ERC FUNDED PROJECTS

The goal of crystal engineering is the design of functional crystalline materials in which the arrangement of basic structural building blocks imparts desired properties. The engineering of organic molecular crystals has, to date, relied largely on empirical rules governing the intermolecular association of functional groups in the solid state. However, many materials properties depend intricately on the complete crystal structure, i.e. the unit cell, space group and atomic positions, which cannot be predicted solely using such rules. Therefore, the development of computational methods for crystal structure prediction (CSP) from first principles has been a goal of computational chemistry that could significantly accelerate the design of new materials. It is only recently that the necessary advances in the modelling of intermolecular interactions and developments in algorithms for identifying all relevant crystal structures have come together to provide predictive methods that are becoming reliable and affordable on a timescale that could usefully complement an experimental research programme. The principle aim of the proposed work is to establish the use of state-of-the-art crystal structure prediction methods as a means of guiding the discovery and design of novel molecular materials. This research proposal both continues the development of the computational methods for CSP and, by developing a computational framework for screening of potential molecules, develops the application of these methods for materials design. The areas on which we will focus are organic molecular semiconductors with high charge carrier mobilities and, building on our recently published results in Nature [1], the development of porous organic molecular materials. The project will both deliver novel materials, as well as improvements in the reliability of computational methods that will find widespread applications in materials chemistry. [1] Nature 2011, 474, 367-371.

1 499 906 €

Start date: 2012-10-01, End date: 2017-09-30

Many parts of Graph Theory have witnessed a huge growth over the last years, partly because of their relation to Theoretical Computer Science and Statistical Physics. These connections arise because graphs can be used to model many diverse structures. The focus of this proposal is on asymptotic results, i.e. the graphs under consideration are large. This often unveils patterns and connections which remain obscure when considering only small graphs. It also allows for the use of powerful techniques such as probabilistic arguments, which have led to spectacular new developments. In particular, my aim is to make decisive progress on central problems in the following 4 areas: (1) Factorizations: Factorizations of graphs can be viewed as partitions of the edges of a graph into simple regular structures. They have a rich history and arise in many different settings, such as edge-colouring problems, decomposition problems and in information theory. They also have applications to finding good tours for the famous Travelling salesman problem. (2) Hamilton cycles: A Hamilton cycle is a cycle which contains all the vertices of the graph. One of the most fundamental problems in Graph Theory/Theoretical Computer Science is to find conditions which guarantee the existence of a Hamilton cycle in a graph. (3) Embeddings of graphs: This is a natural (but difficult) continuation of the previous question where the aim is to embed more general structures than Hamilton cycles - there has been exciting progress here in recent years which has opened up new avenues. (4) Resilience of graphs: In many cases, it is important to know whether a graph `strongly’ possesses some property, i.e. one cannot destroy the property by changing a few edges. The systematic study of this notion is a new and rapidly growing area. I have developed new methods for deep and long-standing problems in these areas which will certainly lead to further applications elsewhere.

818 414 €

Start date: 2012-12-01, End date: 2018-11-30

"One prominent idea for mitigating global climate change is to remove CO2 from the atmosphere by storing it in fluids in the natural environment; for example dissolved within sediments below the ocean floor or in oceanic crust. This carbon sequestration is popular because it would allow us to place carbon into semi-permanent (on human timescales) storage, ‘buying time’ to wean us from our dependence on carbon-based energy sources. Application of such a mitigation technique presumes knowledge of what will happen to carbon when it is dissolved in various environments. Studies of naturally produced excess dissolved CO2 are, however, equivocal; this lack of knowledge represents a huge deficit in our comprehension of the global carbon cycle and specifically the processes removing carbon from the surface of the planet over geological timescales. This proposal will resolve the sink for CO2 within marine sediments and oceanic crust. Beneath much of the ocean floor exists the ‘deep biosphere’, microbial populations living largely in the absence of oxygen, consuming organic carbon that has fallen to the sea floor, producing a large excess of dissolved inorganic carbon. This dissolved inorganic carbon can diffuse back to the ocean or can precipitate in situ as carbonate minerals. Previous attempts to quantify the flux of carbon through the deep biosphere focused mostly on studies of sulfur and carbon, and these studies cannot reveal the fate of the produced inorganic carbon. I propose a novel approach to constrain the fate of carbon through the study of the subsurface calcium cycle. Calcium is the element involved in precipitating carbon as in situ carbonate minerals and thus will directly provide the required mass balance to determine the fate of CO2 in the marine subsurface. This mass balance will be achieved through experiments, measurements, and numerical modeling, to achieve the primary objective of constraining the fate of carbon in submarine environments."

1 945 695 €

Start date: 2012-12-01, End date: 2017-11-30

The early universe is a “laboratory” for testing physics at very high energies, up to a trillion times greater than the energies reached by the Large Hadron Collider. The origin of structure in the universe is deeply tied to this extreme physics, which is imprinted in the primordial ripples seen in the cosmic microwave background (CMB). CMB data have thus far led the way in constraining early universe physics, and ESA’s Planck satellite is currently mapping the CMB at the highest precision ever achieved. However, next generation galaxy surveys – such as the Dark Energy Survey (DES), starting next year – will rival the CMB in their ability to unlock the secrets of the primordial universe. I will use the Planck and DES data to rigorously test the theory of inflation, the dominant paradigm for the origin of cosmic structure, and to seek signatures of new physics that are likely to exist at these unexplored energies. I have already played a leading role in bringing theory and robust data analysis together to understand the very early universe. This proposal aims, for the first time, to go beyond simply testing generic predictions of the inflationary paradigm, to gain a fundamental understanding of the physics responsible for the origin of cosmic structure. The keys to achieving this goal are: theoretical modelling at the cutting edge of fundamental physics (describing not just the inflationary period but also pre- and post-inflationary physics); advanced Bayesian and wavelet methods to extract reliable information from the data; a deep understanding of data limitations and control of systematics. The project will produce definitive results at the interface of cosmology and high energy physics, defining the frontiers of these fields well beyond the lifetimes of the surveys themselves.

1 493 066 €

Start date: 2013-01-01, End date: 2018-12-31