Fiber Optic Monitoring of Fluid Evaporation
Abstract: Monitoring the dynamics of droplet evaporation has diverse potential applications, such as surface characterization and combustion efficiency of fuels. Two different concepts for the fiber-optic recognition and analysis of fluids were proposed, analyzed and experimentally demonstrated. The methods are based on the dynamically-varying interaction between the fluid, the surface to which it is applied and its surroundings.
In one method, sub-nano-liter volumes of a liquid are applied to inline fiber-optic micro-cavities. As the liquid evaporates, light is refracted out of the cavity at the receding index boundary between the fluid and the ambient surroundings. A sharp transient attenuation in the transmission of light through the cavity, by as much as 50 dB and on a sub-second time scale, is observed. Numerical models for the transmission dynamics in terms of ray-tracing and wavefront propagation are provided.
In a second method, the interference fringes of reflections from a sub nano-liter pendent droplet at the tip of a standard fiber are used for the monitoring the evaporation. The technique is simple to implement and requires no instrumentation in the immediate vicinity of the fluid. The technique was validated against the traditional method of evaporation monitoring using direct observation in a contact-angle goniometer. The evaporation of water – ethanol mixtures was studied, and three different evaporation phases were detected. The evaporation rate in the first phase was found to be linearly dependent on the relative concentration of water, and accuracy of 2% was achieved in the estimation of the mixing ratio.
Lastly, a hydrophobic self-assembled monolayer coating was deposited on the fiber tip. A comparative study of the evaporation of ten organic solvent from a bare fiber and a coated fiber demonstrated the connection between the evaporation dynamics and the polarity of the liquid. The evaporation time and the initial droplet length were successfully used in fluid recognition, through clustering analysis.
* The research presented in the seminar was carried out towards the M.Sc. degree in Electrical Engineering, with the supervision of Dr. Avi Zadok