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Dipolar interaction and demagnetizing effects in magnetic nanoparticle dispersions: Introducing the mean-field interacting superparamagnet model

机译:磁性纳米粒子分散体中的偶极相互作用和去磁作用:介绍平均场相互作用的超分析模型

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摘要

Aiming to analyze relevant aspects of interacting magnetic nanoparticle systems (frequently called interactingsuperparamagnets), a model is built from magnetic dipolar interaction and demagnetizing mean-field concepts.By making reasonable simplifying approximations, a simple and useful expression for effective demagnetizingfactors is achieved, which allows the analysis of uniform and nonuniform spatial distributions of nanoparticles,in particular the occurrence of clustering. This expression is a function of demagnetizing factors associatedwith specimen shape and clusters shape, and of the mean distances between near neighbor nanoparticles andbetween clusters, relative to the characteristic sizes of each of these two types of objects, respectively. Themodel explains effects of magnetic dipolar interactions, such as the observation of apparent nanoparticlemagnetic moments smaller than real ones and approaching to zero as temperature decreases. It is shownthat by performing a minimum set of experimental determinations along principal directions of geometricallywell-defined specimens, model application allows retrieval of nanoparticle intrinsic properties, likemean volume,magnetic moment, and susceptibility in the absence of interactions. It also permits the estimation of meaninterparticle and intercluster relative distances, as well as mean values of demagnetizing factors associated withclusters shape. An expression for average magnetic dipolar energy per nanoparticle is also derived, which isa function of specimen effective demagnetizing factor and magnetization. Experimental test of the model wasperformed by analysis of results reported in the literature and of original results reported here. The first casecorresponds to oleic-acid-coated 8-nm magnetite particles dispersed in PEGDA-600 polymer, and the secondone to polyacrilic-acid-coated 13-nm magnetite particles dispersed in PVA solutions from which ferrogels werelater produced by a physical cross-linking route. In both cases, several specimens were studied covering arange of nanoparticle volume fractions between 0.002 and 0.046. Magnetic response is clearly different whenprism-shaped specimens are measured along different principal directions. These results remark the importanceof reporting complete information on measurement geometry when communicating magnetic measurementresults of interacting magnetic nanoparticles. Intrinsic nanoparticle properties as well as structural informationon particles spatial distribution were retrieved from our analysis in addition to, and in excellent agreement with,analysis previously performed by other authors and/or information obtained from FESEM images. In the studiedsamples, nanoparticles were found to be in close contact to each other within almost randomly oriented clusters.Intercluster mean distance, relative to cluster size, was found to vary between 2.2 and 7.5, depending on particlesvolume fraction.
机译:旨在分析相互作用磁性纳米粒子系统的相关方面(经常被称为相互作用SuperParamagnets),一种模型是由磁性偶极交互构建和退磁平均场概念。通过合理简化近似,有效退磁的简单且有用的表达实现了因素,允许分析纳米颗粒的均匀和不均匀的空间分布,特别是群集的发生。该表达是消除相关因素的函数具有标本形状和簇形状,以及邻近邻近纳米颗粒之间的平均距离和在簇之间,相对于这两种类型的每个物体中的每一个的特征尺寸。这模型解释了磁性偶极相互作用的影响,例如表观纳米粒子的观察磁矩小于真实的矩,随着温度降低而接近零。它显示出来这通过沿着几何上的主要方向进行最小一组实验测定定义明确的标本,模型应用允许检索纳米粒子内在属性,素质体积,磁矩和易受相互作用的易感性。它还允许估计平均值颗粒体和聚集簇相对距离,以及与之相关的退磁因子的平均值簇形。也导出了每纳米粒子的平均磁性偶极能的表达,即试样有效退磁因子和磁化的功能。模型的实验测试是通过分析文献中报告的结果和此处报告的原始结果进行。第一个案例对应于分散在PEGDA-600聚合物中的油酸涂覆的8-NM磁铁矿颗粒,第二个一个到聚乙酸涂覆的13-nm磁铁矿颗粒,分散在PVA溶液中,其中甲基葡萄酒溶液后来由物理交联路线生产。在这两种情况下,研究了几种标本覆盖a纳米粒子体积级分的范围为0.002和0.046。磁响应显然是不同的棱镜形标本沿不同的主路线测量。这些结果评论了重要性报告磁测量时测量几何形状的完整信息相互作用磁性纳米颗粒的结果。固有纳米颗粒特性以及结构信息在粒子上,除了我们的分析以及与良好协议之外,我们的分析检索了空间分布,以前由其他作者和/或从FESEM图像获得的信息进行的分析。在研究中发现样品,纳米颗粒在几乎随机取向的簇内彼此紧密接触。聚集簇平均距离,相对于簇大小,发现在2.2和7.5之间,取决于粒子体积分数。

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  • 来源
    《Physical Review. B, Condensed Matter》 |2017年第14期|134421.1-134421.18|共18页
  • 作者单位

    IFLP-CCT-La Plata-CONICET and Departamento de Fisica Facultad de Ciencias Exactas C.C. 67 Universidad Nacional de La Plata 1900 La Plata Argentina;

    IFLP-CCT-La Plata-CONICET and Departamento de Fisica Facultad de Ciencias Exactas C.C. 67 Universidad Nacional de La Plata 1900 La Plata Argentina Departamento de Ciencias Basicas Facultad de Ingenieria Universidad Nacional de La Plata 1900 La Plata Argentina;

    IFLP-CCT-La Plata-CONICET and Departamento de Fisica Facultad de Ciencias Exactas C.C. 67 Universidad Nacional de La Plata 1900 La Plata Argentina;

    IFLP-CCT-La Plata-CONICET and Departamento de Fisica Facultad de Ciencias Exactas C.C. 67 Universidad Nacional de La Plata 1900 La Plata Argentina Departamento de Ciencias Basicas Facultad de Ingenieria Universidad Nacional de La Plata 1900 La Plata Argentina;

    IFLP-CCT-La Plata-CONICET and Departamento de Fisica Facultad de Ciencias Exactas C.C. 67 Universidad Nacional de La Plata 1900 La Plata Argentina;

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