MOSFET-based gas sensors for process industry IoT applications

Khajavizadeh, Lida; Andersson, Mike

doi:10.1109/iceccme55909.2022.9988741

Cited by 3 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the literature, [20][21][22][23] threshold voltage is commonly considered as sensitivity parameter. However, in this work, sensitivity has been determined in terms of subthreshold current, which is an alternative to threshold voltage.…”

Section: Introductionmentioning

confidence: 99%

A highly sensitive MOSFET gas sensor based on charge plasma and catalytic metal gate

Dewangan,

Rajan,

Panchore

et al. 2023

Int J Numerical Modelling

View full text Add to dashboard Cite

This manuscript presents, for the first time, a catalytic metal gate‐based charge plasma (CP) MOSFET with improved sensitivity for gas detection applications. In this design, CP refers to the source and drain boundaries being marked by depositing metal electrodes with appropriate work function over the intrinsic silicon film. To sense hydrogen and oxygen gases, palladium (Pd) and silver (Ag) metals are respectively deposited as gate electrodes on P‐CP‐MOSFET and N‐CP‐MOSFET. Further, sensitivity of CP‐MOSFET sensor is determined as if gas molecules are present and the results have been evaluated in comparison with the sensitivity of conventional gas sensor using bulk MOSFET in ATLAS TCAD device simulator. The effect of process variations on sensitivity has also been compared for both devices. The proposed device resolves fabrication complexity issues and offers better sensitivity.

show abstract

Section: Introductionmentioning

confidence: 99%

A highly sensitive MOSFET gas sensor based on charge plasma and catalytic metal gate

Dewangan,

Rajan,

Panchore

et al. 2023

Int J Numerical Modelling

View full text Add to dashboard Cite

show abstract

IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring

Espinoza de los Monteros,

Tandazo Espinoza,

Punina Cordova

et al. 2024

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

Advanced Electronic and Optoelectronic Sensors, Applications, Modelling and Industry 5.0 Perspectives

Massaro¹

2023

Applied Sciences

View full text Add to dashboard Cite

This review will focus on advances in electronic and optoelectronic technologies by through the analysis of a full research and industrial application scenario. Starting with the analysis of nanocomposite sensors, and electronic/optoelectronic/mechatronic systems, the review describes in detail the principles and the models for finding possible implementations of Industry 5.0 applications. The study then addresses production processes and advanced detection systems integrating Artificial Intelligence (AI) algorithms. Specifically, the review introduces new research topics in Industry 5.0 about AI self-adaptive systems and processes in electronics, robotics and production management. The paper proposes also new Business Process Modelling and Notation (BPMN) Process Mining (PM) workflows, and a simulation of a complex Industry 5.0 manufacturing framework. The performed simulation estimates the diffusion heat parameters of a hypothesized production-line layout, describing the information flux of the whole framework. The simulation enhances the technological key elements, enabling an industrial upscale in the next digital revolution. The discussed models are usable in management engineering and informatics engineering, as they merge the perspectives of advanced sensors with Industry 5.0 requirements. The goal of the paper is to provide concepts, research topics and elements to design advanced production network in manufacturing industry.

show abstract

MOSFET-based gas sensors for process industry IoT applications

Cited by 3 publications

References 3 publications

A highly sensitive MOSFET gas sensor based on charge plasma and catalytic metal gate

A highly sensitive MOSFET gas sensor based on charge plasma and catalytic metal gate

IoT and Business Intelligence Based Model Design for Liquefied Petroleum Gas (LPG) Distribution Monitoring

Advanced Electronic and Optoelectronic Sensors, Applications, Modelling and Industry 5.0 Perspectives

Contact Info

Product

Resources

About