Investigation of Adsorption Kinetics on the Surface of a Copper-Containing Silicon–Carbon Gas Sensor: Gas Identification

Author:

Plugotarenko Nina K.1ORCID,Novikov Sergey P.2ORCID,Myasoedova Tatiana N.1,Mikhailova Tatiana S.1

Affiliation:

1. Institute of Nanotechnologies, Electronics and Electronic Equipment Engineering, Southern Federal University, Taganrog 347900, Russia

2. Faculty of Informatics and Computer Science, Don State Technical University, Rostov-on-Don 344018, Russia

Abstract

The low selectivity of materials to gases of a similar nature may limit their use as sensors. Knowledge of the adsorption kinetic characteristics of each gas on the surface of the material may enable the ability to identify them. In this work, copper-containing silicon–carbon films were formed using electrochemical deposition on the Al2O3 substrate with interdigitated Cr/Cu/Cr electrodes. These films showed good adsorption characteristics with several different gases. The adsorption kinetics of nitrogen dioxide, sulfur dioxide, and carbon monoxide on the film surface were investigated by the change in the resistivity of the material. Pseudo-first-order and pseudo-second-order kinetics, Elovich, Ritchie, and Webber intraparticle diffusion models were applied. It was found that the largest approximation factor and the lowest Root-Mean-Square Error and Mean Bias Error for all three gases were for the Elovich model. The advantages of silicon–carbon copper-containing films for gas sensor applications were shown. An algorithm for gas recognition was proposed based on the dependence of the change in the resistivity of the material under stepwise gas exposure. It was found that parameters such as the values of the extrema of the first and second derivatives of the R vs. t dependence during adsorption and the slope of R vs. t dependence in the Elovich coordinates are responsible for gas identification among several one-nature gases.

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

MDPI AG

Subject

General Medicine

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