Abstract

Biological systems have the unique ability to self-organize, respond to environmental stimuli, and generate autonomous motion and work. The fields of biomaterials and synthetic biology seek to recapitulate these remarkable properties of biological systems in in-vitro reconstitutions of biological systems, and in abiotic or biotic-abiotic hybrid materials to better understand the underlying rules of life and to predict the design principles of biomimetic smart materials. Motivated by this, we create bottom-up mathematical models, rooted in experiments, of network-based synthetic and biological materials. These encompass two-dimensional colloidal networks connected by rhythmic crosslinkers, and three-dimensional biopolymer networks assembled via depletion interactions, physical crosslinking, and adhesive proteins. We use Langevin Dynamics simulations to investigate the spatiotemporal evolution of these systems, probing and characterizing their emergent collective dynamics and structural properties. We refine our models by comparing our results with experimental data when available and make predictions of mechanisms driving the observed collective behavior and possibilities for modulation. By providing insights on what kinds of behavior to expect in different areas of the phase space, we use results from our model studies to help inform the rational design of bio-inspired soft materials with desired properties.

Library of Congress Subject Headings

Molecular dynamics--Mathematical models; Biomedical materials--Mathematical models; Self-assembly (Chemistry); Proteins--Crosslinking; Colloids

Publication Date

9-18-2023

Document Type

Dissertation

Student Type

Graduate

Degree Name

Mathematical Modeling (Ph.D)

Department, Program, or Center

Mathematical Sciences, School of

College

College of Science

Advisor

Moumita Das

Advisor/Committee Member

Poornima Padmanabhan

Advisor/Committee Member

Niels Otani

Campus

RIT – Main Campus

Plan Codes

MATHML-PHD

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