Biopolymers and their networks are fundamental to numerous biological and synthetic systems, with applications ranging from extracellular matrices in biological tissues to engineered nanostructured materials like cellulose-based nanocomposites. Understanding the dynamics of biopolymers in these networks is crucial due to their potential in material science and biotechnology, such as in developing sustainable materials and enhancing drug delivery mechanisms. The intricate network structures, from fibrous matrices in natural systems to designed frameworks in advanced materials, play a pivotal role in determining the mechanical and transport properties of the overall system.
This thesis delves into the dynamics of biopolymers, focusing specifically on the diffusion processes within such networks. The complexity of biopolymer behavior in networked environments involves multiple factors including polymer stiffness, network structure, and the interaction between biopolymer components. The diffusion of biopolymer fibres themselves, as well as nanoparticles within these networks, is explored through detailed coarse-grained molecular dynamics simulations. These simulations aim to model the nuanced interaction dynamics that influence diffusion, providing insights into how these factors affect biopolymer networks' rheological properties and functional capabilities.
This work contributes to the broader understanding of how biopolymers behave in complex environments by investigating the fundamental mechanisms of diffusion in biopolymer networks. It addresses the need for a deeper exploration of biopolymer dynamics to inform the design and synthesis of new biomaterials and bio-based materials. The findings from this thesis are expected to offer implications for enhancing the functionality of biopolymer-based systems in various applications, from improving the efficiency of biomaterials used in medical applications to optimizing the performance of bio-based composites in industrial applications.
QC240527
We demonstrate a framework of interpreting data from x-ray photon correlation spectroscopy experiments with the aid of numerical simulations to describe nanoscale dynamics in soft matter. This is exemplified with the transport of passive tracer gold nanoparticles in networks of charge-stabilized cellulose nanofibers. The main structure of dynamic modes in reciprocal space could be replicated with a simulated system of confined Brownian motion, a digital twin, allowing for a direct measurement of important effective material properties describing the local environment of the tracers.
QC 20230904
QC 20240521
Biopolymer network dynamics play a significant role in both biological and materials science. This study focuses on the dynamics of cellulose nanofibers as a model system given their relevance to biology and nanotechnology applications. Using large-scale coarse-grained simulations with a lattice Boltzmann fluid coupling, we investigated the reptation behavior of individual nanofibers within entangled networks. Our analysis yields essential insights, proposing a scaling law for rotational diffusion, quantifying effective tube diameter, and revealing release mechanisms during reptation, spanning from rigid to semiflexible nanofibers. Additionally, we examine the onset of entanglement in relation to the nanofiber flexibility within the network. Microrheology analysis is conducted to assess macroscopic viscoelastic behavior. Importantly, our results align closely with previous experiments, validating the proposed scaling laws, effective tube diameters, and onset of entanglement. The findings provide an improved fundamental understanding of biopolymer network dynamics and guide the design of processes for advanced biobased materials.
QC 20240216
QC 20240522