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

"Children learn any language that they grow up with, adapting to any of the ca. 7000 languages of the world, no matter how divergent or complex their structures are. What cognitive processes make this extreme flexibility possible? This is one of the most burning questions in cognitive science and the ACQDIV project aims at answering it by testing and refining the following leading hypothesis: Language acquisition is flexible and adaptive to any kind of language because it relies on a small set of universal cognitive processes that variably target different structures at different times during acquisition in every language. The project aims at establishing the precise set of processes and at determining the conditions of variation across maximally diverse languages. This project focuses on three processes: (i) distributional learning, (ii) generalization-based learning and (iii) interaction-based learning. To investigate these processes I will work with a sample of five clusters of languages including longitudinal data of two languages each. The clusters were determined by a clustering algorithm seeking the structurally most divergent languages in a typological database. The languages are: Cluster 1: Slavey and Cree, Cluster 2: Indonesian and Yucatec, Cluster 3: Inuktitut and Chintang, Cluster 4: Sesotho and Russian, Cluster 5: Japanese and Turkish. For all languages, corpora are available, except for Slavey where fieldwork is planned. The leading hypothesis will be tested against the acquisition of aspect and negation in each language of the sample and also against the two structures in each language that are most salient and challenging in them (e. g. complex morphology in Chintang). The acquisition processes also depend on statistical patterns in the input children receive. I will examine these patterns across the sample with respect to repetitiveness effects, applying data-mining methods and systematically comparing child-directed and child-surrounding speech."

1 998 438 €

Start date: 2014-09-01, End date: 2019-08-31

During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute ``wet'' nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, physical modelling and implementation in the wet-lab. The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems. Active-DNA, aims to address this challenge by achieving a number of objectives on computation, DNA-based self-assembly and molecular robotics. Active-DNA research work will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.

2 349 603 €

Start date: 2018-11-01, End date: 2023-10-31