2 research outputs found
Field Effect Transistors Based on Polycyclic Aromatic Hydrocarbons for the Detection and Classification of Volatile Organic Compounds
We show that polycyclic aromatic
hydrocarbon (PAH) based field effect transistor (FET) arrays can serve
as excellent chemical sensors for the detection of volatile organic
compounds (VOCs) under confounding humidity conditions. Using these
sensors, w/o complementary pattern recognition methods, we study the
ability of PAH-FET(s) to: (i) discriminate between aromatic and non-aromatic
VOCs; (ii) distinguish polar and non-polar non-aromatic compounds;
and to (iii) identify specific VOCs within the subgroups (i.e., aromatic
compounds, polar non-aromatic compounds, non-polar non-aromatic compounds).
We further study the effect of water vapor on the sensor array’s
discriminative ability and derive patterns that are stable when exposed
to different constant values of background humidity. Patterns based
on different independent electronic features from an array of PAH-FETs
may bring us one step closer to creating a unique fingerprint for
individual VOCs in real-world applications in atmospheres with varying
levels of humidity
Detection of Volatile Organic Compounds in <i>Brucella abortus</i>-Seropositive Bison
Brucellosis
is of great public health and economic importance worldwide. Detection
of brucellosis currently relies on serologic testing of an antibody
response to <i>Brucella</i> infection, which suffers from
cross-sensitivities to other antibody responses. Here we present a
new method for identifying <i>Brucella</i> exposure that
is based on profiling volatile organic compounds (VOCs) in exhaled
breath. Breath samples from <i>Brucella</i>-seropositive
bison and controls were chemically analyzed and demonstrated statistically
significant differences in the concentration profiles of five VOCs.
A point-of-care device incorporating an array of nanomaterial-based
sensors could identify VOC patterns indicative of <i>Brucella</i> exposure with excellent discriminative power, using a statistical
algorithm. We show that the patterns were not affected by the animals’
environment and that the discriminative power of the approach was
stable over time. The <i>Brucella</i>-indicative VOCs and
collective patterns that were identified in this pilot study could
lead to the development of a novel diagnostic screening test for quickly
detecting infected animals chute-side, pen-side, or even remotely
in populations of free-ranging ungulates. The promising preliminary
results presented encourage subsequent larger scale trials in order
to further evaluate the proposed method