Observations of transmission spectra reveal that hot Jupiters and Neptunes are likely to possess escaping atmospheres driven by stellar radiation.Numerous models predict that magnetic fields may exert significant infl...Observations of transmission spectra reveal that hot Jupiters and Neptunes are likely to possess escaping atmospheres driven by stellar radiation.Numerous models predict that magnetic fields may exert significant influences on the atmospheres of hot planets.Generally,the escaping atmospheres are not entirely ionized,and magnetic fields only directly affect the escape of ionized components within them.Considering the chemical reactions between ionized components and neutral atoms,as well as collision processes,magnetic fields indirectly impact the escape of neutral atoms,thereby influencing the detection signals of planetary atmospheres in transmission spectra.In order to simulate this process,we developed a magnetohydrodynamic multi-fluid model based on MHD code PLUTO.As an initial exploration,we investigated the impact of magnetic fields on the decoupling of H^(+)and H in the escaping atmosphere of the hot Neptune GJ436b.Due to the strong resonant interactions between H and H^(+),the coupling between them is tight even if the magnetic field is strong.Of course,alternatively,our work also suggests that merging H and H^(+)into a single flow can be a reasonable assumption in MHD simulations of escaping atmospheres.However,our simulation results indicate that under the influence of magnetic fields,there are noticeable regional differences in the decoupling of H^(+)and H.With the increase of magnetic field strength,the degree of decoupling also increases.For heavier particles such as O,the decoupling between O and H^(+)is more pronounced.Our findings provide important insights for future studies on the decoupling processes of heavy atoms in the escaping atmospheres of hot Jupiters and hot Neptunes under the influence of magnetic fields.展开更多
Efficient,stable and economical catalysts play a crucial role in enhancing the kinetics of slow oxygen reduction reactions(ORR)in Aluminum-air batteries.Among the potential next-generation candidates,Ag catalysts are ...Efficient,stable and economical catalysts play a crucial role in enhancing the kinetics of slow oxygen reduction reactions(ORR)in Aluminum-air batteries.Among the potential next-generation candidates,Ag catalysts are promising due to their high activity and low cost,but weaker oxygen adsorption has hindered industrialization.To address this bottleneck,Ag-alloying has emerged as a principal strategy.In this work,we successfully prepared Ag-Cu nanoparticles(NPs)with a rich eutectic phase and uniform dispersion structure using plasma evaporation.The increased solid solution of Ag and Cu led to changes in the electronic structure,resulting in an upward shift of the d-band center,which significantly improved oxygen adsorption.The combination of Ag and Cu in the NPs synergistically enhanced the adsorption of Ag and the desorption of Cu.Density functional theory(DFT)calculations revealed that Ag-Cu25 NPs exhibited the smallest limiting reaction barrier,leading to increased ORR activity.To further optimize the catalyst’s performance,we utilized N-doped porous nanocarbon(N-PC)with high electrical conductivity and abundant mesoporous channels as the support for the Ag-Cu NPs.The N-PC support provided optimal mass transfer carriers for the highly active Ag-Cu25 NPs.As a result,the Ag-Cu25/NPC catalyst displayed excellent ORR activity in alkaline media,with a half-wave potential(E_(1/2))of 0.82 V.Furthermore,the Al-air battery incorporating the Ag-Cu25/NPC catalyst exhibited outstanding electrochemical performance.It demonstrated high open-circuit voltages of 1.89 V and remarkable power densities of 193 m W cm^(-2).The battery also sustained a high current output and maintained a stable high voltage for 120 hours under mechanical charging,showcasing its significant potential for practical applications.展开更多
To strengthen border patrol measures, unmanned aerial vehicles(UAVs) are gradually used in many countries to detect illegal entries on borders. However, how to efficiently deploy limited UAVs to patrol on borders of l...To strengthen border patrol measures, unmanned aerial vehicles(UAVs) are gradually used in many countries to detect illegal entries on borders. However, how to efficiently deploy limited UAVs to patrol on borders of large areas remains challenging. In this paper, we first model the problem of deploying UAVs for border patrol as a Stackelberg game. Two players are considered in this game: The border patrol agency is the leader,who optimizes the patrol path of UAVs to detect the illegal immigrant. The illegal immigrant is the follower, who selects a certain area of the border to pass through at a certain time after observing the leader’s strategy. Second, a compact linear programming problem is proposed to tackle the exponential growth of the number of leader’s strategies. Third, a method is proposed to reduce the size of the strategy space of the follower. Then, we provide some theoretic results to present the effect of parameters of the model on leader’s utilities. Experimental results demonstrate the positive effect of limited starting and ending areas of UAV’s patrolling conditions and multiple patrolling altitudes on the leader ’s utility, and show that the proposed solution outperforms two conventional patrol strategies and has strong robustness.展开更多
The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,th...The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.展开更多
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences,grant No.XDB 41000000National Natural Science Foundation of China(NSFC,Grant No.12288102)+4 种基金support of the National Natural Science Foundation of China(NSFC,Grant No.11973082)support of the National Natural Science Foundation of China(NSFC,Grant No.42305136)supported by the National Key R&D Program of China(Grant No.2021YFA1600400/2021YFA1600402)Natural Science Foundation of Yunnan Province(No.202201AT070158)the International Centre of Supernovae,Yunnan Key Laboratory(No.202302AN360001)。
文摘Observations of transmission spectra reveal that hot Jupiters and Neptunes are likely to possess escaping atmospheres driven by stellar radiation.Numerous models predict that magnetic fields may exert significant influences on the atmospheres of hot planets.Generally,the escaping atmospheres are not entirely ionized,and magnetic fields only directly affect the escape of ionized components within them.Considering the chemical reactions between ionized components and neutral atoms,as well as collision processes,magnetic fields indirectly impact the escape of neutral atoms,thereby influencing the detection signals of planetary atmospheres in transmission spectra.In order to simulate this process,we developed a magnetohydrodynamic multi-fluid model based on MHD code PLUTO.As an initial exploration,we investigated the impact of magnetic fields on the decoupling of H^(+)and H in the escaping atmosphere of the hot Neptune GJ436b.Due to the strong resonant interactions between H and H^(+),the coupling between them is tight even if the magnetic field is strong.Of course,alternatively,our work also suggests that merging H and H^(+)into a single flow can be a reasonable assumption in MHD simulations of escaping atmospheres.However,our simulation results indicate that under the influence of magnetic fields,there are noticeable regional differences in the decoupling of H^(+)and H.With the increase of magnetic field strength,the degree of decoupling also increases.For heavier particles such as O,the decoupling between O and H^(+)is more pronounced.Our findings provide important insights for future studies on the decoupling processes of heavy atoms in the escaping atmospheres of hot Jupiters and hot Neptunes under the influence of magnetic fields.
基金supported by the Fundamental Research Funds for the Central Universities of China(DUT20-LAB307)the Supercomputing Center of Dalian University of Technology。
文摘Efficient,stable and economical catalysts play a crucial role in enhancing the kinetics of slow oxygen reduction reactions(ORR)in Aluminum-air batteries.Among the potential next-generation candidates,Ag catalysts are promising due to their high activity and low cost,but weaker oxygen adsorption has hindered industrialization.To address this bottleneck,Ag-alloying has emerged as a principal strategy.In this work,we successfully prepared Ag-Cu nanoparticles(NPs)with a rich eutectic phase and uniform dispersion structure using plasma evaporation.The increased solid solution of Ag and Cu led to changes in the electronic structure,resulting in an upward shift of the d-band center,which significantly improved oxygen adsorption.The combination of Ag and Cu in the NPs synergistically enhanced the adsorption of Ag and the desorption of Cu.Density functional theory(DFT)calculations revealed that Ag-Cu25 NPs exhibited the smallest limiting reaction barrier,leading to increased ORR activity.To further optimize the catalyst’s performance,we utilized N-doped porous nanocarbon(N-PC)with high electrical conductivity and abundant mesoporous channels as the support for the Ag-Cu NPs.The N-PC support provided optimal mass transfer carriers for the highly active Ag-Cu25 NPs.As a result,the Ag-Cu25/NPC catalyst displayed excellent ORR activity in alkaline media,with a half-wave potential(E_(1/2))of 0.82 V.Furthermore,the Al-air battery incorporating the Ag-Cu25/NPC catalyst exhibited outstanding electrochemical performance.It demonstrated high open-circuit voltages of 1.89 V and remarkable power densities of 193 m W cm^(-2).The battery also sustained a high current output and maintained a stable high voltage for 120 hours under mechanical charging,showcasing its significant potential for practical applications.
基金supported by the National Natural Science Foundation of China (71971075,71871079)the National Key Research and Development Program of China (2019YFE0110300)+1 种基金the Anhui Provincial Natural Science Foundation (1808085MG213)the Fundamental R esearch Funds for the Central Universities (PA2019GDPK0082)。
文摘To strengthen border patrol measures, unmanned aerial vehicles(UAVs) are gradually used in many countries to detect illegal entries on borders. However, how to efficiently deploy limited UAVs to patrol on borders of large areas remains challenging. In this paper, we first model the problem of deploying UAVs for border patrol as a Stackelberg game. Two players are considered in this game: The border patrol agency is the leader,who optimizes the patrol path of UAVs to detect the illegal immigrant. The illegal immigrant is the follower, who selects a certain area of the border to pass through at a certain time after observing the leader’s strategy. Second, a compact linear programming problem is proposed to tackle the exponential growth of the number of leader’s strategies. Third, a method is proposed to reduce the size of the strategy space of the follower. Then, we provide some theoretic results to present the effect of parameters of the model on leader’s utilities. Experimental results demonstrate the positive effect of limited starting and ending areas of UAV’s patrolling conditions and multiple patrolling altitudes on the leader ’s utility, and show that the proposed solution outperforms two conventional patrol strategies and has strong robustness.
基金supported in part by the Natural Science Foundation of Shandong Province(ZR2021QE289)in part by State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22201).
文摘The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.
