  This study presents a novel, ultralow-power single-sensor-based electronic
nose (e-nose) system for real-time gas identification, distinguishing itself
from conventional sensor-array-based e-nose systems whose power consumption and
cost increase with the number of sensors. Our system employs a single metal
oxide semiconductor (MOS) sensor built on a suspended 1D nanoheater, driven by
duty cycling-characterized by repeated pulsed power inputs. The sensor's
ultrafast thermal response, enabled by its small size, effectively decouples
the effects of temperature and surface charge exchange on the MOS
nanomaterial's conductivity. This provides distinct sensing signals that
alternate between responses coupled with and decoupled from the thermally
enhanced conductivity, all within a single time domain during duty cycling. The
magnitude and ratio of these dual responses vary depending on the gas type and
concentration, facilitating the early-stage gas identification of five gas
types within 30 s via a convolutional neural network (classification accuracy =
93.9%, concentration regression error = 19.8%). Additionally, the duty-cycling
mode significantly reduces power consumption by up to 90%, lowering it to 160
$\mu$W to heat the sensor to 250$^\circ$C. Manufactured using only wafer-level
batch microfabrication processes, this innovative e-nose system promises the
facile implementation of battery-driven, long-term, and cost-effective IoT
monitoring systems.
