ERC FUNDED PROJECTS

Computational Electromagnetics (CEM) is the scientific field at the origin of all new modeling and simulation tools required by the constantly arising design challenges of emerging and future technologies in applied electromagnetics. As in many other technological fields, however, the trend in all emerging technologies in electromagnetic engineering is going towards miniaturized, higher density and multi-scale scenarios. Computationally speaking this translates in the steep increase of the number of degrees of freedom. Given that the design cost (the cost of a multi-right-hand side problem dominated by matrix inversion) can scale as badly as cubically with these degrees of freedom, this fact, as pointed out by many, will sensibly compromise the practical impact of CEM on future and emerging technologies. For this reason, the CEM scientific community has been looking for years for a FFT-like paradigm shift: a dynamic fast direct solver providing a design cost that would scale only linearly with the degrees of freedom. Such a fast solver is considered today a Holy Grail of the discipline. The Grand Challenge of 321 will be to tackle this Holy Grail in Computational Electromagnetics by investigating a dynamic Fast Direct Solver for Maxwell Problems that would run in a linear-instead-of-cubic complexity for an arbitrary number and configuration of degrees of freedom. The failure of all previous attempts will be overcome by a game-changing transformation of the CEM classical problem that will leverage on a recent breakthrough of the PI. Starting from this, the project will investigate an entire new paradigm for impacting algorithms to achieve this grand challenge. The impact of the FFT’s quadratic-to-linear paradigm shift shows how computational complexity reductions can be groundbreaking on applications. The cubic-to-linear paradigm shift, which the 321 project will aim for, will have such a rupturing impact on electromagnetic science and technology.

2 000 000 €

Start date: 2017-09-01, End date: 2023-08-31

The fundamental 3D-BioMat project aims at providing a biomineralization model to explain the formation of microscopic calcareous single-crystals produced by living organisms. Although these crystals present a wide variety of shapes, associated to various organic materials, the observation of a nanoscale granular structure common to almost all calcareous crystallizing organisms, associated to an extended crystalline coherence, underlies a generic biomineralization and assembly process. A key to building realistic scenarios of biomineralization is to reveal the crystalline architecture, at the mesoscale, (i. e., over a few granules), which none of the existing nano-characterization tools is able to provide. 3D-BioMat is based on the recognized PI’s expertise in the field of synchrotron coherent x-ray diffraction microscopy. It will extend the PI’s disruptive pioneering microscopy formalism, towards an innovative high-throughput approach able at giving access to the 3D mesoscale image of the crystalline properties (crystal-line coherence, crystal plane tilts and strains) with the required flexibility, nanoscale resolution, and non-invasiveness. This achievement will be used to timely reveal the generics of the mesoscale crystalline structure through the pioneering explorations of a vast variety of crystalline biominerals produced by the famous Pinctada mar-garitifera oyster shell, and thereby build a realistic biomineralization scenario. The inferred biomineralization pathways, including both physico-chemical pathways and biological controls, will ultimately be validated by comparing the mesoscale structures produced by biomimetic samples with the biogenic ones. Beyond deciphering one of the most intriguing questions of material nanosciences, 3D-BioMat may contribute to new climate models, pave the way for new routes in material synthesis and supply answers to the pearl-culture calcification problems.

1 966 429 €

Start date: 2017-03-01, End date: 2022-02-28

Faithful repair of double stranded DNA breaks (DSBs) is essential, as they are at the origin of genome instability, chromosomal translocations and cancer. Cells repair DSBs through different pathways, which can be faithful or mutagenic, and the balance between them at a given locus must be tightly regulated to preserve genome integrity. Although, much is known about DSB repair factors, how the choice between pathways is controlled within the nuclear environment is not understood. We have shown that nuclear architecture and non-random genome organization determine the frequency of chromosomal translocations and that pathway choice is dictated by the spatial organization of DNA in the nucleus. Nevertheless, what determines which pathway is activated in response to DSBs at specific genomic locations is not understood. Furthermore, the impact of 3D-genome folding on the kinetics and efficiency of DSB repair is completely unknown. Here we aim to understand how nuclear compartmentalization, chromatin structure and genome organization impact on the efficiency of detection, signaling and repair of DSBs. We will unravel what determines the DNA repair specificity within distinct nuclear compartments using protein tethering, promiscuous biotinylation and quantitative proteomics. We will determine how DNA repair is orchestrated at different heterochromatin structures using a CRISPR/Cas9-based system that allows, for the first time robust induction of DSBs at specific heterochromatin compartments. Finally, we will investigate the role of 3D-genome folding in the kinetics of DNA repair and pathway choice using single nucleotide resolution DSB-mapping coupled to 3D-topological maps. This proposal has significant implications for understanding the mechanisms controlling DNA repair within the nuclear environment and will reveal the regions of the genome that are susceptible to genomic instability and help us understand why certain mutations and translocations are recurrent in cancer

1 999 750 €

Start date: 2017-03-01, End date: 2022-02-28

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

"Bridging the fields of Computer Animation and Computational Fabrication, this proposal will establish the foundations for algorithmic design of physical structures that can generate lifelike movements. Driven by embedded actuators, these types of structures will enable an abundance of possibilities for a wide array of real-world technologies: animatronic characters whose organic motions will enhance their ability to awe, entertain and educate; soft robotic creatures that are both skilled and safe to be around; patient-specific prosthetics and wearable devices that match the soft touch of the human body, etc. Recent advances in additive manufacturing (AM) technologies are particularly exciting in this context, as they allow us to create designs of unparalleled geometric complexity using a constantly expanding range of materials. And if past developments are an indication, within the next decade we will be able to fabricate physical structures that approach, at least at the macro scale, the functional sophistication of their biological counterparts. However, while this unprecedented capability enables fascinating opportunities, it also leads to an explosion in the dimensionality of the space that must be explored during the design process. As AM technologies keep evolving, the gap between ""what we can produce"" and ""what we can design"" is therefore rapidly growing. To effectively leverage the extraordinary design possibilities enabled by AM, 3DPBio will develop the computational and mathematical foundations required to study a fundamental scientific question: how are physical deformations, mechanical movements and overall functional capabilities governed by geometric shape features, material compositions and the design of compliant actuation systems? By enabling computers to reason about this question, our work will establish new ways to algorithmically create digital designs that can be turned into mechanical lifeforms at the push of a button."

2 000 000 €

Start date: 2020-02-01, End date: 2025-01-31

4D reconstruction, the camera-based dense dynamic scene reconstruction, is a grand challenge in computer graphics and computer vision. Despite great progress, 4D capturing the complex, diverse real world outside a studio is still far from feasible. 4DRepLy builds a new generation of high-fidelity 4D reconstruction (4DRecon) methods. They will be the first to efficiently capture all types of deformable objects (humans and other types) in crowded real world scenes with a single color or depth camera. They capture space-time coherent deforming geometry, motion, high-frequency reflectance and illumination at unprecedented detail, and will be the first to handle difficult occlusions, topology changes and large groups of interacting objects. They automatically adapt to new scene types, yet deliver models with meaningful, interpretable parameters. This requires far reaching contributions: First, we develop groundbreaking new plasticity-enhanced model-based 4D reconstruction methods that automatically adapt to new scenes. Second, we develop radically new machine learning-based dense 4D reconstruction methods. Third, these model- and learning-based methods are combined in two revolutionary new classes of 4DRecon methods: 1) advanced fusion-based methods and 2) methods with deep architectural integration. Both, 1) and 2), are automatically designed in the 4D Real World Reconstruction Loop, a revolutionary new design paradigm in which 4DRecon methods refine and adapt themselves while continuously processing unlabeled real world input. This overcomes the previously unbreakable scalability barrier to real world scene diversity, complexity and generality. This paradigm shift opens up a new research direction in graphics and vision and has far reaching relevance across many scientific fields. It enables new applications of profound social pervasion and significant economic impact, e.g., for visual media and virtual/augmented reality, and for future autonomous and robotic systems.

1 977 000 €

Start date: 2018-09-01, End date: 2023-08-31

One of the greatest challenges in exploiting the electron spin for information processing is that it is not a conserved quantity like the electron charge. In addition, spin lifetimes are rather short and correspondingly coherence is quickly lost. This challenge culminates in the coherent manipulation and detection of information from a single spin. Except in a few special systems, so far, single spins cannot be manipulated coherently on the atomic scale, while spin coherence times can only be measured on spin ensembles. A new concept is needed for coherence measurements on arbitrary single spins. Here, the principal investigator (PI) will combine a novel time- and spin-resolved low-temperature scanning tunneling microscope (STM) with the concept of pulsed electron paramagnetic resonance. With this unique and innovative setup, he will be able to address long-standing problems, such as relaxation and coherence times of arbitrary single spin systems on the atomic scale as well as individual spin interactions with the immediate surroundings. Spin readout will be realized through the detection of the absolute spin polarization in the tunneling current by a superconducting tip based on the Meservey-Tedrow-Fulde effect, which the PI has recently demonstrated for the first time in STM. For the coherent excitation, a specially designed pulsed GHz light source will be implemented. The goal is to better understand the spin dynamics and coherence times of single spin systems as well as the spin interactions involved in the decay mechanisms. This will have direct impact on the feasibility of quantum spin information processing with single spin systems on different decoupling surfaces and their scalability at the atomic level. A successful demonstration will enhance the detection limit of spins by several orders of magnitude and fill important missing links in the understanding of spin dynamics and quantum computing with single spins.

2 469 136 €

Start date: 2016-07-01, End date: 2021-06-30

ACHIEVE focuses on the application of Excluded Volume Effect in cell culture systems in order to enhance Extracellular Matrix (ECM) deposition. It represents a new horizon in in vitro cell culture which will address major challenges in medical advancement and food security. ACHIEVE will elucidate extracellular processes which occur during tissue generation, identifying favourable conditions for optimum tissue cultivation in vitro. These results will be applied in the diverse fields of regenerative medicine, drug discovery and cellular agriculture which all require advancements in in vitro tissue engineering to overcome current bottlenecks. Effective in vitro tissue culture is currently limited by lengthy culture periods. An inability to maintain physiologic (in vivo) conditions during this lengthy in vitro culture leads to cellular phenotype drift, ultimately resulting in generation of an undesired tissue. Enhanced tissue generation in vitro will greatly reduce culture times and costs, effecting improved in vitro tissue substitutes which remain true to their original phenotype. The research will be addressed under four work-packages. WP1 will investigate biochemical, biophysical and biological responses to varying culture conditions; WP 2, 3 and 4 will apply results in the fields of Tissue Engineering, Drug Discovery and Cellular Agriculture respectively. Research will involve extensive characterisation of derived- and stem-cell cultures in varying conditions of expansion and relevant health and safety and preclinical testing. The five year programme will be undertaken at the National University of Ireland, Galway, a centre of excellence in tissue engineering research, at a cost of € 2,439,270.

2 076 770 €

Start date: 2020-09-01, End date: 2025-08-31

"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