An Integrated Circuit with Low Power Demands Enables Personal Sensors for Dangerous Pollutants

Achievement date: 

A team of scientists has designed, implemented, and tested a low-power integrated circuit for registering the detection of organic compounds in a sensor. The circuit consumes a fraction of the power of circuits currently used in such sensors, and was developed in research sponsored by the NSF-funded Engineering Research Center (ERC) for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST), based at North Carolina State University (NCSU).


Developing low-power, personal, and wearable sensors for volatile organic compounds (VOCs) can help guard human health against the volatile organic compounds (VOCs) that are increasingly present in work and home environments. The circuit developed by the ASSIST team led by NCSU Prof. Omer Oralkan consumes only 10 microwatts of power, in contrast to the milliwatts used by today’s commercially available sensors. The research indicates that a self-powered, wearable VOC sensor is possible for personalized VOC exposure monitoring.


Monitoring at a personal level is becoming more important at home, where a significant group of environmental pollutants emanate from sources such as household plastics, paints, and cleaners. The same is even more true for manufacturing processes and industrial settings.

High power consumption ranks as a key shortcoming of currently available VOC sensors, which use heated, bulk metal-oxide materials with poor selectivity to different types of VOCs. The ASSIST team uses polymer layers alongside transducer arrays. Target gas molecules attach to the polymer layers, changing the mass of the transducer and shifting the material’s resonant frequency enough that it can be detected by the integrated circuit.


Using classification algorithms, data from multiple channels enabled by different polymers are processed to analyze the air sample. Prof. Oralkan’s group collaborates with investigators in chemical and biomolecular engineering for distinguishing the polymer sensitivity, and with others in electrical and computer engineering for testing the developed sensors.