The use of Minimum Quantity Lubrication(MQL)with bio-lubricants has been extensively studied in aerospace sustainable manufacturing.Enhanced MQL technologies have been proposed to reduce tool wear and improve workpiec...The use of Minimum Quantity Lubrication(MQL)with bio-lubricants has been extensively studied in aerospace sustainable manufacturing.Enhanced MQL technologies have been proposed to reduce tool wear and improve workpiece surface integrity by increasing lubricant activity.However,the relationship between enhancement behavior,physicochemical properties of biolubricants,and processability remains unclear,presenting challenges for MQL technologies,particularly with difficult-to-machine materials.To address this gap,this paper provides an in-depth mechanism analysis and a comprehensive quantitative evaluation of the machinability of enhanced MQL technologies,considering chemistry,molecular dynamics,fluid dynamics,tribology,and heat transfer.Firstly,the cooling and lubrication enhancement mechanisms of nano-lubricants were systematically summarized.focusing on molecular structure.physical properties,and preparation processes.Secondly,the atomization enhancement mechanism of Electrostatic Minimum Quantity Lubrication(EMQL)was analyzed.revealing a 49%reduction in PM2.5 concentration during the atomization process compared to conventional MQL.Thirdly,the transport and infiltration enhancement mechanisms of bio-lubricants in cutting and grinding zones were summarized,incorporating electromagnetic fields and ultrasound-assisted processes.Finally,for cutting and grinding applications involving difficult-to-machine materials in aerospace,the optimized machinability of enhanced MQL technologies was concluded,showing a 50.1%increase in lubricant heat transfer coefficient and a 31.6%decrease in grinding temperature compared to standard MQL.This paper aims to help scientists understand the effective mechanisms,formulate process specifications,and identify future development trends in this technology.展开更多
Crystalline silicon(c-Si)solar cells,though dominating the photovoltaic market,are nearing their theoretical power conversion efficiencies(PCE)limit of 29.4%,necessitating the adoption of multi-junction technology to ...Crystalline silicon(c-Si)solar cells,though dominating the photovoltaic market,are nearing their theoretical power conversion efficiencies(PCE)limit of 29.4%,necessitating the adoption of multi-junction technology to achieve higher performance.Among these,perovskiteon-silicon-based multi-junction solar cells have emerged as a promising alternative,where the perovskite offering tunable bandgaps,superior optoelectronic properties,and cost-effective manufacturing.Recent announced double-junction solar cells(PSDJSCs)have achieved the PCE of 34.85%,surpassing all other double-junction technologies.Encouragingly,the rapid advancements in PSDJSCs have spurred increased research interest in perovskite/perovskite/silicon triple-junction solar cells(PSTJSCs)in 2024.This triple-junction solar cell configuration demonstrates immense potential due to their optimum balance between achieving a high PCE limit and managing device complexity.This review provides a comprehensive analysis of PSTJSCs,covering fundamental principles,and technological milestones.Current challenges,including current mismatch,open-circuit voltage deficits,phase segregation,and stability issues,and their corresponding strategies are also discussed,alongside future directions to achieve long-term stability and high PCE.This work aims to advance the understanding of the development in PSTJSCs,paving the way for their practical implementation.展开更多
The rapid advance of Connected-Automated Vehicles(CAVs)has led to the emergence of diverse delaysensitive and energy-constrained vehicular applications.Given the high dynamics of vehicular networks,unmanned aerial veh...The rapid advance of Connected-Automated Vehicles(CAVs)has led to the emergence of diverse delaysensitive and energy-constrained vehicular applications.Given the high dynamics of vehicular networks,unmanned aerial vehicles-assisted mobile edge computing(UAV-MEC)has gained attention in providing computing resources to vehicles and optimizing system costs.We model the computing offloading problem as a multi-objective optimization challenge aimed at minimizing both task processing delay and energy consumption.We propose a three-stage hybrid offloading scheme called Dynamic Vehicle Clustering Game-based Multi-objective Whale Optimization Algorithm(DVCG-MWOA)to address this problem.A novel dynamic clustering algorithm is designed based on vehiclemobility and task offloading efficiency requirements,where each UAV independently serves as the cluster head for a vehicle cluster and adjusts its position at the end of each timeslot in response to vehiclemovement.Within eachUAV-led cluster,cooperative game theory is applied to allocate computing resourceswhile respecting delay constraints,ensuring efficient resource utilization.To enhance offloading efficiency,we improve the multi-objective whale optimization algorithm(MOWOA),resulting in the MWOA.This enhanced algorithm determines the optimal allocation of pending tasks to different edge computing devices and the resource utilization ratio of each device,ultimately achieving a Pareto-optimal solution set for delay and energy consumption.Experimental results demonstrate that the proposed joint offloading scheme significantly reduces both delay and energy consumption compared to existing approaches,offering superior performance for vehicular networks.展开更多
With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The...With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.展开更多
Soybean pests are one of the major factors limiting yield improvement.With the expansion of area and changes in cropping patterns,a number of new pests have been identified in the main soybean production areas of Chin...Soybean pests are one of the major factors limiting yield improvement.With the expansion of area and changes in cropping patterns,a number of new pests have been identified in the main soybean production areas of China.The common brown leafhopper,Orosius orientalis,is a new pest associated with soybean stay-green virus that has been discovered on cultivated soybean crop in the Yellow-Huai-hai region of China in recent years.The polyphagous insect has a wide feeding range and infests a variety of important grain and cash crops.This paper presents the basic information,geographical distribution,hosts,damage characteristics,plant virus transmission,occurrence patterns,and prevention and control measures O.orientalis.This review also provides insights into integrated prevention and control of the genus Orosius as an insect vector.展开更多
There is increasing evidence that the activation of glucagon-like peptide-1 receptor(GLP-1R)can be used as a therapeutic intervention for cognitive disorders.Here,we have screened GLP-1R targeted compounds from Scutel...There is increasing evidence that the activation of glucagon-like peptide-1 receptor(GLP-1R)can be used as a therapeutic intervention for cognitive disorders.Here,we have screened GLP-1R targeted compounds from Scutellaria baicalensis,which revealed baicalein is a potential GLP-1R small-molecule agonist.Mitophagy,a selective autophagy pathway for mitochondrial quality control,plays a neuroprotective role in multiple cognitive impairment diseases.We noticed that Glp1r knock-out(KO)mice present cognitive impairment symptoms and appear worse in spatial learning memory and learning capacity in Morris water maze(MWM)test than their wide-type(WT)counterparts.Our mechanistic studies revealed that mitophagy is impaired in hippocampus tissue of diabetic mice and Glp1r KO mice.Finally,we verified that the cognitive improvement effects of baicalein on diabetic cognitive dysfunction occur through the enhancement of mitophagy in a GLP-1R-dependent manner.Our findings shed light on the importance of GLP-1R for cognitive function maintenance,and revealed the vital significance of GLP-1R for maintaining mitochondrial homeostasis.Furthermore,we identified the therapeutic potential of baicalein in the treatment of cognitive disorder associated with diabetes.展开更多
Triboelectric materials with high charge density are the building-block for the commercial application of triboelectric nanogenerators(TENGs).Unstable dynamic processes influence the change of the charge density on th...Triboelectric materials with high charge density are the building-block for the commercial application of triboelectric nanogenerators(TENGs).Unstable dynamic processes influence the change of the charge density on the surface and inside of triboelectric materials.The charge density of triboelectric materials depends on the surface and the internal charge transfer processes.The focus of this review is on recent advances in high charge density triboelectric materials and advances in the fabrication of TENGs.We summarize the existing strategies for achieving high charge density in triboelectric materials as well as their fundamental properties.We then review current optimization methods for regulating dynamic charge transfer processes to increase the output charge density:first,increasing charge injection and limiting charge dissipation to achieve a high average surface charge density,and second,regulating the internal charge transfer process and storing charge in triboelectric materials to increase the output charge density.Finally,we present the challenges and prospects in developing high-performance triboelectric materials.展开更多
The machining surface integrity of aero-engine turbine disc slots has a significant impact on their fatigue life and service performance,and achieving efficiency and high-precision machining is still a great challenge...The machining surface integrity of aero-engine turbine disc slots has a significant impact on their fatigue life and service performance,and achieving efficiency and high-precision machining is still a great challenge.The high machining requirements of future aeroengine turbine disc slots will be difficult to satisfy using the broaching method.In addition,existing methods of slot machin-ing face difficulties in ensuring surface integrity.This study explored a cup shaped electroplated Cubic Boron Nitride(CBN)abrasive wheel for profile grinding the turbine disc slots of FGH96 powder metallurgy superalloy.The matrix structure of the cup shaped abrasive wheel was designed and verified.A profile grinding experiment was conducted for fir-tree slots on a five-axis machining center.The accuracy and the surface integrity were analyzed.Results show that the key dimension detection results of the slots were within the allowable tolerance range.Meanwhile,an average sur-face roughness Ra of 0.55μm was achieved,the residual stress was compressive,the plastic defor-mation layer thickness was less than 5μm,and the hardening layer thickness was less than 20μm.The research findings provide a new approach to machining the slots of aviation engine turbine discs and guidance for the high-quality processing of complex components.展开更多
The surface morphology and roughness of a workpiece are crucial parameters in grinding processes.Accurate prediction of these parameters is essential for maintaining the workpiece’s surface integrity.However,the rand...The surface morphology and roughness of a workpiece are crucial parameters in grinding processes.Accurate prediction of these parameters is essential for maintaining the workpiece’s surface integrity.However,the randomness of abrasive grain shapes and workpiece surface formation behaviors poses significant challenges,and accuracy in current physical mechanism-based predictive models is needed.To address this problem,by using the random plane method and accounting for the random morphology and distribution of abrasive grains,this paper proposes a novel method to model CBN grinding wheels and predict workpiece surface roughness.First,a kinematic model of a single abrasive grain is developed to accurately capture the three-dimensional morphology of the grinding wheel.Next,by formulating an elastic deformation and formation model of the workpiece surface based on Hertz theory,the variation in grinding arc length at different grinding depths is revealed.Subsequently,a predictive model for the surface morphology of the workpiece ground by a single abrasive grain is devised.This model integrates the normal distribution model of abrasive grain size and the spatial distribution model of abrasive grain positions,to elucidate how the circumferential and axial distribution of abrasive grains influences workpiece surface formation.Lastly,by integrating the dynamic effective abrasive grain model,a predictive model for the surface morphology and roughness of the grinding wheel is established.To examine the impact of changing the grit size of the grinding wheel and grinding depth on workpiece surface roughness,and to validate the accuracy of the model,experiments are conducted.Results indicate that the predicted three-dimensional morphology of the grinding wheel and workpiece surfaces closely matches the actual grinding wheel and ground workpiece surfaces,with surface roughness prediction deviations as small as 2.3%.展开更多
Traditional traffic management techniques appear to be incompetent in complex data center networks, so proposes a load balancing strategy based on Long Short-Term Memory (LSTM) and quantum annealing by Software Define...Traditional traffic management techniques appear to be incompetent in complex data center networks, so proposes a load balancing strategy based on Long Short-Term Memory (LSTM) and quantum annealing by Software Defined Network (SDN) to dynamically predict the traffic and comprehensively consider the current and predicted load of the network in order to select the optimal forwarding path and balance the network load. Experiments have demonstrated that the algorithm achieves significant improvement in both system throughput and average packet loss rate for the purpose of improving network quality of service.展开更多
基金supported by the following organizations:the Special Fund of Taishan Scholars Project(No.tsqn202211179)the National Natural Science Foundation of China(No.52105457)+2 种基金Young Talent of Lifting engineering for Science and Technology in Shandong,China(No.SDAST2021qt12)the National Natural Science Foundation of China(No.52375447)China Postdoctoral Science Foundation Funded Project(No.2023M732826).
文摘The use of Minimum Quantity Lubrication(MQL)with bio-lubricants has been extensively studied in aerospace sustainable manufacturing.Enhanced MQL technologies have been proposed to reduce tool wear and improve workpiece surface integrity by increasing lubricant activity.However,the relationship between enhancement behavior,physicochemical properties of biolubricants,and processability remains unclear,presenting challenges for MQL technologies,particularly with difficult-to-machine materials.To address this gap,this paper provides an in-depth mechanism analysis and a comprehensive quantitative evaluation of the machinability of enhanced MQL technologies,considering chemistry,molecular dynamics,fluid dynamics,tribology,and heat transfer.Firstly,the cooling and lubrication enhancement mechanisms of nano-lubricants were systematically summarized.focusing on molecular structure.physical properties,and preparation processes.Secondly,the atomization enhancement mechanism of Electrostatic Minimum Quantity Lubrication(EMQL)was analyzed.revealing a 49%reduction in PM2.5 concentration during the atomization process compared to conventional MQL.Thirdly,the transport and infiltration enhancement mechanisms of bio-lubricants in cutting and grinding zones were summarized,incorporating electromagnetic fields and ultrasound-assisted processes.Finally,for cutting and grinding applications involving difficult-to-machine materials in aerospace,the optimized machinability of enhanced MQL technologies was concluded,showing a 50.1%increase in lubricant heat transfer coefficient and a 31.6%decrease in grinding temperature compared to standard MQL.This paper aims to help scientists understand the effective mechanisms,formulate process specifications,and identify future development trends in this technology.
基金supported by the National Natural Science Foundation of China under Grants 62404185the industry-academia joint laboratory collaboration between Hiking PV and Xiamen University(20243160C0010)J.Z.is supported by Nanqiang Outstanding Young Talents Program X2450215 of Xiamen University.
文摘Crystalline silicon(c-Si)solar cells,though dominating the photovoltaic market,are nearing their theoretical power conversion efficiencies(PCE)limit of 29.4%,necessitating the adoption of multi-junction technology to achieve higher performance.Among these,perovskiteon-silicon-based multi-junction solar cells have emerged as a promising alternative,where the perovskite offering tunable bandgaps,superior optoelectronic properties,and cost-effective manufacturing.Recent announced double-junction solar cells(PSDJSCs)have achieved the PCE of 34.85%,surpassing all other double-junction technologies.Encouragingly,the rapid advancements in PSDJSCs have spurred increased research interest in perovskite/perovskite/silicon triple-junction solar cells(PSTJSCs)in 2024.This triple-junction solar cell configuration demonstrates immense potential due to their optimum balance between achieving a high PCE limit and managing device complexity.This review provides a comprehensive analysis of PSTJSCs,covering fundamental principles,and technological milestones.Current challenges,including current mismatch,open-circuit voltage deficits,phase segregation,and stability issues,and their corresponding strategies are also discussed,alongside future directions to achieve long-term stability and high PCE.This work aims to advance the understanding of the development in PSTJSCs,paving the way for their practical implementation.
基金funded by Shandong University of Technology Doctoral Program in Science and Technology,grant number 4041422007.
文摘The rapid advance of Connected-Automated Vehicles(CAVs)has led to the emergence of diverse delaysensitive and energy-constrained vehicular applications.Given the high dynamics of vehicular networks,unmanned aerial vehicles-assisted mobile edge computing(UAV-MEC)has gained attention in providing computing resources to vehicles and optimizing system costs.We model the computing offloading problem as a multi-objective optimization challenge aimed at minimizing both task processing delay and energy consumption.We propose a three-stage hybrid offloading scheme called Dynamic Vehicle Clustering Game-based Multi-objective Whale Optimization Algorithm(DVCG-MWOA)to address this problem.A novel dynamic clustering algorithm is designed based on vehiclemobility and task offloading efficiency requirements,where each UAV independently serves as the cluster head for a vehicle cluster and adjusts its position at the end of each timeslot in response to vehiclemovement.Within eachUAV-led cluster,cooperative game theory is applied to allocate computing resourceswhile respecting delay constraints,ensuring efficient resource utilization.To enhance offloading efficiency,we improve the multi-objective whale optimization algorithm(MOWOA),resulting in the MWOA.This enhanced algorithm determines the optimal allocation of pending tasks to different edge computing devices and the resource utilization ratio of each device,ultimately achieving a Pareto-optimal solution set for delay and energy consumption.Experimental results demonstrate that the proposed joint offloading scheme significantly reduces both delay and energy consumption compared to existing approaches,offering superior performance for vehicular networks.
文摘With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.
基金supported by the National Key Research and Development Program of China(2023YFD1401000)the Earmarked Fund for China Agriculture Research System(CARS-04).
文摘Soybean pests are one of the major factors limiting yield improvement.With the expansion of area and changes in cropping patterns,a number of new pests have been identified in the main soybean production areas of China.The common brown leafhopper,Orosius orientalis,is a new pest associated with soybean stay-green virus that has been discovered on cultivated soybean crop in the Yellow-Huai-hai region of China in recent years.The polyphagous insect has a wide feeding range and infests a variety of important grain and cash crops.This paper presents the basic information,geographical distribution,hosts,damage characteristics,plant virus transmission,occurrence patterns,and prevention and control measures O.orientalis.This review also provides insights into integrated prevention and control of the genus Orosius as an insect vector.
基金funded by the Fundamental Research Funds for the Central Universities(Grant No.:xzd012022099)Natural Science Basic Research Program of Shaanxi(Grant Nos.:2023-JC-ZD-47,and 2023-JC-QN-0921)+2 种基金Research Project of Shaanxi Administration of Traditional Chinese Medicine(Project No.:SZY-KJCYC-2023-008)Research Project of Guangxi Administration of Traditional Chinese Medicine(Project No.:GXZYJ20230711)Basic&Clinical Sciences Integration Innovation Project of Xi'an Jiaotong University(Project No.:YXJLRH2022018).
文摘There is increasing evidence that the activation of glucagon-like peptide-1 receptor(GLP-1R)can be used as a therapeutic intervention for cognitive disorders.Here,we have screened GLP-1R targeted compounds from Scutellaria baicalensis,which revealed baicalein is a potential GLP-1R small-molecule agonist.Mitophagy,a selective autophagy pathway for mitochondrial quality control,plays a neuroprotective role in multiple cognitive impairment diseases.We noticed that Glp1r knock-out(KO)mice present cognitive impairment symptoms and appear worse in spatial learning memory and learning capacity in Morris water maze(MWM)test than their wide-type(WT)counterparts.Our mechanistic studies revealed that mitophagy is impaired in hippocampus tissue of diabetic mice and Glp1r KO mice.Finally,we verified that the cognitive improvement effects of baicalein on diabetic cognitive dysfunction occur through the enhancement of mitophagy in a GLP-1R-dependent manner.Our findings shed light on the importance of GLP-1R for cognitive function maintenance,and revealed the vital significance of GLP-1R for maintaining mitochondrial homeostasis.Furthermore,we identified the therapeutic potential of baicalein in the treatment of cognitive disorder associated with diabetes.
文摘Triboelectric materials with high charge density are the building-block for the commercial application of triboelectric nanogenerators(TENGs).Unstable dynamic processes influence the change of the charge density on the surface and inside of triboelectric materials.The charge density of triboelectric materials depends on the surface and the internal charge transfer processes.The focus of this review is on recent advances in high charge density triboelectric materials and advances in the fabrication of TENGs.We summarize the existing strategies for achieving high charge density in triboelectric materials as well as their fundamental properties.We then review current optimization methods for regulating dynamic charge transfer processes to increase the output charge density:first,increasing charge injection and limiting charge dissipation to achieve a high average surface charge density,and second,regulating the internal charge transfer process and storing charge in triboelectric materials to increase the output charge density.Finally,we present the challenges and prospects in developing high-performance triboelectric materials.
基金supported by the National Natural Science Foundation of China (Nos.52305477,52375447,52305474)Major Special Projects of Aero-engine and Gas Turbine (No.2017-VII-0002-0095)+4 种基金the Special Fund of Taishan Scholars Project (No.tsqn202211179)the Youth Talent Promotion Project in Shandong (No.SDAST2021qt12)the Natural Science Foundation of Shandong Province (Nos.ZR2023QE057,ZR2022QE028,ZR2021QE116,and ZR2020KE027)Qingdao Science and Technology Planning Park Cultivation Plan (No.23-1-5-yqpy-17-qy)the Natural Science Foundation of Jiangsu Province (No.BK20210407).
文摘The machining surface integrity of aero-engine turbine disc slots has a significant impact on their fatigue life and service performance,and achieving efficiency and high-precision machining is still a great challenge.The high machining requirements of future aeroengine turbine disc slots will be difficult to satisfy using the broaching method.In addition,existing methods of slot machin-ing face difficulties in ensuring surface integrity.This study explored a cup shaped electroplated Cubic Boron Nitride(CBN)abrasive wheel for profile grinding the turbine disc slots of FGH96 powder metallurgy superalloy.The matrix structure of the cup shaped abrasive wheel was designed and verified.A profile grinding experiment was conducted for fir-tree slots on a five-axis machining center.The accuracy and the surface integrity were analyzed.Results show that the key dimension detection results of the slots were within the allowable tolerance range.Meanwhile,an average sur-face roughness Ra of 0.55μm was achieved,the residual stress was compressive,the plastic defor-mation layer thickness was less than 5μm,and the hardening layer thickness was less than 20μm.The research findings provide a new approach to machining the slots of aviation engine turbine discs and guidance for the high-quality processing of complex components.
基金Supported by Special Fund of Taishan Scholars Project(Grant No.tsqn202211179)National Natural Science Foundation of China(Grant No.52105457)+2 种基金Shandong Provincial Young Talent of Lifting Engineering for Science and Technology(Grant No.SDAST2021qt12)National Natural Science Foundation of China(Grant No.52375447)China Postdoctoral Science Foundation Funded Project(Grant No.2023M732826).
文摘The surface morphology and roughness of a workpiece are crucial parameters in grinding processes.Accurate prediction of these parameters is essential for maintaining the workpiece’s surface integrity.However,the randomness of abrasive grain shapes and workpiece surface formation behaviors poses significant challenges,and accuracy in current physical mechanism-based predictive models is needed.To address this problem,by using the random plane method and accounting for the random morphology and distribution of abrasive grains,this paper proposes a novel method to model CBN grinding wheels and predict workpiece surface roughness.First,a kinematic model of a single abrasive grain is developed to accurately capture the three-dimensional morphology of the grinding wheel.Next,by formulating an elastic deformation and formation model of the workpiece surface based on Hertz theory,the variation in grinding arc length at different grinding depths is revealed.Subsequently,a predictive model for the surface morphology of the workpiece ground by a single abrasive grain is devised.This model integrates the normal distribution model of abrasive grain size and the spatial distribution model of abrasive grain positions,to elucidate how the circumferential and axial distribution of abrasive grains influences workpiece surface formation.Lastly,by integrating the dynamic effective abrasive grain model,a predictive model for the surface morphology and roughness of the grinding wheel is established.To examine the impact of changing the grit size of the grinding wheel and grinding depth on workpiece surface roughness,and to validate the accuracy of the model,experiments are conducted.Results indicate that the predicted three-dimensional morphology of the grinding wheel and workpiece surfaces closely matches the actual grinding wheel and ground workpiece surfaces,with surface roughness prediction deviations as small as 2.3%.
文摘Traditional traffic management techniques appear to be incompetent in complex data center networks, so proposes a load balancing strategy based on Long Short-Term Memory (LSTM) and quantum annealing by Software Defined Network (SDN) to dynamically predict the traffic and comprehensively consider the current and predicted load of the network in order to select the optimal forwarding path and balance the network load. Experiments have demonstrated that the algorithm achieves significant improvement in both system throughput and average packet loss rate for the purpose of improving network quality of service.
