Exploration of magnetic characteristics in perovskite LaCoO3 by particle swarm optimization combined with Monte Carlo method

被引：21

作者：

Li, Bo-chen ^{[1
]}

Lv, Dan ^{[2
]}

Wang, Wei ^{[1
]}

Li, Hui-yi ^{[2
]}

机构：

[1] Shenyang Univ Technol, Sch Sci, Shenyang 110870, Peoples R China

[2] Shenyang Univ Technol, Sch Environm & Chem Engn, Shenyang 110870, Peoples R China

来源：

PHYSICS LETTERS A | 2023年 / 464卷

关键词：

Perovskite LaCoO 3; Particle swarm optimization; Monte Carlo method; Ising model; Magnetization; Hysteresis loop; EXCHANGE COUPLINGS CALCULATION; PHASE-DIAGRAMS; TEMPERATURE; TRANSITION; TRANSPORT;

D O I：

10.1016/j.physleta.2023.128697

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

In this paper, the new method combined with Monte Carlo simulation and particle swarm optimization is presented to explore the magnetic characteristics of perovskite LaCoO3 described by Ising model. We use the particle swarm optimization to obtain the appropriate physical parameters, such as Jab, Jaa and further adopt the Monte Carlo simulation to calculate the magnetization M, the magnetic susceptibility chi, the entropy S, the internal energy U of system under the influence of the anisotropy D and magnetic field h. The phase diagrams and the hysteresis loops are given. These results are also compared with the relevant theoretical and experimental results.(c) 2023 Elsevier B.V. All rights reserved.

引用

页数：10

共 50 条

[41] Particle Swarm Optimization Method Combined with off Policy Reinforcement Learning Algorithm for the Discovery of High Utility Itemset [J].

Logeswaran, K. ;

Suresh, P. ;

Anandamurugan, S. .

INFORMATION TECHNOLOGY AND CONTROL, 2023, 52 (01) :25-36

[42] Accuracy index selection during optimization of particle accelerator ring tunnel network design based on Monte Carlo method [J].

Wu, Enchen ;

Zhang, Qiuyu ;

Wang, Xiaolong ;

Lin, Yiliang ;

Li, Xiao ;

Wang, Wei ;

He, Xiaoye .

MEASUREMENT SCIENCE AND TECHNOLOGY, 2025, 36 (05)

[43] Study on radiation transfer characteristics and thermal properties in a concentrated solar solid particle receiver based on Monte Carlo method [J].

Deng, Suxiang ;

Tang, Zhong ;

Li, Zhenzhong ;

Tao, Xiangyu ;

Yang, Chen .

ENERGY, 2025, 322

[44] Magnetic properties and large magnetocaloric effect in the perovskite Mn3GeC compound: Ab initio and Monte Carlo calculations [J].

Alaoui, Y. Charif ;

Tahiri, N. ;

El Bounagui, O. ;

Ez-Zahraouy, H. .

PHASE TRANSITIONS, 2022, 95 (01) :10-18

[45] Design of low-frequency broadband flextensional transducers based on combined particle swarm optimization and finite element method [J].

Zheng, Jia ;

Li, Shiyang ;

Wang, Bin .

SMART MATERIALS AND STRUCTURES, 2021, 30 (10)

[46] Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions [J].

Sundareswaran, K. ;

Kumar, V. Vignesh ;

Palani, S. .

RENEWABLE ENERGY, 2015, 75 :308-317

[47] 3D Aided Art Design Method Based on Improved Particle Swarm Optimization Algorithm [J].

Sun J. ;

Chen X. .

Computer-Aided Design and Applications, 2024, 21 (S3) :1-16

[48] Two-step calibration method for three-axis magnetic sensor error based on particle swarm optimization [J].

Liu, Yanxia ;

Hu, Zhikai ;

Fang, JianJun .

SENSOR REVIEW, 2020, 40 (05) :577-583

[49] A Novel Hybrid Method of Parameters Tuning in Support Vector Regression for Reliability Prediction: Particle Swarm Optimization Combined With Analytical Selection [J].

Zhao, Wei ;

Tao, Tao ;

Zio, Enrico ;

Wang, Wenbin .

IEEE TRANSACTIONS ON RELIABILITY, 2016, 65 (03) :1393-1405

[50] Parametric Study of Cavity IEMP Responses in a Cylinder by Coupling Monte Carlo Method and 3-D Electromagnetic Particle-in-Cell Method [J].

Meng, Xuesong ;

Li, Guangrong ;

Zhang, Lingyu ;

Zhao, Zhenguo ;

Liu, Jizhe .

IEEE TRANSACTIONS ON PLASMA SCIENCE, 2023, 51 (07) :1869-1879

← 1 2 3 4 5 →