A Calibration Method for Nanowire Biosensors to Suppress Device-to-Device Variation

Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variat...

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Published inACS nano Vol. 3; no. 12; pp. 3969 - 3976
Main Authors Ishikawa, Fumiaki N, Curreli, Marco, Chang, Hsiao-Kang, Chen, Po-Chiang, Zhang, Rui, Cote, Richard J, Thompson, Mark E, Zhou, Chongwu
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 22.12.2009
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Abstract Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dI ds/dV g) and the absolute response (absolute change in current, ΔI). In2O3 nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (ΔI) and the gate dependence (dI ds/dV g) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI ds/dV g for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.
AbstractList Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dI(ds)/dV(g)) and the absolute response (absolute change in current, DeltaI). In(2)O(3) nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (DeltaI) and the gate dependence (dI(ds)/dV(g)) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI(ds)/dV(g) for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dI(ds)/dV(g)) and the absolute response (absolute change in current, DeltaI). In(2)O(3) nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (DeltaI) and the gate dependence (dI(ds)/dV(g)) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI(ds)/dV(g) for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.
Nanowire/nanotube biosensors have stimulated significant interest; however the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence ( dI ds /dV g ) and the absolute response (absolute change in current, ΔI ). In 2 O 3 nanowire based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response ( ΔI ) and the gate dependence ( dI ds /dV g ) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI ds /dV g for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proved advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.
Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dI ds/dV g) and the absolute response (absolute change in current, ΔI). In2O3 nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (ΔI) and the gate dependence (dI ds/dV g) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI ds/dV g for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.
Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dI(ds)/dV(g)) and the absolute response (absolute change in current, DeltaI). In(2)O(3) nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (DeltaI) and the gate dependence (dI(ds)/dV(g)) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI(ds)/dV(g) for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.
Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dIds/dVg) and the absolute response (absolute change in current, *DI). In2O3 nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (*DI) and the gate dependence (dIds/dVg) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dIds/dVg for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.
Author Chen, Po-Chiang
Ishikawa, Fumiaki N
Curreli, Marco
Chang, Hsiao-Kang
Zhang, Rui
Cote, Richard J
Zhou, Chongwu
Thompson, Mark E
AuthorAffiliation a Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089
c Department of Pathology, University of Southern California, Los Angeles, CA 90089
b Department of Chemistry, University of Southern California, Los Angeles, CA 90089
AuthorAffiliation_xml – name: a Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089
– name: b Department of Chemistry, University of Southern California, Los Angeles, CA 90089
– name: c Department of Pathology, University of Southern California, Los Angeles, CA 90089
Author_xml – sequence: 1
  givenname: Fumiaki N
  surname: Ishikawa
  fullname: Ishikawa, Fumiaki N
– sequence: 2
  givenname: Marco
  surname: Curreli
  fullname: Curreli, Marco
– sequence: 3
  givenname: Hsiao-Kang
  surname: Chang
  fullname: Chang, Hsiao-Kang
– sequence: 4
  givenname: Po-Chiang
  surname: Chen
  fullname: Chen, Po-Chiang
– sequence: 5
  givenname: Rui
  surname: Zhang
  fullname: Zhang, Rui
– sequence: 6
  givenname: Richard J
  surname: Cote
  fullname: Cote, Richard J
– sequence: 7
  givenname: Mark E
  surname: Thompson
  fullname: Thompson, Mark E
– sequence: 8
  givenname: Chongwu
  surname: Zhou
  fullname: Zhou, Chongwu
  email: chongwuz@usc.edu
BackLink https://www.ncbi.nlm.nih.gov/pubmed/19921812$$D View this record in MEDLINE/PubMed
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Snippet Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a...
Nanowire/nanotube biosensors have stimulated significant interest; however the inevitable device-to-device variation in the biosensor performance remains a...
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SubjectTerms Biosensing Techniques - instrumentation
Biosensing Techniques - standards
Calibration
Electrochemistry - instrumentation
Electrochemistry - standards
Equipment Design
Equipment Failure Analysis
Nanotechnology - instrumentation
Nanotechnology - standards
Nanotubes - chemistry
Reproducibility of Results
Sensitivity and Specificity
United States
Title A Calibration Method for Nanowire Biosensors to Suppress Device-to-Device Variation
URI http://dx.doi.org/10.1021/nn9011384
https://www.ncbi.nlm.nih.gov/pubmed/19921812
https://www.proquest.com/docview/733609661
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https://pubmed.ncbi.nlm.nih.gov/PMC2805439
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