Stimuli-responsive polymers for application in molecular sensing
File(s)
Author(s)
Sander, Fiona
Type
Thesis
Abstract
Stimuli-responsive polymers with the ability to change their properties upon smallest changes in their environment are of strong interest for use in molecular sensors. Among these materials, liquid crystal polymers combine properties of both polymers and mesogens to achieve exceptional responses to a variety of stimuli such as light or temperature. The application of these materials for biosensing has been left largely unexplored despite their high potential in the healthcare and biomedical fields. Within this work we present new sensing methods employing both polymers and mesogens using computational and experimental approaches including Molecular Dynamics and Kinetic Monte Carlo methods with the aim to create novel biosensors.
To detect environmental changes we present a novel sensing mechanism based on the hybridisation of DNA and PNA. We show the suitability of hybridisation-based detection of DNA and demonstrate the strong dependence of the gyration radius on the percentage of double-stranded DNA, thus utilising simple polymer physics for the development of new biosensing solutions, exploiting both computational and experimental methods.
Following the development of sensing mechanisms, the polymerisation process of functional polymeric materials is analysed. To optimise the time intensive polymer synthesis and enable computational research of close-to-reality systems, a Kinetic Monte Carlo method is proposed within the frame of this thesis which enables simulation of RAFT polymerisations resulting in linear, block or gradient co-polymers. The model predicts polydispersity, composition and structure of the polymer while also offering differentiation between polymer species for detailed analysis of the process. A computational tool for simple, fast and effective parameter studies is presented with the aim of finding optimum polymerisation conditions for desired polymeric products. This leads to a dramatic reduction of time spent on experimental studies prior to successful synthesis in the lab.
Based on these outcomes, a Molecular Dynamics (LAMMPS) model is presented for assessment of the influence of polydispersity and persistence length on the formation of liquid crystalline phases within a stimuli-responsive polymer. We show, that environmental stimuli affect the liquid crystalline behaviour in the polymeric materials significantly. As the first study on these aspects of stimuli-responsive polymers, the results presented here suggest a high potential for the application of such materials in optical biosensing of DNA and environmental parameters including pH and temperature. In conclusion, within the frame of this thesis, sensing mechanisms are explored both experimentally and computationally, a Kinetic Monte Carlo procedure to predict properties in functional polymers is proposed and liquid-crystalline polymers for application in biosensing are developed based on Molecular Dynamics simulations.
To detect environmental changes we present a novel sensing mechanism based on the hybridisation of DNA and PNA. We show the suitability of hybridisation-based detection of DNA and demonstrate the strong dependence of the gyration radius on the percentage of double-stranded DNA, thus utilising simple polymer physics for the development of new biosensing solutions, exploiting both computational and experimental methods.
Following the development of sensing mechanisms, the polymerisation process of functional polymeric materials is analysed. To optimise the time intensive polymer synthesis and enable computational research of close-to-reality systems, a Kinetic Monte Carlo method is proposed within the frame of this thesis which enables simulation of RAFT polymerisations resulting in linear, block or gradient co-polymers. The model predicts polydispersity, composition and structure of the polymer while also offering differentiation between polymer species for detailed analysis of the process. A computational tool for simple, fast and effective parameter studies is presented with the aim of finding optimum polymerisation conditions for desired polymeric products. This leads to a dramatic reduction of time spent on experimental studies prior to successful synthesis in the lab.
Based on these outcomes, a Molecular Dynamics (LAMMPS) model is presented for assessment of the influence of polydispersity and persistence length on the formation of liquid crystalline phases within a stimuli-responsive polymer. We show, that environmental stimuli affect the liquid crystalline behaviour in the polymeric materials significantly. As the first study on these aspects of stimuli-responsive polymers, the results presented here suggest a high potential for the application of such materials in optical biosensing of DNA and environmental parameters including pH and temperature. In conclusion, within the frame of this thesis, sensing mechanisms are explored both experimentally and computationally, a Kinetic Monte Carlo procedure to predict properties in functional polymers is proposed and liquid-crystalline polymers for application in biosensing are developed based on Molecular Dynamics simulations.
Version
Open Access
Date Issued
2022-12
Date Awarded
2023-08
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Angioletti-Uberti, Stefano
Publisher Department
Materials
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)