ERC FUNDED PROJECTS

The use of renewable feedstocks by the chemical industry is fundamental due to both the depletion of fossil resources and the increasing pressure of environmental concerns. Biomass can act as a sustainable source of organic industrial chemicals; however, the establishment of a renewable chemical industry that is economically competitive with the present oil-based one requires the development of new processes to convert biomass-derived compounds into useful industrial materials following the principles of green chemistry. To achieve these goals, developments in several fields including heterogeneous catalysis are needed. One of the ways to accelerate the discovery of new potentially active, selective and stable catalysts is the massive use of computational chemistry. Recent advances have demonstrated that Density Functional Theory coupled to ab initio thermodynamics, transition state theory and microkinetic analysis can provide a full view of the catalytic phenomena. The aim of the present project is thus to employ these well-tested computational techniques to the development of a theoretical framework that can accelerate the identification of new catalysts for the conversion of biomass derived target compounds into useful chemicals. Since compared to petroleum-based materials-biomass derived ones are multifuncionalized, the search for new catalytic materials and processes has a strong requirement in the selectivity of the chemical transformations. The main challenges in the project are related to the high functionalization of the molecules, their liquid nature and the large number of potentially competitive reaction paths. The requirements of specificity and selectivity in the chemical transformations while keeping a reasonably flexible framework constitute a major objective. The work will be divided in three main work packages, one devoted to the properties of small molecules or fragments containing a single functional group; the second addresses competition in multiple functionalized molecules; and third is dedicated to the specific transformations of two molecules that have already been identified as potential platform generators. The goal is to identify suitable candidates that could be synthetized and tested in the Institute facilities.

1 496 200 €

Start date: 2010-10-01, End date: 2015-09-30

Graphene – a one atom thin material – has the potential to act as a sensor, primarily the surface and the edges of graphene. This proposal aims at exploring new biosensing routes by exploiting the unique surface and edge chemistry of graphene.

1 499 996 €

Start date: 2014-05-01, End date: 2019-04-30

We propose to develop new chemometric and high-throughput analytical methods to assess the effects of environmental and climate changes on target biological systems which are representative of ecosystems. This project will combine powerful chemometric and analytical high-throughput methodologies with toxicological tests to examine the effects of environmental stressors (like chemical pollution) and of climate change (like temperature, water scarcity or food shortage), on genomic and metabonomic profiles of target biological systems. The complex nature of experimental data produced by high-throughput analytical techniques, such as DNA microarrays, hyphenated chromatography-mass spectrometry or multi-dimensional nuclear magnetic resonance spectroscopy, requires powerful data analysis tools to extract, summarize and interpret the large amount of information that such megavariate data sets may contain. There is a need to improve and automate every step in the analysis of the data generated from genomic and metabonomic studies using new chemometric and multi- and megavariate tools. The main purpose of this project is to develop such tools. As a result of the whole study, a detailed report on the effects of global change and chemical pollution on the genomic and metabonomic profiles of a selected set of representative target biological systems will be delivered and used for global risk assessment. The information acquired, data sets and computer software will be stored in public data bases using modern data compression and data management technologies. And all the methodologies developed in the project will be published.

2 454 280 €

Start date: 2013-04-01, End date: 2018-03-31

Cell membranes form a highly complex and heterogeneous mixture of membrane proteins and lipids. Understanding the protein-lipid interplay that gives rise to the lateral organisation principles of cell membranes is essential for life and health. Thus, investigations of these crowded membranes is emerging as a new and exceptionally exciting frontier at the crossroads of biology, life sciences, physics, and chemistry. However, our current understanding of the detailed organisation of cellular membranes remains rather elusive. Characterisation of the structural heterogeneity in-vivo remains very challenging, owing to the lack of experimental methods suitable for studying these fluctuating nanoscale assemblies of lipids and proteins with the required spatio-temporal resolution. In recent years, computer simulations have become a unique investigatory tool for understanding the driving forces governing the lateral organisation of cellular membrane components and this “computational microscopy” has become indispensible as a complement to traditional microscopy methods. In this ERC project I will, using advanced computational microscopy, study the interaction of lipids and proteins in complex, crowded, membrane patches, to enable the driving forces of membrane protein sorting and clustering to be unravelled at conditions closely mimicking real cellular membranes. The specific objectives are: • To develop a novel computational microscopy framework for simulating biomolecular processes at multiple resolutions. • To use this new computational microscopy framework to investigate the driving forces of membrane protein sorting and clustering. • To provide a molecular view of realistic, crowded, biological membranes composed of hundreds of different lipids and proteins. The outcomes will enable subsequent studies of many different types of cell membranes based on forthcoming lipidomics studies and progress in structural characterisation of membrane proteins.

2 396 585 €

Start date: 2015-11-01, End date: 2020-10-31

By virtue of its computational efficiency, Kohn-Sham (KS) density functional theory (DFT) is the method of choice for the electronic structure calculations in computational chemistry and solid-state physics. Despite its enormous successes, KS DFT’s predictive power and overall usefulness are still hampered by inadequate approximations for near-degenerate and strongly-correlated systems. Crucial examples are transition metal complexes (key for catalysis), stretched chemical bonds (key to predict chemical reactions), technologically advanced functional materials, and manmade nanostructures. I aim to address these fundamental issues, by constructing a novel framework for electronic structure calculations at all correlation regimes. This new approach is based on recent formal developments from my group, which reproduce key features of strong correlation within KS DFT, without any artificial symmetry breaking. My results on the exact infinite-coupling-strength expansion of KS DFT will be used to endow that theory with many-body properties from the ground up, thereby removing its intrinsic bias for weak correlation regimes. This requires novel combinations of ideas from three research communities: chemists and physicists that develop approximations for KS DFT, condensed matter physicists that work on strongly-correlated systems using lattice hamiltonians, and mathematicians working on mass transportation theory. The strong-correlation limit of DFT enables these links by defining a natural framework for extending lattice-based results to the real space continuum. On the other hand, this limit has a mathematical structure formally equivalent to the optimal transport problem of mathematics, enabling adaptation of methods and algorithms. The new approximations will be implemented with the assistance of an industrial partner and validated on representative benchmark chemical and physical systems.

1 999 891 €

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

Most of the developments in catalyst are still based on serendipitous and trial-and-error approaches, in which potential systems can be overlooked simply because of the sub-optimal conditions of the initial activity assessment. Mechanistic and kinetic studies could provide a framework for a more adequate assessment of new catalysts, but such rigorous experiments are not practical for general catalyst discovery. Modern chemical theory and computations hold a promise to be employed in new efficient theory-guided approaches for rational catalyst and process development. The main aim of DeLiCat is to formulate a hierarchical computational strategy for the design and synthesis of new non-critical metal-based catalysts for sustainable chemical transformations. New, durable and cheap, yet, highly active and selective tailor-made catalyst for hydrogenation of carboxylic acids and their esters as well as for acceptorless dehydrogenation of alcohols will be developed. The research will follow an innovative strategy combining advanced chemical theory, computational screening and experimental approaches from the fields of homogeneous and heterogeneous catalysis in an efficient knowledge exchange loop. Computer simulations will reveal complex reaction networks that determine the “death” and the “life” of catalyst systems. These insights will be used in targeted design of novel multifunctional catalyst systems to direct the selectivity of the reaction network and to prevent deactivation paths. Complementary experimental studies will guide and validate the theoretical predictions. DeLiCAT represents a leap forward in unified first principles-guided catalyst design for liquid phase chemical transformations. The new theoretical concepts, methodological advances as well as the novel superior catalyst systems developed here will be applicable in various areas including biomass valorization, homogeneous and heterogeneous catalysis as well as hydrogen technology.

1 999 524 €

Start date: 2017-05-01, End date: 2022-04-30

"Scope ""Energy Materials. In this project we develop new concepts for building a novel theoretical framework (the ab-initio non-equilibrium dynamical modelling tool”) for understanding, identifying, and quantifying the different contributions to energy harvesting and storage as well as describing transport mechanisms in natural light harvesting complexes, photovoltaic materials, fluorescent proteins and artificial (nanostructured) devices by means of theories of open quantum systems, non-equilibrium processes and electronic structure. We address cutting-edge applications along three major scientific challenges: i) characterize matter out of equilibrium, ii) control material processes at the electronic level and tailor material properties, iii) master energy and information on the nanoscale. The long-term goal is developing a set of theoretical tools for the quantitative prediction of energy transfer phenomena in real systems. We will provide answers to the following questions: What are the design principles from the environment-assisted quantum transport in photosynthetic organisms that can be transferred to nanostructured materials such as organic photovoltaic materials and biomimetic materials? What are the fundamental limits of excitonic transport properties such as exciton diffusion lengths and recombination rates? What is the role of quantum coherence in the energy transport in photosynthetic complexes and photovoltaic materials? What is the role of spatial confinement in water and proton transfer through porous membranes (nano-capillarity)? The ground-breaking nature of the project lies in being the first systematic development and application of the theories of open quantum systems and quantum optimal control within an ab-initio framework (time-dependent-density functional theory). The project will open new methodological, applicative and theoretical horizons of research."

1 877 497 €

Start date: 2011-04-01, End date: 2016-03-31

Lanthanide metals are ubiquitous nowadays, finding use in luminescent materials, optical amplifiers and waveguides, lasers, photovoltaics, rechargeable batteries, catalysts, alloys, magnets, bio-probes, and therapeutic agents. In addition, they bear potential for high temperature superconductivity, magnetic refrigeration, molecular magnetic storage, spintronics and quantum information. Surprisingly, the study of lanthanide physico-chemical properties on surfaces is at its infancy, particularly at the nanoscale. To address this extraordinary scientific opportunity, I will research the foundations and prospects of lanthanide elements to design functional nanoarchitectures on surfaces and I will study their inherent physico-chemical phenomena in distinct coordination environments, targeting novel approaches for sensing, nanomagnetism and electroluminescence. Importantly, our studies will encompass both metal substrates and decoupling surfaces including ultra-thin film insulators and graphene. Nurturing from these studies and in parallel, we will focus on graphene voltage back-gated supports, thus surpassing the seminal knowledge on electrically-inert substrates and enhancing the scope of our research to address the overarching objective of the proposal, i.e., the design of electrically tunable functional lanthanide nanomaterials. The culmination of ELECNANO project will provide strategies for: 1.-Design of functional nanomaterials on high-technological supports. 2.-Development of advanced coordination chemistry on surfaces. 3.-Rationale of the physico-chemical properties of lanthanide-coordination environments. 4.-Engineering of lanthanide nanoarchitectures for ultimate sensing, nanomagnetism and electroluminescence. 5.-In-situ atomistic views of electrically tunable materials and unprecedented fundamental studies of charge-molecule/metal physics on devices.

1 994 713 €

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

Even today, quantum chemical calculations with experimental accuracy are only feasible for small molecules. This statement is especially true if the considered molecule is far from the equilibrium structure, where the overwhelming majority of quantum chemical models break down. The main purpose of this proposal is to develop new quantum chemical methods that are applicable to at least medium-sized molecules and simultaneously provide results sufficiently close to the experimental data and are capable of describing entire potential energy surfaces. The accuracy goal will be achieved through the reduction of the computational cost of high-precision quantum chemical calculations, which are currently practical for molecules of up to 15 atoms. The cost reduction will be accomplished principally by decreasing the number of numerical parameters to be optimized without sacrificing accuracy. To this end, the negligible parameters will be identified and dropped by adopting the corresponding techniques of computer science. The correct behavior of the models for distorted structures will be ensured by developing new approaches that use a linear combination of functions rather than a single function as a starting point for the description of electronic states. Since the programming work associated with the implementation of the proposed schemes is very complex, the project will rely on the automated programming tools previously developed by the proposer. In addition to the outlined challenging tasks, the proposal aims to implement several more straightforward objectives. In particular, the high-accuracy calculations will be extended to molecular properties that are presently not available. Furthermore, the developed methods will be applied to real-life problems, especially in the field of spectroscopy and atmospheric chemistry.

500 000 €

Start date: 2008-07-01, End date: 2013-06-30