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Description
The data set consists of exemplary results of the product of voltage noise power spectral density S(f) multiplied by frequency f and normalized to squared DC voltage U^2 recorded in the graphene back-gated Field Effect Transistor under UV light assistance (275 nm) in the selected ambient atmospheres (Figure 3) and the results of gas detection by SVM algorithm: 1) chloroform (Figure 5), 2) acetonitrile (Figure 6), and predicted gas concentrations using various number of frequency bins (Figure 7, Figure 8).
The demonstrated data reveals we can determine two gas components in the considered gas mixture (chloroform and acetonitrile) by utilizing flicker noise and the SVM detection algorithm. When we considered noise power spectra in the frequency range 0.5 Hz—2 kHz, the gas detection limit reached 2.9 ppm for chloroform and 49.5 ppm for acetonitrile.
Dataset file
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.Example script for calculation:
https://github.com/antespi/s3md5
File details
- License:
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CC BY-NC-NDNon-commercial - No Derivative Works - Software:
- Origin viewer
Details
- Year of publication:
- 2025
- Verification date:
- 2025-01-08
- Creation date:
- 2024
- Dataset language:
- English
- Fields of science:
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- automation, electronics, electrical engineering and space technologies (Engineering and Technology)
- DOI:
- DOI ID 10.34808/jcf0-t050 open in new tab
- Funding:
- Verified by:
- Gdańsk University of Technology
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