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Publication Date

Fall 2025

Degree Type

Thesis - Campus Access Only

Degree Name

Master of Science (MS)

Department

Chemistry

Advisor

Gianmarc Grazioli; Ningkun Wang; Resa Kelly

Abstract

Our research aims to accomplish two tasks: to expand on existing simulation techniques to model amyloid fibril formation and to diminish the gap between the modeling techniques used in research and in education. Network Hamiltonian Models (NHMs) have shown success in modeling the self-assembly of amyloid fibrils at a low computational cost by coarse-graining the proteins to singular interacting bodies whose multi-body interactions are dictated by a network statistic of an exponential-family random graph model (ERGM). These models are purely topological; therefore, this research aims to improve model detail by incorporating explicit space through a Lennard-Jones fluid representation. To achieve a high degree of accuracy, the Lennard-Jones potential is parameterized using the potential mean force (PMF) of the amyloid fibril. This allows the parameters to incorporate a global energy change rather than the traditional pair-wise potential, as the PMF relates the change in free energy to a change in reaction coordinate. However, the simplicity of the pair-wise potential of a Lennard-Jones simulation can be used to integrate molecular dynamics techniques into the classroom. Thus, this research also proposes high school chemistry laboratory activity incorporating a Lennard-Jones simulation of Helium using the molecular dynamics software LAMMPs. The learning activity provides students with an opportunity to develop an understanding of the simulation technique and the chemical concept of real and. ideal gasses. A pre and posttest was used to assess the effectiveness of molecular dynamics simulations in teaching high school AP Chemistry students.

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