Complex optimization problems hold broad significance across numerous fields and applications.However,as the dimensionality of such problems increases,issues like the curse of dimensionality and local optima trapping ...Complex optimization problems hold broad significance across numerous fields and applications.However,as the dimensionality of such problems increases,issues like the curse of dimensionality and local optima trapping also arise.To address these challenges,this paper proposes a novel Wild Gibbon Optimization Algorithm(WGOA)based on an analysis of wild gibbon population behavior.WGOAcomprises two strategies:community search and community competition.The community search strategy facilitates information exchange between two gibbon families,generating multiple candidate solutions to enhance algorithm diversity.Meanwhile,the community competition strategy reselects leaders for the population after each iteration,thus enhancing algorithm precision.To assess the algorithm’s performance,CEC2017 and CEC2022 are chosen as test functions.In the CEC2017 test suite,WGOA secures first place in 10 functions.In the CEC2022 benchmark functions,WGOA obtained the first rank in 5 functions.The ultimate experimental findings demonstrate that theWildGibbonOptimization Algorithm outperforms others in tested functions.This underscores the strong robustness and stability of the gibbonalgorithm in tackling complex single-objective optimization problems.展开更多
Tetradymite-structured chalcogenides,such as Bi_(2)Te_(3) and Sb_(2)Te_(3),are quasi-two-dimensional(2D)layered compounds,which are significant thermoelectric materials applied near room temperature.The intercalation ...Tetradymite-structured chalcogenides,such as Bi_(2)Te_(3) and Sb_(2)Te_(3),are quasi-two-dimensional(2D)layered compounds,which are significant thermoelectric materials applied near room temperature.The intercalation of guest species in van der Waals(vdW)gap implemented for tunning properties has attracted much attention in recent years.We attempt to insert Ga atoms in the vdW gap between the Te layers in p-type Bi_(0.3)Sb_(1.7)Te_(3)(BST)for further improving thermoelectrics.The vdW-related defects(including extrinsic interstitial and intrinsic defects)induced by Ga intercalation can not only modulate the carrier concentration but also enhance the texture,thereby yielding excellent electrical properties,which are reflected in the power factor PF~4.43 mW·m^(-1)·K^(-2).Furthermore,the intercalation of Ga produces multi-scale lattice imperfections such as point defects,Te precipitations,and nanopores,realizing the low lattice thermal conductivity in BST-Ga samples.Ultimately,a peak zT~1.1 at 373 K is achieved in the BST-1%Ga sample and greatly improved by~22%compared to the pristine BST.The weak bonding of vdW interlayer interaction can boost the synergistic effect for advancing BST-based or other layered thermoelectrics.展开更多
基金funded by Natural Science Foundation of Hubei Province Grant Numbers 2023AFB003,2023AFB004Education Department Scientific Research Program Project of Hubei Province of China Grant Number Q20222208+2 种基金Natural Science Foundation of Hubei Province of China(No.2022CFB076)Artificial Intelligence Innovation Project of Wuhan Science and Technology Bureau(No.2023010402040016)JSPS KAKENHI Grant Number JP22K12185.
文摘Complex optimization problems hold broad significance across numerous fields and applications.However,as the dimensionality of such problems increases,issues like the curse of dimensionality and local optima trapping also arise.To address these challenges,this paper proposes a novel Wild Gibbon Optimization Algorithm(WGOA)based on an analysis of wild gibbon population behavior.WGOAcomprises two strategies:community search and community competition.The community search strategy facilitates information exchange between two gibbon families,generating multiple candidate solutions to enhance algorithm diversity.Meanwhile,the community competition strategy reselects leaders for the population after each iteration,thus enhancing algorithm precision.To assess the algorithm’s performance,CEC2017 and CEC2022 are chosen as test functions.In the CEC2017 test suite,WGOA secures first place in 10 functions.In the CEC2022 benchmark functions,WGOA obtained the first rank in 5 functions.The ultimate experimental findings demonstrate that theWildGibbonOptimization Algorithm outperforms others in tested functions.This underscores the strong robustness and stability of the gibbonalgorithm in tackling complex single-objective optimization problems.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFB3803900 and 2018YFA0702100)the Joint Funds of the National Natural Science Foundation of China and the Chinese Academy of Sciences’Large-Scale Scientific Facility(Grant No.U1932106)the Sichuan University Innovation Research Program of China(Grant No.2020SCUNL112)。
文摘Tetradymite-structured chalcogenides,such as Bi_(2)Te_(3) and Sb_(2)Te_(3),are quasi-two-dimensional(2D)layered compounds,which are significant thermoelectric materials applied near room temperature.The intercalation of guest species in van der Waals(vdW)gap implemented for tunning properties has attracted much attention in recent years.We attempt to insert Ga atoms in the vdW gap between the Te layers in p-type Bi_(0.3)Sb_(1.7)Te_(3)(BST)for further improving thermoelectrics.The vdW-related defects(including extrinsic interstitial and intrinsic defects)induced by Ga intercalation can not only modulate the carrier concentration but also enhance the texture,thereby yielding excellent electrical properties,which are reflected in the power factor PF~4.43 mW·m^(-1)·K^(-2).Furthermore,the intercalation of Ga produces multi-scale lattice imperfections such as point defects,Te precipitations,and nanopores,realizing the low lattice thermal conductivity in BST-Ga samples.Ultimately,a peak zT~1.1 at 373 K is achieved in the BST-1%Ga sample and greatly improved by~22%compared to the pristine BST.The weak bonding of vdW interlayer interaction can boost the synergistic effect for advancing BST-based or other layered thermoelectrics.
基金supported by the National Key Research and Development Program of China (2022YFB3803900 and 2018YFA0702100)Sichuan University Innovation Research Program of China (2020SCUNL112)。
