To mitigate the impact of interdiffusion reactions between the silicide slurry and Ta12W alloy substrate during vacuum sintering process on the oxidation resistance of the silicide coating,a micro-arc oxidation pretre...To mitigate the impact of interdiffusion reactions between the silicide slurry and Ta12W alloy substrate during vacuum sintering process on the oxidation resistance of the silicide coating,a micro-arc oxidation pretreatment was employed to construct a Ta_(2)O_(5)ceramic layer on the Ta12W alloy surface.Subsequently,a slurry spraying-vacuum sintering method was used to prepare a Si-Cr-Ti-Zr coating on the pretreated substrate.Comparative studies were conducted on the microstructure,phase composition,and isothermal oxidation resistance(at 1600℃)of the as-prepared coatings with and without the micro-arc oxidation ceramic layer.The results show that the Ta_(2)O_(5)layer prepared at 400 V is more continuous and has smaller pores than that prepared at 350 V.After microarc oxidation pretreatment,the Si-Cr-Ti-Zr coating on Ta12W alloy consists of three distinct layers:an upper layer dominated by Ti_(5)Si_(3),Ta_(5)Si_(3),and ZrSi;a middle layer dominated by TaSi_(2);a coating/substrate interfacial reaction layer dominated by Ta_(5)Si_(3).Both the Si-Cr-Ti-Zr coatings with and without the Ta_(2)O_(5)ceramic layer do not fail after isothermal oxidation at 1600℃for 5 h.Notably,the addition of the Ta2O5 ceramic layer reduces the high-temperature oxidation rate of the coating.展开更多
A calcium zirconate crucible material with excellent performance was prepared by fixing the particle size proportion and exploring the addition of Y_(2)O_(3).The results show that Y^(3+)solid-dissolves into c-ZrO_(2)t...A calcium zirconate crucible material with excellent performance was prepared by fixing the particle size proportion and exploring the addition of Y_(2)O_(3).The results show that Y^(3+)solid-dissolves into c-ZrO_(2)to occupy the Zr^(4+)positions,leading to structural defects and promoting the sintering of calcium zirconate.Adding 0.5 wt.%Y_(2)O_(3)into calcium zirconate can enhance the modulus of rupture,reduce the thermal expansion coefficient,and improve the thermal shock resistance.Through high-temperature test,it is found that adding 0.5 wt.%Y_(2)O_(3)significantly improves the corrosion resistance of the sample.展开更多
Coral reefs worldwide are losing their species diversity and ecosystem function under threats from global warming and anthropogenic activities.In this study,we investigated the diversity and current state of scleracti...Coral reefs worldwide are losing their species diversity and ecosystem function under threats from global warming and anthropogenic activities.In this study,we investigated the diversity and current state of scleractinian corals surrounding the Qizhou Archipelago.A total of 87 species of scleractinian corals,belonging to 29 genera and 12 families,were found across ten survey sites.The family Merulinidae exhibited the highest species richness(39 species and 12 genera),followed by Acroporidae(15 species and 3genera).The living coral coverage was 16.9%±10.3%(mean±SD)and ranged from 4.6%to 35.1%,which varied significantly.Massive corals such as Porites lutea,Porites lobata,Montipora nodosa,and Favites abdita were dominant species.The recruitment rate of coral larvae was(1.20±0.97)ind/m^(2)(mean±SD).In addition,we constructed an ecological vulnerability assessment system and evaluated the ecological vulnerability of scleractinian corals surrounding the Qizhou Archipelago.The results showed that scleractinian corals at Gouluanpaoshi(GLPS)and Duifan(DF)were highly vulnerable,whereas those on other islands had low to medium vulnerability.In general,the scleractinian corals surrounding the Qizhou Archipelago show low to medium levels of ecological vulnerability.Identifying severely afflicted areas and developing effective methods to manage coral reefs in these regions are crucial.展开更多
Since the advent of smart contracts,security vulnerabilities have remained a persistent challenge,compromsing both the reliability of contract execution and the overall stability of the virtual currency market.Consequ...Since the advent of smart contracts,security vulnerabilities have remained a persistent challenge,compromsing both the reliability of contract execution and the overall stability of the virtual currency market.Consequently,the academic community has devoted increasing attention to these security risks.However,conventional approaches to vulnerability detection frequently exhibit limited accuracy.To address this limitation,the present study introduces a novel vulnerability detection framework called GNNSE that integrates symbolic execution with graph neural networks(GNNs).The proposedmethod first constructs semantic graphs to comprehensively capture the control flow and data flow dependencies within smart contracts.These graphs are subsequently processed using GNNs to efficiently identify contracts with a high likelihood of vulnerabilities.For these high-risk contracts,symbolic execution is employed to perform fine-grained,path-level analysis,thereby improving overall detection precision.Experimental results on a dataset comprising 10,079 contracts demonstrate that the proposed method achieves detection precisions of 93.58% for reentrancy vulnerabilities and 92.73% for timestamp-dependent vulnerabilities.展开更多
The Gabes aquifer system,located in southeastern Tunisia,is a crucial resource for supporting local socio-economic activities.Due to its dual porosity structure,is particularly vulnerable to pollution.This study aims ...The Gabes aquifer system,located in southeastern Tunisia,is a crucial resource for supporting local socio-economic activities.Due to its dual porosity structure,is particularly vulnerable to pollution.This study aims to develop a hybrid model that combines the Fracture Aquifer Index(FAI)with the conventional GOD(Groundwater occurrence,Overall lithology,Depth to water table)method,to assess groundwater vulnerability in fractured aquifer.To develop the hybrid model,the classical GOD method was integrated with FAI to produce a single composite index.Each parameter within both GOD and FAI was scored,and a final index was calculated to delineate vulnerable areas.The results show that the study area can be classified into four vulnerability levels:Very low,low,moderate,and high,indicating that approximately 8%of the area exhibits very low vulnerability,29%has low vulnerability,25%falls into the moderate category,and 38%is considered highly vulnerable.The FAI-GOD model further incorporates fracture network characteristics.This refinement reduces the classification to three vulnerability classes:Low,medium,and high.The outcomes demonstrate that 46%of the area is highly vulnerable due to a dense concentration of fractures,while 17%represents an intermediate zone characterized by either shallow or deeper fractures.In contrast,37%corresponds to areas with lightly fractured rock,where the impact on vulnerability is minimal.Multivariate statistical analysis was employed using Principal Components Analysis(PCA)and Hierarchical Cluster Analysis(HCA)on 24 samples across six variables.The first three components account for over 76%of the total variance,reinforcing the significance of fracture dynamics in classifying vulnerability levels.The FAI-GOD model removes the very-low-vulnerability class and expands the spatial extent of low-and high-vulnerability zones,reflecting the dominant influence of fracture networks on aquifer sensitivity.While both indices use a five-class system,FAI-GOD redistributes vulnerability by eliminating very-low-vulnerability areas and amplifying low/high categories,highlighting the critical role of fractures.A strong correlation(R2=0.94)between the GOD and FAI-GOD indices,demonstrated through second-order polynomial regression,confirms the robustness of the FAI-GOD model in accurately predicting vulnerability to pollution.This model provides a useful framework for assessing the vulnerability of complex aquifers and serves as a decision-making tool for groundwater managers in similar areas.展开更多
As artificial Intelligence(AI)continues to expand exponentially,particularly with the emergence of generative pre-trained transformers(GPT)based on a transformer’s architecture,which has revolutionized data processin...As artificial Intelligence(AI)continues to expand exponentially,particularly with the emergence of generative pre-trained transformers(GPT)based on a transformer’s architecture,which has revolutionized data processing and enabled significant improvements in various applications.This document seeks to investigate the security vulnerabilities detection in the source code using a range of large language models(LLM).Our primary objective is to evaluate the effectiveness of Static Application Security Testing(SAST)by applying various techniques such as prompt persona,structure outputs and zero-shot.To the selection of the LLMs(CodeLlama 7B,DeepSeek coder 7B,Gemini 1.5 Flash,Gemini 2.0 Flash,Mistral 7b Instruct,Phi 38b Mini 128K instruct,Qwen 2.5 coder,StartCoder 27B)with comparison and combination with Find Security Bugs.The evaluation method will involve using a selected dataset containing vulnerabilities,and the results to provide insights for different scenarios according to the software criticality(Business critical,non-critical,minimum effort,best effort)In detail,the main objectives of this study are to investigate if large language models outperform or exceed the capabilities of traditional static analysis tools,if the combining LLMs with Static Application Security Testing(SAST)tools lead to an improvement and the possibility that local machine learning models on a normal computer produce reliable results.Summarizing the most important conclusions of the research,it can be said that while it is true that the results have improved depending on the size of the LLM for business-critical software,the best results have been obtained by SAST analysis.This differs in“NonCritical,”“Best Effort,”and“Minimum Effort”scenarios,where the combination of LLM(Gemini)+SAST has obtained better results.展开更多
The limited high-temperature oxidation resistance of Mg alloys is a key factor restricting their development and application.The addition of some rare earth elements(REs),owing to their unique physical and chemical pr...The limited high-temperature oxidation resistance of Mg alloys is a key factor restricting their development and application.The addition of some rare earth elements(REs),owing to their unique physical and chemical properties,can significantly enhance the oxidation resistance of Mg alloys.Based on our previous study,we conclude that REs such as Gd,Y,and Ce enhance the oxidation resistance of Mg-RE alloys.This article comprehensively reviews recent research progress on high-temperature oxidation behavior and the potential mechanism in Mg-RE alloys.Based on the thermodynamic and kinetic analyses,the evolution of the complex oxide system formed during the high-temperature oxidation of Mg-RE alloys is first summarized.The diffusion behavior and concentration control mechanisms of REs during the oxidation process and how these mechanisms affect the sustained growth of the oxide film and antioxidant properties were elucidated.Moreover,the different structures of the oxide films were classified,and their properties were discussed.Finally,this paper introduces the applications of commonly used REs in Mg alloys and frontier research on their oxidation mechanisms.Based on the above review,we propose that future research perspectives can be explored in terms of expanding the experimental temperature range for oxidation tests,optimizing the chemical composition by adding trace REs to study their synergistic mechanism,revealing the underlying oxidation mechanism through advanced in situ microscopic characterization methods,and investigating the mechanical properties of oxide films using diverse approaches.展开更多
Background:Exposure to environmental vulnerability poses significant threats to adolescent suicidal ideation,while individual resilience can mitigate these adverse effects with notable gender commonalities and differe...Background:Exposure to environmental vulnerability poses significant threats to adolescent suicidal ideation,while individual resilience can mitigate these adverse effects with notable gender commonalities and differences.However,research examining how these factors co-configure at the individual level remains limited,particularly from a gender-specific perspective.Thus,the present study aims to adopt a person-centered analytic approach to identify gender-specific configurations of environmental vulnerability and individual resilience associated with suicidal ideation among Chinese adolescents.Methods:Data were collected from 2616 Chinese primary and secondary school students(aged 10–17;1223 girls).Participants completed validated scales measuring environmental vulnerability,individual resilience,and suicidal ideation.Latent profile analysis(LPA)was conducted separately by gender.Results:Gender differences were prominent:males exhibited higher resilience and lower suicidal ideation,while females reported higher environmental vulnerability and elevated levels of suicidal ideation.LPA identified three distinct profiles for males:Low Vulnerable–High Protective–Low Risk(LHL),Medium Vulnerable–Low Protective–Low Risk(MLL),and High Vulnerable–Low Protective–High Risk(HLH).Four profiles emerged for females:LHL,MLL,Medium Vulnerable–Low Protective–Medium Risk(MLM),and HLH.Crucially,within the HLH profile,males exhibited particularly deficient humor(η^(2)=0.19)and confidence(η^(2)=0.16),while females formed a distinct subgroup characterized by severe academic and family stressors(η^(2)=0.30–0.36).Conclusion:The study underscores developing gender-specific mental health interventions using a nuanced,person-centered approach that considers both environmental risk and individual resilience factors,which allows for targeted suicide prevention strategies addressing the unique needs of male and female adolescents.展开更多
Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve thro...Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve throughout the disease course.This review examined 95 studies(2000-2025)from PubMed,Web of Science,and CNKI databases including longitudinal cohorts,randomized controlled trials,and mixed-methods research,to characterize the complex interplay between biological,psychological,and social factors affecting RA patients’mental health.Findings revealed three distinct vulnerability trajectories(45%persistently low,30%fluctuating improvement,25%persistently high)and four adaptation stages,with critical intervention periods occurring 3-6 months postdiagnosis and during disease flares.Multiple factors significantly influence psychological outcomes,including gender(females showing 1.8-fold increased risk),age(younger patients experiencing 42%higher vulnerability),pain intensity,inflammatory markers,and neuroendocrine dysregulation(48%showing cortisol rhythm disruption).Early psychological intervention(within 3 months of diagnosis)demonstrated robust benefits,reducing depression incidence by 42%with effects persisting 24-36 months,while different modalities showed complementary advantages:Cognitive behavioral therapy for depression(Cohen’s d=0.68),mindfulness for pain acceptance(38%improvement),and peer support for meaning reconstruction(25.6%increase).These findings underscore the importance of integrating routine psychological assessment into standard RA care,developing stage-appropriate interventions,and advancing research toward personalized biopsychosocial approaches that address the dynamic psychological dimensions of the disease.展开更多
The increasing electrification of urban transportation,i.e.,subways and electric vehicles(EV),brings more interactions between the power system and transportation system and further results in fault propagation across...The increasing electrification of urban transportation,i.e.,subways and electric vehicles(EV),brings more interactions between the power system and transportation system and further results in fault propagation across them.To analyze vulnerability of the coupling system under extreme events,this paper establishes a multi-layer urban electric-transportation interdependent network(ETIN)model.First,a weighted coupled metro-road traffic network(CTN)model and network path planning approach are proposed.A prospect theory-based failure load redistribution(FLR)method is further established to account for uncertainty of TN link capacity affected by power supply.Second,topology and emergency control strategy of power network(PN)are modeled,followed by formulation of multi-layer ETIN model.In particular,the inter-layer fault propagation from PN to TN is modeled based on power supply correlation strength,while from TN to PN is modeled based on traffic flow.A few indexes are then defined to quantify vulnerability of ETIN under deliberate attack.Finally,the proposed method is verified on an electric-transportation system to show influence of fault propagations within ETIN on its vulnerability under extreme events.展开更多
Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing M...Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking.To bridge this gap,this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard(CFM-RILH).Validation via a case study of the GarzêTibetan Autonomous Prefecture Road Network(GTPRNs)reveals key characteristics of MRNs system vulnerability under RILH disturbances:(1)Under the disturbance effects of RILH,the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity,exhibiting a distinct critical threshold.When the disturbance intensity exceeds this threshold,the system undergoes a global cascading failure phenomenon analogous to an“avalanche.”(2)Under RILH disturbances,the robustness of the MRNs system possesses a distinct safety boundary.Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure.(3)Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances.Based on these findings,we propose a“Two-Stage Emergency Response and Hierarchical Fortification”strategy specifically to improve the resilience of GTPRNs impacted by RILH.The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards.Furthermore,its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.展开更多
In the context of modern software development characterized by increasing complexity and compressed development cycles,traditional static vulnerability detection methods face prominent challenges including high false ...In the context of modern software development characterized by increasing complexity and compressed development cycles,traditional static vulnerability detection methods face prominent challenges including high false positive rates and missed detections of complex logic due to their over-reliance on rule templates.This paper proposes a Syntax-Aware Hierarchical Attention Network(SAHAN)model,which achieves high-precision vulnerability detection through grammar-rule-driven multi-granularity code slicing and hierarchical semantic fusion mechanisms.The SAHAN model first generates Syntax Independent Units(SIUs),which slices the code based on Abstract Syntax Tree(AST)and predefined grammar rules,retaining vulnerability-sensitive contexts.Following this,through a hierarchical attention mechanism,the local syntax-aware layer encodes fine-grained patterns within SIUs,while the global semantic correlation layer captures vulnerability chains across SIUs,achieving synergistic modeling of syntax and semantics.Experiments show that on benchmark datasets like QEMU,SAHAN significantly improves detection performance by 4.8%to 13.1%on average compared to baseline models such as Devign and VulDeePecker.展开更多
TiB_(2)coatings can significantly enhance the high-temperature oxidation resistance of molybdenum,which would broaden the application range of molybdenum and alloys thereof.However,traditional methods for preparing Ti...TiB_(2)coatings can significantly enhance the high-temperature oxidation resistance of molybdenum,which would broaden the application range of molybdenum and alloys thereof.However,traditional methods for preparing TiB_(2)coatings have disadvantages such as high equipment costs,complicated processes,and highly toxic gas emissions.This paper proposes an environmentally friendly method,which requires inexpensive equipment and simple processing,for preparing TiB_(2)coating on molybdenum via electrophoretic deposition within Na3AlF6-based molten salts.The produced TiB_(2)layer had an approximate thickness of 60μm and exhibited high density,outstanding hardness(38.2 GPa)and robust adhesion strength(51 N).Additionally,high-temperature oxidation experiments revealed that,at900℃,the TiB_(2)coating provided effective protection to the molybdenum substrate against oxidation for 3 h.This result indicates that the TiB_(2)coating prepared on molybdenum using molten salt electrophoretic deposition possesses good high-temperature oxidation resistance.展开更多
In this study,the design,analysis,manufacturing,and testing of a 3D-printed conformal microstrip array antenna for high-temperature environments is presented.3D printing technology is used to fabricate a curved cerami...In this study,the design,analysis,manufacturing,and testing of a 3D-printed conformal microstrip array antenna for high-temperature environments is presented.3D printing technology is used to fabricate a curved ceramic substrate,and laser sintering and microdroplet spraying processes are used to add the conductive metal on the curved substrate.The problems of gain loss,bandwidth reduction,and frequency shift caused by high temperatures are addressed by using a proper antenna design,with parasitic patches,slots,and metal resonant cavities.The antenna prototype is characterized by the curved substrates and the conductive metals for the power dividers,the patch,and the ground plane;its performance is examined up to a temperature of 600℃in a muffle furnace and compared with the results from the numerical analysis.The results show that the antenna can effectively function at 600℃and even higher temperatures.展开更多
Graph neural networks(GNNs)have shown notable success in identifying security vulnerabilities within Ethereum smart contracts by capturing structural relationships encoded in control-and data-flow graphs.Despite their...Graph neural networks(GNNs)have shown notable success in identifying security vulnerabilities within Ethereum smart contracts by capturing structural relationships encoded in control-and data-flow graphs.Despite their effectiveness,most GNN-based vulnerability detectors operate as black boxes,making their decisions difficult to interpret and thus less suitable for critical security auditing.The information bottleneck(IB)principle provides a theoretical framework for isolating task-relevant graph components.However,existing IB-based implementations often encounter unstable optimization and limited understanding of code semantics.To address these issues,we introduce ContractGIB,an interpretable graph information bottleneck framework for function-level vulnerability analysis.ContractGIB introduces three main advances.First,ContractGIB introduces an Hilbert–Schmidt Independence Criterion(HSIC)based estimator that provides stable dependence measurement.Second,it incorporates a CodeBERT semantic module to improve node representations.Third,it initializes all nodes with pretrained CodeBERT embeddings,removing the need for hand-crafted features.For each contract function,ContractGIB identifies themost informative nodes forming an instance-specific explanatory subgraph that supports the model’s prediction.Comprehensive experiments on public smart contract datasets,including ESC andVSC,demonstrate thatContractGIB achieves superior performance compared to competitive GNN baselines,while offering clearer,instance-level interpretability.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
Co-based alloy coating was prepared on Zr alloy using laser melting and cladding technique to study the difference in the high-temperature oxidation behavior between pure metal Co coatings and Co-T800 alloy coatings,a...Co-based alloy coating was prepared on Zr alloy using laser melting and cladding technique to study the difference in the high-temperature oxidation behavior between pure metal Co coatings and Co-T800 alloy coatings,as well as the wear resistance of the coatings.Besides,the effect of changing the laser melting process on the coatings was also investigated.The oxidation mass gain at 800–1200℃and the high-temperature oxidation behavior during high-temperature treatment for 1 h of two coated Zr alloy samples were studied.Results show that the Co coating and the Co-T800 coating have better resistance against high-temperature oxidation.After oxidizing at 1000℃for 1 h,the thickness of the oxide layer of the uncoated sample was 241.0μm,whereas that of the sample with Co-based coating is only 11.8–35.5μm.The friction wear test shows that the depth of the abrasion mark of the coated sample is only 1/2 of that of the substrate,indicating that the hardness and wear resistance of the Zr substrate are greatly improved.The disadvantage of Co-based coatings is the inferior corrosion resistance in 3.5wt%NaCl solution.展开更多
Located in northern China,the Hetao Plain is an important agro-economic zone and population centre.The deterioration of local groundwater quality has had a serious impact on human health and economic development.Nowad...Located in northern China,the Hetao Plain is an important agro-economic zone and population centre.The deterioration of local groundwater quality has had a serious impact on human health and economic development.Nowadays,the groundwater vulnerability assessment(GVA)has become an essential task to identify the current status and development trend of groundwater quality.In this study,the Convolutional Neural Network(CNN)and Long Short-Term Memory(LSTM)models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism.The study firstly builds the CNN-LSTM modelwith self-attention(SA)mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine(SVM),Random Forest(RF),and Extreme Gradient Boosting(XGBoost).The results indicate that the CNNLSTM model outperforms thesemodels,demonstrating its significance in groundwater vulnerability assessment.It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years.This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities.Moreover,the overall groundwater vulnerability risk in the entire region has increased,evident fromboth the notably high value and standard deviation.This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities.The model can be optimized for diverse applications across regional environmental assessment,pollution prediction,and risk statistics.This study holds particular significance for ecological protection and groundwater resource management.展开更多
High-nickel ternary cathodes hold a great application prospect in solid-state lithium metal batteries to achieve high-energy density,but they still suffer from structural instability and detrimental side reactions wit...High-nickel ternary cathodes hold a great application prospect in solid-state lithium metal batteries to achieve high-energy density,but they still suffer from structural instability and detrimental side reactions with the solid-state electrolytes.To circumvent these issues,a continuous uniform layer polyacrylonitrile(PAN)was introduced on the surface of LiNi_(0.8)Mn_(0.1)Co_(0.1)O_(2) via in situ polymerization of acrylonitrile(AN).Furthermore,the partial-cyclized treatment of PAN(cPAN)coating layer presents high ionic and electron conductivity,which can accelerate interfacial Li+and electron diffusion simultaneously.And the thermodynamically stabilized cPAN coating layer cannot only effectively inhibit detrimental side reactions between cathode and solid-state electrolytes but also provide a homogeneous stress to simultaneously address the problems of bulk structural degradation,which contributes to the exceptional mechanical and electrochemical stabilities of the modified electrode.Besides,the coordination bond interaction between the cPAN and NCM811 can suppress the migration of Ni to elevate the stability of the crystal structure.Benefited from these,the In-cPAN-260@NCM811 shows excellent cycling performance with a retention of 86.8%after 300 cycles and superior rate capability.And endow the solid-state battery with thermal safety stability even at hightemperature extreme environment.This facile and scalable surface engineering represents significant progress in developing high-performance solid-state lithium metal batteries.展开更多
High-temperature industries,as the primary consumers of energy,are greatly concerned with energy savings.Designing refractory linings with low thermal conductivity to reduce heat dissipation through high-temperature f...High-temperature industries,as the primary consumers of energy,are greatly concerned with energy savings.Designing refractory linings with low thermal conductivity to reduce heat dissipation through high-temperature furnace linings is a critical concern.In this study,a series of novel entropy-stabilized spinel materials are reported,and their potential applications in high-temperature industries are investigated.XRD and TEM results indicate that all materials possess a cubic spinel crystal structure with the■space group.Furthermore,these materials exhibit good phase stability at high temperatures.All entropy-stabilized spinel aggregates demonstrated high refractoriness(>1800℃)and a high load softening temperature(>1700℃).The impact of configurational entropy on the properties of entropy-stabilized spinel materials was also studied.As configurational entropy increased,the thermal conductivity of the entropy-stabilized spinel decreased,while slag corrosion resistance deteriorated.For the entropy-stabilized spinel with a configurational entropy value of 1.126R,it showed good high-temperature stability,reliable resistance to slag attack,and a low thermal conductivity of 2.776 W·m^(-1)·K^(-1)at 1000℃.展开更多
基金National Natural Science Foundation of China(52071274)Key Research and Development Projects of Shaanxi Province(2023-YBGY-442)Science and Technology Nova Project-Innovative Talent Promotion Program of Shaanxi Province(2020KJXX-062)。
文摘To mitigate the impact of interdiffusion reactions between the silicide slurry and Ta12W alloy substrate during vacuum sintering process on the oxidation resistance of the silicide coating,a micro-arc oxidation pretreatment was employed to construct a Ta_(2)O_(5)ceramic layer on the Ta12W alloy surface.Subsequently,a slurry spraying-vacuum sintering method was used to prepare a Si-Cr-Ti-Zr coating on the pretreated substrate.Comparative studies were conducted on the microstructure,phase composition,and isothermal oxidation resistance(at 1600℃)of the as-prepared coatings with and without the micro-arc oxidation ceramic layer.The results show that the Ta_(2)O_(5)layer prepared at 400 V is more continuous and has smaller pores than that prepared at 350 V.After microarc oxidation pretreatment,the Si-Cr-Ti-Zr coating on Ta12W alloy consists of three distinct layers:an upper layer dominated by Ti_(5)Si_(3),Ta_(5)Si_(3),and ZrSi;a middle layer dominated by TaSi_(2);a coating/substrate interfacial reaction layer dominated by Ta_(5)Si_(3).Both the Si-Cr-Ti-Zr coatings with and without the Ta_(2)O_(5)ceramic layer do not fail after isothermal oxidation at 1600℃for 5 h.Notably,the addition of the Ta2O5 ceramic layer reduces the high-temperature oxidation rate of the coating.
基金provided by the National Natural Science Foundation of China(NSFC)through the Joint Fund Project(No.U24A202815)the Youth Science Fund Project(No.52302031).
文摘A calcium zirconate crucible material with excellent performance was prepared by fixing the particle size proportion and exploring the addition of Y_(2)O_(3).The results show that Y^(3+)solid-dissolves into c-ZrO_(2)to occupy the Zr^(4+)positions,leading to structural defects and promoting the sintering of calcium zirconate.Adding 0.5 wt.%Y_(2)O_(3)into calcium zirconate can enhance the modulus of rupture,reduce the thermal expansion coefficient,and improve the thermal shock resistance.Through high-temperature test,it is found that adding 0.5 wt.%Y_(2)O_(3)significantly improves the corrosion resistance of the sample.
基金funded by the Scientific Research Foundation of Third Institute of Oceanography,Ministry of Natural Resources(Nos.2022024 and 2020006)the National Natural Science Foundation of China(No.42106143)。
文摘Coral reefs worldwide are losing their species diversity and ecosystem function under threats from global warming and anthropogenic activities.In this study,we investigated the diversity and current state of scleractinian corals surrounding the Qizhou Archipelago.A total of 87 species of scleractinian corals,belonging to 29 genera and 12 families,were found across ten survey sites.The family Merulinidae exhibited the highest species richness(39 species and 12 genera),followed by Acroporidae(15 species and 3genera).The living coral coverage was 16.9%±10.3%(mean±SD)and ranged from 4.6%to 35.1%,which varied significantly.Massive corals such as Porites lutea,Porites lobata,Montipora nodosa,and Favites abdita were dominant species.The recruitment rate of coral larvae was(1.20±0.97)ind/m^(2)(mean±SD).In addition,we constructed an ecological vulnerability assessment system and evaluated the ecological vulnerability of scleractinian corals surrounding the Qizhou Archipelago.The results showed that scleractinian corals at Gouluanpaoshi(GLPS)and Duifan(DF)were highly vulnerable,whereas those on other islands had low to medium vulnerability.In general,the scleractinian corals surrounding the Qizhou Archipelago show low to medium levels of ecological vulnerability.Identifying severely afflicted areas and developing effective methods to manage coral reefs in these regions are crucial.
基金supported by the National Key Research and Development Program of China(2020YFB1005704).
文摘Since the advent of smart contracts,security vulnerabilities have remained a persistent challenge,compromsing both the reliability of contract execution and the overall stability of the virtual currency market.Consequently,the academic community has devoted increasing attention to these security risks.However,conventional approaches to vulnerability detection frequently exhibit limited accuracy.To address this limitation,the present study introduces a novel vulnerability detection framework called GNNSE that integrates symbolic execution with graph neural networks(GNNs).The proposedmethod first constructs semantic graphs to comprehensively capture the control flow and data flow dependencies within smart contracts.These graphs are subsequently processed using GNNs to efficiently identify contracts with a high likelihood of vulnerabilities.For these high-risk contracts,symbolic execution is employed to perform fine-grained,path-level analysis,thereby improving overall detection precision.Experimental results on a dataset comprising 10,079 contracts demonstrate that the proposed method achieves detection precisions of 93.58% for reentrancy vulnerabilities and 92.73% for timestamp-dependent vulnerabilities.
文摘The Gabes aquifer system,located in southeastern Tunisia,is a crucial resource for supporting local socio-economic activities.Due to its dual porosity structure,is particularly vulnerable to pollution.This study aims to develop a hybrid model that combines the Fracture Aquifer Index(FAI)with the conventional GOD(Groundwater occurrence,Overall lithology,Depth to water table)method,to assess groundwater vulnerability in fractured aquifer.To develop the hybrid model,the classical GOD method was integrated with FAI to produce a single composite index.Each parameter within both GOD and FAI was scored,and a final index was calculated to delineate vulnerable areas.The results show that the study area can be classified into four vulnerability levels:Very low,low,moderate,and high,indicating that approximately 8%of the area exhibits very low vulnerability,29%has low vulnerability,25%falls into the moderate category,and 38%is considered highly vulnerable.The FAI-GOD model further incorporates fracture network characteristics.This refinement reduces the classification to three vulnerability classes:Low,medium,and high.The outcomes demonstrate that 46%of the area is highly vulnerable due to a dense concentration of fractures,while 17%represents an intermediate zone characterized by either shallow or deeper fractures.In contrast,37%corresponds to areas with lightly fractured rock,where the impact on vulnerability is minimal.Multivariate statistical analysis was employed using Principal Components Analysis(PCA)and Hierarchical Cluster Analysis(HCA)on 24 samples across six variables.The first three components account for over 76%of the total variance,reinforcing the significance of fracture dynamics in classifying vulnerability levels.The FAI-GOD model removes the very-low-vulnerability class and expands the spatial extent of low-and high-vulnerability zones,reflecting the dominant influence of fracture networks on aquifer sensitivity.While both indices use a five-class system,FAI-GOD redistributes vulnerability by eliminating very-low-vulnerability areas and amplifying low/high categories,highlighting the critical role of fractures.A strong correlation(R2=0.94)between the GOD and FAI-GOD indices,demonstrated through second-order polynomial regression,confirms the robustness of the FAI-GOD model in accurately predicting vulnerability to pollution.This model provides a useful framework for assessing the vulnerability of complex aquifers and serves as a decision-making tool for groundwater managers in similar areas.
文摘As artificial Intelligence(AI)continues to expand exponentially,particularly with the emergence of generative pre-trained transformers(GPT)based on a transformer’s architecture,which has revolutionized data processing and enabled significant improvements in various applications.This document seeks to investigate the security vulnerabilities detection in the source code using a range of large language models(LLM).Our primary objective is to evaluate the effectiveness of Static Application Security Testing(SAST)by applying various techniques such as prompt persona,structure outputs and zero-shot.To the selection of the LLMs(CodeLlama 7B,DeepSeek coder 7B,Gemini 1.5 Flash,Gemini 2.0 Flash,Mistral 7b Instruct,Phi 38b Mini 128K instruct,Qwen 2.5 coder,StartCoder 27B)with comparison and combination with Find Security Bugs.The evaluation method will involve using a selected dataset containing vulnerabilities,and the results to provide insights for different scenarios according to the software criticality(Business critical,non-critical,minimum effort,best effort)In detail,the main objectives of this study are to investigate if large language models outperform or exceed the capabilities of traditional static analysis tools,if the combining LLMs with Static Application Security Testing(SAST)tools lead to an improvement and the possibility that local machine learning models on a normal computer produce reliable results.Summarizing the most important conclusions of the research,it can be said that while it is true that the results have improved depending on the size of the LLM for business-critical software,the best results have been obtained by SAST analysis.This differs in“NonCritical,”“Best Effort,”and“Minimum Effort”scenarios,where the combination of LLM(Gemini)+SAST has obtained better results.
基金supported by the Key R&D Program of Shandong Province,China(No.2025CXGC 010412)the National Key Research and Development Program of China(No.2022YFB3709300)the National Natural Science Foundation of China(No.U21A2048).
文摘The limited high-temperature oxidation resistance of Mg alloys is a key factor restricting their development and application.The addition of some rare earth elements(REs),owing to their unique physical and chemical properties,can significantly enhance the oxidation resistance of Mg alloys.Based on our previous study,we conclude that REs such as Gd,Y,and Ce enhance the oxidation resistance of Mg-RE alloys.This article comprehensively reviews recent research progress on high-temperature oxidation behavior and the potential mechanism in Mg-RE alloys.Based on the thermodynamic and kinetic analyses,the evolution of the complex oxide system formed during the high-temperature oxidation of Mg-RE alloys is first summarized.The diffusion behavior and concentration control mechanisms of REs during the oxidation process and how these mechanisms affect the sustained growth of the oxide film and antioxidant properties were elucidated.Moreover,the different structures of the oxide films were classified,and their properties were discussed.Finally,this paper introduces the applications of commonly used REs in Mg alloys and frontier research on their oxidation mechanisms.Based on the above review,we propose that future research perspectives can be explored in terms of expanding the experimental temperature range for oxidation tests,optimizing the chemical composition by adding trace REs to study their synergistic mechanism,revealing the underlying oxidation mechanism through advanced in situ microscopic characterization methods,and investigating the mechanical properties of oxide films using diverse approaches.
基金supported by the Major Planning Project of Philosophy and Social Science of Guangdong Province(GD23ZD17)the Humanities and Social Sciences Program of the Ministry of Education(23YJA190006)+3 种基金the Ministry of Education(MOE)Major Project of Philosophy and Social Sciences Research(2025JZDZ024)the MOE Project of the Key Research Institute of Humanities and Social Sciences in Universities(22JJD190008)a grant from the Research Center for Brain Cognition and Human Development of Guangdong(2024B0303390003)the Psychological Services and Counseling Base for the Happy Guangzhou Project.
文摘Background:Exposure to environmental vulnerability poses significant threats to adolescent suicidal ideation,while individual resilience can mitigate these adverse effects with notable gender commonalities and differences.However,research examining how these factors co-configure at the individual level remains limited,particularly from a gender-specific perspective.Thus,the present study aims to adopt a person-centered analytic approach to identify gender-specific configurations of environmental vulnerability and individual resilience associated with suicidal ideation among Chinese adolescents.Methods:Data were collected from 2616 Chinese primary and secondary school students(aged 10–17;1223 girls).Participants completed validated scales measuring environmental vulnerability,individual resilience,and suicidal ideation.Latent profile analysis(LPA)was conducted separately by gender.Results:Gender differences were prominent:males exhibited higher resilience and lower suicidal ideation,while females reported higher environmental vulnerability and elevated levels of suicidal ideation.LPA identified three distinct profiles for males:Low Vulnerable–High Protective–Low Risk(LHL),Medium Vulnerable–Low Protective–Low Risk(MLL),and High Vulnerable–Low Protective–High Risk(HLH).Four profiles emerged for females:LHL,MLL,Medium Vulnerable–Low Protective–Medium Risk(MLM),and HLH.Crucially,within the HLH profile,males exhibited particularly deficient humor(η^(2)=0.19)and confidence(η^(2)=0.16),while females formed a distinct subgroup characterized by severe academic and family stressors(η^(2)=0.30–0.36).Conclusion:The study underscores developing gender-specific mental health interventions using a nuanced,person-centered approach that considers both environmental risk and individual resilience factors,which allows for targeted suicide prevention strategies addressing the unique needs of male and female adolescents.
基金Supported by Chongqing Health Commission and Chongqing Science and Technology Bureau,No.2023MSXM182。
文摘Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve throughout the disease course.This review examined 95 studies(2000-2025)from PubMed,Web of Science,and CNKI databases including longitudinal cohorts,randomized controlled trials,and mixed-methods research,to characterize the complex interplay between biological,psychological,and social factors affecting RA patients’mental health.Findings revealed three distinct vulnerability trajectories(45%persistently low,30%fluctuating improvement,25%persistently high)and four adaptation stages,with critical intervention periods occurring 3-6 months postdiagnosis and during disease flares.Multiple factors significantly influence psychological outcomes,including gender(females showing 1.8-fold increased risk),age(younger patients experiencing 42%higher vulnerability),pain intensity,inflammatory markers,and neuroendocrine dysregulation(48%showing cortisol rhythm disruption).Early psychological intervention(within 3 months of diagnosis)demonstrated robust benefits,reducing depression incidence by 42%with effects persisting 24-36 months,while different modalities showed complementary advantages:Cognitive behavioral therapy for depression(Cohen’s d=0.68),mindfulness for pain acceptance(38%improvement),and peer support for meaning reconstruction(25.6%increase).These findings underscore the importance of integrating routine psychological assessment into standard RA care,developing stage-appropriate interventions,and advancing research toward personalized biopsychosocial approaches that address the dynamic psychological dimensions of the disease.
文摘The increasing electrification of urban transportation,i.e.,subways and electric vehicles(EV),brings more interactions between the power system and transportation system and further results in fault propagation across them.To analyze vulnerability of the coupling system under extreme events,this paper establishes a multi-layer urban electric-transportation interdependent network(ETIN)model.First,a weighted coupled metro-road traffic network(CTN)model and network path planning approach are proposed.A prospect theory-based failure load redistribution(FLR)method is further established to account for uncertainty of TN link capacity affected by power supply.Second,topology and emergency control strategy of power network(PN)are modeled,followed by formulation of multi-layer ETIN model.In particular,the inter-layer fault propagation from PN to TN is modeled based on power supply correlation strength,while from TN to PN is modeled based on traffic flow.A few indexes are then defined to quantify vulnerability of ETIN under deliberate attack.Finally,the proposed method is verified on an electric-transportation system to show influence of fault propagations within ETIN on its vulnerability under extreme events.
基金financially supported by the National Key R&D Program of China(2024YFE0111900)The National Natural Science Foundation of China(U2468214,52378370,52278372)+1 种基金The National Ten Thousand Talent Program for Young Top-notch Talents(2022QB04978)The Science and Technology Program of Hebei Province(2023HBQZYCSB004)。
文摘Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking.To bridge this gap,this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard(CFM-RILH).Validation via a case study of the GarzêTibetan Autonomous Prefecture Road Network(GTPRNs)reveals key characteristics of MRNs system vulnerability under RILH disturbances:(1)Under the disturbance effects of RILH,the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity,exhibiting a distinct critical threshold.When the disturbance intensity exceeds this threshold,the system undergoes a global cascading failure phenomenon analogous to an“avalanche.”(2)Under RILH disturbances,the robustness of the MRNs system possesses a distinct safety boundary.Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure.(3)Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances.Based on these findings,we propose a“Two-Stage Emergency Response and Hierarchical Fortification”strategy specifically to improve the resilience of GTPRNs impacted by RILH.The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards.Furthermore,its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.
基金supported by the research start-up funds for invited doctor of Lanzhou University of Technology under Grant 14/062402。
文摘In the context of modern software development characterized by increasing complexity and compressed development cycles,traditional static vulnerability detection methods face prominent challenges including high false positive rates and missed detections of complex logic due to their over-reliance on rule templates.This paper proposes a Syntax-Aware Hierarchical Attention Network(SAHAN)model,which achieves high-precision vulnerability detection through grammar-rule-driven multi-granularity code slicing and hierarchical semantic fusion mechanisms.The SAHAN model first generates Syntax Independent Units(SIUs),which slices the code based on Abstract Syntax Tree(AST)and predefined grammar rules,retaining vulnerability-sensitive contexts.Following this,through a hierarchical attention mechanism,the local syntax-aware layer encodes fine-grained patterns within SIUs,while the global semantic correlation layer captures vulnerability chains across SIUs,achieving synergistic modeling of syntax and semantics.Experiments show that on benchmark datasets like QEMU,SAHAN significantly improves detection performance by 4.8%to 13.1%on average compared to baseline models such as Devign and VulDeePecker.
基金supported by the Original Exploratory Program of the National Natural Science Foundation of China(No.52450012)。
文摘TiB_(2)coatings can significantly enhance the high-temperature oxidation resistance of molybdenum,which would broaden the application range of molybdenum and alloys thereof.However,traditional methods for preparing TiB_(2)coatings have disadvantages such as high equipment costs,complicated processes,and highly toxic gas emissions.This paper proposes an environmentally friendly method,which requires inexpensive equipment and simple processing,for preparing TiB_(2)coating on molybdenum via electrophoretic deposition within Na3AlF6-based molten salts.The produced TiB_(2)layer had an approximate thickness of 60μm and exhibited high density,outstanding hardness(38.2 GPa)and robust adhesion strength(51 N).Additionally,high-temperature oxidation experiments revealed that,at900℃,the TiB_(2)coating provided effective protection to the molybdenum substrate against oxidation for 3 h.This result indicates that the TiB_(2)coating prepared on molybdenum using molten salt electrophoretic deposition possesses good high-temperature oxidation resistance.
基金National Natural Science Foundation of China(No.U2241205)the Natural Science Basic Research Program of Shaanxi(Nos.2022JC-33,2023-GHZD-35,and 2024JC-ZDXM-25)+1 种基金the Fundamental Research Funds for the Central Universitiesthe National 111 Project to provide fund for conducting experiments。
文摘In this study,the design,analysis,manufacturing,and testing of a 3D-printed conformal microstrip array antenna for high-temperature environments is presented.3D printing technology is used to fabricate a curved ceramic substrate,and laser sintering and microdroplet spraying processes are used to add the conductive metal on the curved substrate.The problems of gain loss,bandwidth reduction,and frequency shift caused by high temperatures are addressed by using a proper antenna design,with parasitic patches,slots,and metal resonant cavities.The antenna prototype is characterized by the curved substrates and the conductive metals for the power dividers,the patch,and the ground plane;its performance is examined up to a temperature of 600℃in a muffle furnace and compared with the results from the numerical analysis.The results show that the antenna can effectively function at 600℃and even higher temperatures.
基金supported by the National Natural Science Foundation of China(Grant Nos.52208424,52208416,52078091,and 52108399)the Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0102).
文摘Graph neural networks(GNNs)have shown notable success in identifying security vulnerabilities within Ethereum smart contracts by capturing structural relationships encoded in control-and data-flow graphs.Despite their effectiveness,most GNN-based vulnerability detectors operate as black boxes,making their decisions difficult to interpret and thus less suitable for critical security auditing.The information bottleneck(IB)principle provides a theoretical framework for isolating task-relevant graph components.However,existing IB-based implementations often encounter unstable optimization and limited understanding of code semantics.To address these issues,we introduce ContractGIB,an interpretable graph information bottleneck framework for function-level vulnerability analysis.ContractGIB introduces three main advances.First,ContractGIB introduces an Hilbert–Schmidt Independence Criterion(HSIC)based estimator that provides stable dependence measurement.Second,it incorporates a CodeBERT semantic module to improve node representations.Third,it initializes all nodes with pretrained CodeBERT embeddings,removing the need for hand-crafted features.For each contract function,ContractGIB identifies themost informative nodes forming an instance-specific explanatory subgraph that supports the model’s prediction.Comprehensive experiments on public smart contract datasets,including ESC andVSC,demonstrate thatContractGIB achieves superior performance compared to competitive GNN baselines,while offering clearer,instance-level interpretability.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
基金National Natural Science Foundation of China(52071126)Natural Science Foundation of Tianjin City,China(22JCQNJC01240)+2 种基金Central Guidance on Local Science and Technology Development Fund of Hebei Province(226Z1009G)Special Funds for Science and Technology Innovation in Hebei(2022X19)Anhui Provincial Natural Science Foundation(2308085ME135)。
文摘Co-based alloy coating was prepared on Zr alloy using laser melting and cladding technique to study the difference in the high-temperature oxidation behavior between pure metal Co coatings and Co-T800 alloy coatings,as well as the wear resistance of the coatings.Besides,the effect of changing the laser melting process on the coatings was also investigated.The oxidation mass gain at 800–1200℃and the high-temperature oxidation behavior during high-temperature treatment for 1 h of two coated Zr alloy samples were studied.Results show that the Co coating and the Co-T800 coating have better resistance against high-temperature oxidation.After oxidizing at 1000℃for 1 h,the thickness of the oxide layer of the uncoated sample was 241.0μm,whereas that of the sample with Co-based coating is only 11.8–35.5μm.The friction wear test shows that the depth of the abrasion mark of the coated sample is only 1/2 of that of the substrate,indicating that the hardness and wear resistance of the Zr substrate are greatly improved.The disadvantage of Co-based coatings is the inferior corrosion resistance in 3.5wt%NaCl solution.
基金supported by the National Key Research and Development Program of China(No.2021YFA0715900).
文摘Located in northern China,the Hetao Plain is an important agro-economic zone and population centre.The deterioration of local groundwater quality has had a serious impact on human health and economic development.Nowadays,the groundwater vulnerability assessment(GVA)has become an essential task to identify the current status and development trend of groundwater quality.In this study,the Convolutional Neural Network(CNN)and Long Short-Term Memory(LSTM)models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism.The study firstly builds the CNN-LSTM modelwith self-attention(SA)mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine(SVM),Random Forest(RF),and Extreme Gradient Boosting(XGBoost).The results indicate that the CNNLSTM model outperforms thesemodels,demonstrating its significance in groundwater vulnerability assessment.It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years.This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities.Moreover,the overall groundwater vulnerability risk in the entire region has increased,evident fromboth the notably high value and standard deviation.This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities.The model can be optimized for diverse applications across regional environmental assessment,pollution prediction,and risk statistics.This study holds particular significance for ecological protection and groundwater resource management.
基金financially supported by the National Natural Science Foundation of China(Nos.22102212 and 22479067).
文摘High-nickel ternary cathodes hold a great application prospect in solid-state lithium metal batteries to achieve high-energy density,but they still suffer from structural instability and detrimental side reactions with the solid-state electrolytes.To circumvent these issues,a continuous uniform layer polyacrylonitrile(PAN)was introduced on the surface of LiNi_(0.8)Mn_(0.1)Co_(0.1)O_(2) via in situ polymerization of acrylonitrile(AN).Furthermore,the partial-cyclized treatment of PAN(cPAN)coating layer presents high ionic and electron conductivity,which can accelerate interfacial Li+and electron diffusion simultaneously.And the thermodynamically stabilized cPAN coating layer cannot only effectively inhibit detrimental side reactions between cathode and solid-state electrolytes but also provide a homogeneous stress to simultaneously address the problems of bulk structural degradation,which contributes to the exceptional mechanical and electrochemical stabilities of the modified electrode.Besides,the coordination bond interaction between the cPAN and NCM811 can suppress the migration of Ni to elevate the stability of the crystal structure.Benefited from these,the In-cPAN-260@NCM811 shows excellent cycling performance with a retention of 86.8%after 300 cycles and superior rate capability.And endow the solid-state battery with thermal safety stability even at hightemperature extreme environment.This facile and scalable surface engineering represents significant progress in developing high-performance solid-state lithium metal batteries.
基金financially supported by the National Natural Science Foundation of China(Nos.52472032 and 52172023)the Key Program of Natural Science Foundation of Hubei Province(No.2024AFA083)
文摘High-temperature industries,as the primary consumers of energy,are greatly concerned with energy savings.Designing refractory linings with low thermal conductivity to reduce heat dissipation through high-temperature furnace linings is a critical concern.In this study,a series of novel entropy-stabilized spinel materials are reported,and their potential applications in high-temperature industries are investigated.XRD and TEM results indicate that all materials possess a cubic spinel crystal structure with the■space group.Furthermore,these materials exhibit good phase stability at high temperatures.All entropy-stabilized spinel aggregates demonstrated high refractoriness(>1800℃)and a high load softening temperature(>1700℃).The impact of configurational entropy on the properties of entropy-stabilized spinel materials was also studied.As configurational entropy increased,the thermal conductivity of the entropy-stabilized spinel decreased,while slag corrosion resistance deteriorated.For the entropy-stabilized spinel with a configurational entropy value of 1.126R,it showed good high-temperature stability,reliable resistance to slag attack,and a low thermal conductivity of 2.776 W·m^(-1)·K^(-1)at 1000℃.
