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Photoconductivity, pH Sensitivity, Noise, and Channel Length Effects in Si Nanowire FET Sensors

Overview of attention for article published in Discover Nano, March 2018
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Title
Photoconductivity, pH Sensitivity, Noise, and Channel Length Effects in Si Nanowire FET Sensors
Published in
Discover Nano, March 2018
DOI 10.1186/s11671-018-2494-5
Pubmed ID
Authors

Ferdinand Gasparyan, Ihor Zadorozhnyi, Hrant Khondkaryan, Armen Arakelyan, Svetlana Vitusevich

Abstract

Silicon nanowire (NW) field-effect transistor (FET) sensors of various lengths were fabricated. Transport properties of Si NW FET sensors were investigated involving noise spectroscopy and current-voltage (I-V) characterization. The static I-V dependencies demonstrate the high quality of fabricated silicon FETs without leakage current. Transport and noise properties of NW FET structures were investigated under different light illumination conditions, as well as in sensor configuration in an aqueous solution with different pH values. Furthermore, we studied channel length effects on the photoconductivity, noise, and pH sensitivity. The magnitude of the channel current is approximately inversely proportional to the length of the current channel, and the pH sensitivity increases with the increase of channel length approaching the Nernst limit value of 59.5 mV/pH. We demonstrate that dominant 1/f-noise can be screened by the generation-recombination plateau at certain pH of the solution or external optical excitation. The characteristic frequency of the generation-recombination noise component decreases with increasing of illumination power. Moreover, it is shown that the measured value of the slope of 1/f-noise spectral density dependence on the current channel length is 2.7 which is close to the theoretically predicted value of 3.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 30%
Student > Ph. D. Student 4 17%
Student > Bachelor 2 9%
Student > Doctoral Student 1 4%
Lecturer 1 4%
Other 2 9%
Unknown 6 26%
Readers by discipline Count As %
Engineering 7 30%
Physics and Astronomy 3 13%
Agricultural and Biological Sciences 1 4%
Immunology and Microbiology 1 4%
Chemical Engineering 1 4%
Other 3 13%
Unknown 7 30%