A team of engineers at the University of Chicago and the University of Wisconsin-Milwaukee developed a potentially mass-producible $1 sensor that can detect contaminants in drinking water in the home. The sensor features a graphene field-effect transistor (FET) that can identify heavy metals, bacteria, and other toxins at parts-per-billion or even parts-per-trillion concentrations within seconds.
A nanometers-thick semiconducting graphene oxide sheet deposited on a silicon wafer connects the FET's gold source and drain electrodes while a gate electrode directs current through this channel. Attaching chemical and biological molecules to the graphene surface induces conductivity changes whose magnitude correlates to toxin levels.
Machine learning algorithms help the sensors differentiate among the contaminants, says Junhong Chen, a professor of molecular engineering at UChicago and the lead water strategist at Argonne National Laboratory. Chen and colleagues test the sensors in water using impedance spectroscopy to detect defects in the devices.
From IEEE Spectrum
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