The project aims to interlink computer simulations with laboratory experiments to design star polymers with enhanced transfection efficiency. Finally, machine learning techniques will be used to predict the behaviour of these materials to further streamline the design process.

As their name suggests Liquid Crystal Elastomers combine properties of both liquid crystals and elastomers resulting in unique properties which offer possible application in fields ranging from soft robotics and medical applications to highly sensitive sensors. Liquid crystals show changes of optical properties even upon small changes in their environment which makes them highly relevant for use in sensors. In combination with elastomers completely new mechanical properties arise which enable mechanical actuation upon certain stimuli with neglectable energy cost amplyfying extremely small changes to a macroscopic level. This characteristic gives them high relevance for sensoring application.

The research project is focussing on the use of stimuli-responsive polymers in combination with liquid crystals. In the literature only a small range of different polymers and combination of liquid crystal and polymer responsitivity has been investigated. Therefore the exploration of the use of responsive polymers in combination with liquid crystals is of high interest whereas a focus is laid upon molecular sensoring in order to detect specific molecules. This can be of high interest for example in analysis of water qualities in an easy, fast and affordable manner.

The articular cartilage found covering the ends of bones in the synovial joints of mammals exhibit exceptional tribological properties, giving a low friction response (μ = 0.001) even when subjected to normal loads exceeding 100 atm. The goal of this project is to use coarse-grained molecular dynamics in order to study the system focusing on the architecture of the polymers on the surface and thus provide rational design principles for cartilage analogues.

When developing targeted diagnostics, the aim is to create probes that are as selective as possible which can aid in the early and accurate detection of disease. This can be greatly enhanced through the use of multivalent probes that exhibit superselective interactions towards the target of choice. In this study the interactions of functionalised gold nanoparticles and biological receptors in the form of proteins on the surface of exosomes and exosome derived supported lipid bilayers (SLBs) are characterised via acoustic techniques. The binding information collected will be used to create theoretical models that will feed into the design of highly selective biosensors.

The use of plasmonic materials for fluorescent biosensing has been exemplified countless times over the last two decades. Small improvements are made as new nano-fabrication techniques are implemented, but most support the same argument: Plasmonic metals increase fluorescent signals. As large scale manufacturing becomes more feasible and cost-effective, it is now crucial to determine which factors are necessary. The goal of this work is to use Fourier difference time domain (FDTD) and Green's Dyadic Function (GDF) modelling to predict the success of a given substrate on fluorescence enhancement. Modelled data is verified using patterned thin films, electron energy loss spectroscopy, photoluminescence, and flurophore conjugated AFM tips. Together a system is developed that can predict (i) deviations in biosensor concentration measurements, (ii) optimal positioning of flurophores, and (iii) possibilities for dual mode imaging. When used in combination with Bayesian statistics and optimisation algorithms, pivotal design questions can be answered that have so far been taken for granted.

For example: Is the best approach for a plasmonic biosensor truly to reach the highest enhancement? Or does this result in large deviations that bring large errors into identifying a specific concentration? By addressing this problem now, before widespread implementation, research backed decisions can be made about the validity of individual structures as biosensors.

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He will write more once he has done some reading!