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

This proposal relates to the Proof of Concept stage investigation of exciting new findings in the ERC Advanced Grant ‘IMPUNEP’ project relating to the study and use of plasma-based processes. These findings offer significant advantages for the creation of complex 3D ceramic and ceramic-metal products at relatively low cost in an environmentally friendly manner. The potential applications of this new technology are very wide-ranging, and include the creation of new products as diverse as healthcare devices, MEMS and aero/automotive parts. Before we properly and fully identify the most promising applications, we need to investigate key aspects of the performance of materials created by this new method. This aspect wasn’t envisaged in the original proposal and involves research into the mechanical properties (especially the strength and elastic modulus) of these 3D parts and their response to deformation and dynamic displacements, as well as their physical (including electrical) properties. These components will be highly resistant to attack by aggressive (e.g. acidic) media as well as highly tolerant to both low (cryogenic) and high (combustion) temperatures. The expected applications opened up by this new method to produce ceramic and ceramic-metal components of complex shape are extensive. Hence the need for this Proof of Concept study, which will focus on validating the process for 3D ceramic-metal and ceramic parts and evaluating the mechanical, chemical, electrical and physical attributes of the 3D shapes, and will explore their potential applications in this pre-demonstration phase.

149 500 €

Start date: 2019-01-01, End date: 2020-03-31

Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world. In this project, we will focus on three lines of research: A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion. B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape). C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times. Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.

2 000 000 €

Start date: 2015-09-01, End date: 2020-08-31

The realization of high-performance micro-supercapacitors is currently a big challenge but the ineluctable applications requiring such miniaturized energy storage devices are continuously emerging, from wearable electronic gadgets to wireless sensor networks. Although they store less energy than micro-batteries, micro-supercapacitors can be charged and discharged very rapidly and exhibit a quasi-unlimited lifetime. The global scientific research is consequently largely focused on the improvement of their capacitance and energetic performances. However, to date, they are still far from being able to power sensors or electronic components. Here I propose a 3D paradigm shift of micro-supercapacitor design to ensure increased energy storage capacities. Hydrous ruthenium dioxide (RuO2) is a pseudocapacitive material for supercapacitor electrode well-known for its high capacitance. A thin-film of ruthenium will be deposited by atomic layer deposition (ALD), followed by an electrochemical oxidation process, onto a high-surface-area 3D current collector prepared via an ingenious dynamic template built with hydrogen bubbles. The structural features of these 3D architectures will be controllably tailored by the processing methodologies. These electrodes will be combined with an innovative electrolyte in solid form (a protic ionogel) able to operate over an extended cell voltage. In a parallel investigation, we will develop a fundamental understanding of electrochemical reactions occurring at the nanoscale with a FIB-patterned (Focused Ion Beam) RuO2 nano-supercapacitor. The resulting 3D micro-supercapacitors should display extremely high power, long lifetime and – for the first time – energy densities competing or even exceeding that of micro-batteries. As a key achievement, prototypes will be designed using a new concept based on a self-adaptative micro-supercapacitors matrix, which arranges itself according to the global amount of energy stored.

1 673 438 €

Start date: 2018-04-01, End date: 2023-03-31