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Current Research
Our lab develops novel chemical and biological sensing materials, investigates underlying mechanisms and fundamentals, and expands to explore data analytics and integrated device design to complement sensing performance. The main application areas include environmental, healthcare, food safety and homeland security. Current research directions are:
Artificial Olfactory – to address chemical sensor selectivity issue: transforming non-selective chemical sensors to recognize and measure complex environment change enabled by artificial intelligence. This will be applied for environmental monitoring and breath analysis for medical diagnosis.
Biomimetic Receptors Based Biosensors – to address biosensor stability issue: synthesizing low-cost and environmentally stable biosensors to detect water and food contaminations (pesticide, pathogens, toxins, allergens, etc.), biomarkers for medical diagnosis and explosives for homeland security.
Integrated sensor systems / Lab on a chip – to address sensor reliability and long-term stability issues, and add device functionality: integrating multiple functional.
Machine-learning-assisted sensing material development - to build predictive data-driven models to quantify relation between material composition/fabrication parameters and sensing performance through the combination of experimentation, computational methods, and data-driven approaches.
Past Research Projects
Optical fiber-based hydrogen detection in oil for transformer health monitoring
Duel temperature modulated sensor array to mitigate oxygen interference on hydrogen detection. (US Patent, US20180371520A1)
Use machine learning algorithms to determine hydrogen concentration in different oxygen background.
Nanostructured Solid-State Materials for Harsh Environment Gas Detection (High Temperature)
Selected Project: Ce-Ni-O composite nanofibers (NFs) for highly selective propane detection at high temperature. (J. Mater. Chem. A, 2014,2, 14038-14047.)
Ce-Ni-O NFs (Ce : Ni atomic ratio = 1 : 1) were prepared by electrospinning and a subsequent calcination process. The backbone of nanofibers comprised of well-distributed CeO2, highly dispersed NiO, and solid solution Ce1-xNixO2. There are aggregated NiO nanoparticles that decorate on the surface of nanofibers. The gas sensing performance of Ce-Ni-O NFs-based sensor show an excellent sensitivity and selectivity towards C3H8 at 800 C. Two-step reaction kinetics of reducing gases on Ce-Ni-O NFs with much faster kinetics towards C3H8 and the response offset effect of n-CeO2 and p-NiO in Ce-Ni-O composite nanofibers are ascribed to be responsible for the excellent selectivity to C3H8 over CO and CH4 under the tested conditions.
Electrochemical Non-enzymatic Glucose Detection
Glucose sensors play an important role in managing blood glucose level of diabetic patients. This research explores chemically and thermally stable materials as alternative sensing materials for non-enzymatic glucose detection.
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