Highly Sensitive Bulk Silicon Chemical Sensors with Sub‑5 nm Thin Charge Inversion Layers
There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. Here, we report chemical-sensitive field-effect-transistors (CS-FETs) based on bulk silicon wafers, wherein an electrostatically confined sub-5 nm thin charge inversion...
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Published in: | ACS nano Vol. 12; no. 3; pp. 2948 - 2954 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
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American Chemical Society
27-03-2018
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Abstract | There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. Here, we report chemical-sensitive field-effect-transistors (CS-FETs) based on bulk silicon wafers, wherein an electrostatically confined sub-5 nm thin charge inversion layer is modulated by chemical exposure to achieve a high-sensitivity gas-sensing platform. Using hydrogen sensing as a “litmus” test, we demonstrate large sensor responses (>1000%) to 0.5% H2 gas, with fast response (<60 s) and recovery times (<120 s) at room temperature and low power (<50 μW). On the basis of these performance metrics as well as standardized benchmarking, we show that bulk silicon CS-FETs offer similar or better sensing performance compared to emerging nanostructures semiconductors while providing a highly scalable and manufacturable platform. |
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AbstractList | There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. Here, we report chemical-sensitive field-effect-transistors (CS-FETs) based on bulk silicon wafers, wherein an electrostatically confined sub-5 nm thin charge inversion layer is modulated by chemical exposure to achieve a high-sensitivity gas-sensing platform. Using hydrogen sensing as a "litmus" test, we demonstrate large sensor responses (>1000%) to 0.5% H
gas, with fast response (<60 s) and recovery times (<120 s) at room temperature and low power (<50 μW). On the basis of these performance metrics as well as standardized benchmarking, we show that bulk silicon CS-FETs offer similar or better sensing performance compared to emerging nanostructures semiconductors while providing a highly scalable and manufacturable platform. There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. Here, we report chemical-sensitive field-effect-transistors (CS-FETs) based on bulk silicon wafers, wherein an electrostatically confined sub-5 nm thin charge inversion layer is modulated by chemical exposure to achieve a high-sensitivity gas-sensing platform. Using hydrogen sensing as a “litmus” test, we demonstrate large sensor responses (>1000%) to 0.5% H2 gas, with fast response (<60 s) and recovery times (<120 s) at room temperature and low power (<50 μW). On the basis of these performance metrics as well as standardized benchmarking, we show that bulk silicon CS-FETs offer similar or better sensing performance compared to emerging nanostructures semiconductors while providing a highly scalable and manufacturable platform. There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. In this work, we report chemical-sensitive field-effect-transistors (CS-FETs) based on bulk silicon wafers, wherein an electrostatically confined sub-5 nm thin charge inversion layer is modulated by chemical exposure to achieve a high-sensitivity gas-sensing platform. Using hydrogen sensing as a "litmus" test, we demonstrate large sensor responses (>1000%) to 0.5% H2 gas, with fast response (<60 s) and recovery times (<120 s) at room temperature and low power (<50 μW). On the basis of these performance metrics as well as standardized benchmarking, we show that bulk silicon CS-FETs offer similar or better sensing performance compared to emerging nanostructures semiconductors while providing a highly scalable and manufacturable platform. |
Author | Gupta, Niharika Javey, Ali Fahad, Hossain M Han, Rui Desai, Sujay B |
AuthorAffiliation | Lawrence Berkeley National Laboratory Electrical Engineering & Computer Sciences Berkeley Sensor and Actuator Center University of California Materials Sciences Division |
AuthorAffiliation_xml | – name: University of California – name: Berkeley Sensor and Actuator Center – name: Lawrence Berkeley National Laboratory – name: Electrical Engineering & Computer Sciences – name: Materials Sciences Division |
Author_xml | – sequence: 1 givenname: Hossain M orcidid: 0000-0002-6758-5432 surname: Fahad fullname: Fahad, Hossain M organization: Lawrence Berkeley National Laboratory – sequence: 2 givenname: Niharika surname: Gupta fullname: Gupta, Niharika organization: University of California – sequence: 3 givenname: Rui surname: Han fullname: Han, Rui organization: University of California – sequence: 4 givenname: Sujay B surname: Desai fullname: Desai, Sujay B organization: Lawrence Berkeley National Laboratory – sequence: 5 givenname: Ali orcidid: 0000-0001-7214-7931 surname: Javey fullname: Javey, Ali email: ajavey@berkeley.edu organization: Lawrence Berkeley National Laboratory |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29455517$$D View this record in MEDLINE/PubMed https://www.osti.gov/servlets/purl/1642671$$D View this record in Osti.gov |
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Keywords | low power CMOS gas sensors CS-FET tunable sensitivity electrostatic confinement charge inversion layer |
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Snippet | There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. Here, we report... There is an increasing demand for mass-producible, low-power gas sensors in a wide variety of industrial and consumer applications. In this work, we report... |
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SubjectTerms | charge inversion layer CMOS gas sensors CS-FET electrostatic confinement INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY low power tunable sensitivity |
Title | Highly Sensitive Bulk Silicon Chemical Sensors with Sub‑5 nm Thin Charge Inversion Layers |
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