ERC FUNDED PROJECTS

Demand for biofuels and other biologically derived commodities is growing worldwide as efforts increase to reduce reliance on fossil fuels and to limit climate change. Most commercial approaches rely on fermentations of organic matter with its inherent problems in producing CO2 and being in conflict with the food supply of humans. These problems are avoided if CO2 can be used as feedstock. Autotrophic organisms can fix CO2 by producing chemicals that are used as building blocks for the synthesis of cellular components (Biomass). Acetate-forming bacteria (acetogens) do neither require light nor oxygen for this and they can be used in bioreactors to reduce CO2 with hydrogen gas, carbon monoxide or an organic substrate. Gas fermentation using these bacteria has already been realized on an industrial level in two pre-commercial 100,000 gal/yr demonstration facilities to produce fuel ethanol from abundant waste gas resources (by LanzaTech). Acetogens can metabolise a wide variety of substrates that could be used for the production of biocommodities. However, their broad use to produce biofuels and platform chemicals from substrates other than gases or together with gases is hampered by our very limited knowledge about their metabolism and ability to use different substrates simultaneously. Nearly nothing is known about regulatory processes involved in substrate utilization or product formation but this is an absolute requirement for metabolic engineering approaches. The aim of this project is to provide this basic knowledge about metabolic routes in the acetogenic model strain Acetobacterium woodii and their regulation. We will unravel the function of “organelles” found in this bacterium and explore their potential as bio-nanoreactors for the production of biocommodities and pave the road for the industrial use of A. woodii in energy (hydrogen) storage. Thus, this project creates cutting-edge opportunities for the development of biosustainable technologies in Europe.

2 497 140 €

Start date: 2017-10-01, End date: 2022-09-30

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

Algebras of operators on Hilbert spaces were originally introduced as the right framework for the mathematical description of quantum mechanics. In modern mathematics the scope has much broadened due to the highly versatile nature of operator algebras. They are particularly useful in the analysis of groups and their actions. Amenability is a finiteness property which occurs in many different contexts and which can be characterised in many different ways. We will analyse amenability in terms of approximation properties, in the frameworks of abstract C*-algebras, of topological dynamical systems, and of discrete groups. Such approximation properties will serve as bridging devices between these setups, and they will be used to systematically recover geometric information about the underlying structures. When passing from groups, and more generally from dynamical systems, to operator algebras, one loses information, but one gains new tools to isolate and analyse pertinent properties of the underlying structure. We will mostly be interested in the topological setting, and in the associated C*-algebras. Amenability of groups or of dynamical systems then translates into the completely positive approximation property. Systems of completely positive approximations store all the essential data about a C*-algebra, and sometimes one can arrange the systems so that one can directly read of such information. For transformation group C*-algebras, one can achieve this by using approximation properties of the underlying dynamics. To some extent one can even go back, and extract dynamical approximation properties from completely positive approximations of the C*-algebra. This interplay between approximation properties in topological dynamics and in noncommutative topology carries a surprisingly rich structure. It connects directly to the heart of the classification problem for nuclear C*-algebras on the one hand, and to central open questions on amenable dynamics on the other.

1 596 017 €

Start date: 2019-10-01, End date: 2024-09-30

Many complex phenomena in the sciences are described by nonlinear partial differential equations, the solutions of which exhibit oscillations and concentration effects on multiple temporal or spatial scales. Our aim is to use methods from applied analysis to contribute to the understanding of the interplay of effects on different scales. The central question is to determine those quantities on the microscale which are needed to for the correct description of the macroscopic evolution. We aim to develop a mathematical framework for analyzing and modeling coupled systems with multiple scales. This will include Hamiltonian dynamics as well as different types of dissipation like gradient flows or rate-independent dynamics. The choice of models will be guided by specific applications in material modeling (e.g., thermoplasticity, pattern formation, porous media) and optoelectronics (pulse interaction, Maxwell-Bloch systems, semiconductors, quantum mechanics). The research will address mathematically fundamental issues like existence and stability of solutions but will mainly be devoted to the modeling of multiscale phenomena in evolution systems. We will focus on systems with geometric structures, where the dynamics is driven by functionals. Thus, we can go much beyond the classical theory of homogenization and singular perturbations. The novel features of our approach are - the combination of different dynamical effects in one framework, - the use of geometric and metric structures for coupled partial differential equations, - the exploitation of Gamma-convergence for evolution systems driven by functionals.

1 390 000 €

Start date: 2011-04-01, End date: 2017-03-31