Project description DEENESFRITPL Catalysis at the flick of a switch The EU-funded PushQChem project will study molecular nanoswitches that can be reversibly turned on and off to control a chemical reaction. These materials respond to external stimuli with a conformational or configurational change, offering a way for creating artificial molecular machines that can control complex cascade reactions using a chemical switch. Using cutting-edge computational chemistry approaches (e.g. machine learning techniques) and experimental methods that can map their intricate properties, the project will shed more light on the rich morphology and chemistry of these smart catalysts, pushing back the frontiers of modern quantum chemistry. Show the project objective Hide the project objective Objective This project exploits the synergy between the trending area of artificial molecular machines and cutting edge computational chemistry approaches. Specific emphasis is placed on photoswitchable catalysts, which respond to external stimuli with a conformational or configurational change. These controllable motions allow catalytic function to be turned ON/OFF in a switch type fashion by opening/hindering access of a substrate to a catalytic site. On one hand, the rich morphology and chemistry of these smart catalysts calls for computational insights and design principles that complement experiment and push the field forward. On the other hand, the inherent complexity of these highly fluxional molecules makes them perfect subjects for driving modern quantum chemistry out of its comfort zone. To benefit from this synergy, the latest innovations in quantum chemistry-based machine learning techniques will be combined with methods capable of thoroughly mapping the intricate chemistry of molecular actuators. Overall, we aim to bridge the gap between the current state-of-the-art, which has reached reasonable quantum chemical accuracy for rigid medium size organic molecules, and more challenging fluxional architectures. The proposed methodological toolbox will be applied to the field of smart catalysis where general strategies for improving the efficiencies and enhancing enantioselectivity will be formulated. Thus, this project involves exploiting a wide range of modern computational approaches to chemical tasks that are broadly relevant to flexible/switchable catalytic systems. The anticipated output will furnish the computational chemistry community with a comprehensive array of novel next-generation approaches with applicability beyond the field of molecular machines. Fields of science natural scienceschemical sciencesphysical chemistryquantum chemistrynatural scienceschemical sciencescatalysisnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2018-COG - ERC Consolidator Grant Call for proposal ERC-2018-COG See other projects for this call Funding Scheme ERC-COG - Consolidator Grant Coordinator ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE Net EU contribution € 1 949 385,00 Address Batiment ce 3316 station 1 1015 Lausanne Switzerland See on map Region Schweiz/Suisse/Svizzera Région lémanique Vaud Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE Switzerland Net EU contribution € 1 949 385,00 Address Batiment ce 3316 station 1 1015 Lausanne See on map Region Schweiz/Suisse/Svizzera Région lémanique Vaud Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
