Summary
Al-Cu alloys have a wide range of engineering applications due to their low density and high strength provide by a fine dispersion of nm-sized precipitates. The optimization of the mechanical properties of these alloys has been traditionally carried out through costly experimental “trial-and-error” approaches. In this project, a novel methodology is presented to determine the precipitate structure resulting from high temperature ageing and the resulting strength of the alloys from first principles calculations. The strategy is based in two main pillars. The first one is the determination of the Al-rich part of the Al-Cu phase diagram by means the construction of effective cluster expansion Hamiltonians that can extrapolate first-principles calculations in combination with statistical mechanics approaches based on Monte Carlo simulations to include the entropic contributions, enabling parameter-free predictions of the phase diagram. The second one is the combination of this information with phase field modeling to predict the homogeneous and heterogeneous nucleation and growth of precipitates during high temperature ageing and with molecular dynamics and dislocation dynamics simulations to predict the strengthening provided by the precipitates. The approach developed in this proposal will improve the predictive power of Integrated Computational Materials Engineering in Al-Cu alloys. The applicant will transfer her expertise and international connection in the field of multiscale modelling to the host institute. She will work with researchers of the host institution to prompt new areas of research that can attract new funding and receive regular training on transferable skills. All these activities will enlarge her portfolio of skills and will ensure further development of her career.
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| Web resources: | https://cordis.europa.eu/project/id/893883 |
| Start date: | 01-03-2020 |
| End date: | 20-06-2022 |
| Total budget - Public funding: | 172 932,48 Euro - 172 932,00 Euro |
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Original description
Al-Cu alloys have a wide range of engineering applications due to their low density and high strength provide by a fine dispersion of nm-sized precipitates. The optimization of the mechanical properties of these alloys has been traditionally carried out through costly experimental “trial-and-error” approaches. In this project, a novel methodology is presented to determine the precipitate structure resulting from high temperature ageing and the resulting strength of the alloys from first principles calculations. The strategy is based in two main pillars. The first one is the determination of the Al-rich part of the Al-Cu phase diagram by means the construction of effective cluster expansion Hamiltonians that can extrapolate first-principles calculations in combination with statistical mechanics approaches based on Monte Carlo simulations to include the entropic contributions, enabling parameter-free predictions of the phase diagram. The second one is the combination of this information with phase field modeling to predict the homogeneous and heterogeneous nucleation and growth of precipitates during high temperature ageing and with molecular dynamics and dislocation dynamics simulations to predict the strengthening provided by the precipitates. The approach developed in this proposal will improve the predictive power of Integrated Computational Materials Engineering in Al-Cu alloys. The applicant will transfer her expertise and international connection in the field of multiscale modelling to the host institute. She will work with researchers of the host institution to prompt new areas of research that can attract new funding and receive regular training on transferable skills. All these activities will enlarge her portfolio of skills and will ensure further development of her career.Status
CLOSEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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