Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelli...Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.展开更多
Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for lowpermeability res...Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for lowpermeability reservoirs is extremely challenging.Commonly,traditional SI models based on single or averaged capillary tortuosity ignore the influence of heterogeneity of pore seepage channels and the threshold pressure(TP)on imbibition.Therefore,in this work,based on capillary model and fractal theory,a mathematical model of characterizing SI considering heterogeneity of pore seepage channels is established.On this basis,the threshold pressure was introduced to determine the pore radius at which the wetted phase can displace oil.The proposed new SI model was verified by imbibition experimental data.The study shows that for weakly heterogeneous cores with permeability of 0-1 m D,the traditional SI model can characterize the imbibition process relatively accurately,and the new imbibition model can increase the coefficient of determination by 1.05 times.However,traditional model has serious deviations in predicting the imbibition recovery for cores with permeability of 10-50 m D.The new SI model coupling with heterogeneity of pore seepage channels and threshold pressure effectively solves this problem,and the determination coefficient is increased from 0.344 to 0.922,which is increased by2.68 times.For low-permeability reservoirs,the production of the oil in transitional pores(0.01-0.1μm)and mesopores(0.1-1μm)significantly affects the imbibition recovery,as the research shows that when the heterogeneity of pore seepage channels is ignored,the oil recovery in transitional pores and mesopores decreases by 7.54%and 4.26%,respectively.Sensitivity analysis shows that increasing interfacial tension,decreasing contact angle,oil-water viscosity ratio and threshold pressure will increase imbibition recovery.In addition,there are critical values for the influence of these factors on the imbibition recovery,which provides theoretical support for surfactant optimization.展开更多
Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimen...Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.展开更多
Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Bas...Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Basin of China,we presented an integrated workflow to investigate how(1)proppant placement in induced fracture and(2)non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir.Compared with our research before(Yue et al.,2020),here we extended this study into the development of multi-stage fractured horizontal wells(MFHWs)with large-scale complicated fracture geometry.The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow,fracture flow,and non-linear seepage flow,respectively.Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW.When we assign an idealized proppant distribution instead of the real distribution,there will be an overestimation of 44.98%in daily oil rate and 30.63%in cumulative oil production after continuous development of 1000 days.Besides,threshold pressure gradient(TPG)also significantly affects the well performance in tight oil reservoirs.If we simply apply linear Darcy’s law to the reservoir matrix,the overall cumulative oil production can be overrated by 77%after 1000 days of development.In general,this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.展开更多
The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining hall...The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.展开更多
Zirconium hydride(ZrH_(2)) is an ideal neutron moderator material. However, radiation effect significantly changes its properties, which affect its behavior and the lifespan of the reactor. The threshold energy of dis...Zirconium hydride(ZrH_(2)) is an ideal neutron moderator material. However, radiation effect significantly changes its properties, which affect its behavior and the lifespan of the reactor. The threshold energy of displacement is an important quantity of the number of radiation defects produced, which helps us to predict the evolution of radiation defects in ZrH_(2).Molecular dynamics(MD) and ab initio molecular dynamics(AIMD) are two main methods of calculating the threshold energy of displacement. The MD simulations with empirical potentials often cannot accurately depict the transitional states that lattice atoms must surpass to reach an interstitial state. Additionally, the AIMD method is unable to perform largescale calculation, which poses a computational challenge beyond the simulation range of density functional theory. Machine learning potentials are renowned for their high accuracy and efficiency, making them an increasingly preferred choice for molecular dynamics simulations. In this work, we develop an accurate potential energy model for the ZrH_(2) system by using the deep-potential(DP) method. The DP model has a high degree of agreement with first-principles calculations for the typical defect energy and mechanical properties of the ZrH_(2) system, including the basic bulk properties, formation energy of point defects, as well as diffusion behavior of hydrogen and zirconium. By integrating the DP model with Ziegler–Biersack–Littmark(ZBL) potential, we can predict the threshold energy of displacement of zirconium and hydrogen in ε-ZrH_(2).展开更多
基金supported by the Guangdong Basic and Applied Basic Research Foundation(2022A1515110296,2022A1515110432)the Shenzhen Science and Technology Program(No.20231120171032001,20231122125728001).
文摘Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.
基金supported by China Natural Science Foundation(Grant No.52274053)Beijing Natural Science Foundation(Grant No.3232028)Open Fund of State Key Laboratory of Offshore Oil Exploitation(Grant No.CCL2021RCPS0515KQN)。
文摘Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for lowpermeability reservoirs is extremely challenging.Commonly,traditional SI models based on single or averaged capillary tortuosity ignore the influence of heterogeneity of pore seepage channels and the threshold pressure(TP)on imbibition.Therefore,in this work,based on capillary model and fractal theory,a mathematical model of characterizing SI considering heterogeneity of pore seepage channels is established.On this basis,the threshold pressure was introduced to determine the pore radius at which the wetted phase can displace oil.The proposed new SI model was verified by imbibition experimental data.The study shows that for weakly heterogeneous cores with permeability of 0-1 m D,the traditional SI model can characterize the imbibition process relatively accurately,and the new imbibition model can increase the coefficient of determination by 1.05 times.However,traditional model has serious deviations in predicting the imbibition recovery for cores with permeability of 10-50 m D.The new SI model coupling with heterogeneity of pore seepage channels and threshold pressure effectively solves this problem,and the determination coefficient is increased from 0.344 to 0.922,which is increased by2.68 times.For low-permeability reservoirs,the production of the oil in transitional pores(0.01-0.1μm)and mesopores(0.1-1μm)significantly affects the imbibition recovery,as the research shows that when the heterogeneity of pore seepage channels is ignored,the oil recovery in transitional pores and mesopores decreases by 7.54%and 4.26%,respectively.Sensitivity analysis shows that increasing interfacial tension,decreasing contact angle,oil-water viscosity ratio and threshold pressure will increase imbibition recovery.In addition,there are critical values for the influence of these factors on the imbibition recovery,which provides theoretical support for surfactant optimization.
基金M.Zhu acknowledges support by the National Outstanding Youth Program(62322411)the Hundred Talents Program(Chinese Academy of Sciences)+1 种基金the Shanghai Rising-Star Program(21QA1410800)The financial support was provided by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB44010200).
文摘Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.
基金The authors gratefully acknowledge the financial supports from the National Science Foundation of China under Grant 52274027 as well as the High-end Foreign Experts Recruitment Plan of the Ministry of Science and Technology China under Grant G2022105027L.
文摘Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Basin of China,we presented an integrated workflow to investigate how(1)proppant placement in induced fracture and(2)non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir.Compared with our research before(Yue et al.,2020),here we extended this study into the development of multi-stage fractured horizontal wells(MFHWs)with large-scale complicated fracture geometry.The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow,fracture flow,and non-linear seepage flow,respectively.Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW.When we assign an idealized proppant distribution instead of the real distribution,there will be an overestimation of 44.98%in daily oil rate and 30.63%in cumulative oil production after continuous development of 1000 days.Besides,threshold pressure gradient(TPG)also significantly affects the well performance in tight oil reservoirs.If we simply apply linear Darcy’s law to the reservoir matrix,the overall cumulative oil production can be overrated by 77%after 1000 days of development.In general,this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.
基金Project supported by the National Natural Science Foundation of China(Grant No.61871234).
文摘The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.
基金Project supported by the Joint Fund of the National Natural Science Foundation of China–“Ye Qisun”Science Fund(Grant No.U2341251)。
文摘Zirconium hydride(ZrH_(2)) is an ideal neutron moderator material. However, radiation effect significantly changes its properties, which affect its behavior and the lifespan of the reactor. The threshold energy of displacement is an important quantity of the number of radiation defects produced, which helps us to predict the evolution of radiation defects in ZrH_(2).Molecular dynamics(MD) and ab initio molecular dynamics(AIMD) are two main methods of calculating the threshold energy of displacement. The MD simulations with empirical potentials often cannot accurately depict the transitional states that lattice atoms must surpass to reach an interstitial state. Additionally, the AIMD method is unable to perform largescale calculation, which poses a computational challenge beyond the simulation range of density functional theory. Machine learning potentials are renowned for their high accuracy and efficiency, making them an increasingly preferred choice for molecular dynamics simulations. In this work, we develop an accurate potential energy model for the ZrH_(2) system by using the deep-potential(DP) method. The DP model has a high degree of agreement with first-principles calculations for the typical defect energy and mechanical properties of the ZrH_(2) system, including the basic bulk properties, formation energy of point defects, as well as diffusion behavior of hydrogen and zirconium. By integrating the DP model with Ziegler–Biersack–Littmark(ZBL) potential, we can predict the threshold energy of displacement of zirconium and hydrogen in ε-ZrH_(2).
