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Chemical Engineering Seminar

Dr. Yixin Liu

Abstract: Chemical sensors are an integral part of everyday life as they are widely used in industries, environment, food, agriculture, energy, security, etc. There is an increasing demand for robust and reliable chemical sensors which can provide in-situ real time monitoring of targeted chemical species. Desired properties of a chemical sensor include high sensitivity with a large dynamic range, high selectivity to a target analyte (i.e. low cross-sensitivity to interferents), fast response and recovery, perfect reversibility of the sensing process, and high stability over a long lifetime of operation. Due to the intrinsic thermodynamics and kinetics of the reversible sensing material/analyte interaction, it’s unrealistic for a sensor to possess all desired properties. Among them, selectivity has been one of the biggest challenges for most of practical applications.

In this talk, I’ll present how material design and development have improved the selectivity of chemical sensors in both academic and industrial research settings, and how data driven, machine learning approaches have been demonstrated to enable the chemical sensors to recognize and measure complex multi-species chemical environment. I have come to conclude that the development of sensing material is essential to build a successful chemical sensor device which determines the sensor specifications (sensitivity, limit of detection, detection range and lifetime), and data driven approaches open a new avenue to complement sensing performance in many important aspects (selectivity, ambient impact, baseline drift, etc.) to meet the requirements of real-world sensing applications.

Bio: Yixin Liu obtained her Ph.D. in Chemical Engineering from the University of Connecticut in 2014, focusing on nanomaterials development for chemical and biological sensing applications. After graduation, she joined ABB US Corporate Research Center as a research scientist and promoted to senior research scientist in 2018, working on industrial chemical sensor development for 5 years. She also serves on the panel for NSF research fellowship evaluations and as an assistant guest editor for journal [Molecules] special issue “Selective and Sensitive Detection of Biological and Chemical Species”. Her current research interests lie in developing advanced materials for chemical and biological sensors and data driven approaches for sensing performance enhancement.