Self-heating in pulsed mode for signal quality improvement: application to carbon nanostructures-based sensors

Sensor signal instability and drift are still unresolved challenges in conductometric gas sensors. Here, the use of self-heating effect to operate a gas sensor in a pulsed temperature modulation mode (pulsed self-heating operation) is presented as an effective method to enhance signal stability and...

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Detalles Bibliográficos
Autores: Monereo Cuscó, Oriol, Casals Guillén, Olga, Prades García, Juan Daniel, Cirera Hernández, Albert
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2016
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/97490
Acceso en línea:https://hdl.handle.net/2445/97490
Access Level:acceso abierto
Palabra clave:Materials nanoestructurats
Detectors de gasos
Nanostructured materials
Gas detectors
Descripción
Sumario:Sensor signal instability and drift are still unresolved challenges in conductometric gas sensors. Here, the use of self-heating effect to operate a gas sensor in a pulsed temperature modulation mode (pulsed self-heating operation) is presented as an effective method to enhance signal stability and reduce consumption figures down to a few W. The sensor operation temperature was pulsed periodically between two levels, obtaining two different sensing states from one single device driven with self-heating, i.e. free of heater. The signal differences between both operating points correlated well with gas concentrations and displayed no drift. This methodology is exemplified with a thorough study of the response of carbon nanofibers to humidity. Specifically, after analyzing the influence of the pulse characteristics (i.e. temperature variation, pulse period and pulse duty cycle) on the sensor performance, thumb rules to select suitable pulsing conditions are provided. The methodology is successfully extended to other target gases, such as NO2 and NH3. Finally, its implementation in a real-time sensing system with low computational requirements is demonstrated and discussed in detail.