Engineering the future of Hybrid Materials with Coarse-Grained Molecular Dynamics

The rapid evolution of hybrid materials has opened new frontiers in materials science by combining the distinct properties of polymers, nanoparticles, ceramics, metal oxides, and biomolecules to create adaptable, high-performance systems tailored to complex applications. These materials are critical in areas such as energy storage, environmental sustainability, and biomedical engineering, where conventional single-component materials often fall short of the required versatility and performance. A key tool for understanding and designing these complex materials is coarse-grained (CG) molecular dynamics (MD) which allows researchers to capture molecular-level interactions while efficiently modeling larger, structurally diverse systems over longer timescales, bridging the gap between atomic-level insights and macroscopic material properties. This work advances CG MD methodologies by developing chemically mapped, transferable models tailored to a broad library of polymers, lipids, and biomolecules. These models provide predictive insights into the behavior of hybrid systems, focusing on critical transitions and structural responses to external stimuli. For example, the simulation of thermosensitive polymers such as poly(N-isopropylacrylamide) (PNIPAM) reveals key mechanisms underlying coil-to-globule transitions and self-assembly behaviors, which are essential for applications in drug delivery and responsive materials. Our studies further address experimentally observed, complex behaviors in hybrid materials, such as carbohydrate-protein binding dynamics in glycopolymers, by using CG MD simulations to decode structure-function relationships that govern molecular recognition and interaction efficiency. These simulations showcase the significance of factors such as glycan density in enhancing solvent accessibility, which directly impacts binding affinities and bioactivity. In parallel, CG model development efforts are directed at physically representing lipid bilayer systems, facilitating the simulation of cellular interfaces and hybrid membrane systems. By optimizing parameters with advanced techniques like particle swarm optimization (PSO), these CG models replicate key experimental properties such as bilayer thickness, area per lipid, and bending rigidity, ensuring transferability across diverse conditions. Collectively, this dissertation showcases the strategic development and application of CG MD models for hybrid materials, highlighting the ability of molecular simulations to guide the rational design of materials with tailored functionalities. The methodologies established here lay the groundwork for next-generation CG MD studies, aiming to bridge experimental findings with computational insights to drive innovation in hybrid material science.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Chemical Engineering

Department dc:contributor.department

Chemical Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2025

Author dc:creator

• Joshi, Soumil Yogesh

Chair dc:contributor.committeechair

• Deshmukh, Sanket A.

Committee members dc:contributor.committeemember

• Whittington, Abby Rebecca
• Achenie, Luke E. K.
• Ashkar, Rana

• coarse-grained molecular dynamics
• thermosensitive polymers
• force-field development
• glycomaterials

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:44611

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/137807