THESIS
2022
1 online resource (xviii, 119 pages) : illustrations (some color)
Abstract
Artificial olfactory systems, inspired by the human sensory system, can detect and
discriminate a wide variety of gas molecules, which are in resonating demand in real life
applications. The two core components of artificial olfactory systems are the
chemical sensors as the sensing units to perceive chemical compounds and machine
learning algorithms to recognize the gas response patterns for olfactory perception.
Among the sensing techniques, the nanostructured metal oxide gas sensor array
outstands itself for simple structure, miniaturization, sensitivity, and robustness.
However, cross-sensitivity to a broad range of gas molecules hinders its development
as a platform for general artificial olfactory systems. In this thesis, integrated
nanostructured-metal oxide gas sensor arrays, com...[
Read more ]
Artificial olfactory systems, inspired by the human sensory system, can detect and
discriminate a wide variety of gas molecules, which are in resonating demand in real life
applications. The two core components of artificial olfactory systems are the
chemical sensors as the sensing units to perceive chemical compounds and machine
learning algorithms to recognize the gas response patterns for olfactory perception.
Among the sensing techniques, the nanostructured metal oxide gas sensor array
outstands itself for simple structure, miniaturization, sensitivity, and robustness.
However, cross-sensitivity to a broad range of gas molecules hinders its development
as a platform for general artificial olfactory systems. In this thesis, integrated
nanostructured-metal oxide gas sensor arrays, combined with machine learning
algorithms, are explored for gas discrimination.
Throughout the whole work, a 3D nanotube array based on a unique
nanohoneycomb structure is constructed with conformal and dense sensing film for
superior sensing response toward ppb and sub-ppb gases. Next, we addressed the crosssensitivity
issue from several aspects, including materials synthesis, heating modulation,
sensor array construction, and algorithm design.
Starting from the rationally designed sensing materials, the platinum nanoclusters
decorated SnO
2sensors achieved highly sensitive and selective NO
2 sensing, which is
validated by density functional theory and experimental tests. Following the single
sensor-based strategy, a micro-heater integrated sensor working on pulse heating mode
achieved multi-gases discrimination with rich features during these heating and cooling
processes. Multiple gases can be well-recognized with the aid of the conductance-slope
map. The gas sensor array is another possible method for multi-gases discrimination.
We combined principal component analysis and support vector machine to demonstrate
indoor air quality monitoring with self-powered sensor array networks. Moreover, we
proposed a monolithically integrated 3D sensor array chip with up to 10,000
individually addressable sensors in the millimetre chip region. Augmented with neural
network algorithms, the biomimetic olfactory system empowered by sensor array chips
fulfilled excellent distinguishability for more than 4000 samples of multiple gas species
and concentration prediction of gas mixtures with the ultralow absolute relative error
of less than 2.7%. We also demonstrated the capability of the biomimetic olfactory
system to discriminate twenty-four odours. Finally, we have demonstrated the power
of the fusion of vision and olfaction senses on a quadrupedal mobile robot for a mini
reconnaissance mission, which uncovered the alluring potential of our biomimetic
olfactory system for many future vital applications.
Post a Comment