Objectif The possibility to produce materials with ultra-strengths could revolutionize materials design. Since 80 years ultra-strength materials are known to exist only theoretically. Now, new experiments show that traditional believe can be overcome by nanostructured design. Yet, while selected experiments point towards this scientifically fascinating and technologically important possibility (e.g. for advances in structural and functional materials), further progress crucially relies on insight from theoretical simulations. The most successful simulation tool is molecular dynamics. Recent advances in hardware allow to tackle trillions of atoms making a comparison with nano-experiments almost possible. The nagging problem is, however, a huge time-scale gap of up to ten orders of magnitude and none of the presently available approaches is able to cope with this discrepancy.TIME-BRIDGE aims at solving the time-scale problem by borrowing a concept well known and developed in the field of first-principles simulations: the pseudopotential ansatz. In first principles simulations a similar time scale gap exists between slow and fast moving electrons. The solution is to capture the effect of the fast electrons only effectively within a pseudopotential while retaining the motion of slow electrons important for chemical bonding. An equivalent pseudopotential ansatz is envisioned to be applicable to the fast thermal motion of atoms, the origin of the time scale problem. Capturing the thermal motion in an effective potential will allow to simulate the relevant mechanical processes occurring on microsecond and second time scales. In TIME-BRIDGE high risk and high gains apply: the physics of electrons is distinct from the atomic motion possibly making the pseudopotential ansatz non-transferable, but—based on PI’s distinguished expertise and his recent methodological advancements—a route to bridge the fundamental time scale gap might arise. Champ scientifique natural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencescomputer and information sciencessoftwaresoftware applicationssimulation softwarenatural sciencesmathematicsapplied mathematicsmathematical model Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Thème(s) ERC-StG-2014 - ERC Starting Grant Appel à propositions ERC-2014-STG Voir d’autres projets de cet appel Régime de financement ERC-STG - Starting Grant Coordinateur UNIVERSITY OF STUTTGART Contribution nette de l'UE € 326 250,00 Adresse Keplerstrasse 7 70174 Stuttgart Allemagne Voir sur la carte Région Baden-Württemberg Stuttgart Stuttgart, Stadtkreis Type d’activité Higher or Secondary Education Establishments Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 326 250,00 Bénéficiaires (2) Trier par ordre alphabétique Trier par contribution nette de l'UE Tout développer Tout réduire UNIVERSITY OF STUTTGART Allemagne Contribution nette de l'UE € 326 250,00 Adresse Keplerstrasse 7 70174 Stuttgart Voir sur la carte Région Baden-Württemberg Stuttgart Stuttgart, Stadtkreis Type d’activité Higher or Secondary Education Establishments Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 326 250,00 MAX PLANCK INSTITUT FUR EISENFORSCHUNG GMBH Allemagne Contribution nette de l'UE € 1 173 125,00 Adresse Max planck strasse 1 40237 Dusseldorf Voir sur la carte Région Nordrhein-Westfalen Düsseldorf Düsseldorf, Kreisfreie Stadt Type d’activité Research Organisations Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 1 173 125,00