Investigation of gas flow in microstructure for highly selective sensing

在过去的几十年里，通过精密仪器检测微量气体的能力使人们能够前所未有地深入了解许多物理和化学过程。如今，对提高便携性、速度和成本的渴望推动了对气体传感技术的前沿研究。这项研究将通过开发具有无与伦比的选择性和灵敏度的下一代人工嗅觉系统来实现这些目标。其结果将有利于需要实时检测某些气体的行业，其中最重要的是涉及健康，环境，安全和安全以及农业的挥发性有机化合物（VOC）。与行业合作伙伴一起，申请人最近开始开发基于微流体的嗅觉技术，用于在几种应用中检测/定量VOC。这些过去的应用项目主要集中在通过试验和错误来校准嗅觉元件，因此它们缺乏获得洞察力和克服与气体与微流体通道表面的相互作用和技术的选择性相关的科学挑战所需的研究。这项发现补助金旨在支持这种非侵入性技术的实现，优化和鲁棒化的长期愿景。这一愿景将通过严格的数值和实验研究量化表面气体相互作用来实现，同时考虑到环境扰动，并将数据驱动的科学用于特征识别和分类。研究可以分为以下四个任务。任务1将涉及气体吸附沿着与微流体通道中的扩散的建模。任务2将涉及在疏水性和气体极性方面优化表面涂层，以最大限度地提高传感器的选择性。任务3将集中于制造具有复杂疏水性的表面，以提高在含有不同极性气体的VOC混合物中的选择性。任务4将侧重于数据科学方法，包括统计和神经网络技术，以模拟人工嗅觉系统的复杂输入-输出关系。* 拟议的研究将产生必要的知识，以进一步推进微流体嗅觉，用于实时和准确地检测气体。随着这项技术的商业化，这项研究将能够控制危险化学品和非侵入性诊断，影响加拿大人的环境和生活。此外，多方面的研究将为参与培训的学员提供许多前沿研究机会。他们专门从事微流体和嗅觉系统的理论和应用，将接受适当的培训，在学术界和许多行业，包括生物医学，环境和能源部门担任关键职位。

In the last few decades, the ability to sense small traces of gases by sophisticated instrumentation has enabled in-depth understanding of many physical and chemical processes like never before. Nowadays, the desire to have improved portability, speed and cost drives cutting-edge research on gas sensing technologies. This research will achieve these by the development of the next generation of an artificial olfactory system with unparalleled selectivity and sensitivity. The outcome will benefit industries in need of real-time detection of certain gases among them foremost are volatile organic compounds (VOCs) that concern health, environment, safety and security, and agriculture. Together with industry partners, the applicant has recently commenced the development of a microfluidic-based olfaction technology for detection/quantification of VOCs in several applications. These past applied projects focus mainly on the calibration of the olfaction element through trial and error, and hence they lack the research required for gaining insight and overcoming the scientific challenges associated with the gas interaction with the surface of the microfluidic channel and selectivity of the technology. This Discovery Grant seeks support for a long-term vision of realization, optimization and robustification of this nonintrusive technology. This vision will be achieved by quantifying surface-gas interactions through rigorous numerical and experimental studies, taking ambient perturbations into account and taking data-driven science for feature identification and classification. The research can be organized in the following four tasks. Task 1 will involve modeling of gas adsorption along with diffusion in the microfluidic channel. Task 2 will involve the optimization of the surface coating in terms of hydrophobicity and gas polarity to maximize selectivity of the sensor. Task 3 will focus on fabrication of surfaces with complex hydrophobicity to enhance selectivity in a VOC mixture containing gases with different polarities. Task 4 will focus on data science methods including statistical and neural network techniques to model the complex input-output relationship of the artificial olfactory system. ***The proposed research will produce the necessary knowledge to further advance the microfluidic olfaction for real-time and accurate detection of gases. Followed by commercialization of the technology, this research will enable control of hazardous chemicals and noninvasive diagnosis, impacting the environment and life of Canadians. Also, the multifaceted research will provide numerous cutting-edge research opportunities for the trainees involved. Specialized in theory and applications of microfluidics and olfaction systems, they will have the proper training to hold key positions in academia and many industries including biomedical, environmental and energy sectors.