Prigiobbe Valentina, Ko Saebom, Huh Chun, Bryant Steven L
Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, 200 E. Dean Keeton St., C0300, Austin, 78712 TX, USA.
Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, 200 E. Dean Keeton St., C0300, Austin, 78712 TX, USA.
J Colloid Interface Sci. 2015 Jun 1;447:58-67. doi: 10.1016/j.jcis.2015.01.056. Epub 2015 Jan 29.
In this paper, we present settling experiments and mathematical modeling to study the magnetic separation of superparamagnetic iron-oxide nanoparticles (SPIONs) from a brine. The experiments were performed using SPIONs suspensions of concentration between 3 and 202g/L dispersed in water and separated from the liquid under the effect of a permanent magnet. A 1D model was developed in the framework of the sedimentation theory with a conservation law for SPIONs and a mass flux function based on the Newton's law for motion in a magnetic field. The model describes both the hindering effect of suspension concentration (n) during settling due to particle collisions and the increase in settling rate due to the attraction of the SPIONs towards the magnet. The flux function was derived from the settling experiments and the numerical model validated against the analytical solution and the experimental data. Suspensions of SPIONs were of 2.8cm initial height, placed on a magnet, and monitored continuously with a digital camera. Applying a magnetic field of 0.5T of polarization, the SPION's velocity was of approximately 3·10(-5)m/s close to the magnet and decreases of two orders of magnitude across the domain. The process was characterized initially by a classical sedimentation behavior, i.e., an upper interface between the clear water and the suspension slowly moving towards the magnet and a lower interface between the sediment layer and the suspension moving away from the magnet. Subsequently, a rapid separation of nanoparticle occured suggesting a non-classical settling phenomenon induced by magnetic forces which favor particle aggregation and therefore faster settling. The rate of settling decreased with n and an optimal condition for fast separation was found for an initial n of 120g/L. The model agrees well with the measurements in the early stage of the settling, but it fails to describe the upper interface movement during the later stage, probably because of particle aggregation induced by magnetization which is not accounted for in the model.
在本文中，我们展示了沉降实验和数学建模，以研究从盐水中磁分离超顺磁性氧化铁纳米颗粒（SPIONs）的过程。实验使用浓度在3至202g/L之间的SPIONs悬浮液，这些悬浮液分散在水中，并在永久磁铁的作用下与液体分离。在沉降理论框架内开发了一个一维模型，该模型包含SPIONs的守恒定律以及基于牛顿磁场运动定律的质量通量函数。该模型描述了沉降过程中由于颗粒碰撞导致的悬浮液浓度（n）的阻碍作用，以及由于SPIONs对磁铁的吸引力导致的沉降速率增加。通量函数由沉降实验得出，数值模型通过解析解和实验数据进行了验证。SPIONs悬浮液初始高度为2.8cm，放置在磁铁上，并用数码相机连续监测。施加0.5T极化磁场时，靠近磁铁处SPIONs的速度约为3·10(-5)m/s，且在整个区域内下降了两个数量级。该过程最初的特征是典型的沉降行为，即清水与悬浮液之间的上界面缓慢向磁铁移动，沉积物层与悬浮液之间的下界面远离磁铁移动。随后，纳米颗粒迅速分离，这表明磁力诱导了一种非经典的沉降现象，这种现象有利于颗粒聚集，从而沉降更快。沉降速率随n降低，发现初始n为120g/L时存在快速分离的最佳条件。该模型在沉降早期与测量结果吻合良好，但在后期无法描述上界面的移动，可能是因为模型中未考虑磁化引起的颗粒聚集。
