首页|Gas sensors data analysis system: A user-friendly interface for fast and reliable response-recovery analysis
Gas sensors data analysis system: A user-friendly interface for fast and reliable response-recovery analysis
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NSTL
Elsevier
? 2021 Elsevier B.V.Semiconductor-based gas sensors have been commercially available since the early seventies. Over the past decade, the development of nanotechnology and new carbon-nanomaterials has further increased both fundamental research and commercial innovations of such materials and devices. Each sensing element is expected to exhibit a signal for a given gas concentration that is described by three parameters: 1) the response or sensitivity, 2) the response time, and 3) the recovery time. A typical calibration or characterization procedure involves exposing several samples or devices simultaneously to different concentrations of a gas of interest. The response is then dynamically measured over time, and these three parameters can be calculated for each exposure cycle. Within this context, we present an open-source graphical user interface (GUI) that aims to facilitate the analysis procedure of dynamic response-recovery curves of resistive semiconductor-based gas sensors. The code was written in python, and it uses the open-source libraries matplotlib, pandas, NumPy, and SciPy for data visualization, handling, and fitting. PyQt is the library used for the graphical elements because it offers excellent flexibility and compatibility with different operating systems. Our software can analyze eight samples simultaneously that share the same time data, shortening the analysis process to a couple of minutes. Its source code is available at Github. This article describes its main features, the workflow, and we present three examples for data analysis whose data tables are available for user testing.
Data analysisGas sensorGUI
de Lima B.S.、Silva W.A.S.、Mastelaro V.R.、Ndiaye A.L.、Brunet J.
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Sao Carlos Institute of Physics University of Sao Paulo
NSTL
Elsevier
