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- Publisher Website: 10.1109/ISNE.2016.7543348
- Scopus: eid_2-s2.0-84985905044
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Conference Paper: A linear slope analyzing strategy of GMR sensor transfer curve for the detection of superparamagnetic nanoparticles
Title | A linear slope analyzing strategy of GMR sensor transfer curve for the detection of superparamagnetic nanoparticles |
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Authors | |
Keywords | Giant magnetoresistance (GMR) sensors Magnetic biodetection Superparamagnetic nanoparticles |
Issue Date | 2016 |
Publisher | IEEE. |
Citation | The 5th International Symposium on Next-Generation Electronics (ISNE 2016), Hsinchu, Taiwan, 4-6 May 2016. In Conference Proceedings, 2016 How to Cite? |
Abstract | Superparamagnetic nanoparticles are popular magnetic label materials for the magnetic biodetection technologies. The accurate detection of superparamagnetic nanoparticles is one of the key aspects for high performance magnetic biodetection platform. An improved detection protocol of superparamagnetic nanoparticles using giant magnetoresistance (GMR) sensors were studied in this paper. In this study, the as-synthesized iron oxide nanoparticles (IONPs) with superparamagnetic behavior were detected by GMR sensors (GF708, Sensitec GmbH). The sensor transfer curves were measured before and after depositing IONPs onto sensor surfaces. The linear range of the transfer curves were analyzed, and the change of the slope indicated the quantity of IONPs on sensor surfaces. © 2016 IEEE. |
Description | Session W1P: paper no. W1P-4-27 |
Persistent Identifier | http://hdl.handle.net/10722/232318 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Du, Y | - |
dc.contributor.author | Pong, PWT | - |
dc.date.accessioned | 2016-09-20T05:29:11Z | - |
dc.date.available | 2016-09-20T05:29:11Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | The 5th International Symposium on Next-Generation Electronics (ISNE 2016), Hsinchu, Taiwan, 4-6 May 2016. In Conference Proceedings, 2016 | - |
dc.identifier.isbn | 978-150902439-1 | - |
dc.identifier.uri | http://hdl.handle.net/10722/232318 | - |
dc.description | Session W1P: paper no. W1P-4-27 | - |
dc.description.abstract | Superparamagnetic nanoparticles are popular magnetic label materials for the magnetic biodetection technologies. The accurate detection of superparamagnetic nanoparticles is one of the key aspects for high performance magnetic biodetection platform. An improved detection protocol of superparamagnetic nanoparticles using giant magnetoresistance (GMR) sensors were studied in this paper. In this study, the as-synthesized iron oxide nanoparticles (IONPs) with superparamagnetic behavior were detected by GMR sensors (GF708, Sensitec GmbH). The sensor transfer curves were measured before and after depositing IONPs onto sensor surfaces. The linear range of the transfer curves were analyzed, and the change of the slope indicated the quantity of IONPs on sensor surfaces. © 2016 IEEE. | - |
dc.language | eng | - |
dc.publisher | IEEE. | - |
dc.relation.ispartof | International Symposium on Next-Generation Electronics Proceedings | - |
dc.rights | International Symposium on Next-Generation Electronics Proceedings. Copyright © IEEE. | - |
dc.rights | ©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Giant magnetoresistance (GMR) sensors | - |
dc.subject | Magnetic biodetection | - |
dc.subject | Superparamagnetic nanoparticles | - |
dc.title | A linear slope analyzing strategy of GMR sensor transfer curve for the detection of superparamagnetic nanoparticles | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Pong, PWT: ppong@hkucc.hku.hk | - |
dc.identifier.authority | Pong, PWT=rp00217 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ISNE.2016.7543348 | - |
dc.identifier.scopus | eid_2-s2.0-84985905044 | - |
dc.identifier.hkuros | 265564 | - |
dc.publisher.place | United States | - |
dc.customcontrol.immutable | sml 160927 | - |