Analytical methods for separating and isolating magnetic nanoparticles

文献情報

出版日 2012-02-03

DOI 10.1039/C2CP22982J

インパクトファクター 3.676

著者

Jason R. Stephens, Jacob S. Beveridge, Mary Elizabeth Williams

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要旨

Despite the large body of literature describing the synthesis of magnetic nanoparticles, few analytical tools are commonly used for their purification and analysis. Due to their unique physical and chemical properties, magnetic nanoparticles are appealing candidates for biomedical applications and analytical separations. Yet in the absence of methods for assessing and assuring their purity, the ultimate use of magnetic particles and heterostructures is likely to be limited. In this review, we summarize the separation techniques that have been initially used for this purpose. For magnetic nanoparticles, it is the use of an applied magnetic flux or field gradient that enables separations. Flow based techniques are combined with applied magnetic fields to give methods such as magnetic field flow fractionation and high gradient magnetic separation. Additional techniques have been explored for manipulating particles in microfluidic channels and in mesoporous membranes. Further development of these and new analytical tools for separation and analysis of colloidal particles is critically important to enable the practical use of these, particularly for medicinal purposes.

掲載誌

Physical Chemistry Chemical Physics

CiteScore: 5.5

自己引用率: 10.3%

年間論文数: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.