DocumentCode :
1398619
Title :
Performance Analysis of Si Nanowire Biosensor by Numerical Modeling for Charge Sensing
Author :
Yang, Xinrong ; Frensley, William R. ; Zhou, Dian ; Hu, Wenchuang
Author_Institution :
EE Dept., Univ. of Texas at Dallas, Richardson, TX, USA
Volume :
11
Issue :
3
fYear :
2012
fDate :
5/1/2012 12:00:00 AM
Firstpage :
501
Lastpage :
512
Abstract :
A numerical study on the operation of Si nanowire (NW) biosensors in charge-based sensing is presented. The simulation is built on physical models that, upon numerical convergence, coherently account for Fermi-Dirac, Poisson-Boltzman, site-binding and Gouy-Chapman-Stern theories in self-consistent manner. The method enables us to disentangle the impact of key design and experimental setup factors and assess their contribution to the sensitivity, linearity, and stability of such sensors. Our results quantitatively show SiNW sensor is significantly more stable when biased through solution gate than back gate; dense functional group at oxide surface and good SAM coverage are essential to linear and sensitive detection of uniformly distributed targets; compared to high concentration target detection, the effect of NW surface-to-volume ratio (S/V ) plays a more profound role in biomolecule detection when targets are at very low concentration, in which case, optimal S/V exists for a maximum sensitivity. Arbitrary down scaling beyond such S/V point may have reverse effect on sensor sensitivity.
Keywords :
biosensors; molecular biophysics; nanobiotechnology; nanosensors; nanowires; numerical analysis; silicon; Fermi-Dirac theories; Gouy-Chapman-Stern theories; Poisson-Boltzman theories; SAM coverage; Si nanowire biosensor; SiNW sensor; back gate; biomolecule detection; charge sensing; charge-based sensing; down scaling; numerical convergence; numerical modeling; oxide surface; performance analysis; sensor sensitivity; site-binding theories; solution gate; surface-to-volume ratio; Biological system modeling; Electric potential; Electrostatics; Logic gates; Sensors; Silicon; Substrates; Biosensor; SiNR; SiNW; modeling; simulation;
fLanguage :
English
Journal_Title :
Nanotechnology, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-125X
Type :
jour
DOI :
10.1109/TNANO.2011.2178101
Filename :
6104156
Link To Document :
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