• amphiphilic
• chemisrty
• computational
• copolymers
• dynamics
• enhanced
• fluorinated
• folding
• metadynamics
• molecular
• nanoparticles
• sampling
• self
• thermoresponsive

This thesis investigates single-chain nanoparticles (SCNPs), soft nanomaterials formed via self-folding of amphiphilic copolymers, with applications in catalysis, nanomedicine, and environmental remediation. SCNPs exhibit unique properties due to their controlled morphology and dynamic behavior, making them ideal for molecular encapsulation and selective ion capture. By combining computational chemistry, molecular dynamics (MD) simulations, and statistical mechanics, this work examines the folding mechanisms, thermodynamic properties, and structural dynamics of SCNPs in aqueous environments. The study uses enhanced sampling techniques, such as Metadynamics, to overcome free-energy barriers and explore folding pathways, employing the radius of gyration as a key collective variable. Simulations on PEGMA-co-FA copolymers reveal the formation of nanopockets critical for host-guest interactions. Markov State Models (MSMs) provide insights into the kinetics of folding. Key results highlight SCNPs’ potential for sustainable metal-ion sequestration, leveraging reversible aggregation at temperatures above the cloud point for efficient recovery and reuse. This thesis establishes a computational framework for designing functional SCNPs, offering pathways for future experimental validation and novel applications in green chemistry and biocompatible materials.