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| Funder | Swedish Research Council |
|---|---|
| Recipient Organization | Malmö University |
| Country | Sweden |
| Start Date | Jan 01, 2023 |
| End Date | Dec 31, 2026 |
| Duration | 1,460 days |
| Number of Grantees | 4 |
| Roles | Co-Investigator; Principal Investigator |
| Data Source | Swedish Research Council |
| Grant ID | 2022-04497_VR |
The influence of radiation-induced segregation on the mechanical properties of liquid metal plasma-facing materials will be studied with the aim to quantify and enable modelling of its embritteling impact on the grain boundary (GB) strength.
To address this issue, we will establish a novel multi-scale modelling approach - based on atomistically-informed deep learning - to describe the joint impact of radiation-damage and impurity segregation on the GB traction-separation behaviour and to enable micro-scale failure modelling.
The remaining project aims are summarized as follows:Establish a correlation between GB structure and susceptiability for embrittlementExplore the embritteling-resistance of special GBs in engineered polycrystals.The novel features include e.g. the development new schemes to design of mechanism-based interatomic potentials specifically for modelling GB embrittlement and the adoption of deep learning techniques to explore the relation between the intrinsic GB structure and susceptibility to embrittlement.
The project, which involves both cutting-edge modelling and experimentation, is planned for four years involving one full-time PhD student and a team of five senior researchers.
The herein acquired knowledge will lay a foundation for improved life-time predictions and serve as input to engineering fusion components with enhanced microstructural resistance against embrittlement.
Malmö University
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