While three-dimensional perovskites have high defect tolerance and an adjustable bandgap,their charges tend to be free rather than forming excitons,making them unsuitable for use in efficient light-emitting diodes(LED...While three-dimensional perovskites have high defect tolerance and an adjustable bandgap,their charges tend to be free rather than forming excitons,making them unsuitable for use in efficient light-emitting diodes(LEDs).Rather,quasi-two-dimensional(Q-2D)perovskites offer high photoluminescence quantum yield along with the advantages of bulk perovskites,making them ideal for high-performance LEDs.In Q-2D perovskites,the structure(which includes factors like crystal orientation,phase distribution,and layer thickness)directly influences how excitons and charge carriers behave within the material.Growth control techniques,such as varying the synthesis conditions or employing methods,allow for fine-tuning the structural characteristics of these materials,which in turn affect exciton dynamics and charge transport.This review starts with a description of the basic properties of Q-2D perovskites,examines crystal growth in solution,explains how structure affects energy transfer behavior,and concludes with future directions for Q-2D perovskite LEDs.By understanding and optimizing the structure-dependent behavior,researchers can better control exciton dynamics and charge transport,which are crucial for enhancing the performance of optoelectronic devices like solar cells and LEDs.展开更多
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is ...Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is proposed for rotationally symmetric multi-scale problems in anisotropic magnetized plasma.Within the CNDG algorithm,an alternative scheme for the simulation of anisotropic plasma is proposed in body-of-revolution domains.Convolutional perfectly matched layer(CPML)formulation is proposed to efficiently solve the open region problems.Numerical example is carried out for the illustration of effectiveness including the efficiency,resources,and absorption.Through the results,it can be concluded that the proposed scheme shows considerable performance during the simulation.展开更多
文摘While three-dimensional perovskites have high defect tolerance and an adjustable bandgap,their charges tend to be free rather than forming excitons,making them unsuitable for use in efficient light-emitting diodes(LEDs).Rather,quasi-two-dimensional(Q-2D)perovskites offer high photoluminescence quantum yield along with the advantages of bulk perovskites,making them ideal for high-performance LEDs.In Q-2D perovskites,the structure(which includes factors like crystal orientation,phase distribution,and layer thickness)directly influences how excitons and charge carriers behave within the material.Growth control techniques,such as varying the synthesis conditions or employing methods,allow for fine-tuning the structural characteristics of these materials,which in turn affect exciton dynamics and charge transport.This review starts with a description of the basic properties of Q-2D perovskites,examines crystal growth in solution,explains how structure affects energy transfer behavior,and concludes with future directions for Q-2D perovskite LEDs.By understanding and optimizing the structure-dependent behavior,researchers can better control exciton dynamics and charge transport,which are crucial for enhancing the performance of optoelectronic devices like solar cells and LEDs.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
文摘Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is proposed for rotationally symmetric multi-scale problems in anisotropic magnetized plasma.Within the CNDG algorithm,an alternative scheme for the simulation of anisotropic plasma is proposed in body-of-revolution domains.Convolutional perfectly matched layer(CPML)formulation is proposed to efficiently solve the open region problems.Numerical example is carried out for the illustration of effectiveness including the efficiency,resources,and absorption.Through the results,it can be concluded that the proposed scheme shows considerable performance during the simulation.
