Herein,we present a thermo-mechanical analyzer(TMA)and dynamic mechanical analyzer(DMA)of composite multi-layered gun propellant,focusing on thermal expansion coefficients and dynamic thermomechanical properties.The l...Herein,we present a thermo-mechanical analyzer(TMA)and dynamic mechanical analyzer(DMA)of composite multi-layered gun propellant,focusing on thermal expansion coefficients and dynamic thermomechanical properties.The linear thermal expansion coefficient of the prepared energetic material is determined as approx.0.1800×10^(-4)-0.2081×10^(-4)K^(-1).According to DMA test and dynamic thermomechanical properties,the glass transition temperature is also obtained.The tested value is within the range of 223.01-223.50 K,which indicates the lower limit of the energetic material.However,DMA tests reveal temperature changes,which occur due to thermal expansion.Moreover,the geometrical factor decreases with increasing temperature.Therefore,thermal expansion significantly affects the storage modulus and loss modulus.Additionally,the thermal expansion coefficient can be used to modify the storage and loss modulus.The results show that the proposed method provides effective and reliable modified results.展开更多
Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanism...Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.展开更多
Metallic glass composites hold significant potential as structural materials.However,few methods are available to enhance their mechanical properties postcasting.In this study,simple pre-tensile training was applied t...Metallic glass composites hold significant potential as structural materials.However,few methods are available to enhance their mechanical properties postcasting.In this study,simple pre-tensile training was applied to a TRIP-reinforced metallic glass composite,resulting in a more than one-third increase in plasticity,while the reliability of plasticity was also enhanced.The deformation mechanism was further elucidated,revealing that pre-tension induced the formation of multilayered nanostructures at the dendrite-glass interface.This microstructural evolution facilitates the formation of finer martensite laths within the dendrites and multiple shear bands in the glass matrix during compression,thereby enabling more uniform plastic deformation.These findings suggest that simple preloading treatments may offer a viable approach to regulating the microstructure of as-cast metallic glass composites and optimizing their mechanical properties.展开更多
Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technologic...Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.展开更多
The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m...The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.展开更多
Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynam...Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.展开更多
A composite electrocatalyst,CoMoNiO-S/NF-110(NF is nickel foam),was synthesized through electrodeposition,followed by pyrolysis and then the vulcanization process.CoMoNiO-S/NF-110 exhibited a structure where Ni3S2 and...A composite electrocatalyst,CoMoNiO-S/NF-110(NF is nickel foam),was synthesized through electrodeposition,followed by pyrolysis and then the vulcanization process.CoMoNiO-S/NF-110 exhibited a structure where Ni3S2 and Mo2S3 nanoparticles were integrated at the edges of Co3O4 nanosheets,creating a rich,heterogeneous interface that enhances the synergistic effects of each component.In an alkaline electrolyte,the synthesized CoMoNiO-S/NF-110 exhibited superior electrocatalytic performance for oxygen evolution reaction(OER),achieving current densities of 100 and 200 mA·cm^(-2) with low overpotentials of 199.4 and 224.4 mV,respectively,outperforming RuO2 and several high-performance Mo and Ni-based catalysts.This excellent performance is attributed to the rich interface formed between the components and active sites exposed by the defect structure.展开更多
KIT-5/Beta composite supports were synthesized using an in situ self-assembly hydrothermal method,and NiW/KIT-5/Beta catalysts were prepared by impregnation.A series of characterization techniques were utilized to eva...KIT-5/Beta composite supports were synthesized using an in situ self-assembly hydrothermal method,and NiW/KIT-5/Beta catalysts were prepared by impregnation.A series of characterization techniques were utilized to evaluate the influence of varying hydrothermal synthesis temperatures on the physicochemical properties of both the KIT-5/Beta supports and the resulting catalysts.The catalytic performances of catalysts were evaluated under reaction conditions of 320℃,4 MPa H_(2)pressure,and a weight hourly space velocity(WHSV)of 4.8 h^(-1)for hydrodenitrogenation(HDN)of quinoline.The results indicated that the specific surface area and pore structure of the materials could be effectively regulated by adjusting the hydrothermal synthesis temperature,which in turn influenced the number of active sites on the catalyst.The NiW/KB-125 catalyst,synthesized at 125℃,presented the highest quinoline HDN efficiency(96.8%),which can be attributed to its favorable pore channel structure,greater Brønsted acid number,higher degree of metal sulfidation(80.12%)and appropriate metal-support interaction(MSI).展开更多
The poor electrical conductivity of metal-organic frameworks(MOFs)limits their electrocatalytic performance in the oxygen evolution reaction(OER).In this study,a Py@Co-MOF composite material based on pyrene(Py)molecul...The poor electrical conductivity of metal-organic frameworks(MOFs)limits their electrocatalytic performance in the oxygen evolution reaction(OER).In this study,a Py@Co-MOF composite material based on pyrene(Py)molecules and{[Co2(BINDI)(DMA)_(2)]·DMA}_(n)(Co-MOF,H4BINDI=N,N'-bis(5-isophthalic acid)naphthalenediimide,DMA=N,N-dimethylacetamide)was synthesized via a one-pot method,leveragingπ-πinteractions between pyrene and Co-MOF to modulate electrical conductivity.Results demonstrate that the Py@Co-MOF catalyst exhibited significantly enhanced OER performance compared to pure Co-MOF or pyrene-based electrodes,achieving an overpotential of 246 mV at a current density of 10 mA·cm^(-2) along with excellent stability.Density functional theory(DFT)calculations reveal that the formation of O*in the second step is the rate-determining step(RDS)during the OER process on Co-MOF,with an energy barrier of 0.85 eV due to the weak adsorption affinity of the OH*intermediate for Co sites.CCDC:2419276.展开更多
The TiB+TiC dual-reinforced B_(4)C/TC4 composite was in-situ fabricated via incorporating 0.5wt%B_(4)C reinforcement during the laser melting deposition process.Different heat treatments of annealing and solid solutio...The TiB+TiC dual-reinforced B_(4)C/TC4 composite was in-situ fabricated via incorporating 0.5wt%B_(4)C reinforcement during the laser melting deposition process.Different heat treatments of annealing and solid solution were used to regulate the microstructure,mechanical properties,and corrosion properties of B_(4)C/TC4 composite.Results show that with the increase in temperature from 500℃to 800°C,partial lamellarα-Ti in the as-deposited sample is gradually transformed into equiaxedα-Ti,accompanied by the disappearance of basketweave microstructure.At 1100°C,a small portion of TiC phase suffers fusion.This composite exhibits the optimal combination of strength and plasticity after annealing at 500℃for 4 h followed by furnace cooling,which is attributed to the stress release effect and the refined basketweave microstructure.However,this composite shows a decline in corrosion resistance after various heat treatments due to grain coarsening and micro-galvanic corrosion.展开更多
In this study,using 3,5‑di(3′,5′‑dicarboxylphenyl)‑1H‑1,2,4‑triazole(H4L)as ligands,a gadolinia‑based organic framework complex{[GdNa(L)(H_(2)O)3]·2H_(2)O}_(n)(Gd‑Na‑MOF)was successfully designed and synthesize...In this study,using 3,5‑di(3′,5′‑dicarboxylphenyl)‑1H‑1,2,4‑triazole(H4L)as ligands,a gadolinia‑based organic framework complex{[GdNa(L)(H_(2)O)3]·2H_(2)O}_(n)(Gd‑Na‑MOF)was successfully designed and synthesized by hydrothermal method.The structure and properties were systematically characterized and tested by techniques such as single‑crystal X‑ray diffraction,powder X‑ray diffraction,thermogravimetric analysis,infrared spectroscopy,and fluorescence spectroscopy.The results indicate that this complex has a unique 3D structure,excellent thermal stability,and outstanding luminescent performance.Based on its luminescent properties,a polymer‑embedding method was employed to fabricate the Gd‑Na‑MOF into a flexible,washable composite fluorescent film,Gd‑Na‑MOF@PMMA/BMA(PMMA=polymethyl methacrylate,BMA=butyl methacrylate).This fluorescent film exhibited highly sensitive recognition capability for tyramine,with a low detection limit of 1.66μmol·L^(-1).It was used for the detection of tyramine in bananas,with a recovery rate of 96.92%‑100.26%.CCDC:2466949.展开更多
Biochar and biochar composites are versatile materials that can be used in many applications.In this study,biochar was prepared from sawdust and combined with the yttrium iron garnet(YIG)nanocrystal to investigate the...Biochar and biochar composites are versatile materials that can be used in many applications.In this study,biochar was prepared from sawdust and combined with the yttrium iron garnet(YIG)nanocrystal to investigate the shielding effectiveness of the composite structure.Firstly,the effect of the pyrolysis temperature on the shielding effectiveness of biochar was investigated.Secondly,biochars combined with YIG nanocrystals with different contents and shielding effectiveness of the composites were investigated.The electromagnetic effectiveness of the samples was investigated within the X band(8-12 GHz).The findings indicate that biochar demonstrates enhanced absorption properties with elevated pyrolysis temperatures.Biochars demonstrated an approximate 40 d B shielding effectiveness,while YIG exhibited approximately 7 d B,corresponding to absorption at 8 GHz.However,the combination of biochar and YIG exhibited exceptional absorption,reaching 67.12 d B at 8 GHz.展开更多
There is an urgent need to develop magnesium-matrix materials that exhibit both high thermal conductivity and low thermal expansion to ensure compatibility with chips.This study aims to develop a Mg-Zn-Cu alloy with h...There is an urgent need to develop magnesium-matrix materials that exhibit both high thermal conductivity and low thermal expansion to ensure compatibility with chips.This study aims to develop a Mg-Zn-Cu alloy with high thermal conductivity.Furthermore,it explores the preparation of AlN_(P)/Mg-Zn-Cu composites featuring low coefficients of thermal expansion.The stir casting method was utilized to fabricate the composites and an investigation was conducted to examine their microstructure and thermal properties.Results indicate that the addition of AlN_(P)reduces the thermal expansion coefficient while maintaining relatively high thermal conductivity.Specifically,the AlN_(P)/Mg-0.5Zn-0.5Cu composite with 30wt.%AlN_(P)achieves a thermal conductivity of 132.7 W·m^(-1)·K^(-1)and a thermal expansion coefficient of 18.5×10^(-6)K^(-1),rendering it suitable for electronic packaging applications where thermal management is critical.展开更多
The curing behavior of composites significantly influences their performance,making it crucial to understand the curing process.This study experimentally measured specific heat capacity,thermal conductivity,glass tran...The curing behavior of composites significantly influences their performance,making it crucial to understand the curing process.This study experimentally measured specific heat capacity,thermal conductivity,glass transition temperature,coefficient of thermal expansion,and cure shrinkage of materials.A simulation model of its curing deformation was established and validated against strain data obtained from fiber Bragg grating experiments.The effects of thickness,heating rate,and cooling rate on the curing temperature field and residual stress field during the molding of thick-section composite plates were analyzed.展开更多
In this study,multilayer lamination welding was employed to prepare graphene/copper(Gr/Cu)composite billets from graphene-coated copper foils,followed by multi-pass cold drawing to produce Φ1 mm Gr/Cu composite wires...In this study,multilayer lamination welding was employed to prepare graphene/copper(Gr/Cu)composite billets from graphene-coated copper foils,followed by multi-pass cold drawing to produce Φ1 mm Gr/Cu composite wires.Microstructure and property analyses in both the cold-drawn and annealed states show that the incorporation of graphene significantly improves the ductility and electrical conductivity of the copper wire.After annealing at 350℃ for 30 minutes,the composite wire demonstrates a tensile strength of 270 MPa and an electrical conductivity of 102.74%IACS,both superior to those of pure copper wire under identical conditions.At 150℃,the electrical conductivity of the annealed composite wire reaches 72.60%IACS,notably higher than the 68.19%IACS of pure copper.The results suggest that graphene is uniformly distributed within the composite wire,with minimal impact on conductivity,while effectively refining the copper grain structure to enhance ductility.Moreover,graphene suppresses copper lattice vibrations at elevated temperatures,reducing the rate of conductivity degradation.展开更多
The complex interactions and conflicting performance demands in multi-component composites pose significant challenges for achieving balanced multi-property optimization through conventional trial-and-error approaches...The complex interactions and conflicting performance demands in multi-component composites pose significant challenges for achieving balanced multi-property optimization through conventional trial-and-error approaches.Machine learning(ML)offers a promising solution,markedly improving materials discovery efficiency.However,the high dimensionality of feature spaces in such systems has long impeded effective ML-driven feature representation and inverse design.To overcome this,we present an Intelligent Screening System(ISS)framework to accelerate the discovery of optimal formulations balancing four key properties in 15-component PTFE-based copper-clad laminate composites(PTFE-CCLCs).ISS adopts modular descriptors based on the physical information of component volume fractions,thereby simplifying the feature representation.By leveraging the inverse prediction capability of ML models and constructing a performance-driven virtual candidate database,ISS significantly reduced the computational complexity associated with high-dimensional spaces.Experimental validation confirmed that ISSoptimized formulations exhibited superior synergy,notably resolving the trade-off between thermal conductivity and peel strength,and outperform many commercial counterparts.Despite limited data and inherent process variability,ISS achieved an average prediction accuracy of 76.5%,with thermal conductivity predictions exceeding 90%,demonstrating robust reliability.This work provides an innovative,efficient strategy for multifunctional optimization and accelerated discovery in ultra-complex composite systems,highlighting the integration of ML and advanced materials design.展开更多
To counteract small sample size,severe class imbalance and high feature redundancy in 90-day mRS prediction after stroke,this study proposes a four-stage pipeline-“ADASYN re-sampling→clinical+statistical feature scr...To counteract small sample size,severe class imbalance and high feature redundancy in 90-day mRS prediction after stroke,this study proposes a four-stage pipeline-“ADASYN re-sampling→clinical+statistical feature screening→dimensionality reduction→5-fold cross-validation”-and benchmark composite deep-learning architectures.ADASYN first balances the minority classes in the original feature space.Next,a tri-level filter(clinical domain knowledge,variance threshold,mutual information)removes clinically meaningless or redundant variables,after which PCA compresses the remaining features while preserving critical neurological signatures(e.g.,brain-herniation history).Four hybrid CNN-RNN models are trained and compared under strict 5-fold cross-validation;the optimal ensemble yields stable,clinically interpretable probabilities that can support individualized rehabilitation planning.展开更多
This work aims to evaluate the feasibility of the fabrication of nanostructured Cu/Al/Ag multi-layered composites by accumulative roll bonding(ARB),and to analyze the tensile properties and electrical conductivity of ...This work aims to evaluate the feasibility of the fabrication of nanostructured Cu/Al/Ag multi-layered composites by accumulative roll bonding(ARB),and to analyze the tensile properties and electrical conductivity of the produced composites.A theoretical model using strengthening mechanisms and some structural parameters extracted from X-ray diffraction is also developed to predict the tensile strength of the composites.It was found that by progression of ARB,the experimental and calculated tensile strengths are enhanced,reach a maximum of about 450 and 510 MPa at the fifth cycle of ARB,respectively and then are reduced.The electrical conductivity decreased slightly by increasing the number of ARB cycles at initial ARB cycles,but the decrease was intensified at the final ARB cycles.In conclusion,the merit of ARB to fabricate this type of multi-layered nanocomposites and the accuracy of the developed model to predict tensile strength were realized.展开更多
This study investigates the anisotropic thermal conductivity of aluminum matrix composites reinforced with graphene nano-plates(GNPs)and in situ ZrB_(2) nanoparticles,while simultaneously maintaining high strength and...This study investigates the anisotropic thermal conductivity of aluminum matrix composites reinforced with graphene nano-plates(GNPs)and in situ ZrB_(2) nanoparticles,while simultaneously maintaining high strength and toughness.A discontinuous layered GNPs-ZrB_(2)/AA6111 composite was prepared using in situ melt reactions and semi-solid stirring casting technology,combined with hot rolling deformation processing.Microstructural analysis revealed that the GNPs were aligned parallel to the rolling direction-transverse direction(RD-TD)plane,whereas the ZrB_(2) nanoparticles aggregated into cluster strips,collectively forming a discontinuous layered structure.This multilayer arrangement maximized the in-plane thermal conductivity of the GNPs.The tightly bonded GNP/Al interfaces with the locking of CuAl_(2) nanoparticles ensured that the GNPs fully exploited their high thermal conductivity.Therefore,the GNPs-ZrB_(2)/AA6111 composite achieved high in-plane thermal conductivity(230 W/(m·K)),which is higher than that of the matrix(206 W/(m·K)).The improved in-plane thermal conductivity is primarily attributed to the exceptionally high intrinsic in-plane thermal conductivity of the GNPs and their two-dimensional layered structure.However,the composite exhibited pronounced thermal conductivity anisotropy in the in-plane and through-plane directions.The reduced through-plane thermal conductivity is predominantly caused by the intrinsically low through-plane thermal conductivity of the GNPs and the increased interfacial thermal resistance from the additional grain boundaries.展开更多
Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement ...Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement in the field of material inverse design.However,VAEs are inherently prone to generating blurred images,posing challenges for precise inverse design and microstructure manufacturing.While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent,it simultaneously imposes a substantial burden on target optimization due to an excessively high search space.To address these limitations,this study adopts a Variational Autoencoder guided Conditional Diffusion Generative Model(VAE-CDGM)framework integrated with Bayesian optimization to achieve the inverse design of composite materials with targeted mechanical properties.The VAE-CDGM model synergizes the strengths of VAEs and Denoising Diffusion Probabilistic Models(DDPM),enabling the generation of high-quality,sharp images while preserving a manipulable latent space.To accommodate varying dimensional requirements of the latent space,two optimization strategies are proposed.When the latent space dimensionality is excessively high,SHapley Additive exPlanations(SHAP)sensitivity analysis is employed to identify critical latent features for optimization within a reduced subspace.Conversely,direct optimization is performed in the low-dimensional latent space of VAE-CDGM when dimensionality is modest.The results demonstrate that both strategies accurately achieve the targeted design of composite materials while circumventing the blurred reconstruction flaws of VAEs,which offers a novel pathway for the precise design of advanced materials.展开更多
文摘Herein,we present a thermo-mechanical analyzer(TMA)and dynamic mechanical analyzer(DMA)of composite multi-layered gun propellant,focusing on thermal expansion coefficients and dynamic thermomechanical properties.The linear thermal expansion coefficient of the prepared energetic material is determined as approx.0.1800×10^(-4)-0.2081×10^(-4)K^(-1).According to DMA test and dynamic thermomechanical properties,the glass transition temperature is also obtained.The tested value is within the range of 223.01-223.50 K,which indicates the lower limit of the energetic material.However,DMA tests reveal temperature changes,which occur due to thermal expansion.Moreover,the geometrical factor decreases with increasing temperature.Therefore,thermal expansion significantly affects the storage modulus and loss modulus.Additionally,the thermal expansion coefficient can be used to modify the storage and loss modulus.The results show that the proposed method provides effective and reliable modified results.
基金supported by Fundamental Research Funds for the Central Universities(No.lzujbky-2024-05)Innovation Foundation of Provincial Education Department of Gansu(2024B-005)+2 种基金Scientific Department of Gansu(24CXGA083,24CXGA024,JK2024-28,JK2024-32 and 23CXJA0007)Industrial Support Plan Project of Provincial Education Department of Gansu(2025CYZC-003 and CYZC-2024-10)the Hunan Natural Science Foundation Science and Education Joint Fund Project(2022JJ60109).
文摘Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.
基金financially supported by the National Key Research and Development Plan(No.2021YFA1600600)the National Natural Science Foundation of China(Nos.52271093 and 52074257)+3 种基金the Rare Earth Advanced Materials Technology Innovation Center(No.CXZX-B-2023110011)the Space Application System of China Manned Space Program(No.YYMT1201-EXP08)the special fund for Science and Technology Innovation Teams of Shanxi Province(No.202304051001036)the Fundamental Research Funds for the Central Universities(No.N2325008)
文摘Metallic glass composites hold significant potential as structural materials.However,few methods are available to enhance their mechanical properties postcasting.In this study,simple pre-tensile training was applied to a TRIP-reinforced metallic glass composite,resulting in a more than one-third increase in plasticity,while the reliability of plasticity was also enhanced.The deformation mechanism was further elucidated,revealing that pre-tension induced the formation of multilayered nanostructures at the dendrite-glass interface.This microstructural evolution facilitates the formation of finer martensite laths within the dendrites and multiple shear bands in the glass matrix during compression,thereby enabling more uniform plastic deformation.These findings suggest that simple preloading treatments may offer a viable approach to regulating the microstructure of as-cast metallic glass composites and optimizing their mechanical properties.
文摘Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.
基金National Natural Science Foundation of China(52175237)。
文摘The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.
基金Supported by the National Natural Science Foundation of China(Nos.52293472,22473096 and 22471164)。
文摘Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.
文摘A composite electrocatalyst,CoMoNiO-S/NF-110(NF is nickel foam),was synthesized through electrodeposition,followed by pyrolysis and then the vulcanization process.CoMoNiO-S/NF-110 exhibited a structure where Ni3S2 and Mo2S3 nanoparticles were integrated at the edges of Co3O4 nanosheets,creating a rich,heterogeneous interface that enhances the synergistic effects of each component.In an alkaline electrolyte,the synthesized CoMoNiO-S/NF-110 exhibited superior electrocatalytic performance for oxygen evolution reaction(OER),achieving current densities of 100 and 200 mA·cm^(-2) with low overpotentials of 199.4 and 224.4 mV,respectively,outperforming RuO2 and several high-performance Mo and Ni-based catalysts.This excellent performance is attributed to the rich interface formed between the components and active sites exposed by the defect structure.
基金Supported by the Autonomous Research Project of SKLCC(2024BWZ003)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA0390401)the Doctoral Research Start-up Funding of Shanxi Institute of Technology(026012).
文摘KIT-5/Beta composite supports were synthesized using an in situ self-assembly hydrothermal method,and NiW/KIT-5/Beta catalysts were prepared by impregnation.A series of characterization techniques were utilized to evaluate the influence of varying hydrothermal synthesis temperatures on the physicochemical properties of both the KIT-5/Beta supports and the resulting catalysts.The catalytic performances of catalysts were evaluated under reaction conditions of 320℃,4 MPa H_(2)pressure,and a weight hourly space velocity(WHSV)of 4.8 h^(-1)for hydrodenitrogenation(HDN)of quinoline.The results indicated that the specific surface area and pore structure of the materials could be effectively regulated by adjusting the hydrothermal synthesis temperature,which in turn influenced the number of active sites on the catalyst.The NiW/KB-125 catalyst,synthesized at 125℃,presented the highest quinoline HDN efficiency(96.8%),which can be attributed to its favorable pore channel structure,greater Brønsted acid number,higher degree of metal sulfidation(80.12%)and appropriate metal-support interaction(MSI).
文摘The poor electrical conductivity of metal-organic frameworks(MOFs)limits their electrocatalytic performance in the oxygen evolution reaction(OER).In this study,a Py@Co-MOF composite material based on pyrene(Py)molecules and{[Co2(BINDI)(DMA)_(2)]·DMA}_(n)(Co-MOF,H4BINDI=N,N'-bis(5-isophthalic acid)naphthalenediimide,DMA=N,N-dimethylacetamide)was synthesized via a one-pot method,leveragingπ-πinteractions between pyrene and Co-MOF to modulate electrical conductivity.Results demonstrate that the Py@Co-MOF catalyst exhibited significantly enhanced OER performance compared to pure Co-MOF or pyrene-based electrodes,achieving an overpotential of 246 mV at a current density of 10 mA·cm^(-2) along with excellent stability.Density functional theory(DFT)calculations reveal that the formation of O*in the second step is the rate-determining step(RDS)during the OER process on Co-MOF,with an energy barrier of 0.85 eV due to the weak adsorption affinity of the OH*intermediate for Co sites.CCDC:2419276.
基金Tianjin Municipal Natural Science Foundation(23JCYBJC00040)National Natural Science Foundation of China(52175369)。
文摘The TiB+TiC dual-reinforced B_(4)C/TC4 composite was in-situ fabricated via incorporating 0.5wt%B_(4)C reinforcement during the laser melting deposition process.Different heat treatments of annealing and solid solution were used to regulate the microstructure,mechanical properties,and corrosion properties of B_(4)C/TC4 composite.Results show that with the increase in temperature from 500℃to 800°C,partial lamellarα-Ti in the as-deposited sample is gradually transformed into equiaxedα-Ti,accompanied by the disappearance of basketweave microstructure.At 1100°C,a small portion of TiC phase suffers fusion.This composite exhibits the optimal combination of strength and plasticity after annealing at 500℃for 4 h followed by furnace cooling,which is attributed to the stress release effect and the refined basketweave microstructure.However,this composite shows a decline in corrosion resistance after various heat treatments due to grain coarsening and micro-galvanic corrosion.
文摘In this study,using 3,5‑di(3′,5′‑dicarboxylphenyl)‑1H‑1,2,4‑triazole(H4L)as ligands,a gadolinia‑based organic framework complex{[GdNa(L)(H_(2)O)3]·2H_(2)O}_(n)(Gd‑Na‑MOF)was successfully designed and synthesized by hydrothermal method.The structure and properties were systematically characterized and tested by techniques such as single‑crystal X‑ray diffraction,powder X‑ray diffraction,thermogravimetric analysis,infrared spectroscopy,and fluorescence spectroscopy.The results indicate that this complex has a unique 3D structure,excellent thermal stability,and outstanding luminescent performance.Based on its luminescent properties,a polymer‑embedding method was employed to fabricate the Gd‑Na‑MOF into a flexible,washable composite fluorescent film,Gd‑Na‑MOF@PMMA/BMA(PMMA=polymethyl methacrylate,BMA=butyl methacrylate).This fluorescent film exhibited highly sensitive recognition capability for tyramine,with a low detection limit of 1.66μmol·L^(-1).It was used for the detection of tyramine in bananas,with a recovery rate of 96.92%‑100.26%.CCDC:2466949.
基金support provided by the Center for Fabrication and Application of Electronic Materials at Dokuz Eylül University,Türkiye。
文摘Biochar and biochar composites are versatile materials that can be used in many applications.In this study,biochar was prepared from sawdust and combined with the yttrium iron garnet(YIG)nanocrystal to investigate the shielding effectiveness of the composite structure.Firstly,the effect of the pyrolysis temperature on the shielding effectiveness of biochar was investigated.Secondly,biochars combined with YIG nanocrystals with different contents and shielding effectiveness of the composites were investigated.The electromagnetic effectiveness of the samples was investigated within the X band(8-12 GHz).The findings indicate that biochar demonstrates enhanced absorption properties with elevated pyrolysis temperatures.Biochars demonstrated an approximate 40 d B shielding effectiveness,while YIG exhibited approximately 7 d B,corresponding to absorption at 8 GHz.However,the combination of biochar and YIG exhibited exceptional absorption,reaching 67.12 d B at 8 GHz.
基金financially supported by National Natural Science Foundation of China(No.52175321)the Fund of Key Laboratory of High Temperature Electromagnetic Materials and Structure of MOE(No.KB202505)。
文摘There is an urgent need to develop magnesium-matrix materials that exhibit both high thermal conductivity and low thermal expansion to ensure compatibility with chips.This study aims to develop a Mg-Zn-Cu alloy with high thermal conductivity.Furthermore,it explores the preparation of AlN_(P)/Mg-Zn-Cu composites featuring low coefficients of thermal expansion.The stir casting method was utilized to fabricate the composites and an investigation was conducted to examine their microstructure and thermal properties.Results indicate that the addition of AlN_(P)reduces the thermal expansion coefficient while maintaining relatively high thermal conductivity.Specifically,the AlN_(P)/Mg-0.5Zn-0.5Cu composite with 30wt.%AlN_(P)achieves a thermal conductivity of 132.7 W·m^(-1)·K^(-1)and a thermal expansion coefficient of 18.5×10^(-6)K^(-1),rendering it suitable for electronic packaging applications where thermal management is critical.
基金supported by the National Natural Science Foundation of China(Grant Nos.12172045,U2241240,and 12221002)the National Program on Key Basic Research Project,China(Grant No.2019-JCJQ-ZD-308-00).
文摘The curing behavior of composites significantly influences their performance,making it crucial to understand the curing process.This study experimentally measured specific heat capacity,thermal conductivity,glass transition temperature,coefficient of thermal expansion,and cure shrinkage of materials.A simulation model of its curing deformation was established and validated against strain data obtained from fiber Bragg grating experiments.The effects of thickness,heating rate,and cooling rate on the curing temperature field and residual stress field during the molding of thick-section composite plates were analyzed.
基金Funded by Hunan Provincial Natural Science Foundation(No.2023JJ40074)Hunan Provincial Education Department Excellent Youth Project(No.21B0757)Hunan Provincial Engineering Technology Center(No.2022TP2036)。
文摘In this study,multilayer lamination welding was employed to prepare graphene/copper(Gr/Cu)composite billets from graphene-coated copper foils,followed by multi-pass cold drawing to produce Φ1 mm Gr/Cu composite wires.Microstructure and property analyses in both the cold-drawn and annealed states show that the incorporation of graphene significantly improves the ductility and electrical conductivity of the copper wire.After annealing at 350℃ for 30 minutes,the composite wire demonstrates a tensile strength of 270 MPa and an electrical conductivity of 102.74%IACS,both superior to those of pure copper wire under identical conditions.At 150℃,the electrical conductivity of the annealed composite wire reaches 72.60%IACS,notably higher than the 68.19%IACS of pure copper.The results suggest that graphene is uniformly distributed within the composite wire,with minimal impact on conductivity,while effectively refining the copper grain structure to enhance ductility.Moreover,graphene suppresses copper lattice vibrations at elevated temperatures,reducing the rate of conductivity degradation.
基金financially supported by the National Key Research and Development Project of China(No.2022YFB3806900)。
文摘The complex interactions and conflicting performance demands in multi-component composites pose significant challenges for achieving balanced multi-property optimization through conventional trial-and-error approaches.Machine learning(ML)offers a promising solution,markedly improving materials discovery efficiency.However,the high dimensionality of feature spaces in such systems has long impeded effective ML-driven feature representation and inverse design.To overcome this,we present an Intelligent Screening System(ISS)framework to accelerate the discovery of optimal formulations balancing four key properties in 15-component PTFE-based copper-clad laminate composites(PTFE-CCLCs).ISS adopts modular descriptors based on the physical information of component volume fractions,thereby simplifying the feature representation.By leveraging the inverse prediction capability of ML models and constructing a performance-driven virtual candidate database,ISS significantly reduced the computational complexity associated with high-dimensional spaces.Experimental validation confirmed that ISSoptimized formulations exhibited superior synergy,notably resolving the trade-off between thermal conductivity and peel strength,and outperform many commercial counterparts.Despite limited data and inherent process variability,ISS achieved an average prediction accuracy of 76.5%,with thermal conductivity predictions exceeding 90%,demonstrating robust reliability.This work provides an innovative,efficient strategy for multifunctional optimization and accelerated discovery in ultra-complex composite systems,highlighting the integration of ML and advanced materials design.
基金Shanghai University of Engineering Science Undergraduate Innovation Training Program(Project No.:cx2521005)。
文摘To counteract small sample size,severe class imbalance and high feature redundancy in 90-day mRS prediction after stroke,this study proposes a four-stage pipeline-“ADASYN re-sampling→clinical+statistical feature screening→dimensionality reduction→5-fold cross-validation”-and benchmark composite deep-learning architectures.ADASYN first balances the minority classes in the original feature space.Next,a tri-level filter(clinical domain knowledge,variance threshold,mutual information)removes clinically meaningless or redundant variables,after which PCA compresses the remaining features while preserving critical neurological signatures(e.g.,brain-herniation history).Four hybrid CNN-RNN models are trained and compared under strict 5-fold cross-validation;the optimal ensemble yields stable,clinically interpretable probabilities that can support individualized rehabilitation planning.
文摘This work aims to evaluate the feasibility of the fabrication of nanostructured Cu/Al/Ag multi-layered composites by accumulative roll bonding(ARB),and to analyze the tensile properties and electrical conductivity of the produced composites.A theoretical model using strengthening mechanisms and some structural parameters extracted from X-ray diffraction is also developed to predict the tensile strength of the composites.It was found that by progression of ARB,the experimental and calculated tensile strengths are enhanced,reach a maximum of about 450 and 510 MPa at the fifth cycle of ARB,respectively and then are reduced.The electrical conductivity decreased slightly by increasing the number of ARB cycles at initial ARB cycles,but the decrease was intensified at the final ARB cycles.In conclusion,the merit of ARB to fabricate this type of multi-layered nanocomposites and the accuracy of the developed model to predict tensile strength were realized.
基金supported by the National Natural Science Foundation of China(Nos.52471156,U20A20274,and 52071158)the China Postdoctoral Science Foundation(Nos.2024M751173 and 2024M752703)+1 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent,China(No.2024ZB229)the Natural Science Foundation of Jiangsu Higher Education Institutions,China(No.24KJB430012).
文摘This study investigates the anisotropic thermal conductivity of aluminum matrix composites reinforced with graphene nano-plates(GNPs)and in situ ZrB_(2) nanoparticles,while simultaneously maintaining high strength and toughness.A discontinuous layered GNPs-ZrB_(2)/AA6111 composite was prepared using in situ melt reactions and semi-solid stirring casting technology,combined with hot rolling deformation processing.Microstructural analysis revealed that the GNPs were aligned parallel to the rolling direction-transverse direction(RD-TD)plane,whereas the ZrB_(2) nanoparticles aggregated into cluster strips,collectively forming a discontinuous layered structure.This multilayer arrangement maximized the in-plane thermal conductivity of the GNPs.The tightly bonded GNP/Al interfaces with the locking of CuAl_(2) nanoparticles ensured that the GNPs fully exploited their high thermal conductivity.Therefore,the GNPs-ZrB_(2)/AA6111 composite achieved high in-plane thermal conductivity(230 W/(m·K)),which is higher than that of the matrix(206 W/(m·K)).The improved in-plane thermal conductivity is primarily attributed to the exceptionally high intrinsic in-plane thermal conductivity of the GNPs and their two-dimensional layered structure.However,the composite exhibited pronounced thermal conductivity anisotropy in the in-plane and through-plane directions.The reduced through-plane thermal conductivity is predominantly caused by the intrinsically low through-plane thermal conductivity of the GNPs and the increased interfacial thermal resistance from the additional grain boundaries.
文摘Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement in the field of material inverse design.However,VAEs are inherently prone to generating blurred images,posing challenges for precise inverse design and microstructure manufacturing.While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent,it simultaneously imposes a substantial burden on target optimization due to an excessively high search space.To address these limitations,this study adopts a Variational Autoencoder guided Conditional Diffusion Generative Model(VAE-CDGM)framework integrated with Bayesian optimization to achieve the inverse design of composite materials with targeted mechanical properties.The VAE-CDGM model synergizes the strengths of VAEs and Denoising Diffusion Probabilistic Models(DDPM),enabling the generation of high-quality,sharp images while preserving a manipulable latent space.To accommodate varying dimensional requirements of the latent space,two optimization strategies are proposed.When the latent space dimensionality is excessively high,SHapley Additive exPlanations(SHAP)sensitivity analysis is employed to identify critical latent features for optimization within a reduced subspace.Conversely,direct optimization is performed in the low-dimensional latent space of VAE-CDGM when dimensionality is modest.The results demonstrate that both strategies accurately achieve the targeted design of composite materials while circumventing the blurred reconstruction flaws of VAEs,which offers a novel pathway for the precise design of advanced materials.
