dynamic-mechanical, and thermomechanical measurements define these transitions differently, so pooled datasets embed instrumental as well as chemical variance. We critically assess explainable artificial intelligence methods and the way accuracy is reported, arguing that headline metrics are not comparable across studies, and we examine how the first community-scale prediction challenge, chemistry-aware data splitting, and calibrated uncertainty can place reporting on a common footing. Finally, we connect representations, architectures, and interpretability to high-performance and sustainable polymer design, synthesizability-aware screening, and closed-loop discovery, and outline open challenges in data scarcity, domain transfer, and chemical-space extrapolation.
Salt-induced asphalt interface failure severely limits the service life of salt-storage snow-melting asphalt pavements. Employing eco-friendly sodium formate as organic salts representative, this study employs interfacial strength tests and molecular modeling to reveal salt interactions with asphalt and asphalt-aggregate interfaces. On this basis, the degradation pathways of interfacial interaction under salt-water coupling are further revealed by introducing water molecular to construct the ternary system coupled (asphalt/water/aggregate) interface molecular models. Key findings reveal that sodium formate storage filler incorporation significantly reduces asphalt components diffusivity by 34.5%–41.9% within the asphalt model. This inhibition impedes molecular conformational adjustment and accelerates asphalt damage accumulation. Concurrently, sodium formate molecule degrades the asphalt/aggregate interfacial properties through the dual mechanism: Salt enhances asphalt molecular surface mobility, while simultaneously promoting interfacial salt aggregation. The dual synergistic effect would reduce the molecular folding level and interfacial electrostatic energy, which leads to the adhesion properties showing high salt sensitivity. Comparatively, it was found that silicon dioxide minerals showed superior interfacial stability than calcium carbonate minerals in salt-eroding environments. Under saline-water coupling conditions, progressive salt precipitation from salt-storage asphalt induces a sustained increase in salinity concentration of water layer. This phenomenon can cause the reduction in the water mobility by about 30% and an increase in the interlayer retention effect, and thereby forming a barrier that further weakens interface interaction energy. These results provide theoretical foundation for optimizing salt-storage asphalt pavement design and enhancing the sustainability of asphalt pavements.
Structural supercapacitors (SSCs) are an emerging class of multifunctional materials that combine energy storage with load-bearing capability, offering a pathway to lighter and more efficient composite systems in applications such as aerospace, automotive, and renewable energy. Although significant progress has been made in improving electrochemical performance, most research has focused on metrics such as capacitance and energy density, with less attention given to structural performance, scalability, and real-world implementation. This Perspective highlights a growing gap between laboratory-scale demonstrations and practical applications. Key challenges include limited consideration of mechanical behavior, a lack of understanding of interfacial interactions, the underdeveloped role of solid polymer electrolytes as structural components, and the absence of standardized evaluation methods. In addition, many fabrication approaches are not compatible with large-scale composite manufacturing, hindering translation beyond the lab. We argue that SSCs should be designed as fully integrated systems, where electrochemical, mechanical, and manufacturing requirements are considered together. By focusing on interphase design, mechanically robust electrolytes, and scalable processing methods, the field can move toward practical deployment. This work provides a framework and future directions to guide the development of SSCs into viable structural energy storage solutions.
The disposal of red mud (RM), a hazardous industrial residue, has become a global environmental challenge. This study aims to develop a well-performing, high-strength RM-based geopolymer (RG) using RM, fly ash, and granulated blast furnace slag. RM was calcined to maximize its reactivity. Taguchi orthogonal method was employed to systematically investigate the effects of solid ratio, calcination temperature, water-solid (W/S) ratio, alkaline activator modulus, and dosage on the workability, mechanical properties, and bulk density of RG. ANOVA was performed to determine the optimal mix for the mechanical performance of RG. The results indicated that after calcining RM at 800 °C, the 28-day compressive strength of RG increased by 35.99%, reaching 51.11 MPa. The W/S ratio is the primary factor affecting the mechanical properties of RG. Excessive water suppresses the generation of N-A-S-H and C-A-S-H gels, weakening the RG performance.
IntroductionPulsed Alternating Current Field Measurement (PACFM) has been proven to offer significant advantages in detecting surface and subsurface defects in structural components, and has been successfully applied to nondestructive testing of multilayer structures such as aircraft wings. Although pulsed excitation response signals carry rich time-domain and frequency-domain information, conventional methods that rely solely on a single time-domain feature are susceptible to noise interference, which may reduce detection accuracy and limit the ability to distinguish different defect types.MethodsTo overcome this limitation, this study employed the Smoothed Pseudo Wigner–Ville Distribution (SPWVD) to perform time–frequency analysis on the defect response signals, generating three dimensional time–frequency distribution maps that include time, frequency, and amplitude dimensions. Subsequently, Principal Component Analysis (PCA) was applied to reduce the dimensionality of the time–frequency results, eliminate redundant information, and extract the signal features characterized by the parameter ω2, which served as the key feature for defect identification and classification.ResultsExperiments were carried out on an aluminum plate with artificially machined defects of varying depths and positions. The results show that the extracted ω2 signal features can accurately identify and distinguish both surface and subsurface defects, achieving clear classification under different defect conditions.DiscussionThe proposed strategy combining SPWVD with PCA effectively utilizes the joint time–frequency information of the pulsed responses, overcoming the noise sensitivity of single-domain features. The successful classification of surface and subsurface defects in the experiments indicates that this method provides a reliable technical means for inspecting multilayer structures.
Lightweight lattice structures based on Triply Periodic Minimal Surface (TPMS) geometries are promising sandwich-core candidates due to their high stiffness-to-weight ratio and favorable energy absorption characteristics. Fused deposition modeling (FDM) enables the fabrication of these complex architectures using reinforced thermoplastics such as carbon-fiber-reinforced polylactic acid (PLA-CF). During sandwich manufacturing, lattice cores may experience simultaneous thermal and compressive loads arising from adhesive curing and consolidation processes, making their thermo-mechanical stability a critical design requirement. This study investigates the compressive behavior of FDM-manufactured PLA-CF gyroid lattices with 20% relative density under isothermal loading at 20, 50, and 80 °C. Experimental results showed a pronounced temperature-dependent degradation in mechanical performance. The compressive modulus decreased from 84.23 ± 1.76 MPa at 20 °C to 44.89 ± 4.92 MPa at 50 °C (−47%) and 1.60 ± 0.02 MPa at 80 °C (−98% reduction). Similarly, the compressive strength decreased from 2.68 ± 0.06 MPa to 1.17 ± 0.11 MPa (−56%) and 0.049 ± 0.004 MPa (−98% reduction), accompanied by a transition from stable progressive collapse to severe thermal softening above the glass transition region. A finite element model was developed using nominal tensile properties and calibrated through temperature-dependent lattice-scale correction factors identified from the compression tests. The calibrated model reproduced the experimental thermo-mechanical response, providing a practical predictive framework for preliminary manufacturing-oriented assessment and process design of FDM lattice sandwich cores.
BackgroundTendons have limited vascularity and low cell density, and their spontaneous healing often results in fibrosis and impaired mechanical properties. This study sought to construct polyphosphate (polyP)–functionalized silk fibroin/polycaprolactone (SF/PCL) electrospun nanofiber scaffolds and evaluate their effects on tendon regeneration.MethodsSF/PCL composite nanofibers were fabricated by electrospinning, incorporated with polyP, and then subjected to methanol treatment to induce β-sheet formation. The scaffolds were characterized by scanning electron microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), water contact angle measurements, and tensile testing. In vitro experiments using tendon-related cells and L929 fibroblasts were conducted to assess their cytocompatibility and function (CCK-8, live/dead staining, scratch assay, reactive oxygen species (ROS) and adenosine triphosphate (ATP) assays, qPCR, and Western blot for collagen type I (COL1), decorin (DCN), and proliferating cell nuclear antigen (PCNA). In vivo experiments were carried out in a rat Achilles tendon defect model, in which the tissue repair capability of the nanofibers was examined using H&E and Masson’s trichrome staining.ResultsThe fibers obtained were in the submicron range. Fourier Transform Infrared Spectroscopy (FTIR) spectra showed P=O, P–O, and P–O–P bands, confirming the presence of polyP. The water contact angle decreased from ∼70° to ∼64°, indicative of improved surface hydrophilicity. The scaffolds remained mechanically stable after polyP incorporation, with a Young’s modulus of ∼179–182 MPa and elongation at break of ∼32–35%. PolyP functionalization enhanced cell proliferation and migration, reduced ROS, increased ATP production, and upregulated the mRNA and protein expressions of COL1, DCN, and PCNA. In a rat model, the polyP-SF/PCL group attenuated inflammation during the early stages and increased deposition of longitudinally aligned collagen during the late stages.ConclusionPolyP-functionalized SF/PCL electrospun nanofibers can provide structural support and bioactivity, creating a favorable microenvironment for collagen synthesis and tissue remodeling. They are promising materials for tendon regeneration. Their biomechanical and functional results further substantiate their “functional” repair capability.
Nanomaterials, with their unique advantages, are expected to provide a strong impetus for breakthroughs in many real-world technologies, and they are particularly attractive in the field of drug detection. Currently, research on the development and application of nanomaterials in sample pretreatment and nanosensors is booming. New materials and applications are constantly being reported. This review provides a comprehensive and heuristic overview of the applications of nanomaterials in drug analysis. Various nanomaterials, including carbon nanotubes (CNTs), graphene derivatives, silicon-based materials, molecularly imprinted polymers, metal-organic frameworks (MOFs), covalent organic frameworks (COFs), microporous organic networks (MONs), and dopamine nanoparticles, have emerged as powerful tools for sample pretreatment, largely owing to their distinctive structural and chemical properties. This enables more efficient purification, concentration, and isolation of analytes in fields such as pharmaceutical analysis, environmental monitoring, and clinical testing. In addition, nanomaterials exhibit a suite of unique properties-such as large specific surface areas, tunable surface chemistries, excellent electrical conductivity, superior optical responsiveness, and high affinity for target analytes-that make them highly suitable for the development of sensitive and selective nanosensors across various fields, including clinical diagnostics, environmental monitoring, and food safety testing. These inherent characteristics enable nanosensors to achieve ultra-low detection limits, distinguish target drugs from complex matrix interferences with remarkable precision, and even realize real-time or in situ detection, thereby addressing critical challenges in traditional sensing technologies.
IntroductionMany mesoscale fracture studies focus primarily on reducing error through progressive mesh refinement. However, in heterogeneous materials such as concrete, fracture predictions are influenced not only by numerical discretization but also by the underlying meso- or micro-structure.MethodsIn this paper, an efficient procedure for modeling complex fracture processes in concrete structures is presented, combining virtual and interface elements and exploiting observed statistical ergodicity. Concrete is modeled at the mesoscopic scale as a heterogeneous material comprising a mortar matrix and randomly distributed aggregate inclusions, connected through cohesive mortar-mortar and mortar-aggregate interfaces of differentiated strength. The procedure is demonstrated on the benchmark problem of a notched concrete beam (400 mm × 100 mm, with a 4 mm wide, 30 mm deep eccentric notch) under three-point bending, considering mesh densities of 600, 800, and 1200 elements in the active fracture zone and ensembles of up to 100 stochastic realizations per configuration. Three sources of variability are investigated: mesh geometry with a fixed aggregate arrangement, random aggregate position with a fixed mesh density, and the mortar, aggregate, and interface mechanical properties.ResultsThe results demonstrate that the ensemble-averaged peak load and its standard deviation converge within approximately 75 realizations, and that the variability induced by aggregate placement is approximately three to five times larger than the variability associated with mesh discretization.DiscussionThese findings suggest that, for heterogeneous mesoscale fracture analyses, increasing the number of realizations provides more reliable predictions of the expected structural response than further refining individual meshes.
This study investigates the effects of alkali-treated rice straw fibers on the mechanical performance and interfacial characteristics of concrete. To address the limited understanding of the combined influence of fiber length and dosage in rice-straw-fiber-reinforced concrete, rice straw fibers with lengths of 1, 2, and 3 cm were pretreated in a 2% sodium hydroxide solution and incorporated into concrete at volume fractions of 0.3%, 0.5%, and 0.7%. Compressive strength was evaluated at 3, 7, and 28 days to characterize early-age strength development and the standard 28-day mechanical performance, whereas splitting tensile strength and flexural strength were measured at 28 days because these tests were intended to assess the mature crack-bridging and toughness-related behavior of the fiber-reinforced concrete. Scanning electron microscopy was used to observe the surface morphology of the fibers and the fiber–matrix interface. The results show that the incorporation of rice straw fibers generally decreased compressive strength, although the trend depended on fiber length and dosage. In contrast, fiber addition improved the tensile and flexural performance of concrete. The maximum increase in splitting tensile strength was about 17.4%, and the flexural strength increased by up to 58% compared with plain concrete. Microscopic observations indicated that alkali treatment roughened the fiber surface and improved mechanical interlocking with hydration products, thereby promoting crack bridging and energy dissipation during fracture. This study clarifies the trade-off between compressive-strength reduction and tensile/flexural toughening in alkali-treated rice straw fiber concrete.
Based on the fatigue life data of 30CrMnSiA steel and fatigue tests of pontoon bridge connecting joints, this study improves the stress field intensity approach. In the absence of fatigue life data for smooth specimens, a method for determining the spherical center of the fatigue damage zone in standard notched specimens was established by combining fatigue tests. Consequently, a general method for calculating the stress field intensity radius, applicable to 30CrMnSiA standard notched specimens with arbitrary stress concentration factors, was derived and applied to the pontoon bridge connecting joint, providing a generalizable framework for calculating the field intensity radius of notched components. Subsequently, the stress field intensity of the joint was calculated using ANSYS Workbench software. Factors influencing structural fatigue life, such as size and surface condition, were incorporated, and the model was calibrated based on experimental results to predict the fatigue life of the pontoon bridge connecting joints.The results show that the improved stress field intensity method, which does not require fatigue life data of smooth specimens, significantly extends the applicability of the original stress field intensity approach. The minimum clearance between the single lug and the double lugs in the pontoon bridge connecting joints has a pronounced influence on the location of fatigue failure and the fatigue life of the joints. Under stress-controlled fatigue conditions, the location of the spherical center of the fatigue damage zone in the notched joint can be predicted using the maximum stress amplitude, and the predictions are in good agreement with experimental results. The predicted high-cycle fatigue life of the pontoon bridge connecting joints in the range of 104–105 cycles obtained using this method shows high accuracy, with errors within 10%. The good agreement between predictions and experimental results demonstrates the high practical value of this method. This research provides a practical and feasible scheme for the fatigue life assessment of single-lug and yoke joints.
In this work, microscale laser shock peening without coating (μLSPwC) was applied to the surface of SLM-fabricated GH3625 alloy to enhance its mechanical performance. The effects of μLSPwC on surface roughness, microstructure, residual stress, microhardness, and tensile properties were systematically investigated. The results showed that μLSPwC effectively eliminated most surface manufacturing defects and significantly reduced surface roughness. The average grain size in the near-surface region decreased from 69.04 μm to 41.51 μm. In addition, a compressive residual stress (CRS) layer with a depth of approximately 360 μm and a hardened layer with a depth of about 250 μm were introduced. As a result, the ultimate tensile strength (UTS) and yield strength (YS) increased by approximately 1.1% and 8.9%, respectively, while the elongation (EL) remained nearly unchanged, indicating that μLSPwC effectively enhanced the strength of the SLM-fabricated GH3625 alloy without sacrificing its ductility.
The alloy SJ1100, independently developed by Zhejiang Shenji Titanium Industry Co., Ltd, is a new type of lightweight, high-strength, high-elasticity titanium alloy with independent intellectual property rights. Rolled SJ1100 titanium-alloy plates and sheets were manufactured with different processes and parameters, and their microstructure and uniaxial tensile properties were characterized and compared by using metallography, scanning electron microscope, electron backscattering diffraction and tensile tests. The 2-mm sheet annealed at 820 °C for 40 min and straightened at 600 °C for 4 h exhibited the highest yield strength and ultimate tensile strength as well as the lowest ductility, while the 30-mm one annealed at 820 °C for 40 min and aged at 600 °C for 16 h exhibited the lowest yield strength and ultimate tensile strength with the highest ductility. Straightening is thought to be more deleterious to ductility compared with aging. Annealing after straightening decreases the average grain size, lowers the intensity level of texture, and relieves the residual stress of the sheet. A larger plastic deformation results in an energetically more unstable regime, which makes the sheet easier to recrystallize during annealing.
Under heavy traffic loading combined with temperature effects, bridge deck pavement structures frequently exhibit a shortened service life, severely compromising both structural integrity and vehicular safety. This study developed a temperature field model for bridge deck pavement, with its reliability validated against published field measurements. Temperature distributions within the pavement layers across various temperature zones were obtained via Abaqus simulations. Prony series parameters for the asphalt mixture were fitted, enabling computation of temperature-induced stresses as a function of climatic variations and analysis of the influences of pavement material properties and structural layer thicknesses on these stresses. Results indicate that the pavement temperature field undergoes periodic fluctuations in response to ambient temperature, with temperatures decreasing progressively with depth. Employing high-thermal-conductivity materials in summer reduces peak pavement temperatures, whereas high-specific-heat-capacity materials in winter elevate minimum temperatures. The temporal variation of temperature-induced stresses mirrors that of the temperature field, with winter stresses significantly exceeding summer values. In summer, surface temperatures (e.g., 62.5 °C in extremely hot zones) are higher than those in lower layers, whereas in winter (e.g., −24.7 °C in severe winter zones), the pattern is reversed, providing a data foundation for thermodynamic analysis.
