Sensing and Controlling Liquids in Ordered Porous Materials

Sensing;Machine Learning;Adaptive;Sniffing;Colorimetric;Microfluidics;Emulsification

Brandt, Soeren ; Aizenberg, Joanna

University:Havard University

Department:Engineering and Applied Sciences - Applied Physics

关键词: Sensing;    Machine Learning;    Adaptive;    Sniffing;    Colorimetric;    Microfluidics;    Emulsification;   

Others  :  https://dash.harvard.edu/bitstream/handle/1/37365893/BRANDT-DISSERTATION-2020.pdf?sequence=1&isAllowed=n

美国|英语

来源: Digital Access to Scholarship at Harvard

【 摘 要 】

The ability to sense and control liquid behavior is integral to applications in the transportation of hazardous materials, chemical analysis, medical diagnostics, cosmetics, food, and pharmaceuticals. Here, I will discuss different approaches to combine order and porosity to take advantage of capillary forces and structural color to sense liquids, and the role of pore shape on droplet formation in membranes and microfluidics. In these systems, porosity becomes a tuning parameter that affects the pressure differences that drive the adsorption, wetting, and flow. In Bragg stacks, porosity enhances the adsorption of liquid vapors that results in a characteristic color change that we interpret using machine learning and determine the properties of liquid mixtures. In contrast, the well-defined geometry of inverse opal pores controls the infiltration of liquids based on a wetting-threshold which enables fast, easy-to-read sensing. In microfluidics, channels of non-uniform width increase pressure oscillations between channels leading to oscillatory formation of multiple droplet sizes. I will describe the design and mechanisms of these materials in detail and discuss the emerging properties of porosity. The examples in this dissertation are meant to highlight some of the diversity of applications for ordered porous materials in sensing and droplet production.