UCL Logo
Page tree
Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 6 Next »

Surface charge on insulators

Supervisors: Sergio Bertazzo, Elena Tsolaki


Electrostatic induction phenomena have been studied for centuries and results are consolidated e.g. in Maxwell’s Treatise. Fundamental concept are well established and their application is straightforward for metals and semiconductors but not for insulators. Insulator electrostatic charging is hardly reproducible or predictable and this is related to the current lack of agreement on the nature of charge carriers in electrified insulators.

Current thinking considers that electrification of a dielectric arises from charge displacement within the solid under the action of an external electric field. A macroscopic electric dipole (or multipole) is thus formed, aligned with the field on which the solid is immersed. Following these ideas, charge displacement from one solid to another is held as the mechanism for electret formation by contact electrification.

The influence of the surrounding atmosphere on electrostatic phenomena is well-known but it is not well understood. Some reports describe the effect of water adsorption on polymer contact charging but it is interpreted as a modifying factor in the electron-pair donor-acceptor interactions that these authors hold responsible for contact charging.

These results led to the formulation of the following hypothesis: electrostatic phenomena under atmospheric conditions have a contribution from atmospheric ions as well as from excess ions generated by charging of adsorbed water. Atmospheric ions are charge carriers that migrate under the action of electric fields, distribute within electric potential gradients according to Poisson-Boltzmann equation, adsorb on solid and liquid surfaces, and discharge electrochemically on metal and semiconductor surfaces.

The project will consist to design and create an electrical isolated apparatus to measure the build-up and dissipation of electrical charges in insulators. The student need to be trained at the Institute of Making and will use its facilities for the project. The student will participate in the development of the project, experimental measurements, analysis of the data and interpretation. This is an experimental research project where laboratory experience is a plus but not a requirement.

Developing a Phase Unwrapping Technique for MRI Using Machine Learning

Supervisors: Barbara Dymerska, Karin Shmueli


The signal in Magnetic Resonance Imaging (MRI) has two constituents: magnitude and phase. In most clinical MRI studies, only the magnitude information is used. Recently, there has been rapid development of MRI methods which utilise the phase as it can be used to increase image contrast, correct image distortions or provide information about the tissue magnetic properties (e.g. in quantitative susceptibility mapping). Phase image processing is not trivial as the range of phase values which can be measured in MRI is limited to 2π radians. This means that any phase value larger than 2π is wrapped back into this range and phase unwrapping methods are necessary to recover the true phase values. Existing unwrapping methods are often time-consuming and fail in regions which are noisy or have strong phase variations. The initial aim of this project is to develop realistic numerical models of phase variations in the human brain. These models will then be used to train a convolutional neural network to give a fast and robust solution to the phase unwrapping problem and compare it against existing unwrapping algorithms. This project, in a fast-moving and exciting research area, will give you an insight into MRI signal properties, MRI image processing, Matlab programming and machine learning algorithms.

Characterising phantoms for elastography

Supervisors: Peter Munro and Pilar Garcia Souto

Student: Ana-Maria Nicolaie

Optical Coherence Elastrography obtains images of the mechanical properties of tissue and is performed by using Optical Coherence Tomography to image how tissue deforms in response to a mechanical load. A crucial part of this project is the development of phantoms with controllable mechanical properties. This project entails the construction of such phantoms along with their characterisation using an instron machine which provides gold standard characterisation of the mechanical properties of materials. This project is largely experimental, though an elementary understanding of continuum mechanics will be beneficial.

  • No labels