Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult t...Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult to compare their research results.Methods:The time for wound closure was evaluated and recorded through gross observation.The regression equation between the healing time and the diameter of skin defect was established,which can be used to predict the healing time for a certain skin defect size in rats.Histochemical and immunohistochemical staining was used to observe the regeneration and reconstruction of skin appendages,and the functional skin repair was quantitatively scored.Results:The critical-size defect of rats was determined based on the maximum capacity of structural skin repair,and the functional skin repair was quantitatively scored based on the regeneration and reconstruction of skin appendages.The allowable range of critical-size skin defect of SD rats lies between 45 and 50 mm in diameter.The concept of structural repair and the category of functional repair of injured skin are put forward.The regression equation between the structural skin healing time and defect diameters is established.Conclusion:The allowable range of skin critical-size defect of SD rats lies between 45 and 50 mm in diameter.The regression equation between the structural skin healing time and defect diameters can be used to predict the healing time for a certain skin defect size in rats.展开更多
Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propo...Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propose BearFusionNet,an attention-based deep learning architecture with multi-stream,which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19.This hybrid design,figuratively beaming from one layer to another,extracts the enormity of representations on different scales,backed by a prepreprocessing pipeline that brings defect saliency to the fore through contrast adjustment,denoising,and edge detection.The use of multi-head self-attention enhances feature fusion,enabling the model to capture both large and small spatial features.BearFusionNet achieves an accuracy of 99.66%and Cohen’s kappa score of 0.9929 in Kaggle’s Real-life Industrial Casting Defects dataset.Both McNemar’s and Wilcoxon signed-rank statistical tests,as well as fivefold cross-validation,are employed to assess the robustness of our proposed model.To interpret the model,we adopt Grad-Cam visualizations,which are the state of the art standard.Furthermore,we deploy BearFusionNet as a webbased system for near real-time inference(5-6 s per prediction),which enables the quickest yet accurate detection with visual explanations.Overall,BearFusionNet is an interpretable,accurate,and deployable solution that can automatically detect casting defects,leading to significant advances in the innovative industrial environment.展开更多
The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precis...The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.展开更多
The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermo...The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermoperation.The complex relationship between the defect phenomenon andmulti-layer causes and the probabilistic influence of secondary equipment cannot be described through knowledge extraction and fusion technology by existing methods,which limits the real-time and accuracy of defect identification.Therefore,a defect recognition method based on the Bayesian network and knowledge graph fusion is proposed.The defect data of secondary equipment is transformed into the structured knowledge graph through knowledge extraction and fusion technology.The knowledge graph of power grid secondary equipment is mapped to the Bayesian network framework,combined with historical defect data,and introduced Noisy-OR nodes.The prior and conditional probabilities of the Bayesian network are then reasonably assigned to build a model that reflects the probability dependence between defect phenomena and potential causes in power grid secondary equipment.Defect identification of power grid secondary equipment is achieved by defect subgraph search based on the knowledge graph,and defect inference based on the Bayesian network.Practical application cases prove this method’s effectiveness in identifying secondary equipment defect causes,improving identification accuracy and efficiency.展开更多
With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-...With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.展开更多
Vacancy defects,as fundamental disruptions in metallic lattices,play an important role in shaping the mechanical and electronic properties of aluminum crystals.However,the influence of vacancy position under coupled t...Vacancy defects,as fundamental disruptions in metallic lattices,play an important role in shaping the mechanical and electronic properties of aluminum crystals.However,the influence of vacancy position under coupled thermomechanical fields remains insufficiently understood.In this study,transmission and scanning electron microscopy were employed to observe dislocation structures and grain boundary heterogeneities in processed aluminum alloys,suggesting stress concentrations and microstructural inhomogeneities associated with vacancy accumulation.To complement these observations,first-principles calculations and molecular dynamics simulations were conducted for seven single-vacancy configurations in face-centered cubic aluminum.The stress response,total energy,density of states(DOS),and differential charge density were examined under varying compressive strain(ε=0–0.1)and temperature(0–600 K).The results indicate that face-centered vacancies tend to reduce mechanical strength and perturb electronic states near the Fermi level,whereas corner and edge vacancies appear to have weaker effects.Elevated temperatures may partially restore electronic uniformity through thermal excitation.Overall,these findings suggest that vacancy position exerts a critical but position-dependent influence on coupled structure-property relationships,offering theoretical insights and preliminary experimental support for defect-engineered aluminum alloy design.展开更多
Magnesium(Mg)and its alloys,known for their low density and high specific strength,are increasingly explored as lightweight structural materials across a broad range of industrial applications.However,their widespread...Magnesium(Mg)and its alloys,known for their low density and high specific strength,are increasingly explored as lightweight structural materials across a broad range of industrial applications.However,their widespread application remains constrained by intrinsic mechanical limitations,fundamentally rooted in the nature of crystallographic defects.Atomic-scale modeling techniques are transforming our ability to unravel the structures,energetics,and dynamics of these defects and to explore their complex interactions,thereby guiding defect engineering in Mg alloys.However,the growing body of available data can make it difficult for researchers to identify critical knowledge gaps and promising areas for further exploration.To address this challenge,we highlight key research domains with significant potential for impactful advancements,aiming to illuminate these areas while inspiring innovative approaches and encouraging deeper exploration of pivotal topics that may shape the future of Mg alloy development.This review presents a comprehensive overview of the state-of-the-art in atomic-scale modeling of defects in Mg and its alloys.We introduce key simulation methodologies,including density functional theory and atomistic simulations,and highlight their applications to defect distribution,defect dynamics,and defect-defect interactions.By bridging fundamental insights in defects with alloy design strategies,this review aims to support and inspire the broader Mg research community and to underscore the growing impact of atomic-scale modeling in the accelerated development of high-performance Mg alloys.展开更多
Due to their chiral structure,carbon nanosprings possess unique properties that are promising for nanotechnology applications.The structural transformations of carbon nanosprings in the form of spiral macromolecules d...Due to their chiral structure,carbon nanosprings possess unique properties that are promising for nanotechnology applications.The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules(graphene helicoids and spiral nanoribbons)are analyzed using molecular dynamics simulations.The interatomic interactions are described by a force field including valence bonds,bond angles,torsional and dihedral angles,as well as van derWaals interactions.While the tension/compression of such nanosprings has been analyzed in the literature,this study investigates other modes of deformation,including bending and twisting.Depending on the geometric characteristics of the carbon nanosprings,the formation of structural and helix reversal topological defects is described.During these structural transformations of the nanosprings,only van der Waals bonds break and recover,but breaking or recovery of covalent bonds does not take place.It is found that nanosprings demonstrate a significantly higher coefficient of axial thermal expansion than many metals and alloys.Under axial compression,Euler instability leads to lateral bending with continuous deformation of the nanospring axis at relatively low compression,while at high compression,bending kinks form.Various types of topological defects form on the instantly released nanospring during its relaxation from a highly stretched configuration.These results are useful for the development of nanosensors operating over a wide temperature range.展开更多
Dear Editor,The Cay2.1 channel,also known as the P/Q-type Ca^(2+) channel,is a particular type of voltage-gated Ca^(2+) channel primarily expressed on the presynaptic membrane in the brain[1].It serves as an essential...Dear Editor,The Cay2.1 channel,also known as the P/Q-type Ca^(2+) channel,is a particular type of voltage-gated Ca^(2+) channel primarily expressed on the presynaptic membrane in the brain[1].It serves as an essential part of the precisely orchestrated neurotransmitter release machinery.展开更多
To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of ...To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.展开更多
Nuclear reactor coolant pumps require frequent maintenance to ensure operational safety.One critical aspect of this maintenance is verifying the integrity of the mechanical sealing system.Due to the lack of an evaluat...Nuclear reactor coolant pumps require frequent maintenance to ensure operational safety.One critical aspect of this maintenance is verifying the integrity of the mechanical sealing system.Due to the lack of an evaluation criteria and an incomplete understanding of how end-face defects lead to failure,defective mechanical seals are often replaced empirically,which not only contributes to economic losses but also poses risks to reactor safety.To reveal the mechanism by which surface defects affect sealing performance,this study proposes a classification method for end-face defects based on the analysis of approximately one hundred used mechanical seals.A defect characterization model was established by extracting key features of the observed defects.The influence of these defects on sealing performance was analyzed using a liquid-thermal-solid coupling model.Changes in sealing gap,leakage rates,and film stiffness with respect to defect size,location,and other characteristics are discussed.This work contributes to a deeper understanding of defect failure mechanisms.These results can serve as a reference for evaluating defective seals.展开更多
In ultrasonic non-destructive testing of high-temperature industrial equipment,sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy.Conventional approache...In ultrasonic non-destructive testing of high-temperature industrial equipment,sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy.Conventional approaches that rely on room-temperature sound velocities introduce systematic errors,potentially leading to misjudgment of safety-critical components.Two primary challenges hinder current methods:first,it is difficult to monitor real-time changes in sound velocity distribution within a thermal gradient;second,traditional uniform-temperature correction models fail to capture the nonlinear dependence of material properties on temperature and their effect on ultrasonic velocity fields.Here,we propose a defect localization correction method based on multiphysics coupling.A two-dimensional coupled heat transfer–wave propagation model is established in COMSOL,and a one-dimensional steady-state heat transfer condition is used to design a numerical pulse–echo experiment in 1020 steel.Temperature-dependent material properties are incorporated,and the intrinsic relationship between sound velocity and temperature is derived,confirming consistency with classical theories.To account for gradient temperature fields,a micro-element integration algorithm discretizes the propagation path into segments,each associated with a locally computed temperature from the steady-state heat conduction solution.Defect positions are dynamically corrected through cumulative displacement along the propagation path.By integrating heat conduction and elastic wave propagation in a multiphysics framework,this method overcomes the limitations of uniform-temperature assumptions.The micro-element integration approach enables dynamic tracking of spatially varying sound velocities,offering a robust strategy to enhance ultrasonic testing accuracy in high-temperature industrial environments.展开更多
In order to investigate the effect of die wall thickness on morphologies of defect band,a stepped mold with a wall thickness of 5 mm,4 mm,3 mm,2 mm,and 1 mm was designed to carry out high pressure die casting experime...In order to investigate the effect of die wall thickness on morphologies of defect band,a stepped mold with a wall thickness of 5 mm,4 mm,3 mm,2 mm,and 1 mm was designed to carry out high pressure die casting experiments with AlSi10 MgMn alloy.For castings with wall thickness of 2-4 mm,the ratio of the mean defect band width(w)and mean grain size(d)in the defect band(w/d)ranges 7-18,while it increases to 24.47 for the 5 mm-thick casting.This difference is related with the filling speed and the distribution of externally solidified crystals(ESCs).The mold flow analysis indicates that the filling speed decreases from 25.41 m·s^(-1)to 11.07 m·s^(-1)when wall thickness increases from 2 mm to 5 mm.Due to the decreasing filling speed along the wall thickness,ESCs gradually diffuse from the center to the defect band,which keep the shear strength in the defect band at a high-level during filling.Meanwhile,the shear strength generated during the filling also decreases as the shear rate drops.Finally,the defect bands in the 5 mm-thick region become widen and indistinct,and the porosity is as high as 5.25%.展开更多
The cemented tailings backfill(CTB)with initial defects is more prone to destabilization damage under the influence of various unfavorable factors during the mining process.In order to investigate its influence on the...The cemented tailings backfill(CTB)with initial defects is more prone to destabilization damage under the influence of various unfavorable factors during the mining process.In order to investigate its influence on the stability of underground mining engineering,this paper simulates the generation of different degrees of initial defects inside the CTB by adding different contents of air-entraining agent(AEA),investigates the acoustic emission RA/AF eigenvalues of CTB with different contents of AEA under uniaxial compression,and adopts various denoising algorithms(e.g.,moving average smoothing,median filtering,and outlier detection)to improve the accuracy of the data.The variance and autocorrelation coefficients of RA/AF parameters were analyzed in conjunction with the critical slowing down(CSD)theory.The results show that the acoustic emission RA/AF values can be used to characterize the progressive damage evolution of CTB.The denoising algorithm processed the AE signals to reduce the effects of extraneous noise and anomalous spikes.Changes in the variance curves provide clear precursor information,while abrupt changes in the autocorrelation coefficient can be used as an auxiliary localization warning signal.The phenomenon of dramatic increase in the variance and autocorrelation coefficient curves during the compression-tightening stage,which is influenced by the initial defects,can lead to false warnings.As the initial defects of the CTB increase,its instability precursor time and instability time are prolonged,the peak stress decreases,and the time difference between the CTB and the instability damage is smaller.The results provide a new method for real-time monitoring and early warning of CTB instability damage.展开更多
The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab b...The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab ballastless track structure.This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects.Specimens were fabricated through on-site experiment.The percent of each area of 6 cm^(2)or more bubble defect was 0 in most of specimens.When the cumulative area of all bub-ble defects reached 12%,the splitting tensile strength value was 0.67 MPa,which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion.Furthermore,when the cumulative area of all bubble defects reached 8%,the splitting tensile strength value was 0.85 MPa,which exceeded the minimum required value of 0.8 MPa,thereby over-coming the negative impact of each area of 10 cm^(2) or more bubble defect.Additionally,keeping the cumulative area of each area of 6 cm^(2) or more bubble defect below 6%ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.展开更多
Although hot-rolled La(Fe,Co,Si)13-based alloys are promising magnetocaloric materials for solidstate cooling with near-net shaping capabilities,their underlying hot deformation mechanisms remain largely unexplored.In...Although hot-rolled La(Fe,Co,Si)13-based alloys are promising magnetocaloric materials for solidstate cooling with near-net shaping capabilities,their underlying hot deformation mechanisms remain largely unexplored.In this study,a comprehensive and systematic investigation was conducted,by encompassing the analysis of hot deformation mechanisms,along with the microstructure evolution and magnetoc aloric properties of hot-rolled La-Fe-Co-Si alloy.The La_(1.05)Fe_(11.2)Co_(0.7)Si_(1.38)alloy was examined using multiscale mechanical analysis to assess the effects of temperature.A series of macroscale hot compression and microscale nanoindentation tests were performed to access global and local mechanical properties,including variations in hardness and indentation modulus of the primaryα-Fe and secondary 1:1:1 phases up to 800℃.A significant decrease in hardness and elastic recovery of the secondary phase was observed between 600and 800℃,above half of its melting point(1113℃),suggesting pronounced flow softening in both theα-Fe and 1:1:1 phases.Additionally,a novel multi-step annealing process was introduced for hot-rolled La-Fe-Co-Si alloys,involving partial transient liquid-phase diffusion in the 1:1:1 phase to address deformation-induced defects,such as residualα-Fe and lattice distortions in the 1:13 phase,which have not been previously reported.As a result,a primary La(Fe,Co,Si)13phase with a volume fraction of97.5%was achieved after multi-step annealing,compared to 87.5%using conventional annealing.Correspondingly,the magnetocaloric properties were restored,with the Curie temperature(TC)recovering from 276 to 268 K and the maximum magnetic entropy change(ΔSM)increasing from 7.56 to 8.67 J kg^(-1)K^(-1)under a 2 T magnetic field.展开更多
With the rapid development of computer vision technology,artificial intelligence algorithms,and high-performance computing platforms,machine vision technology has gradually shown its great potential in automated produ...With the rapid development of computer vision technology,artificial intelligence algorithms,and high-performance computing platforms,machine vision technology has gradually shown its great potential in automated production lines,especially in defect detection.Machine vision technology can be applied in many industries such as semiconductor,automobile manufacturing,aerospace,food,and drugs,which can significantly improve detection efficiency and accuracy,reduce labor costs,improve product quality,enhance market competitiveness,and provide strong support for the arrival of Industry 4.0 era.In this article,the concept,advantages,and disadvantages of machine vision and the algorithm framework of machine vision in the defect detection system are briefly described,aiming to promote the rapid development of industry and strengthen China’s industry.展开更多
Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,an...Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.展开更多
The impact of casting defects on the weldability of K4951 superalloy was investigated using tungsten inert gas(TIG)welding.The as-cast K4951 superalloy samples with prefabricated U-shaped grooves of varying depths and...The impact of casting defects on the weldability of K4951 superalloy was investigated using tungsten inert gas(TIG)welding.The as-cast K4951 superalloy samples with prefabricated U-shaped grooves of varying depths and widths were TIG welded,and the microstructures,cracks morphology,and precipitated phases were analyzed using optical microscope,scanning electron microscope,transmission electron microscope,and energy dispersive X-ray spectrometer.The results reveal that the dimensions of casting defects significantly affect the weldability of K4951.Deep defects(greater than 2 mm)lead to rapid crack propagation,while wider defects can moderate the propagation process of cracks.Elemental segregation and the formation of precipitated phases,such as MC carbides,are observed in the fusion zone,contributing to welding cracks.An optimal groove aspect ratio(depth-to-width)between 0.2 and 0.5 minimizes crack formation tendency and enhances tensile strength,resulting in a mixed brittle-ductile fracture mode of joint after high-temperature tensile testing.展开更多
Achieving high-quality perovskite films without surface defects is regarded as a crucial target for the development of durable high-performance perovskite solar cells.Additive engineering is commonly employed to simul...Achieving high-quality perovskite films without surface defects is regarded as a crucial target for the development of durable high-performance perovskite solar cells.Additive engineering is commonly employed to simultaneously control the growth of perovskite crystals and passivate defects.Here,4-(trifluoromethyl)benzoic anhydride(4-TBA)composed of benzene rings functionalized with carbonyl and trifluoromethyl groups was used as an example additive to study the characteristics of additives used for producing high-quality perovskites and controlling their surface properties.The interaction between4-TBA and perovskite precursor materials was investigated using density functional theory(DFT)simulations.The electron-rich carbonyl group efficiently passivated the under-coordinated lead-ion defects.Additionally,hydrogen bonding between trifluoromethyl and organic cations prevents the generation of cation vacancies.Because of its intrinsic hydrophobicity,the trifluoromethyl group simultaneously improves the moisture and heat stability of the film.4-TBA serves as a universal modifier for various perovskite compositions.The power conversion efficiency(PCE)of inverted perovskite solar cells(PSCs)based on methylammonium(MA)with 4-TBA was improved from 16.15%to 19.28%.Similarly,the PCE of inverted PSCs based on a cesium formamidinium MA(CsFAMA)perovskite film increased from20.72%to 23.58%,upon addition of 4-TBA.Furthermore,the moisture and thermal stability of 4-TBAtreated films and devices was significantly enhanced,along with prolonged device performance.Our work provides guidance on selecting the structure and functional groups that are essential for surface defect passivation and the production of high-quality perovskites.展开更多
基金National Key Research and Development Program of China,Grant/Award Number:2023YFC2410403。
文摘Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult to compare their research results.Methods:The time for wound closure was evaluated and recorded through gross observation.The regression equation between the healing time and the diameter of skin defect was established,which can be used to predict the healing time for a certain skin defect size in rats.Histochemical and immunohistochemical staining was used to observe the regeneration and reconstruction of skin appendages,and the functional skin repair was quantitatively scored.Results:The critical-size defect of rats was determined based on the maximum capacity of structural skin repair,and the functional skin repair was quantitatively scored based on the regeneration and reconstruction of skin appendages.The allowable range of critical-size skin defect of SD rats lies between 45 and 50 mm in diameter.The concept of structural repair and the category of functional repair of injured skin are put forward.The regression equation between the structural skin healing time and defect diameters is established.Conclusion:The allowable range of skin critical-size defect of SD rats lies between 45 and 50 mm in diameter.The regression equation between the structural skin healing time and defect diameters can be used to predict the healing time for a certain skin defect size in rats.
基金funded by Multimedia University,Cyberjaya,Selangor,Malaysia(Grant Number:PostDoc(MMUI/240029)).
文摘Manual inspection of onba earing casting defects is not realistic and unreliable,particularly in the case of some micro-level anomalies which lead to major defects on a large scale.To address these challenges,we propose BearFusionNet,an attention-based deep learning architecture with multi-stream,which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19.This hybrid design,figuratively beaming from one layer to another,extracts the enormity of representations on different scales,backed by a prepreprocessing pipeline that brings defect saliency to the fore through contrast adjustment,denoising,and edge detection.The use of multi-head self-attention enhances feature fusion,enabling the model to capture both large and small spatial features.BearFusionNet achieves an accuracy of 99.66%and Cohen’s kappa score of 0.9929 in Kaggle’s Real-life Industrial Casting Defects dataset.Both McNemar’s and Wilcoxon signed-rank statistical tests,as well as fivefold cross-validation,are employed to assess the robustness of our proposed model.To interpret the model,we adopt Grad-Cam visualizations,which are the state of the art standard.Furthermore,we deploy BearFusionNet as a webbased system for near real-time inference(5-6 s per prediction),which enables the quickest yet accurate detection with visual explanations.Overall,BearFusionNet is an interpretable,accurate,and deployable solution that can automatically detect casting defects,leading to significant advances in the innovative industrial environment.
基金supported by the National Natural Science Foundation of China(No.52403035)the Shanghai Sailing Program(23YF1400300)+1 种基金the Fundamental Research Funds for the Central Universities(2232023D-05)the Weiqiao Teaching and Research Innovation Program.
文摘The lack of macro-continuity and mechanical strength of covalent organic frameworks(COFs)has significantly limited their practical applications.Here,we propose an“alcohol-triggered defect cleavage”strategy to precisely regulate the growth and stacking of COF grains through a moderate reversed Schiff base reaction,realizing the direct synthesis of COF nanofibers(CNFs)with high aspect ratio(L/D=103.05)and long length(>20μm).An individual CNF exhibits a biomimetic scale-like architecture,achieving superior flexibility and fatigue resistance under dynamic bending via a multiscale stress dissipation mechanism.Taking advantages of these structural features,we engineer CNF aerogels(CNF-As)with programmable porous structures(e.g.,honeycomb,lamellar,isotropic)via directional ice-template methodology.CNF-As demonstrate 100%COF content,high specific surface area(396.15 m^(2)g^(-1))and superelasticity(~0%elastic deformation after 500 compression cycles at 50%strain),outperforming most COF-based counterparts.Compared with the conventional COF aerogels,the unique structural features of CNF-A enable it to perform outstandingly in uranium extraction,with an 11.72-fold increment in adsorption capacity(920.12 mg g^(-1))and adsorption rate(89.9%),and a 2.48-fold improvement in selectivity(U/V=2.31).This study provides a direct strategy for the development of next-generation COF materials with outstanding functionality and structural robustness.
基金supported by the State Grid Southwest Branch Project“Research on Defect Diagnosis and Early Warning Technology of Relay Protection and Safety Automation Devices Based on Multi-Source Heterogeneous Defect Data”.
文摘The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermoperation.The complex relationship between the defect phenomenon andmulti-layer causes and the probabilistic influence of secondary equipment cannot be described through knowledge extraction and fusion technology by existing methods,which limits the real-time and accuracy of defect identification.Therefore,a defect recognition method based on the Bayesian network and knowledge graph fusion is proposed.The defect data of secondary equipment is transformed into the structured knowledge graph through knowledge extraction and fusion technology.The knowledge graph of power grid secondary equipment is mapped to the Bayesian network framework,combined with historical defect data,and introduced Noisy-OR nodes.The prior and conditional probabilities of the Bayesian network are then reasonably assigned to build a model that reflects the probability dependence between defect phenomena and potential causes in power grid secondary equipment.Defect identification of power grid secondary equipment is achieved by defect subgraph search based on the knowledge graph,and defect inference based on the Bayesian network.Practical application cases prove this method’s effectiveness in identifying secondary equipment defect causes,improving identification accuracy and efficiency.
基金supported in part by the Technical Service for the Development and Application of an Intelligent Visual Management Platformfor Expressway Construction Progress Based on BIM Technology(grant NO.JKYZLX-2023-09)in partby the Technical Service for the Development of an Early Warning Model in the Research and Application of Key Technologies for Tunnel Operation Safety Monitoring and Early Warning Based on Digital Twin(grant NO.JK-S02-ZNGS-202412-JISHU-FA-0035)sponsored by Yunnan Transportation Science Research Institute Co.,Ltd.
文摘With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.
基金supported by the Research Project on Strengthening the Construction of an Important Ecological Security Barrier in Northern China by Higher Education Institutions in the Inner Mongolia Autonomous Region(STAQZX202313)the Inner Mongolia Autonomous Region Education Science‘14th Five-Year Plan’2024 Annual Research Project(NGJGH2024635).
文摘Vacancy defects,as fundamental disruptions in metallic lattices,play an important role in shaping the mechanical and electronic properties of aluminum crystals.However,the influence of vacancy position under coupled thermomechanical fields remains insufficiently understood.In this study,transmission and scanning electron microscopy were employed to observe dislocation structures and grain boundary heterogeneities in processed aluminum alloys,suggesting stress concentrations and microstructural inhomogeneities associated with vacancy accumulation.To complement these observations,first-principles calculations and molecular dynamics simulations were conducted for seven single-vacancy configurations in face-centered cubic aluminum.The stress response,total energy,density of states(DOS),and differential charge density were examined under varying compressive strain(ε=0–0.1)and temperature(0–600 K).The results indicate that face-centered vacancies tend to reduce mechanical strength and perturb electronic states near the Fermi level,whereas corner and edge vacancies appear to have weaker effects.Elevated temperatures may partially restore electronic uniformity through thermal excitation.Overall,these findings suggest that vacancy position exerts a critical but position-dependent influence on coupled structure-property relationships,offering theoretical insights and preliminary experimental support for defect-engineered aluminum alloy design.
基金support by the Deutsche Forschungsgemeinschaft(DFG)-Projektnummer 505716422the French National Research Agency(ANR)grants ANR22-CE92-0058-01(SILA)and ANR-21-CE08-0001(ATOUUM)+2 种基金support by the DFG through the projects A05 of the SFB1394 StructuralChemical Atomic Complexity-From Defect Phase Diagrams to Material Properties,project ID 409476157support funded by the DFG-Projektnummer 562592407 and 555365333.
文摘Magnesium(Mg)and its alloys,known for their low density and high specific strength,are increasingly explored as lightweight structural materials across a broad range of industrial applications.However,their widespread application remains constrained by intrinsic mechanical limitations,fundamentally rooted in the nature of crystallographic defects.Atomic-scale modeling techniques are transforming our ability to unravel the structures,energetics,and dynamics of these defects and to explore their complex interactions,thereby guiding defect engineering in Mg alloys.However,the growing body of available data can make it difficult for researchers to identify critical knowledge gaps and promising areas for further exploration.To address this challenge,we highlight key research domains with significant potential for impactful advancements,aiming to illuminate these areas while inspiring innovative approaches and encouraging deeper exploration of pivotal topics that may shape the future of Mg alloy development.This review presents a comprehensive overview of the state-of-the-art in atomic-scale modeling of defects in Mg and its alloys.We introduce key simulation methodologies,including density functional theory and atomistic simulations,and highlight their applications to defect distribution,defect dynamics,and defect-defect interactions.By bridging fundamental insights in defects with alloy design strategies,this review aims to support and inspire the broader Mg research community and to underscore the growing impact of atomic-scale modeling in the accelerated development of high-performance Mg alloys.
基金funded by the Russian Science Foundation(RSF),grant No.25-73-20038(conceptualization,methodology,manuscript writing).
文摘Due to their chiral structure,carbon nanosprings possess unique properties that are promising for nanotechnology applications.The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules(graphene helicoids and spiral nanoribbons)are analyzed using molecular dynamics simulations.The interatomic interactions are described by a force field including valence bonds,bond angles,torsional and dihedral angles,as well as van derWaals interactions.While the tension/compression of such nanosprings has been analyzed in the literature,this study investigates other modes of deformation,including bending and twisting.Depending on the geometric characteristics of the carbon nanosprings,the formation of structural and helix reversal topological defects is described.During these structural transformations of the nanosprings,only van der Waals bonds break and recover,but breaking or recovery of covalent bonds does not take place.It is found that nanosprings demonstrate a significantly higher coefficient of axial thermal expansion than many metals and alloys.Under axial compression,Euler instability leads to lateral bending with continuous deformation of the nanospring axis at relatively low compression,while at high compression,bending kinks form.Various types of topological defects form on the instantly released nanospring during its relaxation from a highly stretched configuration.These results are useful for the development of nanosensors operating over a wide temperature range.
基金supported by the National Natural Science Foundation of China(32100773 and U20A6005)the National Science and Technology Innovation 2030-Major Project of China(2021ZD0202500)+4 种基金Shenzhen Medical Research Fund(B2402024)China Postdoctoral Science Foundation(2021M693296)Shenzhen Science and Technology Program(JCYJ20230807093815032)Guangdong High-level Hospital Construction Fund(ynkt2021-zz33 and LCYJ2022093)the Natural Science Foundation of Guangdong Province,China(2022A1515010297).
文摘Dear Editor,The Cay2.1 channel,also known as the P/Q-type Ca^(2+) channel,is a particular type of voltage-gated Ca^(2+) channel primarily expressed on the presynaptic membrane in the brain[1].It serves as an essential part of the precisely orchestrated neurotransmitter release machinery.
基金supported by the Jilin Science and Technology Development Plan (20240101029JJ) for the following study:synchronized high-speed detection of surface shape and defects in the grinding stage of complex surfaces (KLMSZZ202305)for the high-precision wide dynamic large aperture optical inspection system for fine astronomical observation by the National Major Research Instrument Development Project (62127901)+2 种基金for ultrasmooth manufacturing technology of large diameter complex curved surface by the National Key R&D Program(2022YFB3403405)for research on the key technology of rapid synchronous detection of surface shape and subsurface defects in the grinding stage of large diameter complex surfaces by the International Cooperation Project(2025010157)The Key Laboratory of Optical System Advanced Manufacturing Technology,Chinese Academy of Sciences (2022KLOMT02-04) also supported this study
文摘To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.
基金Supported by National Natural Science Foundation of China(Grant No.51975315)National Science and Technology Major Project of China(Grant No.2019-IV-0020-0088).
文摘Nuclear reactor coolant pumps require frequent maintenance to ensure operational safety.One critical aspect of this maintenance is verifying the integrity of the mechanical sealing system.Due to the lack of an evaluation criteria and an incomplete understanding of how end-face defects lead to failure,defective mechanical seals are often replaced empirically,which not only contributes to economic losses but also poses risks to reactor safety.To reveal the mechanism by which surface defects affect sealing performance,this study proposes a classification method for end-face defects based on the analysis of approximately one hundred used mechanical seals.A defect characterization model was established by extracting key features of the observed defects.The influence of these defects on sealing performance was analyzed using a liquid-thermal-solid coupling model.Changes in sealing gap,leakage rates,and film stiffness with respect to defect size,location,and other characteristics are discussed.This work contributes to a deeper understanding of defect failure mechanisms.These results can serve as a reference for evaluating defective seals.
基金supported by the following projects:National Natural Science Foundation of China[U24A20135]Science and Technology Program of the State Administration for Market Regulation[2024MK016]+9 种基金Basic Scientific Research Fund Project for Higher Education Institutions of Inner Mongolia(2024YXXS057)Key Project of Natural Science Foundation of Inner Mongolia[2023ZD12]2023 Inner Mongolia Autonomous Region Key R&D and Achievement Transformation Program[2023YFHH0090]Natural Science Foundation of Inner Mongolia[2022MS05006]Talent Development Fund of Inner Mongolia Autonomous RegionFundamental Research Funds for Universities[2023RCTD012]Fundamental Research Funds for Universities[2023QNJS075]Inner Mongolia Autonomous Region Postgraduate Research Innovation Project[KC2024053B]Fundamental Research Funds for Universities[2024YXXS012]Open Project of the National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology[GZ2023KF012].
文摘In ultrasonic non-destructive testing of high-temperature industrial equipment,sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy.Conventional approaches that rely on room-temperature sound velocities introduce systematic errors,potentially leading to misjudgment of safety-critical components.Two primary challenges hinder current methods:first,it is difficult to monitor real-time changes in sound velocity distribution within a thermal gradient;second,traditional uniform-temperature correction models fail to capture the nonlinear dependence of material properties on temperature and their effect on ultrasonic velocity fields.Here,we propose a defect localization correction method based on multiphysics coupling.A two-dimensional coupled heat transfer–wave propagation model is established in COMSOL,and a one-dimensional steady-state heat transfer condition is used to design a numerical pulse–echo experiment in 1020 steel.Temperature-dependent material properties are incorporated,and the intrinsic relationship between sound velocity and temperature is derived,confirming consistency with classical theories.To account for gradient temperature fields,a micro-element integration algorithm discretizes the propagation path into segments,each associated with a locally computed temperature from the steady-state heat conduction solution.Defect positions are dynamically corrected through cumulative displacement along the propagation path.By integrating heat conduction and elastic wave propagation in a multiphysics framework,this method overcomes the limitations of uniform-temperature assumptions.The micro-element integration approach enables dynamic tracking of spatially varying sound velocities,offering a robust strategy to enhance ultrasonic testing accuracy in high-temperature industrial environments.
基金supported by the National Natural Science Foundation of China(No.52474396 and 52175284)the National Key Research and Development Program of China(Grant No.2022YFB3404201)。
文摘In order to investigate the effect of die wall thickness on morphologies of defect band,a stepped mold with a wall thickness of 5 mm,4 mm,3 mm,2 mm,and 1 mm was designed to carry out high pressure die casting experiments with AlSi10 MgMn alloy.For castings with wall thickness of 2-4 mm,the ratio of the mean defect band width(w)and mean grain size(d)in the defect band(w/d)ranges 7-18,while it increases to 24.47 for the 5 mm-thick casting.This difference is related with the filling speed and the distribution of externally solidified crystals(ESCs).The mold flow analysis indicates that the filling speed decreases from 25.41 m·s^(-1)to 11.07 m·s^(-1)when wall thickness increases from 2 mm to 5 mm.Due to the decreasing filling speed along the wall thickness,ESCs gradually diffuse from the center to the defect band,which keep the shear strength in the defect band at a high-level during filling.Meanwhile,the shear strength generated during the filling also decreases as the shear rate drops.Finally,the defect bands in the 5 mm-thick region become widen and indistinct,and the porosity is as high as 5.25%.
基金Projects(52374138,51764013)supported by the National Natural Science Foundation of ChinaProject(20204BCJ22005)supported by the Training Plan for Academic and Technical Leaders of Major Disciplines of Jiangxi Province,China+1 种基金Project(2019M652277)supported by the China Postdoctoral Science FoundationProject(20192ACBL21014)supported by the Natural Science Youth Foundation Key Projects of Jiangxi Province,China。
文摘The cemented tailings backfill(CTB)with initial defects is more prone to destabilization damage under the influence of various unfavorable factors during the mining process.In order to investigate its influence on the stability of underground mining engineering,this paper simulates the generation of different degrees of initial defects inside the CTB by adding different contents of air-entraining agent(AEA),investigates the acoustic emission RA/AF eigenvalues of CTB with different contents of AEA under uniaxial compression,and adopts various denoising algorithms(e.g.,moving average smoothing,median filtering,and outlier detection)to improve the accuracy of the data.The variance and autocorrelation coefficients of RA/AF parameters were analyzed in conjunction with the critical slowing down(CSD)theory.The results show that the acoustic emission RA/AF values can be used to characterize the progressive damage evolution of CTB.The denoising algorithm processed the AE signals to reduce the effects of extraneous noise and anomalous spikes.Changes in the variance curves provide clear precursor information,while abrupt changes in the autocorrelation coefficient can be used as an auxiliary localization warning signal.The phenomenon of dramatic increase in the variance and autocorrelation coefficient curves during the compression-tightening stage,which is influenced by the initial defects,can lead to false warnings.As the initial defects of the CTB increase,its instability precursor time and instability time are prolonged,the peak stress decreases,and the time difference between the CTB and the instability damage is smaller.The results provide a new method for real-time monitoring and early warning of CTB instability damage.
基金supported by a grant from China railway corporation science and technology research and development plan project(Grant No.2017G005-B)funding support by Wuyi University’s Hong Kong and Macao Joint Research and Development Fund(Grants No.2021WGALH15)funding support by the Innovation and Technology Commission of Hong Kong SAR Government to the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center(Grant No.K-BBY1).
文摘The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab ballastless track structure.This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects.Specimens were fabricated through on-site experiment.The percent of each area of 6 cm^(2)or more bubble defect was 0 in most of specimens.When the cumulative area of all bub-ble defects reached 12%,the splitting tensile strength value was 0.67 MPa,which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion.Furthermore,when the cumulative area of all bubble defects reached 8%,the splitting tensile strength value was 0.85 MPa,which exceeded the minimum required value of 0.8 MPa,thereby over-coming the negative impact of each area of 10 cm^(2) or more bubble defect.Additionally,keeping the cumulative area of each area of 6 cm^(2) or more bubble defect below 6%ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.
基金financially supported by the Fundamental Research Program of the Korea Institute of Materials Science(No.PNKA330)
文摘Although hot-rolled La(Fe,Co,Si)13-based alloys are promising magnetocaloric materials for solidstate cooling with near-net shaping capabilities,their underlying hot deformation mechanisms remain largely unexplored.In this study,a comprehensive and systematic investigation was conducted,by encompassing the analysis of hot deformation mechanisms,along with the microstructure evolution and magnetoc aloric properties of hot-rolled La-Fe-Co-Si alloy.The La_(1.05)Fe_(11.2)Co_(0.7)Si_(1.38)alloy was examined using multiscale mechanical analysis to assess the effects of temperature.A series of macroscale hot compression and microscale nanoindentation tests were performed to access global and local mechanical properties,including variations in hardness and indentation modulus of the primaryα-Fe and secondary 1:1:1 phases up to 800℃.A significant decrease in hardness and elastic recovery of the secondary phase was observed between 600and 800℃,above half of its melting point(1113℃),suggesting pronounced flow softening in both theα-Fe and 1:1:1 phases.Additionally,a novel multi-step annealing process was introduced for hot-rolled La-Fe-Co-Si alloys,involving partial transient liquid-phase diffusion in the 1:1:1 phase to address deformation-induced defects,such as residualα-Fe and lattice distortions in the 1:13 phase,which have not been previously reported.As a result,a primary La(Fe,Co,Si)13phase with a volume fraction of97.5%was achieved after multi-step annealing,compared to 87.5%using conventional annealing.Correspondingly,the magnetocaloric properties were restored,with the Curie temperature(TC)recovering from 276 to 268 K and the maximum magnetic entropy change(ΔSM)increasing from 7.56 to 8.67 J kg^(-1)K^(-1)under a 2 T magnetic field.
文摘With the rapid development of computer vision technology,artificial intelligence algorithms,and high-performance computing platforms,machine vision technology has gradually shown its great potential in automated production lines,especially in defect detection.Machine vision technology can be applied in many industries such as semiconductor,automobile manufacturing,aerospace,food,and drugs,which can significantly improve detection efficiency and accuracy,reduce labor costs,improve product quality,enhance market competitiveness,and provide strong support for the arrival of Industry 4.0 era.In this article,the concept,advantages,and disadvantages of machine vision and the algorithm framework of machine vision in the defect detection system are briefly described,aiming to promote the rapid development of industry and strengthen China’s industry.
文摘Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.
基金National Natural Science Foundation of China(52201054,52175368)National Science and Technology Major Projects(J2019-VI-0018-0133)+2 种基金Liaoning Provincial Science and Technology Program(2023-BS-019,2023-MS-020)National Key R&D Program of China(2021YFB3700401)Key Specialized Research and Development Break-Through-Unveiling and Commanding the Special Project Program in Liaoning Province(2021JH15)。
文摘The impact of casting defects on the weldability of K4951 superalloy was investigated using tungsten inert gas(TIG)welding.The as-cast K4951 superalloy samples with prefabricated U-shaped grooves of varying depths and widths were TIG welded,and the microstructures,cracks morphology,and precipitated phases were analyzed using optical microscope,scanning electron microscope,transmission electron microscope,and energy dispersive X-ray spectrometer.The results reveal that the dimensions of casting defects significantly affect the weldability of K4951.Deep defects(greater than 2 mm)lead to rapid crack propagation,while wider defects can moderate the propagation process of cracks.Elemental segregation and the formation of precipitated phases,such as MC carbides,are observed in the fusion zone,contributing to welding cracks.An optimal groove aspect ratio(depth-to-width)between 0.2 and 0.5 minimizes crack formation tendency and enhances tensile strength,resulting in a mixed brittle-ductile fracture mode of joint after high-temperature tensile testing.
基金supported by a Research Grant of Pukyong National University(2023)。
文摘Achieving high-quality perovskite films without surface defects is regarded as a crucial target for the development of durable high-performance perovskite solar cells.Additive engineering is commonly employed to simultaneously control the growth of perovskite crystals and passivate defects.Here,4-(trifluoromethyl)benzoic anhydride(4-TBA)composed of benzene rings functionalized with carbonyl and trifluoromethyl groups was used as an example additive to study the characteristics of additives used for producing high-quality perovskites and controlling their surface properties.The interaction between4-TBA and perovskite precursor materials was investigated using density functional theory(DFT)simulations.The electron-rich carbonyl group efficiently passivated the under-coordinated lead-ion defects.Additionally,hydrogen bonding between trifluoromethyl and organic cations prevents the generation of cation vacancies.Because of its intrinsic hydrophobicity,the trifluoromethyl group simultaneously improves the moisture and heat stability of the film.4-TBA serves as a universal modifier for various perovskite compositions.The power conversion efficiency(PCE)of inverted perovskite solar cells(PSCs)based on methylammonium(MA)with 4-TBA was improved from 16.15%to 19.28%.Similarly,the PCE of inverted PSCs based on a cesium formamidinium MA(CsFAMA)perovskite film increased from20.72%to 23.58%,upon addition of 4-TBA.Furthermore,the moisture and thermal stability of 4-TBAtreated films and devices was significantly enhanced,along with prolonged device performance.Our work provides guidance on selecting the structure and functional groups that are essential for surface defect passivation and the production of high-quality perovskites.
