Predicting Resistance Changes in Light-Activated Gas Sensors: A New Phenomenological Model
FOXES partners at the University of Barcelona (UB) have developed a phenomenological model that accurately predicts resistance changes in light-activated gas sensors. This model relies solely on a set of parameters determined in advance through dedicated experiments.
Light activation offers a superior alternative to heating for promoting gas responses in semiconductor gas sensors, significantly improving energy efficiency. While the mechanisms behind light-activated gas responses are still under discussion, two decades of experiments have revealed consistent trends across various light conditions and gas concentrations.
Drawing on these consolidated qualitative observations, the team led by Oscal Alonso and Dani Prades at the University of Barcelona has created a model that quantitatively predicts resistance changes in light-activated gas sensors. The model incorporates various effects, such as photoconductivity, dynamic gas responses, irradiance influence on sensitivity, and baseline drift.
This modular Verilog-A model has been validated with experimental data, demonstrating its ability to predict observations over both short and long timescales. The source code is fully available to the community, enabling engineers to design interfaces for these sensors immediately and allowing peers to modify and refine the model further.
By making this model accessible, the UB team aims to accelerate the development and optimization of light-activated gas sensors, paving the way for more energy-efficient sensing technologies.
Bibliographic information: J. L. Soler-Fernández et al., “A Verilog-A model for a light-activated semiconductor gas sensor,” in IEEE Sensors Journal,
DOI: 10.1109/JSEN.2024.3407651