Alive to anomalies

Motorola Labs and Arizona State University have announced what they say is a key advancement in the use of Single-Walled Carbon Nanotubes in Field Effect Transistors to sense chemical agents.


Motorola Labs and Arizona State University have announced what they say is a key advancement in the use of Single-Walled Carbon Nanotubes (SWNTs) in Field Effect Transistors (FETs) to sense biological and chemical agents.



The research teams have developed a method to functionalise SWNTs with peptides to produce low-power SWNT-FETs that are said to be highly sensitive and can selectively detect heavy metal ions down to the parts-per-trillion level.



‘Integration of nanosensors into devices and sensor networks will enable the detection of biological and chemical agents at very low concentrations, which could be vital in the areas of public safety and homeland security,’ said Vida Ilderem, Vice President of Embedded Systems Research Labs in Tempe, Arizona. ‘In the future, these sensors could be integrated into devices to produce a powerful network that can seamlessly communicate environmental changes to people or other devices.’



Researchers have tuned SWNT-FETs to sense specific agents by applying a peptide-functionalised polymer coating that does not affect their ability to transmit electrical signals. This developing sensor technology could be used to monitor a host of environmental and health issues including air and water quality, industrial chemicals and biological agents.



‘Our sensor is based on the unique properties of peptides and carbon nanotubes. Peptides can be used to recognise and detect various chemical species with astonishing sensitivity and selectivity while carbon nanotubes are known for their unique electronic properties,’ said Nongjian Tao, a professor in the Department of Electrical Engineering in ASU’s Ira A. Fulton School of Engineering. ‘The combination of the two allows us to quickly convert the recognition events of the peptides into an electronic signal.’



Researchers will now investigate the sensing of other analytes and the feasibility of multi-analyte detection with selective sensing libraries.