Osaci Mihaela, Cacciola Matteo
"Politehnica" University of Timisoara, Department of Electrical Engineering and Industrial Informatics, 2 Victoriei Square, 300006 Timisoara, Timis County, Romania.
Cooperativa TEC, Via Nazionale, n. 439, 89134 Pellaro di Reggio Calabria, Italy.
Beilstein J Nanotechnol. 2020 Aug 12;11:1207-1216. doi: 10.3762/bjnano.11.105. eCollection 2020.
Colloidal systems consisting of monodomain superparamagnetic nanoparticles have been used in biomedical applications, such as the hyperthermia treatment for cancer. In this type of colloid, called a nanofluid, the nanoparticles tend to agglomeration. It has been shown experimentally that the nanoparticle coating plays an important role in the nanoparticle dispersion stability and biocompatibility. However, theoretical studies in this field are lacking. In addition, the ways in which the nanoparticle coating influences the magnetic properties of the nanoparticles are not yet understood. In order to fill in this gap, this study presents a numerical simulation model that elucidates how the nanoparticle coating affects the nanoparticle agglomeration tendency as well as the effective magnetic relaxation time of the system. To simulate the self-organization of the colloidal nanoparticles, a stochastic Langevin dynamics method was applied based on the effective Verlet-type algorithm. The Néel magnetic relaxation time was obtained via the Coffey method in an oblique magnetic field, adapted to the local magnetic field on a nanoparticle.
由单畴超顺磁性纳米颗粒组成的胶体系统已被用于生物医学应用，如癌症的热疗。在这种被称为纳米流体的胶体类型中，纳米颗粒容易发生团聚。实验表明，纳米颗粒涂层在纳米颗粒的分散稳定性和生物相容性方面起着重要作用。然而，该领域缺乏理论研究。此外，纳米颗粒涂层影响纳米颗粒磁性的方式尚未得到理解。为了填补这一空白，本研究提出了一个数值模拟模型，该模型阐明了纳米颗粒涂层如何影响纳米颗粒的团聚趋势以及系统的有效磁弛豫时间。为了模拟胶体纳米颗粒的自组织，基于有效的Verlet型算法应用了随机朗之万动力学方法。通过科菲方法在倾斜磁场中获得奈尔磁弛豫时间，并将其应用于纳米颗粒上的局部磁场。
