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The Washington Research Foundation Fellowship
Alex Vaschillo - Physics & Mathematics (Comprehensive), Chemistry (ACS Certified)
As an undergraduate student I have had many scientific interests - I have worked in fields ranging from physiology to biochemistry to synthetic chemistry before reaching my current position as a computational physicist. In my Sophomore year I joined the research group of professor David Masiello; for two years we have worked together to understand how metal nanoparticles absorb, transport, and scatter electromagnetic energy. We have discovered fundamental symmetries behind the selection rules that govern how different electromagnetic stimuli interact with nanoparticles, and have designed an intuitive theoretical model that explains the electromagnetic response of metal nanoparticles. I am currently working on extending this model to better understand recently observed large magnetic responses of cyclic nanoparticle systems. I hope that as a result of my work I will be able to design nanoparticle systems with arbitrary magnetic responses, opening new doors in rapidly-growing fields such as single-molecule sensing and electromagnetic cloaking.
Mentors: David Masiello, Chemistry
Project Title: A Study of the Excitation and Decay Pathways of Plasmonic Resonances
Abstract: Collective oscillations of conduction electrons in metal nanoparticles, known as localized surface plasmon resonances (LSPRs), have been the source of much scientific study over the last decade due to their immediate and significant applications in chemical catalysis, drug delivery, and cancer reduction therapy. In previous studies we have thoroughly analyzed the radiative decay pathways of both light- and electron beam- induced LSPRs and have implemented a computational model to simulate LSPR generation and decay. The purpose of this work is to study the nonradiative decay pathways of LSPRs, specifically heat, which govern many of the aforementioned applications. We propose to simulate the heating of nanoparticles by computationally solving the driven heat equation under the discrete (thermal) dipole approximation. Much previous literature has solved the driven heat equation using approaches such as the finite elements method and boundary value method, but these are computationally inefficient for large systems. This work proposes an approach that is analogous to our simulation of radiative LSPR decay and eliminates the need to discretize the medium and thus vastly reduces computational time. Upon successful implementation of a predictive computational model we will be able to study the relationships between radiative and nonradiative decay pathways of LSPRs.