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 in | ACS nano Vol. 3; no. 12; pp. 3969 - 3976 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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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. |
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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 |
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