Artificial solid electrolyte interphase(SEI) is promising to inhibit uncontrollable lithium dendrites and enable long cycling stability for lithium metal batteries. However, the essential mechanical stability is limit...Artificial solid electrolyte interphase(SEI) is promising to inhibit uncontrollable lithium dendrites and enable long cycling stability for lithium metal batteries. However, the essential mechanical stability is limited since organic layers generally have low modulus whereas intrinsic brittleness for inorganic ones remains a great concern. Polymer-based SEIs with rigid and flexible chains in adequate mechanical properties are supposed to address this issue. Herein, a homogeneous and mechanically stable diffusion layer is achieved by blending rigid chains of polyphenylene sulfone(PPSU) with flexible chains of poly(vinylidene fluoride)(PVDF) in a hybrid membrane, enabling uniform diffusion and stabilizing the lithium metal anode. The Li||Cu cell with the protected electrode exhibits a long lifetime more than 450 cycles(0.5 m A cm^(-2), 1.0 m A h cm^(-2))(fourfold longer than the control group) with higher average Coulombic efficiency of 98.7%. Enhanced performances are also observed at Li||Li and full cell configurations. The improved performances are attributed to the controlled morphology and stable interphase, according to scanning electron microscopy(SEM) and electrochemical impedance. This research advances the idea of uniform lithium plating and provides a new insight on how to create a homogeneous and mechanically stable diffusion layer using rigid-flexible polymers.展开更多
Rigid-flexible composite pavement has gained significant popularity in recent decades.This paper provides a comprehensive review of the research progress concerning rigid-flexible composite pavement,aiming to promote ...Rigid-flexible composite pavement has gained significant popularity in recent decades.This paper provides a comprehensive review of the research progress concerning rigid-flexible composite pavement,aiming to promote its application and address key issues while identifying future directions.The design theory and methodology of rigid-flexible composite pavement are discussed,followed by a description of its structural and mechanical behavior characteristics.The load stress,temperature stress,and their interactive effects between the asphalt layer and the rigid base were analyzed.It is clarified that the asphalt layer serves a dual role as both a“functional layer”and a“structural layer”.Typical distresses of rigid-flexible composite pavement,which primarily occur in the asphalt layer,were discussed.These distresses include reflective cracking,top-down cracking,rutting,and compressive-shear failure.Generally,the integrity of the rigid base and the interlaminar bonding conditions significantly impact the performance and distress of the asphalt layer.The technology for enhancing the performance of rigid-flexible composite pavement is summarized in three aspects:asphalt layer properties,rigid base integrity,and interlaminar bonding condition.The study concludes that developing high-performance pavement materials based on their structural behaviors is an effective approach to improve the performance and durability of rigid-flexible composite pavement.The integrated design of structure and materials represents the future direction of road design.展开更多
The demand for adopting neural networks in resource-constrained embedded devices is continuously increasing.Quantization is one of the most promising solutions to reduce computational cost and memory storage on embedd...The demand for adopting neural networks in resource-constrained embedded devices is continuously increasing.Quantization is one of the most promising solutions to reduce computational cost and memory storage on embedded devices.In order to reduce the complexity and overhead of deploying neural networks on Integeronly hardware,most current quantization methods use a symmetric quantization mapping strategy to quantize a floating-point neural network into an integer network.However,although symmetric quantization has the advantage of easier implementation,it is sub-optimal for cases where the range could be skewed and not symmetric.This often comes at the cost of lower accuracy.This paper proposed an activation redistribution-based hybrid asymmetric quantizationmethod for neural networks.The proposedmethod takes data distribution into consideration and can resolve the contradiction between the quantization accuracy and the ease of implementation,balance the trade-off between clipping range and quantization resolution,and thus improve the accuracy of the quantized neural network.The experimental results indicate that the accuracy of the proposed method is 2.02%and 5.52%higher than the traditional symmetric quantization method for classification and detection tasks,respectively.The proposed method paves the way for computationally intensive neural network models to be deployed on devices with limited computing resources.Codes will be available on https://github.com/ycjcy/Hybrid-Asymmetric-Quantization.展开更多
Rail vehicles generate huge longitudinal impact loads in collisions.If unreasonable matching exists between the compressive strength of the intermediate coupler and the structural strength of the car body,the risk of ...Rail vehicles generate huge longitudinal impact loads in collisions.If unreasonable matching exists between the compressive strength of the intermediate coupler and the structural strength of the car body,the risk of car body structure damage and train derailment will increase.Herein,a four-stage rigid-flexible coupling finite element model of the coupler is established considering the coupler buckling load.The influence of the coupler buckling load on the train longitudinal-vertical-hori-zontal buckling behavior was studied,and the mechanism of the train horizontal buckling instability in train collisions was revealed.Analysis results show that an intermediate coupler should be designed to ensure that the actual buckling load is less than the compressive load when the car body structure begins to deform plastically.The actual buckling load of the coupler and the asymmetry of the structural strength of the car body in the lateral direction are two important influencing factors for the lateral buckling of a train collision.If the strength of the two sides of the car body structure in the lateral direction is asymmetrical,the deformation on the weaker side will be larger,and the end of the car body will begin to deflect under the action of the coupler force,which in turn causes the train to undergo sawtooth buckling.展开更多
The rational design of metal single-atom catalysts(SACs)for electrochemical nitrogen reduction reaction(NRR)is challenging.Two-dimensional metal-organic frameworks(2DMOFs)is a unique class of promising SACs.Up to now,...The rational design of metal single-atom catalysts(SACs)for electrochemical nitrogen reduction reaction(NRR)is challenging.Two-dimensional metal-organic frameworks(2DMOFs)is a unique class of promising SACs.Up to now,the roles of individual metals,coordination atoms,and their synergy effect on the electroanalytic performance remain unclear.Therefore,in this work,a series of 2DMOFs with different metals and coordinating atoms are systematically investigated as electrocatalysts for ammonia synthesis using density functional theory calculations.For a specific metal,a proper metal-intermediate atoms p-d orbital hybridization interaction strength is found to be a key indicator for their NRR catalytic activities.The hybridization interaction strength can be quantitatively described with the p-/d-band center energy difference(Δd-p),which is found to be a sufficient descriptor for both the p-d hybridization strength and the NRR performance.The maximum free energy change(ΔG_(max))andΔd-p have a volcanic relationship with OsC_(4)(Se)_(4)located at the apex of the volcanic curve,showing the best NRR performance.The asymmetrical coordination environment could regulate the band structure subtly in terms of band overlap and positions.This work may shed new light on the application of orbital engineering in electrocatalytic NRR activity and especially promotes the rational design for SACs.展开更多
In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hy...In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.展开更多
The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based ...The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.展开更多
Cation additives can efficiently enhance the total electrochemical capabilities of zinc-ion hybrid capacitors (ZHCs).However their energy storage mechanisms in zinc-based systems are still under debate.Herein,we modul...Cation additives can efficiently enhance the total electrochemical capabilities of zinc-ion hybrid capacitors (ZHCs).However their energy storage mechanisms in zinc-based systems are still under debate.Herein,we modulate the electrolyte and achieve dual-ion storage by adding magnesium ions.And we assemble several Zn//activated carbon devices with different electrolyte concentrations and investigate their electrochemical reaction dynamic behaviors.The zinc-ion capacitor with Mg^(2+)mixed solution delivers 82 mAh·g^(-1)capacity at 1 A·g^(-1) and maintains 91%of the original capacitance after 10000 cycling.It is superior to the other assembled zinc-ion devices in single-component electrolytes.The finding demonstrates that the double-ion storage mechanism enables the superior rate performance and long cycle lifetime of ZHCs.展开更多
Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-l...Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.展开更多
Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer eff...Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer efficiency of vertically oriented carbon structures is a challenging task.Herein,an orthotropic three-dimensional(3D)hybrid carbon network(VSCG)is fabricated by depositing vertically aligned carbon nanotubes(VACNTs)on the surface of a horizontally oriented graphene film(HOGF).The interfacial interaction between the VACNTs and HOGF is then optimized through an annealing strategy.After regulating the orientation structure of the VACNTs and filling the VSCG with polydimethylsi-loxane(PDMS),VSCG/PDMS composites with excellent 3D thermal conductive properties are obtained.The highest in-plane and through-plane thermal conduc-tivities of the composites are 113.61 and 24.37 W m^(-1)K^(-1),respectively.The high contact area of HOGF and good compressibility of VACNTs imbue the VSCG/PDMS composite with low thermal resistance.In addition,the interfacial heat-transfer efficiency of VSCG/PDMS composite in the TIM performance was improved by 71.3%compared to that of a state-of-the-art thermal pad.This new structural design can potentially realize high-performance TIMs that meet the need for high thermal conductivity and low contact thermal resistance in interfacial heat-transfer processes.展开更多
The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated...The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.展开更多
The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attr...The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.展开更多
The two bay scallop subspecies,Argopecten irradians irradians(NN)and A.i.concentricus(SS),are fast growing and major cultured bivalves in China.However,their relatively small sizes and decreasing production traits cau...The two bay scallop subspecies,Argopecten irradians irradians(NN)and A.i.concentricus(SS),are fast growing and major cultured bivalves in China.However,their relatively small sizes and decreasing production traits caused by long-term inbreeding have been major concerns to the industry in the last two decades.Hybridization between the two bay scallop subspecies may provide a new approach to breed a new variety with superior production traits for the industry.For this end,in this study,we hybridized the two bay scallop subspecies in order to obtain a new strain that incorporates the genes of both subspecies.No significant difference was found in fertilization rate,hatching rate and metamorphosis rate between the purebred and crossbred cohorts(NN♀×SS♂,denoted as NS;SS♀×NN♂,denoted as SN).Both mating strategy(intra-vs.inter-population crosses)and egg origin had significant effects on growth and survival at the larval stage.Heterosis was observed in the crossbred and was more pronounced in older stages.Genetic diversity of the reciprocal hybrids,especially that of SN,was increased compared with the purebred cohorts.Almost all hybrids were completely fertile and able to reproduce by selffertilization or by backcrossing with either parent.Apparently,male sterile individuals whose gonads were fully occupied by the ovary part at mature stage were found in the hybrids for the first time.The hybrids,especially SN,may provide precious germplasm resources for the production of ternary hybrids with the Peruvian scallop,A.purpuratus.展开更多
This study aimed to discriminate ten Cameroonian cocoa hybrids according to their total fat, fatty acid composition, tocopherol and tocotrienol profiles. Six cocoa clones from the gene banks of the Cameroon Cocoa Deve...This study aimed to discriminate ten Cameroonian cocoa hybrids according to their total fat, fatty acid composition, tocopherol and tocotrienol profiles. Six cocoa clones from the gene banks of the Cameroon Cocoa Development Corporation were used to create hybrids. The determination of fatty acid composition was carried out by using a gas chromatography (GC) apparatus coupled by a flame ion detector (FID). Tocopherol and tocotrienol analysis was performed by upper high-performance liquid chromatography (UHPLC). Information on the impact of the genotype on the cocoa fat composition was provided. The major fatty acids (FA) in fermented samples are stearic (34.57%), palmitic (26.13%), oleic (34.13%) and linoleic (3.16%) acids. (35.05% to 35.6%). SCA12 × ICS40, SCA12 × SNK13, SNK13 × T79/501 have the least hard cocoa butters. Tocopherols analysis showed a predominance of γ-tocopherols (94.64 ± 1.51 to 292.16 ± 3.17 µg∙g<sup>−1</sup>), whereas only a small amount of β and δ-tocopherol (from 0.46 to 2.78 µg∙g<sup>−1</sup> and 0.12 to 5.82 respectively) was observed. No γ-tocotrienol was found in fermented samples. A differentiation in terms of total fat and tocopherol content was observed amongst hybrids with the same mother-clone, suggesting an impact of pollen on these compounds.展开更多
This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative ...This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.展开更多
Organic solar cells(OSCs)have gained conspicuous progress during the past few decades due to the development of materials and upgrading of the device structure.The power conversion efficiency(PCE)of the single-junctio...Organic solar cells(OSCs)have gained conspicuous progress during the past few decades due to the development of materials and upgrading of the device structure.The power conversion efficiency(PCE)of the single-junction device had surpassed 19%.The cathode interface layer(CIL),by optimizing the connection between the active layer and the cathode electrode,has become a momentous part to strengthen the performances of the OSCs.Simultaneously,CIL is also indispensable to illustrating the working mechanism of OSCs and enhancing the stability of the OSCs.In this essay,hybrid CILs in OSCs have been summarized.Firstly,the advancement and operating mechanism of OSCs,and the effects and relevant design rules of CIL are briefly concluded;secondly,the significant influence of CIL on enhancing the stability and PCE of OSCs is presented;thirdly,the characteristics of organic hybrid CIL and organic-inorganic hybrid CIL are introduced.Finally,the conclusion and outlook of CIL are summarized.展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 22109008)。
文摘Artificial solid electrolyte interphase(SEI) is promising to inhibit uncontrollable lithium dendrites and enable long cycling stability for lithium metal batteries. However, the essential mechanical stability is limited since organic layers generally have low modulus whereas intrinsic brittleness for inorganic ones remains a great concern. Polymer-based SEIs with rigid and flexible chains in adequate mechanical properties are supposed to address this issue. Herein, a homogeneous and mechanically stable diffusion layer is achieved by blending rigid chains of polyphenylene sulfone(PPSU) with flexible chains of poly(vinylidene fluoride)(PVDF) in a hybrid membrane, enabling uniform diffusion and stabilizing the lithium metal anode. The Li||Cu cell with the protected electrode exhibits a long lifetime more than 450 cycles(0.5 m A cm^(-2), 1.0 m A h cm^(-2))(fourfold longer than the control group) with higher average Coulombic efficiency of 98.7%. Enhanced performances are also observed at Li||Li and full cell configurations. The improved performances are attributed to the controlled morphology and stable interphase, according to scanning electron microscopy(SEM) and electrochemical impedance. This research advances the idea of uniform lithium plating and provides a new insight on how to create a homogeneous and mechanically stable diffusion layer using rigid-flexible polymers.
基金This manuscript is supported by the National Key Research and Development Program of China(Grant No.2021YFB2601000)the National Natural Science Foundation of China(Grant Nos.52278437,52008044)+2 种基金the Natural Science Foundation of Hunan Province(Grant No.2022JJ40479)the Science and Technology Innovation Program of Hunan Provincial Department of Transportation(Grant No.202236)the Changsha Outstanding Innovative Youth Training Program Project(Grant No.kq2306009).
文摘Rigid-flexible composite pavement has gained significant popularity in recent decades.This paper provides a comprehensive review of the research progress concerning rigid-flexible composite pavement,aiming to promote its application and address key issues while identifying future directions.The design theory and methodology of rigid-flexible composite pavement are discussed,followed by a description of its structural and mechanical behavior characteristics.The load stress,temperature stress,and their interactive effects between the asphalt layer and the rigid base were analyzed.It is clarified that the asphalt layer serves a dual role as both a“functional layer”and a“structural layer”.Typical distresses of rigid-flexible composite pavement,which primarily occur in the asphalt layer,were discussed.These distresses include reflective cracking,top-down cracking,rutting,and compressive-shear failure.Generally,the integrity of the rigid base and the interlaminar bonding conditions significantly impact the performance and distress of the asphalt layer.The technology for enhancing the performance of rigid-flexible composite pavement is summarized in three aspects:asphalt layer properties,rigid base integrity,and interlaminar bonding condition.The study concludes that developing high-performance pavement materials based on their structural behaviors is an effective approach to improve the performance and durability of rigid-flexible composite pavement.The integrated design of structure and materials represents the future direction of road design.
基金The Qian Xuesen Youth Innovation Foundation from China Aerospace Science and Technology Corporation(Grant Number 2022JY51).
文摘The demand for adopting neural networks in resource-constrained embedded devices is continuously increasing.Quantization is one of the most promising solutions to reduce computational cost and memory storage on embedded devices.In order to reduce the complexity and overhead of deploying neural networks on Integeronly hardware,most current quantization methods use a symmetric quantization mapping strategy to quantize a floating-point neural network into an integer network.However,although symmetric quantization has the advantage of easier implementation,it is sub-optimal for cases where the range could be skewed and not symmetric.This often comes at the cost of lower accuracy.This paper proposed an activation redistribution-based hybrid asymmetric quantizationmethod for neural networks.The proposedmethod takes data distribution into consideration and can resolve the contradiction between the quantization accuracy and the ease of implementation,balance the trade-off between clipping range and quantization resolution,and thus improve the accuracy of the quantized neural network.The experimental results indicate that the accuracy of the proposed method is 2.02%and 5.52%higher than the traditional symmetric quantization method for classification and detection tasks,respectively.The proposed method paves the way for computationally intensive neural network models to be deployed on devices with limited computing resources.Codes will be available on https://github.com/ycjcy/Hybrid-Asymmetric-Quantization.
基金This work was supported by the National Natural Science Foundation of China(No.52172409)Sichuan Outstanding Youth Fund(No.2022JDJQ0025).
文摘Rail vehicles generate huge longitudinal impact loads in collisions.If unreasonable matching exists between the compressive strength of the intermediate coupler and the structural strength of the car body,the risk of car body structure damage and train derailment will increase.Herein,a four-stage rigid-flexible coupling finite element model of the coupler is established considering the coupler buckling load.The influence of the coupler buckling load on the train longitudinal-vertical-hori-zontal buckling behavior was studied,and the mechanism of the train horizontal buckling instability in train collisions was revealed.Analysis results show that an intermediate coupler should be designed to ensure that the actual buckling load is less than the compressive load when the car body structure begins to deform plastically.The actual buckling load of the coupler and the asymmetry of the structural strength of the car body in the lateral direction are two important influencing factors for the lateral buckling of a train collision.If the strength of the two sides of the car body structure in the lateral direction is asymmetrical,the deformation on the weaker side will be larger,and the end of the car body will begin to deflect under the action of the coupler force,which in turn causes the train to undergo sawtooth buckling.
基金supported by the National Natural Science Foundation of China(21905253,51973200,and 52122308)the Natural Science Foundation of Henan(202300410372)the National Supercomputing Center in Zhengzhou
文摘The rational design of metal single-atom catalysts(SACs)for electrochemical nitrogen reduction reaction(NRR)is challenging.Two-dimensional metal-organic frameworks(2DMOFs)is a unique class of promising SACs.Up to now,the roles of individual metals,coordination atoms,and their synergy effect on the electroanalytic performance remain unclear.Therefore,in this work,a series of 2DMOFs with different metals and coordinating atoms are systematically investigated as electrocatalysts for ammonia synthesis using density functional theory calculations.For a specific metal,a proper metal-intermediate atoms p-d orbital hybridization interaction strength is found to be a key indicator for their NRR catalytic activities.The hybridization interaction strength can be quantitatively described with the p-/d-band center energy difference(Δd-p),which is found to be a sufficient descriptor for both the p-d hybridization strength and the NRR performance.The maximum free energy change(ΔG_(max))andΔd-p have a volcanic relationship with OsC_(4)(Se)_(4)located at the apex of the volcanic curve,showing the best NRR performance.The asymmetrical coordination environment could regulate the band structure subtly in terms of band overlap and positions.This work may shed new light on the application of orbital engineering in electrocatalytic NRR activity and especially promotes the rational design for SACs.
基金Projects(42177164,52474121)supported by the National Science Foundation of ChinaProject(PBSKL2023A12)supported by the State Key Laboratory of Precision Blasting and Hubei Key Laboratory of Blasting Engineering,China。
文摘In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.
基金financially supported by the National Natural Science Foundation of China (Nos.51974023 and52374321)the funding of State Key Laboratory of Advanced Metallurgy,University of Science and Technology Beijing,China (No.41620007)。
文摘The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.
基金financially supported by the National Natural Science Foundation of China (No.52172218)。
文摘Cation additives can efficiently enhance the total electrochemical capabilities of zinc-ion hybrid capacitors (ZHCs).However their energy storage mechanisms in zinc-based systems are still under debate.Herein,we modulate the electrolyte and achieve dual-ion storage by adding magnesium ions.And we assemble several Zn//activated carbon devices with different electrolyte concentrations and investigate their electrochemical reaction dynamic behaviors.The zinc-ion capacitor with Mg^(2+)mixed solution delivers 82 mAh·g^(-1)capacity at 1 A·g^(-1) and maintains 91%of the original capacitance after 10000 cycling.It is superior to the other assembled zinc-ion devices in single-component electrolytes.The finding demonstrates that the double-ion storage mechanism enables the superior rate performance and long cycle lifetime of ZHCs.
基金financial support from Project funded by National Natural Science Foundation of China(52172038,22179017)funding from Dalian University of Technology Open Fund for Large Scale Instrument Equipment
文摘Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52130303,52327802,52303101,52173078,51973158)the China Postdoctoral Science Foundation(2023M732579)+2 种基金Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)National Key R&D Program of China(No.2022YFB3805702)Joint Funds of Ministry of Education(8091B032218).
文摘Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer efficiency of vertically oriented carbon structures is a challenging task.Herein,an orthotropic three-dimensional(3D)hybrid carbon network(VSCG)is fabricated by depositing vertically aligned carbon nanotubes(VACNTs)on the surface of a horizontally oriented graphene film(HOGF).The interfacial interaction between the VACNTs and HOGF is then optimized through an annealing strategy.After regulating the orientation structure of the VACNTs and filling the VSCG with polydimethylsi-loxane(PDMS),VSCG/PDMS composites with excellent 3D thermal conductive properties are obtained.The highest in-plane and through-plane thermal conduc-tivities of the composites are 113.61 and 24.37 W m^(-1)K^(-1),respectively.The high contact area of HOGF and good compressibility of VACNTs imbue the VSCG/PDMS composite with low thermal resistance.In addition,the interfacial heat-transfer efficiency of VSCG/PDMS composite in the TIM performance was improved by 71.3%compared to that of a state-of-the-art thermal pad.This new structural design can potentially realize high-performance TIMs that meet the need for high thermal conductivity and low contact thermal resistance in interfacial heat-transfer processes.
文摘The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.
基金Anhui Province Natural Science Research Project of Colleges and Universities(2023AH040321)Excellent Scientific Research and Innovation Team of Anhui Colleges(2022AH010098).
文摘The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.
基金the National Natural Science Foundation of China(No.31972791)the Earmarked Fund for Agriculture Seed Improvement Project of Shandong Province(No.2020LZGC016)+1 种基金the Scientific and Technological Project of Yantai,Shandong Province(No.2022XCZX083)the Earmarked Fund for Shandong Modern Agro-Industry Technology Research System(No.SDAIT-14)。
文摘The two bay scallop subspecies,Argopecten irradians irradians(NN)and A.i.concentricus(SS),are fast growing and major cultured bivalves in China.However,their relatively small sizes and decreasing production traits caused by long-term inbreeding have been major concerns to the industry in the last two decades.Hybridization between the two bay scallop subspecies may provide a new approach to breed a new variety with superior production traits for the industry.For this end,in this study,we hybridized the two bay scallop subspecies in order to obtain a new strain that incorporates the genes of both subspecies.No significant difference was found in fertilization rate,hatching rate and metamorphosis rate between the purebred and crossbred cohorts(NN♀×SS♂,denoted as NS;SS♀×NN♂,denoted as SN).Both mating strategy(intra-vs.inter-population crosses)and egg origin had significant effects on growth and survival at the larval stage.Heterosis was observed in the crossbred and was more pronounced in older stages.Genetic diversity of the reciprocal hybrids,especially that of SN,was increased compared with the purebred cohorts.Almost all hybrids were completely fertile and able to reproduce by selffertilization or by backcrossing with either parent.Apparently,male sterile individuals whose gonads were fully occupied by the ovary part at mature stage were found in the hybrids for the first time.The hybrids,especially SN,may provide precious germplasm resources for the production of ternary hybrids with the Peruvian scallop,A.purpuratus.
文摘This study aimed to discriminate ten Cameroonian cocoa hybrids according to their total fat, fatty acid composition, tocopherol and tocotrienol profiles. Six cocoa clones from the gene banks of the Cameroon Cocoa Development Corporation were used to create hybrids. The determination of fatty acid composition was carried out by using a gas chromatography (GC) apparatus coupled by a flame ion detector (FID). Tocopherol and tocotrienol analysis was performed by upper high-performance liquid chromatography (UHPLC). Information on the impact of the genotype on the cocoa fat composition was provided. The major fatty acids (FA) in fermented samples are stearic (34.57%), palmitic (26.13%), oleic (34.13%) and linoleic (3.16%) acids. (35.05% to 35.6%). SCA12 × ICS40, SCA12 × SNK13, SNK13 × T79/501 have the least hard cocoa butters. Tocopherols analysis showed a predominance of γ-tocopherols (94.64 ± 1.51 to 292.16 ± 3.17 µg∙g<sup>−1</sup>), whereas only a small amount of β and δ-tocopherol (from 0.46 to 2.78 µg∙g<sup>−1</sup> and 0.12 to 5.82 respectively) was observed. No γ-tocotrienol was found in fermented samples. A differentiation in terms of total fat and tocopherol content was observed amongst hybrids with the same mother-clone, suggesting an impact of pollen on these compounds.
基金supported by the National Natural Science Foundation of China (62073303,61673356)Hubei Provincial Natural Science Foundation of China (2015CFA010)the 111 Project(B17040)。
文摘This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.
基金supported by the National Natural Science Foundation of China(52263017,21965023,52173170,51973087,and22065025)the Science Fund for Distinguished Young Scholars of Jiangxi Province(20212ACB214009)+2 种基金the Natural Science Foundation of Jiangxi Province(20212ACB203010,20224BAB214007 and20212BAB204052)the Training Project of High-level and Highskilled Leading Talents of Jiangxi Province(2023)the Thousand Talents Plan of Jiangxi Province(jxsq2019201004 and jxsq2020101068)。
文摘Organic solar cells(OSCs)have gained conspicuous progress during the past few decades due to the development of materials and upgrading of the device structure.The power conversion efficiency(PCE)of the single-junction device had surpassed 19%.The cathode interface layer(CIL),by optimizing the connection between the active layer and the cathode electrode,has become a momentous part to strengthen the performances of the OSCs.Simultaneously,CIL is also indispensable to illustrating the working mechanism of OSCs and enhancing the stability of the OSCs.In this essay,hybrid CILs in OSCs have been summarized.Firstly,the advancement and operating mechanism of OSCs,and the effects and relevant design rules of CIL are briefly concluded;secondly,the significant influence of CIL on enhancing the stability and PCE of OSCs is presented;thirdly,the characteristics of organic hybrid CIL and organic-inorganic hybrid CIL are introduced.Finally,the conclusion and outlook of CIL are summarized.