Abstract

It has been theorized that Quantum Dots (QD) can solve the temperature sensor issue with microfluidic devices. Quantum Dots are nano-sized semiconducting crystals with a radius of an excited electron-hole pair. When a QD is excited by a short wavelength light, the QD produces fluorescent light. As the temperature of the dot changes, the dot expands and shifts the fluorescent spectrum. Quantum Dots are small enough to be placed inside the microfluidic devices, and a spectrometer can measure the change in fluorescent data. This fluorescent data can be used to create fluorescent images corresponding to the QD temperature. These fluorescent images can then be used to create temperature maps. Fluorescent images created by QDs have been used with curve-fitting techniques to create temperature maps with accuracy near 1\textdegree K RMSE. When using neural networks that take advantage of the spacial properties of the image, a sub 1\textdegree K RMSE has been achieved. When the neural network architecture mimics heat diffusion and uses known physics equations, an accuracy of 0.03619\textdegree K RMSE has been reached on microfluidic chips.

Degree

PhD

College and Department

Computational, Mathematical, and Physical Sciences; Computer Science

Rights

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