Computational Simulation of Self Assembly on Fixed Lattices

Presenter Information

Joy (Xinyue) Zhong, Oberlin College

Location

PANEL: Chemistry Honors: Pharmaceutics and Essential Biological Molecules
Science Center A126, Nancy Schrom Dye Lecture Hall

Document Type

Presentation - Open Access

Start Date

5-13-2022 3:00 PM

End Date

5-13-2022 5:00 PM

Abstract

The phenomenon self-assembly occurs when the molecules spontaneously form an organized structure due to interactions among themselves. This project studies this phenomenon by looking at the ways that a totally self-assembled system arises. Simulations were seeded with systems of randomly oriented identical agents on fixed lattices. The agents were designed to only interact with their nearest neighbors through magnetic dipole-dipole interactions. Then, the metropolis algorithm was incorporated to drive the system to the energy frustration states. We surveyed the arising lowest-energy geometries of such systems with a range of complexity combinations and characterized the patterns that the geometries established. This project served as a foundational study in understanding the mechanism of self-assembly, providing a geometrical basis for potential experimental design in materials chemistry.

Keywords:

Self Assembly, Computation, Geometry

Project Mentor(s)

Manish Mehta, Chemistry and Biochemistry

2022

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May 13th, 3:00 PM May 13th, 5:00 PM

Computational Simulation of Self Assembly on Fixed Lattices

PANEL: Chemistry Honors: Pharmaceutics and Essential Biological Molecules
Science Center A126, Nancy Schrom Dye Lecture Hall

The phenomenon self-assembly occurs when the molecules spontaneously form an organized structure due to interactions among themselves. This project studies this phenomenon by looking at the ways that a totally self-assembled system arises. Simulations were seeded with systems of randomly oriented identical agents on fixed lattices. The agents were designed to only interact with their nearest neighbors through magnetic dipole-dipole interactions. Then, the metropolis algorithm was incorporated to drive the system to the energy frustration states. We surveyed the arising lowest-energy geometries of such systems with a range of complexity combinations and characterized the patterns that the geometries established. This project served as a foundational study in understanding the mechanism of self-assembly, providing a geometrical basis for potential experimental design in materials chemistry.