Qiliang Li, Professor, Electrical and Computer Engineering, Volgenau School of Engineering, and Mason doctoral students are performing modeling, simulation, calculation, and design of gas sensor arrays using multivariate regression analysis. Their goal is to provide an effective and efficient simulation technology to design high performance gas sensors and sensor arrays.
Li will lead the research activities for the project. He will be responsible for modeling and design of gas sensor devices and arrays. He will advise graduate students on the simulation and optimization of device models.
The doctoral students (TBD) will work on the modeling and simulation of gas sensors. The students will design the structures and electrical properties of the sensor devices. They will also simulate and optimize the sensor array design.
Work for the project will consist of two tasks.
First, the researchers will model the physisorption and chemisorption of gas molecules on the sensor surface. In the real-world settings, chemical sensors usually show an electrochemical or optoelectronic response to a complex combination of effects of the target chemicals and environment. It is, thus, very important for researchers to identify the signature of target chemicals against the disturbance of the surrounding environment and atmosphere. Therefore, the physisorption and chemisorption of target gas molecules on different sensor surfaces should be precisely modeled.
For this step, the researchers will apply first principle calculation and density functional theory (DFT) to model the impact of the absorption processes and their effects on the carrier density, energy band structures, surface potential and other electrochemical properties of the sensing materials and devices.
First principle calculation is a method to calculate physical properties directly from basic physical quantities such as the mass and charge based on the principle of quantum mechanics.
Density functional theory is a computational quantum mechanical modeling method used to investigate the electronic structure of many-body systems, in particular atoms, molecules, and condensed phases.
For the absorption process modeling, the details of the gas molecules, including molecular structures, polarization, magnetic moment and charge distribution, and their impacts will be explored and categorized to assist the design of sensor devices and arrays.
Second, they will model the impact of environmental variables. Variations in temperature, humidity, oxygen, and other gases, will induce significant impact on the sensing, and therefore, their effects should be precisely calculated. For this part of the research, the environment effect on sensing will be studied following two approaches: modeling how the environment factor affects the interaction between gas molecules and sensors, and analyzing how the gas absorption affects the noise spectrum.
Li received $30,000 from the Department of Homeland Security for this work. Funding began in January 2020 and will end in January 2021.