ERC FUNDED PROJECTS

1.2 billion people worldwide lack access to safe drinking water. Drinking water quality is threatened by newly emerging organic micro-pollutants (pesticides, pharmaceuticals, industrial chemicals) in source waters. Nanofiltration is a technology that is expected to play a key role in future water treatment processes due to its effectiveness in removal of micropollutants. However, the loss of membrane flux due to fouling is one of the main impediments in the development of membrane processes for use in drinking water treatment. Currently there is a wholly inadequate mechanistic understanding of the role of biofilm on the fouling of nanofiltration membranes. Applying techniques including confocal microscopy, force spectroscopy, and infrared spectroscopy using an experimental programme informed by a technique known as scale-down together with mathematical modelling, it is confidently expected that significant advances will be gained in the mechanistic understanding of nanofiltration biofouling. The specific objectives are 1. How is the rate of formation and extent of such biofilms influenced by the biological response to the local microenvironment? 2 Elucidate the effect of extracellular polysaccharide substances on physical properties, composition and structure of these biofilms. 3: Investigate mechanisms to enhance biofilm removal by a physical detachment process complemented by techniques that alter biofilm material properties. A more fundamental insight into the mechanisms of nanofiltration operation will help in further development of this treatment method in future water treatment processes.

1 468 987 €

Start date: 2011-10-01, End date: 2016-09-30

As technologies based on semiconductors and ferromagnets are reaching their limits in computational and memory-storage capabilities, new technologies based on spin are emerging as alternative. Magnetic molecules represent the ultimate small-scale magnetic unit that can be synthesized and processed into a device for spintronics and quantum computing applications but their use is confined to very low temperatures. The grand challenge of this proposal is to design magnetic molecules with long spin lifetime at ambient temperature by tuning the main microscopic interaction responsible for spin relaxation: the spin-phonon coupling. AI-DEMON will address this challenge by developing a novel first-principles and machine-learning computational framework able to cover all the essential aspects of the design of new coordination compounds with tailored properties. AI-DEMON has three main objectives, each one representing a major contribution to the field: i) I will unveil the mechanism of spin-phonon relaxation in magnetic molecules by developing a quantitative first-principles spin relaxation theory, ii) I will efficiently explore the chemical space of magnetic coordination compounds by developing a universal machine-learning model able to predict vibrational and magnetic properties, and iii) I will design molecular prototypes with tailored magnetic and vibrational properties by developing generative machine-learning methods. Preliminary results on spin relaxation theory and machine-learning applied to magnetic properties show great promise and set the cornerstone of the project. The use of novel methodologies, such as machine learning and first-principles spin dynamics, represent a strong disruption in the current approach to theoretical modelling and discovery of new magnetic molecules and will propel the field into a new and modern era. Significant impact beyond the field of molecular magnetism, e.g. bio-inorganic chemistry and solid-state qubits, can also be anticipated.

1 499 786 €

Start date: 2021-01-01, End date: 2025-12-31

What does the fossil record tell us about the evolution of colour in animals through deep time? Evidence of colour in fossils can inform on the visual signalling strategies used by ancient animals. Research to date often has a narrow focus, lacks a broad phylogenetic and temporal context, and rarely incorporates information on taphonomy. This proposal represents a bold new holistic approach to the study of fossil colour: it will couple powerful imaging- and chemical analytical techniques with a rigorous programme of fossilisation experiments simulating decay, burial, and transport, and analysis of fossils and their sedimentary context, to construct the first robust models for the evolution of colour in animals through deep time. The research will resolve the original integumentary colours of fossil higher vertebrates, and the original colours of fossil hair; the fossil record of non-melanin pigments in feathers and insects; the biological significance of monotonal patterning in fossil insects; and the evolutionary history of scales and 3D photonic crystals in insects. Critically, the research will test, for the first time, whether evidence of fossil colour can solve broader evolutionary questions, e.g. the true affinities of enigmatic Cambrian chordate-like metazoans, and feather-like integumentary filaments in dinosaurs. The proposal entails construction of a dedicated experimental maturation laboratory for simulating the impact of burial on tissues. This laboratory will form the core of the world’s first integrated ‘experimental fossilisation facility’, consolidating the PI’s team as the global hub for fossil colour research. The research team comprises the PI, three postdoctoral researchers, and three PhD students, and will form an extensive research network via collaborations with 13 researchers from Europe and beyond. The project will reach out to diverse scientists and will inspire a positive attitude to science among the general public and policymakers alike.

1 562 000 €

Start date: 2016-01-01, End date: 2021-04-30

With the advent of new sequencing technologies, population geneticists now have access to more data than ever before. We have access to thousands of human genomes from a diverse set of populations around the globe, and, thanks to advances in DNA extraction and library preparation, we now are beginning to have access to ancient DNA sequence data. These data have greatly improved our knowledge of human history, human adaptation to different environments and human disease. Genome-wide studies have highlighted many genes or genomic loci that may play a role in adaptive or disease related phenotypes of biological importance. With these collections of modern and ancient sequence data we want to answer a key evolutionary question: how do human adaptations arise? We strongly believe that the state-of-the-art methodologies for uncovering signatures of adaptation are blind to potential modes of adaptation because they are lacking two critical components – more complete integration of multiple population haplotype data (including archaic, ancient and modern samples), and an account of population interactions that facilitate adaptation. Therefore I plan to develop new methods to detect shared selective events across populations by creating novel statistical summaries, and to detect admixture-facilitated adaptation which we believe is likely a common mode of natural selection. We will apply these tools to new datasets to characterize the interplay of natural selection, archaic and modern admixture in populations in the Americas and make a comparative analysis of modern and ancient European samples to understand the origin and changing profile of adaptive archaic alleles. As a result our work will reveal evolutionary processes that have played an important role in human evolution and disease.

1 500 000 €

Start date: 2020-12-01, End date: 2025-11-30