Journal article
Computational study of a magnetic design to improve the diagnosis of malaria: 2D model
Journal of magnetism and magnetic materials, v 423
01 Feb 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper investigates the feasibility of a cost effective high gradient magnetic separation based device for the detection and identification of malaria parasites in a blood sample. The design utilizes magnetic properties of hemozoin present in malaria-infected red blood cells (mRBCs) in order to separate and concentrate them inside a microfluidic channel slide for easier examination under the microscope. The design consists of a rectangular microfluidic channel with multiple magnetic wires positioned on top of and underneath it along the length of the channel at a small angle with respect to the channel axis. Strong magnetic field gradients, produced by the wires, exert sufficient magnetic forces on the mRBCs in order to separate and concentrate them in a specific region small enough to fit within the microscope field of view at magnifications typically required to identify the malaria parasite type. The feasibility of the device is studied using a model where the trajectories of the mRBCs inside the channel are determined using first-order ordinary differential equations (ODEs) solved numerically using a multistep ODE solver available within MATLAB. The mRBCs trajectories reveal that it is possible to separate and concentrate the mRBCs in less than 5 min, even in cases of very low parasitemia (1-10 parasites/mu L of blood) using blood sample volumes of around 3 mu L employed today.
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Details
- Title
- Computational study of a magnetic design to improve the diagnosis of malaria: 2D model
- Creators
- Siddharth Vyas - Drexel UniversityVladimir Genis - Drexel UniversityGary Friedman - Drexel University
- Publication Details
- Journal of magnetism and magnetic materials, v 423
- Publisher
- Elsevier
- Number of pages
- 5
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; [Retired Faculty]
- Web of Science ID
- WOS:000397192800047
- Scopus ID
- 2-s2.0-84990828172
- Other Identifier
- 991019167420704721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Materials Science, Multidisciplinary
- Physics, Condensed Matter