ERC FUNDED PROJECTS

My vision is to establish, within the framework of an ERC CoG, a multidisciplinary group which will work in concert towards pioneering the integration of novel 2-Dimensional nanomaterials with novel additive fabrication techniques to develop a unique class of energy storage devices. Batteries and supercapacitors are two very complementary types of energy storage devices. Batteries store much higher energy densities; supercapacitors, on the other hand, hold one tenth of the electricity per unit of volume or weight as compared to batteries but can achieve much higher power densities. Technology is currently striving to improve the power density of batteries and the energy density of supercapacitors. To do so it is imperative to develop new materials, chemistries and manufacturing strategies. 3D2DPrint aims to develop micro-energy devices (both supercapacitors and batteries), technologies particularly relevant in the context of the emergent industry of micro-electro-mechanical systems and constantly downsized electronics. We plan to use novel two-dimensional (2D) nanomaterials obtained by liquid-phase exfoliation. This method offers a new, economic and easy way to prepare ink of a variety of 2D systems, allowing to produce wide device performance window through elegant and simple constituent control at the point of fabrication. 3D2DPrint will use our expertise and know-how to allow development of advanced AM methods to integrate dissimilar nanomaterial blends and/or “hybrids” into fully embedded 3D printed energy storage devices, with the ultimate objective to realise a range of products that contain the above described nanomaterials subcomponent devices, electrical connections and traditional micro-fabricated subcomponents (if needed) ideally using a single tool.

2 499 942 €

Start date: 2016-10-01, End date: 2021-09-30

In todays advanced technological world, we can track the exact movement of individuals, analyse their genetic makeup and predict predisposition to certain diseases. However, we are unable to accurately assess an individual’s dietary intake. This is without a doubt one of the main stumbling blocks in assessing the link between diet and disease/health. The present proposal (A-DIET) will address this issue with the overarching objective to develop novel strategies for assessment of dietary intake. Using approaches to (1) identify biomarkers of specific foods (2) classify people into dietary patterns (nutritypes) and (3) develop a tool for integration of dietary and biomarker data, A-DIET has the potential to dramatically enhance our ability to accurately assess dietary intake. The ultimate output from A-DIET will be a dietary assessment tool which can be used to obtain an accurate assessment of dietary intake by combining dietary and biomarker data which in turn will allow investigations into relationships between diet, health and disease. New biomarkers of specific foods will be identified and validated using intervention studies and metabolomic analyses. Methods will be developed to classify individuals into dietary patterns based on biomarker/metabolomic profiles thus demonstrating the novel concept of nutritypes. Strategies for integration of dietary and biomarker data will be developed and translated into a tool that will be made available to the wider scientific community. Advances made in A-DIET will enable nutrition epidemiologist’s to properly examine the relationship between diet and disease and develop clear public health messages with regard to diet and health. Additionally results from A-DIET will allow researchers to accurately assess people’s diet and implement health promotion strategies and enable dieticians in a clinical environment to assess compliance to therapeutic diets such as adherence to a high fibre diet or a gluten free diet.

1 995 548 €

Start date: 2015-08-01, End date: 2020-07-31

The proposed work concerns the theoretical and numerical development of robust and adaptive methodologies for broadband imaging in clutter. The word clutter expresses our uncertainty on the wave speed of the propagation medium. Our results are expected to have a strong impact in a wide range of applications, including underwater acoustics, exploration geophysics and ultrasound non-destructive testing. Our machinery is coherent interferometry (CINT), a state-of-the-art statistically stable imaging methodology, highly suitable for the development of imaging methods in clutter. We aim to extend CINT along two complementary directions: novel types of applications, and further mathematical and numerical development so as to assess and extend its range of applicability. CINT is designed for imaging with partially coherent array data recorded in richly scattering media. It uses statistical smoothing techniques to obtain results that are independent of the clutter realization. Quantifying the amount of smoothing needed is difficult, especially when there is no a priori knowledge about the propagation medium. We intend to address this question by coupling the imaging process with the estimation of the medium's large scale features. Our algorithms rely on the residual coherence in the data. When the coherent signal is too weak, the CINT results are unsatisfactory. We propose two ways for enhancing the resolution of CINT: filter the data prior to imaging (noise reduction) and waveform design (optimize the source distribution). Finally, we propose to extend the applicability of our imaging-in-clutter methodologies by investigating the possibility of utilizing ambient noise sources to perform passive sensor imaging, as well as by studying the imaging problem in random waveguides.

690 000 €

Start date: 2010-06-01, End date: 2015-11-30

"Ageing is the gradual and irreversible breakdown of living systems associated with the advancement of time, which leads to an increase in vulnerability and eventual mortality. Despite recent advances in ageing research, the intrinsic complexity of the ageing process has prevented a full understanding of this process, therefore, ageing remains a grand challenge in contemporary biology. In AGELESS, we will tackle this challenge by uncovering the molecular mechanisms of halted ageing in a unique model system, the bats. Bats are the longest-lived mammals relative to their body size, and defy the ‘rate-of-living’ theories as they use twice as much the energy as other species of considerable size, but live far longer. This suggests that bats have some underlying mechanisms that may explain their exceptional longevity. In AGELESS, we will identify the molecular mechanisms that enable mammals to achieve extraordinary longevity, using state-of-the-art comparative genomic methodologies focused on bats. We will identify, using population transcriptomics and telomere/mtDNA genomics, the molecular changes that occur in an ageing wild population of bats to uncover how bats ‘age’ so slowly compared with other mammals. In silico whole genome analyses, field based ageing transcriptomic data, mtDNA and telomeric studies will be integrated and analysed using a networks approach, to ascertain how these systems interact to halt ageing. For the first time, we will be able to utilize the diversity seen within nature to identify key molecular targets and regions that regulate and control ageing in mammals. AGELESS will provide a deeper understanding of the causal mechanisms of ageing, potentially uncovering the crucial molecular pathways that can be modified to halt, alleviate and perhaps even reverse this process in man."

1 499 768 €

Start date: 2013-01-01, End date: 2017-12-31