Manipulating polymer composition to create low-cost, high-fidelity sensors for indoor CO2 monitoring.

Carbon dioxide (CO2) has been linked to many deleterious health effects, and it has also been used as a proxy for building occupancy measurements. These applications have created a need for low-cost and low-power CO2 sensors that can be seamlessly incorporated into existing buildings. We report a resonant mass sensor coated with a solution-processable polymer blend of poly(ethylene oxide) (PEO) and poly(ethyleneimine) (PEI) for the detection of CO2 across multiple use conditions. Controlling the polymer blend composition and nanostructure enabled better transport of the analyte gas into the sensing layer, which allowed for significantly enhanced CO2 sensing relative to the state of the art. Moreover, the hydrophilic nature of PEO resulted in water uptake, which provided for higher sensing sensitivity at elevated humidity conditions. Therefore, this key integration of materials and resonant sensor platform could be a potential solution in the future for CO2 monitoring in smart infrastructure.

A method for estimating the parameters of electrodynamic drivers in thermoacoustic coolers.

The electroacoustic efficiency of high-power actuators used in thermoacoustic coolers may be estimated using a linear model involving a combination of six parameters. A method to identify these equivalent driver parameters from measured total electrical impedance and velocity-voltage transfer function data was developed. A commercially available, moving-magnet driver coupled to a functional thermoacoustic cooler was used to demonstrate the procedure experimentally. The method, based on linear electrical circuit theory, allowed for the possible frequency and amplitude dependence of the driver parameters to be estimated. The results demonstrated that driver parameters measured in vacuo using this method can be used to predict the driver efficiency and performance for operating conditions which may be encountered under load.

Adaptive tuning of an electrodynamically driven thermoacoustic cooler.

The commercial development of thermoacoustic coolers has been hampered in part by their low efficiencies compared to vapor compression systems. A key component of electrodynamically driven coolers is the electromechanical transducer, or driver. The driver's electroacoustic transduction efficiency, defined as the ratio of the acoustic power delivered to the working gas by the moving piston and the electrical power supplied, must be maintained near its maximum value if a high overall system efficiency is to be achieved. Modeling and experiments have shown that the electroacoustic efficiency peaks sharply near the resonance frequency of the electro-mechano-acoustic system. The optimal operating frequency changes as the loading condition changes, and as the properties of the working gas vary. The driver efficiency may thus drop significantly during continuous operation at a fixed frequency. In this study, an on-line driver efficiency measurement scheme was implemented. It was found that the frequency for maximum electroacoustic efficiency does not precisely match any particular resonance frequency, and that the efficiency at resonance can be significantly lower than the highest achievable efficiency. Therefore, a direct efficiency measurement scheme was implemented and validated using a functional thermoacoustic cooler. An adaptive frequency-tuning scheme was then implemented. Experiments were performed to investigate the effectiveness of the control scheme to maintain the maximum achievable driver efficiency for varying operating conditions.