Working in collaboration with other departments within the university, the group are developing femtosecond laser-based soft X-ray sources. The X-ray source can be used for high-resolution imaging, with the aim of probing the shape of single proteins and other nanoscale objects, and also for ultrafast time-resolved measurements, as the pulses are less that 10fs long. The source is based on a high-power femtosecond laser, which produces ultrafast soft X-ray pulses via high harmonic generation.
All PhD Projects:
Supervisor: Dr W.S. Brocklesby
Co-Supervisor: Professor J Frey
A new area of imaging has recently been opened up which uses coherent light to illuminate objects, and computer algorithms to analyse the scattered light and generate images. Developments in ultrafast lasers have made sources of coherent soft X-rays possible in the lab, rather than relying on large-scale installations like synchrotrons. The combination of these two techniques has been successful in producing a new generation of X-ray microscopes, and at Southampton we have been at the forefront of this development. In particular, we have chosen areas of biology where imaging below the 100nm length scale can provide new information about processes occurring within cells.
Recently, the idea of combining algorithmic image reconstruction techniques with techniques based on machine learning has been proposed. Many of the problems of image reconstruction are similar to those addressed by machine learning (ML), particularly using convolutional neural networks. We aim in this project to use soft X-ray scattering and a combination of algorithmic and ML-based computer techniques to develop new ways of imaging, particularly in the area of biological science.
As part of the project you will become familiar with high-energy ultrafast laser science, using lasers with pulse lengths below 50 femtoseconds and peak powers in the terawatt regime, and you will also be trained in the use of algorithmic and ML techniques for data analysis and image reconstruction. Significant research expertise in both high-energy ultrafast lasers and machine learning exists in Southampton, and this project will involve working with members of the EPSRC-funded AI for Scientific Discovery network.
Supervisory team: W.S. Brocklesby, J.G. Frey (Chemistry), K. Deinhardt (Biological sciences)
Within the healthy brain, neurons form large, highly controlled communication networks with multiple other cells. Study of the structure of neurons on a scale less than 100 nm is challenging. Within our research group we have developed an ultrafast coherent soft X-ray source, based on a high-energy femtosecond pulsed laser, which can be used for high resolution imaging at the nanometer scale, and we have demonstrated the first ever application of such a source to biological structures. The new technique of coherent X-ray imaging uses a combination of femtosecond X-ray pulses and sophisticated computational algorithms to calculate images from X-rays scattered from the object as the X-ray beam is moved, known as ptychography.
The aim of this studentship is to interweave the multi-disciplinary strands of X-ray physics, ptychographic image analysis and neuroscience in order to observe neuronal structures at a resolutions of 50nm and below, which will allow us to study fundamental functions and uncover pathological mechanisms and early morphological changes, such as those which can cause neurodegenerative diseases.
The student will benefit from the multi-disciplinary nature of their supervisory team, and act as a point of crystallisation for the application of nanometre-resolution imaging technologies to the nanometre-scale neuronal molecular machines whose properties are fundamental to brain function. The student will gain experience in high-energy femtosecond lasers, confocal fluorescence microscopy techniques, and development and application of ptychographic image reconstruction algorithms. Dependent on funding, the project may extend to work with the Rosalind Franklin Institute, one of the UK’s leading research institutes in the area of biological imaging.