Being cheap,nondestructive,and easy to use,gas sensors play important roles in the food industry.However,most gas sensors are suitable more for laboratory-quality fast testing rather than for cold-chain continuous and...Being cheap,nondestructive,and easy to use,gas sensors play important roles in the food industry.However,most gas sensors are suitable more for laboratory-quality fast testing rather than for cold-chain continuous and cumulative testing.Also,an ideal electronic nose(E-nose)in a cold chain should be stable to its surroundings and remain highly accurate and portable.In this work,a portable film bulk acoustic resonator(FBAR)-based E-nose was built for real-time measurement of banana shelf time.The sensor chamber to contain the portable circuit of the E-nose is as small as a smartphone,and by introducing an air-tight FBAR as a reference,the E-nose can avoid most of the drift caused by surroundings.With the help of porous layer by layer(LBL)coating of the FBAR,the sensitivity of the E-nose is 5 ppm to ethylene and 0.5 ppm to isoamyl acetate and isoamyl butyrate,while the detection range is large enough to cover a relative humidity of 0.8.In this regard,the E-nose can easily discriminate between yellow bananas with green necks and entirely yellow bananas while allowing the bananas to maintain their biological activities in their normal storage state,thereby showing the possibility of real-time shelf time detection.This portable FBAR-based E-nose has a large testing scale,high sensitivity,good humidity tolerance,and low frequency drift to its surroundings,thereby meeting the needs of cold-chain usage.展开更多
Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop...Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop cultivation. Increases in the frequency of these rare events in a future warmer climate would have significant societal impact. This study uses an ensemble of 10 Coupled Model Intercomparison Project(CMIP) models to investigate the projected change in agricultural flash drought during the 21st century. Comparison across geographical regions and climatic zones indicates that individual events are preceded by anomalously low relative humidity and precipitation, with long-term trends governed by changes in temperature, relative humidity, and soil moisture. As a result of these processes, the frequency of both upperlevel and root-zone flash drought is projected to more than double in the mid-and high latitudes over the 21st century, with hot spots developing in the temperate regions of Europe, and humid regions of South America, Europe, and southern Africa.展开更多
Boron is an important industrial raw material often sourced from minerals containing different compounds that cocrystallize,which makes it difficult to separate the mineral phases through conventional beneficiation.Th...Boron is an important industrial raw material often sourced from minerals containing different compounds that cocrystallize,which makes it difficult to separate the mineral phases through conventional beneficiation.This study proposed a new treatment called flash reduction-melting separation(FRMS)for boron-bearing iron concentrates.In this method,the concentrates were first flash-reduced at the temperature under which the particles melt,and the slag and the reduced iron phases disengaged at the particle scale.Good reduc-tion and melting effects were achieved above 1550℃.The B_(2)O_(3) content in the separated slag was over 18wt%,and the B content in the iron was less than 0.03wt%.The proposed FRMS method was tested to investigate the effects of factors such as ore particle size and tem-perature on the reduction and melting steps with and without pre-reducing the raw concentrate.The mineral phase transformation and morphology evolution in the ore particles during FRMS were also comprehensively analyzed.展开更多
With the rapid development of machine learning,the demand for high-efficient computing becomes more and more urgent.To break the bottleneck of the traditional Von Neumann architecture,computing-in-memory(CIM)has attra...With the rapid development of machine learning,the demand for high-efficient computing becomes more and more urgent.To break the bottleneck of the traditional Von Neumann architecture,computing-in-memory(CIM)has attracted increasing attention in recent years.In this work,to provide a feasible CIM solution for the large-scale neural networks(NN)requiring continuous weight updating in online training,a flash-based computing-in-memory with high endurance(10^(9) cycles)and ultrafast programming speed is investigated.On the one hand,the proposed programming scheme of channel hot electron injection(CHEI)and hot hole injection(HHI)demonstrate high linearity,symmetric potentiation,and a depression process,which help to improve the training speed and accuracy.On the other hand,the low-damage programming scheme and memory window(MW)optimizations can suppress cell degradation effectively with improved computing accuracy.Even after 109 cycles,the leakage current(I_(off))of cells remains sub-10pA,ensuring the large-scale computing ability of memory.Further characterizations are done on read disturb to demonstrate its robust reliabilities.By processing CIFAR-10 tasks,it is evident that~90%accuracy can be achieved after 109 cycles in both ResNet50 and VGG16 NN.Our results suggest that flash-based CIM has great potential to overcome the limitations of traditional Von Neumann architectures and enable high-performance NN online training,which pave the way for further development of artificial intelligence(AI)accelerators.展开更多
Flash boiling atomization(FBA)is a promising approach for enhancing spray atomization,which can generate a fine and more evenly distributed spray by increasing the fuel injection temperature or reducing the ambient pr...Flash boiling atomization(FBA)is a promising approach for enhancing spray atomization,which can generate a fine and more evenly distributed spray by increasing the fuel injection temperature or reducing the ambient pressure.However,when the outlet speed of the nozzle exceeds 400 m/s,investigating high-speed flash boiling atomization(HFBA)becomes quite challenging.This difficulty arises fromthe involvement ofmany complex physical processes and the requirement for a very fine mesh in numerical simulations.In this study,an HFBA model for gasoline direct injection(GDI)is established.This model incorporates primary and secondary atomization,as well as vaporization and boilingmodels,to describe the development process of the flash boiling spray.Compared to lowspeed FBA,these physical processes significantly impact HFBA.In this model,the Eulerian description is utilized for modeling the gas,and the Lagrangian description is applied to model the droplets,which effectively captures the movement of the droplets and avoids excessive mesh in the Eulerian coordinates.Under various conditions,numerical solutions of the Sauter mean diameter(SMD)for GDI show good agreement with experimental data,validating the proposed model’s performance.Simulations based on this HFBA model investigate the influences of fuel injection temperature and ambient pressure on the atomization process.Numerical analyses of the velocity field,temperature field,vapor mass fraction distribution,particle size distribution,and spray penetration length under different superheat degrees reveal that high injection temperature or low ambient pressure significantly affects the formation of small and dispersed droplet distribution.This effect is conducive to the refinement of spray particles and enhances atomization.展开更多
基金supported financially by the National Natural Science Foundation of China (Grant Nos.22078051 and U1801258)the Fundamental Research Funds for the Central Universities (Grant No.DUT22LAB610).
文摘Being cheap,nondestructive,and easy to use,gas sensors play important roles in the food industry.However,most gas sensors are suitable more for laboratory-quality fast testing rather than for cold-chain continuous and cumulative testing.Also,an ideal electronic nose(E-nose)in a cold chain should be stable to its surroundings and remain highly accurate and portable.In this work,a portable film bulk acoustic resonator(FBAR)-based E-nose was built for real-time measurement of banana shelf time.The sensor chamber to contain the portable circuit of the E-nose is as small as a smartphone,and by introducing an air-tight FBAR as a reference,the E-nose can avoid most of the drift caused by surroundings.With the help of porous layer by layer(LBL)coating of the FBAR,the sensitivity of the E-nose is 5 ppm to ethylene and 0.5 ppm to isoamyl acetate and isoamyl butyrate,while the detection range is large enough to cover a relative humidity of 0.8.In this regard,the E-nose can easily discriminate between yellow bananas with green necks and entirely yellow bananas while allowing the bananas to maintain their biological activities in their normal storage state,thereby showing the possibility of real-time shelf time detection.This portable FBAR-based E-nose has a large testing scale,high sensitivity,good humidity tolerance,and low frequency drift to its surroundings,thereby meeting the needs of cold-chain usage.
基金supported by the National Centre for Atmospheric Science through the NERC National Capability International Programmes Award (NE/ X006263/1)the Global Challenges Research Fund, via Atmospheric hazard in developing Countries: Risk assessment and Early Warning (ACREW) (NE/R000034/1)the Natural Environmental Research Council and the Department for Foreign International Development through the Sat WIN-ALERT project (NE/ R014116/1)。
文摘Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop cultivation. Increases in the frequency of these rare events in a future warmer climate would have significant societal impact. This study uses an ensemble of 10 Coupled Model Intercomparison Project(CMIP) models to investigate the projected change in agricultural flash drought during the 21st century. Comparison across geographical regions and climatic zones indicates that individual events are preceded by anomalously low relative humidity and precipitation, with long-term trends governed by changes in temperature, relative humidity, and soil moisture. As a result of these processes, the frequency of both upperlevel and root-zone flash drought is projected to more than double in the mid-and high latitudes over the 21st century, with hot spots developing in the temperate regions of Europe, and humid regions of South America, Europe, and southern Africa.
基金supported by the Science and Technology Special Plan Project from China Minmetals Group (No.2020ZXA01)the International Exchange and Growth Program for Young Teachers (No.QNXM20220061)the National Key Research and Development Program of China (No.2022YFC2906100).
文摘Boron is an important industrial raw material often sourced from minerals containing different compounds that cocrystallize,which makes it difficult to separate the mineral phases through conventional beneficiation.This study proposed a new treatment called flash reduction-melting separation(FRMS)for boron-bearing iron concentrates.In this method,the concentrates were first flash-reduced at the temperature under which the particles melt,and the slag and the reduced iron phases disengaged at the particle scale.Good reduc-tion and melting effects were achieved above 1550℃.The B_(2)O_(3) content in the separated slag was over 18wt%,and the B content in the iron was less than 0.03wt%.The proposed FRMS method was tested to investigate the effects of factors such as ore particle size and tem-perature on the reduction and melting steps with and without pre-reducing the raw concentrate.The mineral phase transformation and morphology evolution in the ore particles during FRMS were also comprehensively analyzed.
基金This work was supported by the National Natural Science Foundation of China(Nos.62034006,92264201,and 91964105)the Natural Science Foundation of Shandong Province(Nos.ZR2020JQ28 and ZR2020KF016)the Program of Qilu Young Scholars of Shandong University.
文摘With the rapid development of machine learning,the demand for high-efficient computing becomes more and more urgent.To break the bottleneck of the traditional Von Neumann architecture,computing-in-memory(CIM)has attracted increasing attention in recent years.In this work,to provide a feasible CIM solution for the large-scale neural networks(NN)requiring continuous weight updating in online training,a flash-based computing-in-memory with high endurance(10^(9) cycles)and ultrafast programming speed is investigated.On the one hand,the proposed programming scheme of channel hot electron injection(CHEI)and hot hole injection(HHI)demonstrate high linearity,symmetric potentiation,and a depression process,which help to improve the training speed and accuracy.On the other hand,the low-damage programming scheme and memory window(MW)optimizations can suppress cell degradation effectively with improved computing accuracy.Even after 109 cycles,the leakage current(I_(off))of cells remains sub-10pA,ensuring the large-scale computing ability of memory.Further characterizations are done on read disturb to demonstrate its robust reliabilities.By processing CIFAR-10 tasks,it is evident that~90%accuracy can be achieved after 109 cycles in both ResNet50 and VGG16 NN.Our results suggest that flash-based CIM has great potential to overcome the limitations of traditional Von Neumann architectures and enable high-performance NN online training,which pave the way for further development of artificial intelligence(AI)accelerators.
基金supported by the National Natural Science Foundation of China(Project Nos.12272270,11972261).
文摘Flash boiling atomization(FBA)is a promising approach for enhancing spray atomization,which can generate a fine and more evenly distributed spray by increasing the fuel injection temperature or reducing the ambient pressure.However,when the outlet speed of the nozzle exceeds 400 m/s,investigating high-speed flash boiling atomization(HFBA)becomes quite challenging.This difficulty arises fromthe involvement ofmany complex physical processes and the requirement for a very fine mesh in numerical simulations.In this study,an HFBA model for gasoline direct injection(GDI)is established.This model incorporates primary and secondary atomization,as well as vaporization and boilingmodels,to describe the development process of the flash boiling spray.Compared to lowspeed FBA,these physical processes significantly impact HFBA.In this model,the Eulerian description is utilized for modeling the gas,and the Lagrangian description is applied to model the droplets,which effectively captures the movement of the droplets and avoids excessive mesh in the Eulerian coordinates.Under various conditions,numerical solutions of the Sauter mean diameter(SMD)for GDI show good agreement with experimental data,validating the proposed model’s performance.Simulations based on this HFBA model investigate the influences of fuel injection temperature and ambient pressure on the atomization process.Numerical analyses of the velocity field,temperature field,vapor mass fraction distribution,particle size distribution,and spray penetration length under different superheat degrees reveal that high injection temperature or low ambient pressure significantly affects the formation of small and dispersed droplet distribution.This effect is conducive to the refinement of spray particles and enhances atomization.
