In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of...The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of energy systems.To enhance the consumption capacity of green power,the green power system consumption optimization scheduling model(GPS-COSM)is proposed,which comprehensively integrates green power system,electric boiler,combined heat and power unit,thermal energy storage,and electrical energy storage.The optimization objectives are to minimize operating cost,minimize carbon emission,and maximize the consumption of wind and solar curtailment.The multi-objective particle swarm optimization algorithm is employed to solve the model,and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set,thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency,environmental friendliness,and energy utilization efficiency.Three typical operating modes are designed for comparative analysis.The results demonstrate that the mode involving the coordinated operation of electric boiler,thermal energy storage,and electrical energy storage performs the best in terms of economic efficiency,environmental friendliness,and renewable energy utilization efficiency,achieving the wind and solar curtailment consumption rate of 99.58%.The application of electric boiler significantly enhances the direct accommodation capacity of the green power system.Thermal energy storage optimizes intertemporal regulation,while electrical energy storage strengthens the system’s dynamic regulation capability.The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.展开更多
In the parallel steering coordination control strategy for path tracking,it is difficult to match the current driver steering model using the fixed parameters with the actual driver,and the designed steering coordinat...In the parallel steering coordination control strategy for path tracking,it is difficult to match the current driver steering model using the fixed parameters with the actual driver,and the designed steering coordination control strategy under a single objective and simple conditions is difficult to adapt to the multi-dimensional state variables’input.In this paper,we propose a deep reinforcement learning algorithm-based multi-objective parallel human-machine steering coordination strategy for path tracking considering driver misoperation and external disturbance.Firstly,the driver steering mathematical model is constructed based on the driver preview characteristics and steering delay response,and the driver characteristic parameters are fitted after collecting the actual driver driving data.Secondly,considering that the vehicle is susceptible to the influence of external disturbances during the driving process,the Tube MPC(Tube Model Predictive Control)based path tracking steering controller is designed based on the vehicle system dynamics error model.After verifying that the driver steering model meets the driver steering operation characteristics,DQN(Deep Q-network),DDPG(Deep Deterministic Policy Gradient)and TD3(Twin Delayed Deep Deterministic Policy Gradient)deep reinforcement learning algorithms are utilized to design a multi-objective parallel steering coordination strategy which satisfies the multi-dimensional state variables’input of the vehicle.Finally,the tracking accuracy,lateral safety,human-machine conflict and driver steering load evaluation index are designed in different driver operation states and different road environments,and the performance of the parallel steering coordination control strategies with different deep reinforcement learning algorithms and fuzzy algorithms are compared by simulations and hardware in the loop experiments.The results show that the parallel steering collaborative strategy based on a deep reinforcement learning algorithm can more effectively assist the driver in tracking the target path under lateral wind interference and driver misoperation,and the TD3-based coordination control strategy has better overall performance.展开更多
This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balanc...This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.展开更多
In this paper,distributed power flow controller(DPFC)constraints are analyzed.The energy balance relationship between fundamental wave and third harmonic in series and shunt-side converter is deduced.A proportional in...In this paper,distributed power flow controller(DPFC)constraints are analyzed.The energy balance relationship between fundamental wave and third harmonic in series and shunt-side converter is deduced.A proportional integral(PI)controller of the DPFC is constructed.The PI controller uses the voltage amplitude and phase angle injected into the system in the series side,along with the modulation ratio of the three-phase converter on the shunt side as the control variables.A multiobjective coordinated control equation is proposed,which factors the constraints of the energy balance between series and shunt side,device capacity limit,safe operation limit,fundamental component,as well as third harmonic component of the injection voltage at the series side.The equation minimizes the variance between the actual value of the control target and its given value to ensure that the DC capacitor voltage,both in the series and shunt side,is stable at target value.Simulations are conducted to verify correctness and effectiveness of the proposed control method.展开更多
Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longe...Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.展开更多
A novel coordination polymer(CP){[Cd_(2)(L)(1,4-bimb)_(1.5)(DMF)_(2)]·DMF}n(1)(H_(4)L=5,5'-[1,1'-biphenyl-4,4'-diylbis(oxy)]diisophthalic acid,1,4-bimb=1,4-bis(imidazole-1-ylmethyl)-benzene)has been d...A novel coordination polymer(CP){[Cd_(2)(L)(1,4-bimb)_(1.5)(DMF)_(2)]·DMF}n(1)(H_(4)L=5,5'-[1,1'-biphenyl-4,4'-diylbis(oxy)]diisophthalic acid,1,4-bimb=1,4-bis(imidazole-1-ylmethyl)-benzene)has been designed and synthesized through solvothermal reaction.Structural analysis shows that Cd(Ⅱ)is connected by H4L and 1,4-bimb to form a 2D network,and 1,4-bimb further expands the 2D network into a 3D framework.CP 1 can be used as an excellent fluorescence sensor for Fe^(3+)and 4-nitrophenol(4-NP),with low detection limits and good anti-interference.The detection limits of Fe^(3+)and 4-NP were 0.034 and 0.031μmol·L^(-1),respectively.In addition,the fluorescence quenching mechanism was studied.1 was successfully applied to determine Fe^(3+)and 4-NP content in the Yanhe River water sample.CCDC:2351092.展开更多
The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition...The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.展开更多
With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm impro...With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.展开更多
Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoti...Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.展开更多
With the boom in maritime activities,the need for highly reliable maritime communication is becoming urgent,which is an important component of 5G/6G communication networks.However,the bandwidth reuse characteristic of...With the boom in maritime activities,the need for highly reliable maritime communication is becoming urgent,which is an important component of 5G/6G communication networks.However,the bandwidth reuse characteristic of 5G/6G networks will inevitably lead to severe interference,resulting in degradation in the communication performance of maritime users.In this paper,we propose a safe deep reinforcement learning based interference coordination scheme to jointly optimize the power control and bandwidth allocation in maritime communication systems,and exploit the quality-of-service requirements of users as the risk value references to evaluate the communication policies.In particular,this scheme designs a deep neural network to select the communication policies through the evaluation network and update the parameters using the target network,which improves the communication performance and speeds up the convergence rate.Moreover,the Nash equilibrium of the interference coordination game and the computational complexity of the proposed scheme are analyzed.Simulation and experimental results verify the performance gain of the proposed scheme compared with benchmarks.展开更多
A genetic algorithm based multi-objective coordinative optimization strategy is developed to optimize the operation of a binary feed atmospheric and vacuum distillation system, in which the objective functions cover t...A genetic algorithm based multi-objective coordinative optimization strategy is developed to optimize the operation of a binary feed atmospheric and vacuum distillation system, in which the objective functions cover the economic benefit, the furnace energy consumption and the CO_2 emissions, and meanwhile the simultaneous effect of binary feed composition is also investigated. A cross-call integration of software is developed to implement the optimization algorithm,and once the maximum economic benefit, the minimum furnace energy consumption and the minimum CO_2 emissions are obtained, the Pareto-optimal solution set is worked out, with the practical problems of the refinery being solved. The optimization result shows that under the same furnace energy consumption and the CO_2 emissions as the existing working condition, the economic benefit still allows for a considerable potential of increment by adjusting the heavy oil proportion of the binary feed crude oil.展开更多
In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimizatio...In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.展开更多
One Yb(Ⅲ)-based coordination polymer,{[Yb(H_(2)dhtp)1.5(H_(2)O)_(4)]·3H_(2)O}n(1)(H_(4)dhtp=2,5-dihydroxytere-phthalic acid),was fabricated and structurally characterized by single-crystal X-ray diffraction,IR,p...One Yb(Ⅲ)-based coordination polymer,{[Yb(H_(2)dhtp)1.5(H_(2)O)_(4)]·3H_(2)O}n(1)(H_(4)dhtp=2,5-dihydroxytere-phthalic acid),was fabricated and structurally characterized by single-crystal X-ray diffraction,IR,powder X-ray diffraction,X-ray diffraction,and elemental analysis.Complex 1 displays a 1D chain structure,and belongs to P1 group.The solid-state luminescent spectrum of 1 showed an emission band with the maximum at 508 nm(λex=408 nm).It exhibited the emission characteristic of the H_(4)dhtp ligand.The fluorescence of 1 in water displayed the stron-gest intensity.In detecting various metal ions,adding Zr^(4+)led to a blue shift in fluorescence,accompanied by an increase in intensity,whereas the presence of Fe^(3+)resulted in a decrease in luminescence.The changes observed in the IR spectrum indicate an interaction between Fe^(3+)/Zr^(4+)and complex 1,resulting in the variation of luminescence properties.展开更多
Under the condition of solvothermal synthesis,the viologen ligand 1,1′-bis(3-carboxyphenyl)-(4,4′-bipyri-dine)dichloride(H_(2)bcbpy·2Cl)and KI are coordinated with the metal cadmium ions.A case of thermochromic...Under the condition of solvothermal synthesis,the viologen ligand 1,1′-bis(3-carboxyphenyl)-(4,4′-bipyri-dine)dichloride(H_(2)bcbpy·2Cl)and KI are coordinated with the metal cadmium ions.A case of thermochromic coor-dination polymer[Cd(bcbpy)I_(2)]·2H_(2)O(1)was constructed.Complex 1 displays a 1D chain structure and exhibits thermochromic behavior.Under different temperature stimulation,the complex(ground)slowly changed from green to yellow-green,and with the increase of temperature,the color of complex 1 gradually deepened,and finally became orange-yellow.Therefore,complex 1 was prepared as a thermochromic film.In addition,we also performed electrochemical tests on complex 1,which showed that the complex is a semiconductor material.CCDC:2391802.展开更多
We report five coordination polymers(CPs)based on fluorescent ligands[1,6-di(1H-imidazol-1-yl)pyrene(dip),9,10-di(1H-imidazol-1-yl)anthracene(dia)]and anionic ligands[cyclohexane-1,4-dicarboxylic acid(H_(2)cda),campho...We report five coordination polymers(CPs)based on fluorescent ligands[1,6-di(1H-imidazol-1-yl)pyrene(dip),9,10-di(1H-imidazol-1-yl)anthracene(dia)]and anionic ligands[cyclohexane-1,4-dicarboxylic acid(H_(2)cda),camphoric acid(H_(2)cpa)].In[Cd(dip)(cda)]·4H_(2)O}_(n)(1),the Cd^(2+)ions,acting as tetrahedral nodes,are linked by dipand cda^(2-)ligands with four Cd^(2+)ions into five-fold interpenetrating network array of topology of dia.In{[Cd(dip)(cpa)]·4H_(2)O}_(n)(2),the Cd^(2+)ions,acting as a 4-connector,are linked by cpa^(2-)and dip ligands into a 3D framework ofcds topology.In{[Ni(dia)_(2)Cl_(2)]·DMF}_(n)(3),the Ni^(2+)ion is linked by four dia ligands into a layer structure,and 1Dchannels of a cross-section of 1.35 nm×0.96 nm are formed.In{[Cd(dia)_(2)(H_(2)O)_(2)](NO_(3))_(2)·2DMSO}n(4),the dia ligandsconnected Cd^(2+)ions into a 2D layer,and 1D channels are formed between adjacent layers with a cross-section of0.87 nm×0.43 nm.In[Zn(dip)Cl_(2)]_(n)(5),the Zn^(2+)ion is linked by dip ligands into an infinite 1D chain.The infrared,thermal gravimetric,and fluorescent emission data were collected and analyzed for these coordination polymers.CCDC:2356055,1;2440075,2;2356057,3;2356057,4;2356059,5.展开更多
A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism a...A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.展开更多
Exploring optimal operational schemes for synergistic development is crucial for sustainable management in river basins.This study introduces a multi-objective synergistic optimization framework aimed at analyzing the...Exploring optimal operational schemes for synergistic development is crucial for sustainable management in river basins.This study introduces a multi-objective synergistic optimization framework aimed at analyzing the interplay among flood control,ecological integrity,and desilting objectives under varying watersediment conditions.The framework encompasses multi-objective reservoir optimal operation,scheme decision,and trade-off analysis among competing objectives.To address the optimization model,an elite mutation-based multiobjective particle swarm optimization(MOPSO)algorithm that integrates genetic algorithms(GA)is developed.The coupling coordination degree is employed for optimal scheme decision-making,allowing for the adjustment of weight ratios to investigate the trade-offs between objectives.This research focuses on the Sanmenxia and Xiaolangdi cascade reservoirs in the Yellow River,utilizing three representative hydrological years:1967,1969,and 2002.The findings reveal that:(1)the proposed model effectively generates Pareto fronts for multi-objective operations,facilitating the recommendation of optimal schemes based on coupling coordination degrees;(2)as water-sediment conditions shift from flooding to drought,competition intensifies between the flood control and desilting objectives.While flood control and ecological objectives compete during flood and dry years,they demonstrate synergies in normal years(r=0.22);conversely,ecological and desilting objectives are consistently competitive across all three typical years,with the strongest competition observed in the normal year(r=-0.95);(3)the advantages conferred to ecological objectives increase as water-sediment conditions shift from flooding to drought.However,the promotion of the desilting objective requires more complex trade-offs.This study provides a model and methodological approach for the multi-objective optimization of flood control,sediment management,and ecological considerations in reservoir clusters.Moreover,the methodologies presented herein can be extended to other water resource systems for multi-objective optimization and decision-making.展开更多
Six coordination polymers based on 9,10-di(pyridine-4-yl)-anthracene(DPA)and 1,6-di(1H-imidazol-1-yl)pyrene(DIP)were obtained by solvothermal reactions.{[Zn(DPA)Cl_(2)]·DMF·2H_(2)O}n(1)and{[Zn_(1.5)(DPA)_(1....Six coordination polymers based on 9,10-di(pyridine-4-yl)-anthracene(DPA)and 1,6-di(1H-imidazol-1-yl)pyrene(DIP)were obtained by solvothermal reactions.{[Zn(DPA)Cl_(2)]·DMF·2H_(2)O}n(1)and{[Zn_(1.5)(DPA)_(1.5)Cl_(3)]·5H_(2)O}n(2)are framework isomers,which both contain zigzag chains formed by DPA,Zn^(2+),and Cl-.The zigzag chains in 1 are further assembled by C—H…Cl interactions into layers,and these layers exhibit two different orientations,displaying a rare 2D to 3D interpenetration mode.The zigzag chains in 2 are parallelly arranged.{[Zn_(3)(DPA)_(3)Br_(6)]·2DMF·_(1.5)H_(2)O}n(3)is isostructural to 2.3 was obtained using ZnBr_(2)instead of ZnCl_(2).[M(DPA)(formate)_(2)(H_(2)O)_(2)]n[M=Co(4),Cu(5)]are isostructural,contain chain structures formed by DPA,Cu^(2+)/Co^(2+),and for-mate ions,which were formed in situ in the solvothermal reaction.{[Zn(DIP)_(2)Cl]ClO_(4)}n(6)contains a layer structure formed by DIP and Zn^(2+).Free DPA and DIP ligands exhibited high fluorescence at room temperature,and coordina-tion polymers 3 and 6 displayed enhanced fluorescent emissions.展开更多
Two new Mn(Ⅱ)coordination polymers,namely{[Mn_(2)(HL)(phen)_(3)(H_(2)O)_(2)]·7.5H_(2)O}_n(1)and[Mn_(4)(HL)_(2)(1,4-bib)_(3)(H_(2)O)_(2)]_n(2),were synthesized under hydrothermal conditions by using Mn(Ⅱ)ions an...Two new Mn(Ⅱ)coordination polymers,namely{[Mn_(2)(HL)(phen)_(3)(H_(2)O)_(2)]·7.5H_(2)O}_n(1)and[Mn_(4)(HL)_(2)(1,4-bib)_(3)(H_(2)O)_(2)]_n(2),were synthesized under hydrothermal conditions by using Mn(Ⅱ)ions and 6-(3',4'-dicarboxylphenoxy)-1,2,4-benzenetricarboxylic acid(H_(5)L)in the presence of N-auxiliary ligands 1,10-phenanthroline(phen)and1,4-bis(1H-imidazol-1-yl)benzene(1,4-bib).The structures of coordination polymers 1 and 2 were characterized by infrared spectroscopy,single-crystal X-ray diffraction,thermogravimetric analysis,and powder X-ray diffraction.Single-crystal X-ray diffraction reveals that 1 has a 1D chain structure based on binuclear Mn(Ⅱ)units,while 2 features a(3,8)-connected 3D network structure based on tetranuclear Mn(Ⅱ)units.Magnetic studies show that 1 and 2exhibit antiferromagnetic interactions between manganese ions.2 shows stronger antiferromagnetic interactions due to the shorter Mn…Mn distances within the tetranuclear manganese units.CCDC:2357601,1;2357602,2.展开更多
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
基金funded by the National Key Research and Development Program of China(2024YFE0106800)Natural Science Foundation of Shandong Province(ZR2021ME199).
文摘The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of energy systems.To enhance the consumption capacity of green power,the green power system consumption optimization scheduling model(GPS-COSM)is proposed,which comprehensively integrates green power system,electric boiler,combined heat and power unit,thermal energy storage,and electrical energy storage.The optimization objectives are to minimize operating cost,minimize carbon emission,and maximize the consumption of wind and solar curtailment.The multi-objective particle swarm optimization algorithm is employed to solve the model,and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set,thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency,environmental friendliness,and energy utilization efficiency.Three typical operating modes are designed for comparative analysis.The results demonstrate that the mode involving the coordinated operation of electric boiler,thermal energy storage,and electrical energy storage performs the best in terms of economic efficiency,environmental friendliness,and renewable energy utilization efficiency,achieving the wind and solar curtailment consumption rate of 99.58%.The application of electric boiler significantly enhances the direct accommodation capacity of the green power system.Thermal energy storage optimizes intertemporal regulation,while electrical energy storage strengthens the system’s dynamic regulation capability.The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.
基金Supported by National Natural Science Foundation of China(Grant Nos.U22A20246,52372382)Hefei Municipal Natural Science Foundation(Grant No.2022008)+1 种基金the Open Fund of State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures(Grant No.KF2023-06)S&T Program of Hebei(Grant No.225676162GH).
文摘In the parallel steering coordination control strategy for path tracking,it is difficult to match the current driver steering model using the fixed parameters with the actual driver,and the designed steering coordination control strategy under a single objective and simple conditions is difficult to adapt to the multi-dimensional state variables’input.In this paper,we propose a deep reinforcement learning algorithm-based multi-objective parallel human-machine steering coordination strategy for path tracking considering driver misoperation and external disturbance.Firstly,the driver steering mathematical model is constructed based on the driver preview characteristics and steering delay response,and the driver characteristic parameters are fitted after collecting the actual driver driving data.Secondly,considering that the vehicle is susceptible to the influence of external disturbances during the driving process,the Tube MPC(Tube Model Predictive Control)based path tracking steering controller is designed based on the vehicle system dynamics error model.After verifying that the driver steering model meets the driver steering operation characteristics,DQN(Deep Q-network),DDPG(Deep Deterministic Policy Gradient)and TD3(Twin Delayed Deep Deterministic Policy Gradient)deep reinforcement learning algorithms are utilized to design a multi-objective parallel steering coordination strategy which satisfies the multi-dimensional state variables’input of the vehicle.Finally,the tracking accuracy,lateral safety,human-machine conflict and driver steering load evaluation index are designed in different driver operation states and different road environments,and the performance of the parallel steering coordination control strategies with different deep reinforcement learning algorithms and fuzzy algorithms are compared by simulations and hardware in the loop experiments.The results show that the parallel steering collaborative strategy based on a deep reinforcement learning algorithm can more effectively assist the driver in tracking the target path under lateral wind interference and driver misoperation,and the TD3-based coordination control strategy has better overall performance.
基金supported by the National Natural Science Foundation of China(Project No.5217232152102391)+2 种基金Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.
基金This work was supported in part by the State Grid Corporation of China(Grant No.52150016000Y)in part by the State Key Laboratory of Power Grid Safety and Energy Conservation(China Electric Power Research Institute)Open Fund,the Major Projects of Technical Innovation in Hubei(Grant No.2018AAA050)the Major Projects of Technical Innovation in Hubei(Grant No.2019AAA016).
文摘In this paper,distributed power flow controller(DPFC)constraints are analyzed.The energy balance relationship between fundamental wave and third harmonic in series and shunt-side converter is deduced.A proportional integral(PI)controller of the DPFC is constructed.The PI controller uses the voltage amplitude and phase angle injected into the system in the series side,along with the modulation ratio of the three-phase converter on the shunt side as the control variables.A multiobjective coordinated control equation is proposed,which factors the constraints of the energy balance between series and shunt side,device capacity limit,safe operation limit,fundamental component,as well as third harmonic component of the injection voltage at the series side.The equation minimizes the variance between the actual value of the control target and its given value to ensure that the DC capacitor voltage,both in the series and shunt side,is stable at target value.Simulations are conducted to verify correctness and effectiveness of the proposed control method.
基金supported by a Horizontal Project on the Development of a Hybrid Energy Storage Simulation Model for Wind Power Based on an RT-LAB Simulation System(PH2023000190)the Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.
文摘A novel coordination polymer(CP){[Cd_(2)(L)(1,4-bimb)_(1.5)(DMF)_(2)]·DMF}n(1)(H_(4)L=5,5'-[1,1'-biphenyl-4,4'-diylbis(oxy)]diisophthalic acid,1,4-bimb=1,4-bis(imidazole-1-ylmethyl)-benzene)has been designed and synthesized through solvothermal reaction.Structural analysis shows that Cd(Ⅱ)is connected by H4L and 1,4-bimb to form a 2D network,and 1,4-bimb further expands the 2D network into a 3D framework.CP 1 can be used as an excellent fluorescence sensor for Fe^(3+)and 4-nitrophenol(4-NP),with low detection limits and good anti-interference.The detection limits of Fe^(3+)and 4-NP were 0.034 and 0.031μmol·L^(-1),respectively.In addition,the fluorescence quenching mechanism was studied.1 was successfully applied to determine Fe^(3+)and 4-NP content in the Yanhe River water sample.CCDC:2351092.
基金supported by National Natural Science Foundations of China(nos.12271326,62102304,61806120,61502290,61672334,61673251)China Postdoctoral Science Foundation(no.2015M582606)+2 种基金Industrial Research Project of Science and Technology in Shaanxi Province(nos.2015GY016,2017JQ6063)Fundamental Research Fund for the Central Universities(no.GK202003071)Natural Science Basic Research Plan in Shaanxi Province of China(no.2022JM-354).
文摘The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.
基金supported by the Open Fund of Guangxi Key Laboratory of Building New Energy and Energy Conservation(Project Number:Guike Energy 17-J-21-3).
文摘With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0102)the China Scholarship Council Program(202406190114)。
文摘Studying the coupling coordination development of new energy vehicles(NEVs)and the ecological environment in China is helpful in promoting the development of NEVs in the country and is of great significance in promoting high-quality development of new energy in China.This paper constructs an evaluation index system for the development of NEVs and the ecological environment.It uses game theory combining weighting model,particle swarm optimized projection tracking evaluation model,coupling coordination degree model,and machine learning algorithms to calculate and analyze the level of coupling coordination development of NEVs and the ecological environment in China from 2010 to 2021,and identifies the driving factors.The research results show that:(i)From 2010 to 2021,the development index of NEVs in China has steadily increased from 0.085 to 0.634,while the ecological environment level index significantly rose from 0.170 to 0.884,reflecting the continuous development of China in both NEVs and the ecological environment.(ii)From 2010 to 2012,the two systems—new energy vehicle(NEV)development and the ecological environment—were in a period of imbalance and decline.From 2013 to 2016,they underwent a transition period,and from 2017 to 2021,they entered a period of coordinated development showing a trend of benign and continuous improvement.By 2021,they reached a good level of coordination.(iii)Indicators such as the number of patents granted for NEVs,water consumption per unit of GDP,and energy consumption per unit of GDP are the main driving factors affecting the coupling coordination development of NEVs and the ecological environment in China.
文摘With the boom in maritime activities,the need for highly reliable maritime communication is becoming urgent,which is an important component of 5G/6G communication networks.However,the bandwidth reuse characteristic of 5G/6G networks will inevitably lead to severe interference,resulting in degradation in the communication performance of maritime users.In this paper,we propose a safe deep reinforcement learning based interference coordination scheme to jointly optimize the power control and bandwidth allocation in maritime communication systems,and exploit the quality-of-service requirements of users as the risk value references to evaluate the communication policies.In particular,this scheme designs a deep neural network to select the communication policies through the evaluation network and update the parameters using the target network,which improves the communication performance and speeds up the convergence rate.Moreover,the Nash equilibrium of the interference coordination game and the computational complexity of the proposed scheme are analyzed.Simulation and experimental results verify the performance gain of the proposed scheme compared with benchmarks.
基金supported financially by the Promotive Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (Grant No. BS2014NJ010)the National Natural Science Foundation of China (Grant No. 21506255)
文摘A genetic algorithm based multi-objective coordinative optimization strategy is developed to optimize the operation of a binary feed atmospheric and vacuum distillation system, in which the objective functions cover the economic benefit, the furnace energy consumption and the CO_2 emissions, and meanwhile the simultaneous effect of binary feed composition is also investigated. A cross-call integration of software is developed to implement the optimization algorithm,and once the maximum economic benefit, the minimum furnace energy consumption and the minimum CO_2 emissions are obtained, the Pareto-optimal solution set is worked out, with the practical problems of the refinery being solved. The optimization result shows that under the same furnace energy consumption and the CO_2 emissions as the existing working condition, the economic benefit still allows for a considerable potential of increment by adjusting the heavy oil proportion of the binary feed crude oil.
基金sponsored by R&D Program of Beijing Municipal Education Commission(KM202410009013).
文摘In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.
文摘One Yb(Ⅲ)-based coordination polymer,{[Yb(H_(2)dhtp)1.5(H_(2)O)_(4)]·3H_(2)O}n(1)(H_(4)dhtp=2,5-dihydroxytere-phthalic acid),was fabricated and structurally characterized by single-crystal X-ray diffraction,IR,powder X-ray diffraction,X-ray diffraction,and elemental analysis.Complex 1 displays a 1D chain structure,and belongs to P1 group.The solid-state luminescent spectrum of 1 showed an emission band with the maximum at 508 nm(λex=408 nm).It exhibited the emission characteristic of the H_(4)dhtp ligand.The fluorescence of 1 in water displayed the stron-gest intensity.In detecting various metal ions,adding Zr^(4+)led to a blue shift in fluorescence,accompanied by an increase in intensity,whereas the presence of Fe^(3+)resulted in a decrease in luminescence.The changes observed in the IR spectrum indicate an interaction between Fe^(3+)/Zr^(4+)and complex 1,resulting in the variation of luminescence properties.
文摘Under the condition of solvothermal synthesis,the viologen ligand 1,1′-bis(3-carboxyphenyl)-(4,4′-bipyri-dine)dichloride(H_(2)bcbpy·2Cl)and KI are coordinated with the metal cadmium ions.A case of thermochromic coor-dination polymer[Cd(bcbpy)I_(2)]·2H_(2)O(1)was constructed.Complex 1 displays a 1D chain structure and exhibits thermochromic behavior.Under different temperature stimulation,the complex(ground)slowly changed from green to yellow-green,and with the increase of temperature,the color of complex 1 gradually deepened,and finally became orange-yellow.Therefore,complex 1 was prepared as a thermochromic film.In addition,we also performed electrochemical tests on complex 1,which showed that the complex is a semiconductor material.CCDC:2391802.
文摘We report five coordination polymers(CPs)based on fluorescent ligands[1,6-di(1H-imidazol-1-yl)pyrene(dip),9,10-di(1H-imidazol-1-yl)anthracene(dia)]and anionic ligands[cyclohexane-1,4-dicarboxylic acid(H_(2)cda),camphoric acid(H_(2)cpa)].In[Cd(dip)(cda)]·4H_(2)O}_(n)(1),the Cd^(2+)ions,acting as tetrahedral nodes,are linked by dipand cda^(2-)ligands with four Cd^(2+)ions into five-fold interpenetrating network array of topology of dia.In{[Cd(dip)(cpa)]·4H_(2)O}_(n)(2),the Cd^(2+)ions,acting as a 4-connector,are linked by cpa^(2-)and dip ligands into a 3D framework ofcds topology.In{[Ni(dia)_(2)Cl_(2)]·DMF}_(n)(3),the Ni^(2+)ion is linked by four dia ligands into a layer structure,and 1Dchannels of a cross-section of 1.35 nm×0.96 nm are formed.In{[Cd(dia)_(2)(H_(2)O)_(2)](NO_(3))_(2)·2DMSO}n(4),the dia ligandsconnected Cd^(2+)ions into a 2D layer,and 1D channels are formed between adjacent layers with a cross-section of0.87 nm×0.43 nm.In[Zn(dip)Cl_(2)]_(n)(5),the Zn^(2+)ion is linked by dip ligands into an infinite 1D chain.The infrared,thermal gravimetric,and fluorescent emission data were collected and analyzed for these coordination polymers.CCDC:2356055,1;2440075,2;2356057,3;2356057,4;2356059,5.
基金Project(2002CB312203) supported by the National Key Fundamental Research and Development Programof China pro-ject(60574030) supported bythe National Natural Science Foundation of China project(06FD026) supported bythe Natural Science Foun-dation of Hunan Province , China
文摘A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.
基金National Natural Science Foundation of China,Grant/Award Number:U2243228The Belt and Road Special Foundation of the National Key Laboratory of Water Disaster Prevention,Grant/Award Number:2022nkms04+1 种基金MOE(Ministry of Education in China)Liberal Arts and Social Sciences Foundation,Grant/Award Number:23YJCZH332Natural Science Foundation of Anhui Province,Grant/Award Numbers:2208085US03,2308085US13。
文摘Exploring optimal operational schemes for synergistic development is crucial for sustainable management in river basins.This study introduces a multi-objective synergistic optimization framework aimed at analyzing the interplay among flood control,ecological integrity,and desilting objectives under varying watersediment conditions.The framework encompasses multi-objective reservoir optimal operation,scheme decision,and trade-off analysis among competing objectives.To address the optimization model,an elite mutation-based multiobjective particle swarm optimization(MOPSO)algorithm that integrates genetic algorithms(GA)is developed.The coupling coordination degree is employed for optimal scheme decision-making,allowing for the adjustment of weight ratios to investigate the trade-offs between objectives.This research focuses on the Sanmenxia and Xiaolangdi cascade reservoirs in the Yellow River,utilizing three representative hydrological years:1967,1969,and 2002.The findings reveal that:(1)the proposed model effectively generates Pareto fronts for multi-objective operations,facilitating the recommendation of optimal schemes based on coupling coordination degrees;(2)as water-sediment conditions shift from flooding to drought,competition intensifies between the flood control and desilting objectives.While flood control and ecological objectives compete during flood and dry years,they demonstrate synergies in normal years(r=0.22);conversely,ecological and desilting objectives are consistently competitive across all three typical years,with the strongest competition observed in the normal year(r=-0.95);(3)the advantages conferred to ecological objectives increase as water-sediment conditions shift from flooding to drought.However,the promotion of the desilting objective requires more complex trade-offs.This study provides a model and methodological approach for the multi-objective optimization of flood control,sediment management,and ecological considerations in reservoir clusters.Moreover,the methodologies presented herein can be extended to other water resource systems for multi-objective optimization and decision-making.
文摘Six coordination polymers based on 9,10-di(pyridine-4-yl)-anthracene(DPA)and 1,6-di(1H-imidazol-1-yl)pyrene(DIP)were obtained by solvothermal reactions.{[Zn(DPA)Cl_(2)]·DMF·2H_(2)O}n(1)and{[Zn_(1.5)(DPA)_(1.5)Cl_(3)]·5H_(2)O}n(2)are framework isomers,which both contain zigzag chains formed by DPA,Zn^(2+),and Cl-.The zigzag chains in 1 are further assembled by C—H…Cl interactions into layers,and these layers exhibit two different orientations,displaying a rare 2D to 3D interpenetration mode.The zigzag chains in 2 are parallelly arranged.{[Zn_(3)(DPA)_(3)Br_(6)]·2DMF·_(1.5)H_(2)O}n(3)is isostructural to 2.3 was obtained using ZnBr_(2)instead of ZnCl_(2).[M(DPA)(formate)_(2)(H_(2)O)_(2)]n[M=Co(4),Cu(5)]are isostructural,contain chain structures formed by DPA,Cu^(2+)/Co^(2+),and for-mate ions,which were formed in situ in the solvothermal reaction.{[Zn(DIP)_(2)Cl]ClO_(4)}n(6)contains a layer structure formed by DIP and Zn^(2+).Free DPA and DIP ligands exhibited high fluorescence at room temperature,and coordina-tion polymers 3 and 6 displayed enhanced fluorescent emissions.
文摘Two new Mn(Ⅱ)coordination polymers,namely{[Mn_(2)(HL)(phen)_(3)(H_(2)O)_(2)]·7.5H_(2)O}_n(1)and[Mn_(4)(HL)_(2)(1,4-bib)_(3)(H_(2)O)_(2)]_n(2),were synthesized under hydrothermal conditions by using Mn(Ⅱ)ions and 6-(3',4'-dicarboxylphenoxy)-1,2,4-benzenetricarboxylic acid(H_(5)L)in the presence of N-auxiliary ligands 1,10-phenanthroline(phen)and1,4-bis(1H-imidazol-1-yl)benzene(1,4-bib).The structures of coordination polymers 1 and 2 were characterized by infrared spectroscopy,single-crystal X-ray diffraction,thermogravimetric analysis,and powder X-ray diffraction.Single-crystal X-ray diffraction reveals that 1 has a 1D chain structure based on binuclear Mn(Ⅱ)units,while 2 features a(3,8)-connected 3D network structure based on tetranuclear Mn(Ⅱ)units.Magnetic studies show that 1 and 2exhibit antiferromagnetic interactions between manganese ions.2 shows stronger antiferromagnetic interactions due to the shorter Mn…Mn distances within the tetranuclear manganese units.CCDC:2357601,1;2357602,2.
