Researchers in the US have used Graphenea graphene to produce chemical sensors with selectivity and discrimination unseen before in any other sensor type. The sensors are made from untreated off-the-shelf CVD graphene, which makes them commercially interesting.

The consortium of an army research center, an academic institution, and two private companies constructed the sensors using a straightforward, CMOS-compatible procedure. They exposed the sensors to vapours of chemically diverse as well as chemically similar compounds and found unprecedented selectivity. The exposure and data analysis was performed in an automated way, enabling wide-scale use of such devices.

Graphene chemical sensors have fast response and unprecedented specificity. Reprinted with permission from ACS Sens., 2016, 1 (1), pp 26–31. Copyright 2016 American Chemical Society.

The sensors were held above open vials containing the analyte for only 30 seconds. Although all compounds caused an initial change in electrical resistance of the graphene, followed by a decline, the responses to the different molecules all exhibited different shapes. The temporal response was then analyzed with principle component analysis to discriminate between the compounds. Machine learning-based techniques were used to create a training algorithm for sensing a wide spectrum of chemicals. The entire sensing process lasts less than 5 minutes. Strikingly, these simple sensors discriminate even between monosubstituted compounds, i.e. chemicals in which only one hydrogen group has been replaced by another group of atoms. 11 chemically diverse compounds and 9 monosubstituted benzene compounds were classified with an accuracy of 96% and 92%, respectively. Other notable characteristics of the sensor include room temperature operation, rapid response and recovery, reversibility, reproducibility, and stable operation, all important for use in real-world scenarios.

Furthermore, graphene sensors are an excellent candidate to serve as a platform for surface modified elements in cross-reactive sensor arrays to further increase discrimination and classification.