The key aim of this project is to understand and utilise optically-produced forces on the atomic scale through pico-photonics, in order to devise future nano-mechanisms and nano-machines. Key goals are to move individual metal atoms by light, twist and compress and flip individual molecules on demand, and provide a step-change in the comprehension of how ions, solvent, molecules and electrons interact at interfaces, which is critical in catalysis, molecular electronics, electrochemistry, and nano-assembly.

Huntington´s disease (HD) is one of the nine neurodegenerative diseases (ND) caused by (CAG)n trinucleotide tract expansions that encode abnormally long polyglutamine (polyQ) tracts. The common features shared by many ND are the misfolding and aggregation of toxic proteins. Thus, HD recapitulates features of other, more complicated ND. As HD is an autosomal dominant disorder, modeling this disease in vitro and in vivo is straightforward. Unfortunately, HD is, to date, incurable and there are no drugs or therapies that are known to slow or prevent the disease. Thus, the strategies proposed in this project, taking advantage of the unique characteristics of the zebrafish as model organism to study human diseases, will allow me to gain a deeper understanding of its pathogenesis, and to generate tools to accelerate the development of new therapies. Moreover, my findings may have relevance to other ND. First, I propose to generate new zebrafish transgenic lines expressing different forms of human huntingtin (htt) (wild-type/mutant, full-length/exon1) fused to the photoconvertible fluorescent protein Dendra in whole body, neurons or glial cells using the UAS-GAL4 system. Next, I will validate the construct integration in the fish genome and characterize the transgenic lines. After that, I will use these new generated models to study the life cycles of the previously mentioned forms of htt in vivo, and I will examine their clearance kinetics in vivo in different tissues in the context of inhibition/stimulation of autophagy or ubiquitin-proteasome pathways. Moreover, I will assess the role played by the inflammasome in the context of the neuroinflammation present in HD. Finally, I will use these new zebrafish lines to test novel therapeutic targets recently identified in the host lab, in order to develop new treatments for HD.

Research in the field of micro and nanotechnology has led to the development of materials with fundamentally new or improved functionality, which have the potential to revolutionise electronics, drug delivery, water purification, and energy storage. These scientific discoveries can help address many of the grand challenges our society is facing, but unfortunately, too few of these new materials are implemented in real commercial devices. This is not because of a lack of interest or commercial potential, but often because there are no manufacturing methods available that allow for controlled processing of these materials at scale. This project aims to address this challenge by developing advanced nano and microstructures directly on a scalable Roll-to-Roll manufacturing platform, rather than considering manufacturing as an after-thought. This will be achieved by following a methodical approach, where material organisation is optimised from the bottom-up, starting with the nanoscale chemical material composition, followed by the microscale particle morphology, and finally their large area coating using Roll-to-Roll manufacturing. This hierarchical material build-up will be achieved by taking advantage of emerging scientific insights in robust self-assembly processes, combined with novel coating processes to allow for precise control over the particle flow and assembly on Roll-to-Roll. Our Roll-to-Roll process will be optimised to manufacture Li-Ion batteries with new form factors that allow the enhancement of their volumetric performance. This project will demonstrate for the first time how complex hierarchical battery electrodes can be manufactured with a continuous process. These batteries are important to support the EU’s strong automotive industry as it transitions to electric vehicles, and therefore this project will contribute to the EU economy as well as to the de-carbonisation of our society.

Urban soil contamination resulting from former land-use is important but challenging to measure. Direct measurements are expensive and time-consuming to acquire, making a city-wide assessment impossible. Current statistical methods for modelling the distribution of pollution in urban environments, such as kriging, often fail to do so properly, since the contamination is highly local and uncorrelated with the surroundings. The problems can be mitigated by using multi-output models, such as co-kriging, where several datasets are modelled concurrently. The methods are, however, slow to train and have limited flexibility. DeepGeo will develop state-of-the-art methods for assessing urban soil contamination and provide an open-source software library for geostatistical data analysis, directly making the novel discoveries available to a wide audience. DeepGeo aims to solve the mentioned problems by the use of deep Gaussian processes for estimating urban soil pollution. This recently developed class of models promises enormous flexibility and can model highly nonlinear correlations between outputs, making them far superior to standard co-kriging. They do, however, suffer from scalability issues and empirical studies show flexibility issues with increasing depth. DeepGeo will address the scalability issue by developing new algorithms for approximate inference and for inducing sparsity. Inspired by recent advances in training of deep neural networks, specialised covariance functions that allow for deeper Gaussian process architectures will be constructed. Finally, new and improved methods for learning complicated correlations between outputs will be investigated, thus increasing the amount of information that can be gained from already available data. By making the developed methods available as open-source software, DeepGeo seeks to reach a broad range of research fields as well as benefitting the geochemical industry.