Abstract We perform computer simulations to study the relaxation in a one-dimensional chain of dipolar interacting magnetic nanoparticles (MNPs). Using the two-level approximation of the energy barrier, we perform kinetic Monte Carlo simulations to probe the relaxation mechanism as a function of dipolar interaction strength and temperature. The anisotropy axes of the MNPs are assumed to have random orientations. At high temperatures, the magnetization decay curve is exponential for weak dipolar interactions. It is found that dipolar interactions slow down the magnetic relaxation and increase the effective Neel relaxation time τ N , which is affected by thermal fluctuations. In the weak dipolar limit, there is a perfect agreement between simulated and analytically evaluated values of τ N for a wide range of temperatures. Microscopic analyses such as magnetic moments correlations and dynamic domain formation also suggest an increase in ferromagnetic coupling with an increase in dipolar interaction strength or decrease in thermal fluctuations. We believe that the concepts presented in this work are relevant in the context of applications such as data storage, digital data processing, and magnetic hyperthermia, in which the linear chain of MNPs are pervasive.

中文翻译：

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热和偶极相互作用对磁性纳米粒子线性链中弛豫的影响

摘要 我们通过计算机模拟来研究偶极相互作用磁性纳米粒子 (MNP) 的一维链中的弛豫。使用能垒的两级近似，我们执行动力学蒙特卡罗模拟来探测作为偶极相互作用强度和温度函数的弛豫机制。假设 MNP 的各向异性轴具有随机方向。在高温下，磁化衰减曲线对于弱偶极相互作用呈指数。发现偶极相互作用减慢了磁弛豫并增加了受热波动影响的有效尼尔弛豫时间τ N 。在弱偶极极限下，在很宽的温度范围内，τ N 的模拟值和分析评估值之间存在完美的一致性。磁矩相关性和动态畴形成等微观分析也表明，铁磁耦合会随着偶极相互作用强度的增加或热波动的减少而增加。我们认为，这项工作中提出的概念与数据存储、数字数据处理和磁热疗等应用相关，其中 MNP 的线性链普遍存在。