ERC FUNDED PROJECTS

The astonishing properties of the f-elements have been exploited in numerous consumer technologies, despite their fundamental chemistry being poorly developed. It is now crucial to address this issue to provide the necessary insights to develop future applications. Design criteria exist to build f-element complexes with maximised physical attributes. This adventurous proposal targets the synthesis and thorough analysis of two complementary molecular f-element architectures that 1) optimise magnetic properties and 2) stabilise unusual oxidation states. In Part 1, we target highly axial f-element complexes that lack equatorial ligand interactions. These molecules can exhibit maximised single-molecule magnet properties, including magnetic hysteresis, a memory effect and as a prerequisite of data storage, at liquid nitrogen temperatures. This is the necessary first step towards achieving high-density molecular data storage without expensive liquid helium cooling and future commercial applications. In Part 2, we target trigonal f-element complexes that lack axial ligand interactions. These are optimal ligand fields for the stabilisation of low oxidation states, thus we aim for rare lanthanide/actinide(II) and unprecedented lanthanide/actinide(I) complexes. These compounds are ideal candidates for unique measurements of covalency by pulsed electron paramagnetic resonance spectroscopy, which will provide textbook data that can be transferable to nuclear fuel cycles. An ERC CoG will provide the necessary resources to build a world-leading research team that will deliver landmark synthetic results and fresh insights into f-element electronic structure, whilst opening up new chemical space for future exploitation. These findings will underpin current technologies and will facilitate the discovery of future applications, supporting key Horizon 2020 priority areas including the Flagship on Quantum Technologies, and enhancing the scientific reputation and economy of the EU.

1 990 801 €

Start date: 2019-09-01, End date: 2024-08-31

InOutBioLight aims to design multifunctional rubbers with enhanced mechanical, thermal, color-converting, and light-guiding features towards advanced biohybrid lighting and photovoltaic technologies. The latter are placed at the forefront of the EU efforts for low-cost production and efficient consumption of electricity, a critical issue for a sustainable development. In this context, the use of biomolecules as functional components in lighting and photovoltaic devices is still a challenge, as they quickly denature under storage and device operation conditions. This paradigm has changed using an innovative rubber-like material, in which the biofunctionality is long preserved. As a proof-of-concept, color down-converting rubbers based on fluorescent proteins were used to design the first biohybrid white light-emitting diode (bio-HWLED). To develop a new generation of biohybrid devices, InOutBioLight will address the following critical issues, namely i) the nature of the protein-matrix stabilization, ii) how to enhance the thermal/mechanical features, iii) how to design multifunctional rubbers, iv) how to mimic natural patterns for light-guiding, and v) how to expand the technological use of the rubber approach. To achieve these goals, InOutBioLight involves comprehensive spectroscopic, microscopic, and mechanical studies to investigate the protein-matrix interaction using new polymer matrices, additives, and protein-based nanoparticles. In addition, the mechanical, thermal, and light-coupling features will be enhanced using structural biocompounds and reproducing biomorphic patterns. As such, InOutBioLight offers three major advances: i) a thorough scientific basis for the rubber approach, ii) a significant thrust of the emerging bio-HWLEDs, and iii) innovative breakthroughs beyond state-of-the-art biohybrid solar cells.

1 999 188 €

Start date: 2020-01-01, End date: 2024-12-31

"Living organisms are sophisticated self-assembled structures that exist and operate far from thermodynamic equilibrium and, as such, represent the ultimate example of dissipative self-assembly. They remain stable at highly organized (low-entropy) states owing to the continuous consumption of energy stored in ""chemical fuels"", which they convert into low-energy waste. Dissipative self-assembly is ubiquitous in nature, where it gives rise to complex structures and properties such as self-healing, homeostasis, and camouflage. In sharp contrast, nearly all man-made materials are static: they are designed to serve a given purpose rather than to exhibit different properties dependent on external conditions. Developing the means to rationally design dissipative self-assembly constructs will greatly impact a range of industries, including the pharmaceutical and energy sectors. The goal of the proposed research program is to develop novel principles for designing dissipative self-assembly systems and to fabricate a range of dissipative materials based on these principles. To achieve this goal, we will employ novel, unconventional approaches based predominantly on integrating organic and colloidal-inorganic building blocks. Specifically, we will (WP1) drive dissipative self-assembly using chemical reactions such as polymerization, oxidation of sugars, and CO2-to-methanol conversion, (WP2) develop new modes of intrinsically dissipative self-assembly, whereby the activated building blocks are inherently unstable, and (WP3&4) conceive systems whereby self-assembly is spontaneously followed by disassembly. The proposed studies will lead to new classes of ""driven"" materials with features such as tunable lifetimes, time-dependent electrical conductivity, and dynamic exchange of building blocks. Overall, this project will lay the foundations for developing new synthetic dissipative materials, bringing us closer to the rich and varied functionality of materials found in nature."

1 999 572 €

Start date: 2019-01-01, End date: 2023-12-31

Artificial molecular motors and switches have the potential to become a core part of nanotechnology. However, a wide gap in length scales still remains unaccounted for, between the operation of these molecules in solution, where their individual mechanical action is randomly dispersed in the Brownian storm, and on the other hand their action at the macroscopic level, e.g. in polymer networks and crystals. This proposal is about bridging this gap, by developing chemo-mechanical transduction strategies that will allow dynamic molecules to perform a range of unprecedented tasks, e.g. by generating strong directional forces at the nanoscale, and through shape-shifting microscopic formations. This project aims to harness the mechanically-purposeful motion of dynamic molecules as to generate measurable forces from the nanoscale, and ultimately establish operational principles for chemo-mechanical transduction in supramolecular systems. In my wholly synthetic approach, I draw inspiration from the operational principles of microtubules. I will incorporate molecular photo-switches into supramolecular tubes, and enable the controlled growth and disassembly of the tubes by using light as the energy input. Thus, I will: (i) Synthesize stiff supramolecular tubes that grow actively under continuous illumination, and disassemble with a power stroke as soon as illumination stops; (ii) Measure, and harvest the forces generated by the tubes to manipulate individual nanoparticles with a sense of directionality; and (iii) Encapsulate the tubes into water droplets and vesicles, to yield shape-shifting, and eventually rudimentary splitting models for cells. This project reaches beyond the state of the art in adaptive molecular nano-systems, by pioneering strategies to engineer and harness strain in supramolecular assemblies. It thus lays the foundations for machineries that are capable of manipulating matter at length scales that are also those at which the cytoskeleton operates.

2 000 000 €

Start date: 2019-03-01, End date: 2024-02-29

How does experience alter the functional architecture of synaptic connections in neural circuits? This question is particularly pertinent for the complex circuits of the medial prefrontal cortex (mPFC), a high-order associative neocortical area that plays a crucial role in flexible, goal-directed behavior. The mPFC is densely interconnected with cortical and subcortical circuits, and its neurons were shown to undergo substantial experience-dependent structural remodeling that is thought to support learning and memory consolidation. However, little is known regarding the synaptic organization of this complex circuit, and of the functional implications of its experience-dependent structural remodeling. In this proposal, we aim to uncover the organization and learning-associated dynamics of functional connectivity in the mouse mPFC. To obtain high-resolution maps of cell type-specific synaptic connectivity in the mPFC, we will combine single-cell optogenetic manipulation with calcium imaging and electrophysiology in vitro, and establish the circuit-wide organization of connectivity within and between defined projecting neuron populations. We will test the hypothesis that pyramidal neurons projecting to subcortical targets form tightly interconnected subnetworks, and that inhibitory inputs to these networks, through selective innervation, can modulate information output from the mPFC. To understand how learning changes the functional synaptic organization of the mPFC, we will establish an all-optical system for interrogation of synaptic connectivity in vivo. We will utilize this powerful platform to test the hypothesis that prefrontal-dependent learning is associated with reorganization of local-circuit functional connectivity among identified subcortically-projecting cell assemblies. Our innovative technology will be widely applicable for neural circuit analysis in a variety of systems, and allow us to gain new insights into the complex circuitry of the mPFC.

1 880 003 €

Start date: 2019-02-01, End date: 2024-01-31

Despite the abundance of organic compounds in Nature, only 12 contain fluorine. In contrast, fluorinated organic materials account for over 40% of all pharmaceuticals and agrochemicals. Closer inspection of the fluorination patterns in these functional molecules reveals striking extremes towards perfluorination (in both 2D and 3D scaffolds) or single site fluorination predominantly in aryl substituents. Consequently, most fluorinated moieties in functional materials lack stereochemical information and are thus achiral. This disparity between the paucity of naturally occurring organofluorine compounds and their venerable history in functional molecule design confirms the enormous potential of fluorinated materials in the discovery of novel properties. That progress has largely been confined to 3 dimensional achiral and 2 dimensional achiral architectures reflects the synthetic challenges associated with preparing stereochemical defined multiply fluorinated systems. A major limitation in the construction of C(sp3)-F units remains the need for substrate pre-functionalisation via oxidation and the competing substitution/elimination scenario that compromises efficiency in the deoxyfluorination. This problem is magnified in the synthesis of optically active fluorides where the deoxyfluorination can compromise the enantiopurity of the starting materials. The principle aim of RECON is to facilitate exploration of 3D, chiral space by providing access to multiply fluorinated, stereochemically complex organofluorine materials from simple feedstock using inexpensive, commercially available fluoride sources. In providing a modular platform to rationally place function on a structural basis, exploration of uncharted chemical space will accelerate the discovery of next generation materials for medicinal and agrochemistry, material sciences and bio-medicine.

1 999 375 €

Start date: 2019-02-01, End date: 2024-01-31

The production of chemicals, plastics, solvents, etc., contributes to 20 % of the Gross Value Added in the EU, where sales have doubled over the last 20 years. Despite this dynamism, the chemical industry is energy intensive and 95 % of organic chemicals derive from fossil oil and natural gas. To sustain the growth of this industry, the replacement of fossil feedstocks with renewable carbon, phosphorus and silicon sources should be encouraged. Nonetheless, such a sourcing shift represents a paradigm shift: while the development of petrochemistry has relied on the selective oxidation of hydrocarbons, the conversion of renewable feedstocks (e.g. CO2, phosphates, silicates or biomass) requires efficient reduction methods and catalysts to overcome their oxidized nature. Today, no reduction method meets the criteria for a versatile and energy efficient reduction of oxidized feedstocks and the aim of the ReNewHydrides project is to design novel reductants and catalytic reactions to achieve this important aim. At the crossroads of main group element chemistry, organometallic chemistry, electrochemistry and homogenous catalysis, I propose to develop innovative and recyclable reductants based on silicon and boron compounds, and to utilize them to tackle catalytic challenges in the reduction of C–O, P–O and Si–O bonds. The overarching principle is to build a balanced synthetic cycle, where the electrochemical reduction of functionalized and oxidized substrates is ensured by silicon and boron based hydride donors, with a high energy efficiency and selectivity. This project will foster innovative routes in the utilization of renewable carbon, phosphorus and silicon feedstocks. It is therefore of high risk, but ultimately extremely rewarding. The results will also also open-up new horizons in silicon and boron chemistry and they will finally serve the scientific community involved in the fields of organic and inorganic chemistry, sustainable chemistry and energy storage.

1 999 838 €

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

How do we learn to dance, play an instrument, or a game as complex as chess or go? How do we make a memory? The common answer to these questions is “through synaptic plasticity”, through changing the synaptic connectivity of neural circuits so that representative brain activity can be reliably triggered. Such connectivity changes are governed by rules, i.e., synaptic mechanisms which monitor the activity of their environment and stereotypically strengthen or weaken synapses accordingly. The shape and mode of operation of these rules is still largely unknown: For the more than hundred different connection types in cortical circuits, only a handful of rules has been described at all. Similarly, testing observed rules in simulations of cortical function has only seen limited success. Our slow progress is due to the extraordinary difficulty of measuring and observing synapses without interference. Here, we propose a new approach. By utilizing the growing power of machine learning methods we can deduce synaptic plasticity rules directly. Newly developed search algorithms and sheer computational power allow us to integrate published data and infer synaptic rules in silico. We aim to (1) develop a new mathematical expression of synaptic plasticity rules, experimentally appropriate and flexible enough to be implemented in a Machine Learning framework, dubbed SYNAPSEEK. Next (2), we will apply SYNAPSEEK to deduce the rules for building various neural structures with increasing complexity. Finally (3), we will incorporate additional constraints to SYNAPSEEK to develop synaptic rules that shape network function as much as its structure. Our work will establish, for the first time, canonical sets of synaptic plasticity rules, based on the circuit structure they must produce, and the function they are meant to support. SYNAPSEEK will have immediate and wide ranging applications, from a basic understanding of cortical development to better protocols for Deep Brain Stimulation.

1 798 605 €

Start date: 2019-06-01, End date: 2024-05-31