ERC FUNDED PROJECTS

Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”

1 494 892 €

Start date: 2010-09-01, End date: 2015-08-31

In the last ten years there has been a surge of interest in non-modal analysis applied to canonical problems in fundamental fluid mechanics. Even in simple flows, the stability behaviour predicted by non-modal analysis can be completely different from and far more accurate than that predicted by conventional eigenvalue analysis. As well as being more accurate, the tools of non-modal analysis, such as Lagrangian optimization, are very versatile. Furthermore, the outputs, such as receptivity and sensitivity maps of a flow, provide powerful insight for engineers. They describe where a flow is most receptive to forcing or where the flow is most sensitive to modification. The application of non-modal analysis to canonical problems has set the scene for step changes in engineering practice in fluid mechanics and thermoacoustics. The technical objectives of this proposal are to apply non-modal analysis to high Reynolds number flows, reacting flows and thermoacoustic systems, to compare theoretical predictions with experimental measurements and to embed these techniques within an industrial design tool that has already been developed by the group. This research group s vision is that future generations of engineering CFD tools will contain modules that can perform non-modal analysis. The generalized approach proposed here, combined with challenging scientific and engineering examples that are backed up by experimental evidence, will make this possible and demonstrate it to a wider engineering community.

1 301 196 €

Start date: 2010-12-01, End date: 2016-06-30

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

Back pain affects eight out of ten adults during their lifetime. It a huge economic burden on society, estimated to cost as much as 1-2% of gross national product in several European countries. Treatments for back pain have lower levels of success and are not as technologically mature as those for other musculoskeletal disorders such as hip and knee replacement. This application proposes to tackle one of the major barriers to the development of better surgical treatments for back pain. At present, new spinal devices are commonly assessed in isolation in the laboratory under standardised conditions that do not represent the variation across the patient population. Consequently many interventions have failed during clinical trials or have proved to have poor long term success rates. Using a combination of computational and experimental models, a new testing methodology will be developed that will enable the variation between patients to be simulated for the first time. This will enable spinal implants and therapies to be more robustly evaluated across a virtual patient population prior to clinical trial. The tools developed will be used in collaboration with clinicians and basic scientists to develop and, crucially, optimise new treatments that reduce back pain whilst preserving the unique functions of the spine. If successful, this approach could be translated to evaluate and optimise emerging minimally invasive treatments in other joints such as the hip and knee. Research in the spine could then, for the first time, lead rather than follow that undertaken in other branches of orthopaedics.

1 498 777 €

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

Next generation sequencing (NGS) is revolutionizing all fields of biological research but it fails to extract the full range of information associated with genetic material and is lacking in its ability to resolve variations between genomes. The high degree of genome variation exhibited both on the population level as well as between genetically “identical” cells (even in the same organ) makes genetic and epigenetic analysis on the single cell and single genome level a necessity. Chromosomes may be conceptually represented as a linear one-dimensional barcode. However, in contrast to a traditional binary barcode approach that considers only two possible bits of information (1 & 0), I will use colour and molecular structure to expand the variety of information represented in the barcode. Like colourful beads threaded on a string, where each bead represents a distinct type of observable, I will label each type of genomic information with a different chemical moiety thus expanding the repertoire of information that can be simultaneously measured. A major effort in this proposal is invested in the development of unique chemistries to enable this labelling. I specifically address three types of genomic variation: Variations in genomic layout (including DNA repeats, structural and copy number variations), variations in the patterns of chemical DNA modifications (such as methylation of cytosine bases) and variations in the chromatin composition (including nucleosome and transcription factor distributions). I will use physical extension of long DNA molecules on surfaces and in nanofluidic channels to reveal this information visually in the form of a linear, fluorescent “barcode” that is read-out by advanced imaging techniques. Similarly, DNA molecules will be threaded through a nanopore where the sequential position of “bulky” molecular groups attached to the DNA may be inferred from temporal modulation of an ionic current measured across the pore.

1 627 600 €

Start date: 2013-10-01, End date: 2018-09-30

Imagine in the future, bionic devices that can merge device and biology which can perform molecular sensing, simulate the functions of grown-organs in the lab, or even replace or improve parts of the organ as smart implants? Such bionic devices is set to transform a number of emerging fields, including synthetic biotechnology, regenerative medicine, and human-machine interfaces. Merging biology and man-made devices also mean that materials of vastly different properties need to be seamlessly integrated. One of the promising strategies to manufacture these devices is through 3D printing, which can structure different materials into functional devices, and simultaneously intertwining with biological matters. However, the requirement for biocompatibility, miniaturisation, portability and high performance in bionic devices pushes the current limit for micro- nanoscale 3D printing. This proposal aims to develop a new multi-material, cross-length scale biofabrication platform, with specific focus in making future smart bionic devices. In particular, a new mechanism is proposed to smoothly interface diverse classes of materials, such that an active device component can be ‘shrunk’ into a single small fibre. This mechanism utilises the polymeric materials’ flow property under applied tensile forces, and their abilities to combine with other classes of materials, such as semi-conductors and metals to impart further functionalities. This smart device fibre can be custom-made to perform different tasks, such as light emission or energy harvesting, to bridge 3D bioprinting for the future creation of high performance, compact, and cell-friendly bionic and medical devices.

1 486 938 €

Start date: 2018-01-01, End date: 2022-12-31

Enzymes created by Nature are still more selective and can be orders of magnitude more efficient than man-made catalysts, in spite of recent advances in the design of de novo catalysts and in enzyme redesign. The optimal engineering of either small molecular or of complex biological catalysts requires both (i) accurate quantitative computational methods capable of a priori assessing catalytic efficiency, and (ii) molecular design principles and corresponding algorithms to achieve, understand and control biomolecular catalytic function and mechanisms. Presently, the computational design of biocatalysts is challenging due to the need for accurate yet computationally-intensive quantum mechanical calculations of bond formation and cleavage, as well as to the requirement for proper statistical sampling over very many degrees of freedom. Pioneering enhanced sampling and analysis methods have been developed to address crucial challenges bridging the gap between the available simulation length and the biologically relevant timescales. However, biased simulations do not generally permit the direct calculation of kinetic information. Recently, I and others pioneered simulation tools that can enable not only accurate calculations of free energies, but also of the intrinsic molecular kinetics and the underlying reaction mechanisms as well. I propose to develop more robust, automatic, and system-tailored sampling algorithms that are optimal in each case. I will use our kinetics-based methods to develop a novel theoretical framework to address catalytic efficiency and to establish molecular design principles to key design problems for new bio-inspired nanocatalysts, and to identify and characterize small molecule modulators of enzyme activity. This is a highly interdisciplinary project that will enable fundamental advances in molecular simulations and will unveil the physical principles that will lead to design and control of catalysis with Nature-like efficiency.

1 499 999 €

Start date: 2018-02-01, End date: 2023-01-31

Craniosynostosis is a group of congenital craniofacial abnormalities consisting in premature fusion (ossification) of one or more cranial sutures during infancy. This results in growth restriction perpendicular to the axis of the suture and promotes growth parallel to it, causing physical deformation of the cranial and facial skeleton, as well as distortion of the underling brain, with potential detrimental effects on its function: visual loss, sleep apnoea, feeding and breathing difficulties, and neurodevelopment delay. Conventional management of craniosynostosis involves craniofacial surgery delivered by excision of the prematurely fused sutures, multiple bone cuts and remodelling of the skull deformities, with the primary goal of improving patient function, while normalising their appearance. Cranial vault remodelling surgical procedures, aided by internal and external devices, have proven functionally and aesthetically effective in correcting skull deformities, but final results remain unpredictable and often suboptimal because of an incomplete understanding of the biomechanical interaction between the device and the skull. The overall aim of this grant is to create a validated and robust computational framework that integrates patient information and device design to deliver personalised care in paediatric craniofacial surgery in order to improve clinical outcomes. A virtual model of the infant skull with craniosynostosis, including viscoelastic properties and mechano-biology regulation, will be developed to simulate device implantation and performance over time, and will be validated using clinical data from patient populations treated with current devices. Bespoke new devices will be designed allowing for pre-programmed 3D shapes to be delivered with continuous force during the implantation period. Patient specific skull models will be used to virtually test and optimise the personalised devices, and to tailor the surgical approach for each individual case.

1 498 772 €

Start date: 2018-03-01, End date: 2023-02-28

In the biomedical sciences, where endless combinatorial diversity of genes, proteins and synthetic molecules is involved, miniaturisation has not simply allowed an increase in the speed at which experiment can be performed: it has given birth to new areas such as combinatorial chemistry and biology, proteomics, genomics, and more recently, systems and synthetic biology. In all these areas, the synthesis, assay and analysis of large molecular ensembles has become the essence of experimental progress. However, it is the systematic analysis of the enormous amounts of data generated that will ultimately lead to an understanding of fundamental chemical and biological problems. This proposal deals with approaches in which libraries of molecules are employed to give such mechanistic insight – into how enzyme catalysis is brought about in proteins and polymeric enzyme models and into the molecular recognition and cell biology of drug delivery reagents. In each case considerable technical challenges are involved in the way diversity is brought about and probed: ranging from either using the tools of synthetic chemistry to using gene repertoires in emulsion microdroplet reactors with femtolitre volumes, handled in microfluidic devices.

563 848 €

Start date: 2008-09-01, End date: 2013-08-31