Analytical Prediction of Highly Sensitive CNT-FET-Based Sensor Performance for Detection of Gas Molecules

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24210%2F20%3A00007884" target="_blank" >RIV/46747885:24210/20:00007884 - isvavai.cz</a>
Alternative codes found
RIV/46747885:24620/20:00007884
Result on the web
<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8955777" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8955777</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2020.2965806" target="_blank" >10.1109/ACCESS.2020.2965806</a>

Result language
angličtina
Original language name
Analytical Prediction of Highly Sensitive CNT-FET-Based Sensor Performance for Detection of Gas Molecules
Original language description
In this study, a set of new analytical models to predict and investigate the impacts of gas adsorption on the electronic band structure and electrical transport properties of the single-wall carbon nanotube field-effect transistor (SWCNT-FET) based gas sensor are proposed. The sensing mechanism is based on introducing new hopping energy and on-site energy parameters for gas-carbon interactions representing the charge transfer between gas molecules (CO2, NH3, and H2O) and the hopping energies between carbon atoms of the CNT and gas molecule. The modeling starts from the atomic level to the device level using the tight-binding technique to formulate molecular adsorption effects on the energy band structure, density of states, carrier velocity, and I-V characteristics. Therefore, the variation of the energy bandgap, density of states and current-voltage properties of the CNT sensor in the presence of the gas molecules is discovered and discussed. The simulated results show that the proposed analytical models can be used with an electrical CNT gas sensor to predict the behavior of sensing mechanisms in gas sensors.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20201 - Electrical and electronic engineering

Project
<a href="/en/project/EF16_025%2F0007293" target="_blank" >EF16_025/0007293: Modular platform for autonomous chassis of specialized electric vehicles for freight and equipment transportation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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