Objective 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. Fields of science 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 Topic(s) ERC-StG-2014 - ERC Starting Grant Call for proposal ERC-2014-STG See other projects for this call Funding Scheme ERC-STG - Starting Grant Coordinator UNIVERSITY OF STUTTGART Net EU contribution € 326 250,00 Address Keplerstrasse 7 70174 Stuttgart Germany See on map Region Baden-Württemberg Stuttgart Stuttgart, Stadtkreis 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 (2) Sort alphabetically Sort by Net EU contribution Expand all Collapse all UNIVERSITY OF STUTTGART Germany Net EU contribution € 326 250,00 Address Keplerstrasse 7 70174 Stuttgart See on map Region Baden-Württemberg Stuttgart Stuttgart, Stadtkreis 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 MAX PLANCK INSTITUT FUR EISENFORSCHUNG GMBH Germany Net EU contribution € 1 173 125,00 Address Max planck strasse 1 40237 Dusseldorf See on map Region Nordrhein-Westfalen Düsseldorf Düsseldorf, Kreisfreie Stadt Activity type Research Organisations 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
