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Title
Performance Validation of a Planar Hall Resistance Biosensor through Beta-Amyloid Biomarker
DGIST Authors
Lee, SungBaeKim, CheolGi
Issued Date
2020-01
Citation
Kim, SungJoon. (2020-01). Performance Validation of a Planar Hall Resistance Biosensor through Beta-Amyloid Biomarker. doi: 10.3390/s20020434
Type
Article
Article Type
Article
Author Keywords
planar Hall effectMR sensorself-fieldbeta-amyloidimmobilizationdetection
Keywords
ALZHEIMERS-DISEASEPLATFORMSYSTEMSSENSOR
ISSN
1424-8220
Abstract
Magnetic sensors have great potential for biomedical applications, particularly, detection of magnetically-labeled biomolecules and cells. On the basis of the advantage of the planar Hall effect sensor, which consists of improved thermal stability as compared with other magnetic sensors, we have designed a portable biosensor platform that can detect magnetic labels without applying any external magnetic field. The trilayer sensor, with a composition of Ta (5 nm)/NiFe (10 nm)/Cu (x = 0 nm~1.2 nm)/IrMn (10 nm)/Ta (5 nm), was deposited on a silicon wafer using photolithography and a sputtering system, where the optimized sensor sensitivity was 6 μV/(Oe∙mA). The detection of the magnetic label was done by comparing the signals obtained in first harmonic AC mode (1f mode) using an external magnetic field and in the second harmonic AC mode (2f mode) with a self-field generated by current passing through the sensor. In addition, a technique for the β-amyloid biomarker-based antibody-antigen sandwich model was demonstrated for the detection of a series of concentrations of magnetic labels using the self-field mode method, where the signal-to-noise ratio (SNR) was high. The generated self-field was enough to detect an immobilized magnetic tag without an additional external magnetic field. Hence, it could be possible to reduce the device size to use the point-of-care testing using a portable circuit system.
URI
http://hdl.handle.net/20.500.11750/11419
DOI
10.3390/s20020434
Publisher
MDPI AG
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Lee, Sung Bae이성배

Department of Brain Sciences

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