Amel Shamseldeen Ali Alhassan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Amel Shamseldeen Ali Alhassan has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
Benjamin Berkels
AICES Graduate School, RWTH Aachen University, Schinkelstr. 2, 52062 Aachen, Germany
1 shared publication- Benjamin Berkels
RWTH Aachen University
1 shared publication - Christina Scheu
Max Planck Institute for Sustainable Materials Düsseldorf Germany
1 shared publication - Dierk Raabe
Max Planck Institute for Sustainable Materials, Düsseldorf 40237, Germany
1 shared publication - Gerhard Dehm
Max Planck Institute for Sustainable Materials Max-Planck-Straße 1 40237 Düsseldorf Germany
1 shared publication Jochen M. Schneider
Materials Chemistry RWTH Aachen University Kopernikusstraße 10 52074 Aachen Germany
1 shared publication
Latest Publications
- Open Access
- 17 November 2024
- Published by Wiley in Advanced Materials
- Vol. 37 (3) , e2402191
Materials Design by Constructing Phase Diagrams for Defects
Phase transformations and crystallographic defects are two essential tools to drive innovations in materials. Bulk materials design via tuning chemical compositions is systematized using phase diagrams. It is shown here that the same thermodynamic concept can be applied to manipulate the chemistry at defects. Grain boundaries in Mg–Ga system are chosen as a model system, because Ga segregates to the boundaries, while simultaneously improving the strength and ductility of Mg alloys. To reveal the role of grain boundaries, correlated atomic‐scale characterization and simulation to scope and build phase diagrams for defects are presented. The discovery is enabled by triggering phase transformations of individual grain boundaries through local alloying, and sequentially imaging the structural and chemical changes using atomic‐resolution scanning transmission electron microscopy. Ab initio simulations determined the thermodynamic stability of grain boundary phases, and found out that increasing Ga content enhances grain boundary cohesion, relating to improved ductility. The methodology to trigger, trace, and simulate defect transformation at atomic resolution enables a systematic development of defect phase diagrams, providing a valuable tool to utilize chemical complexity and phase transformations at defects.
- 17 November 2024
- Published by Wiley in Advanced Materials
- Vol. 37 (3) , e2402191
Open AccessMaterials Design by Constructing Phase Diagrams for Defects
Phase transformations and crystallographic defects are two essential tools to drive innovations in materials. Bulk materials design via tuning chemical compositions is systematized using phase diagrams. It is shown here that the same thermodynamic concept can be applied to manipulate the chemistry at defects. Grain boundaries in Mg–Ga system are chosen as a model system, because Ga segregates to the boundaries, while simultaneously improving the strength and ductility of Mg alloys. To reveal the role of grain boundaries, correlated atomic‐scale characterization and simulation to scope and build phase diagrams for defects are presented. The discovery is enabled by triggering phase transformations of individual grain boundaries through local alloying, and sequentially imaging the structural and chemical changes using atomic‐resolution scanning transmission electron microscopy. Ab initio simulations determined the thermodynamic stability of grain boundary phases, and found out that increasing Ga content enhances grain boundary cohesion, relating to improved ductility. The methodology to trigger, trace, and simulate defect transformation at atomic resolution enables a systematic development of defect phase diagrams, providing a valuable tool to utilize chemical complexity and phase transformations at defects.
- 5 August 2023
- Published by Elsevier in Ultramicroscopy
- Vol. 254, 113827
Direct motif extraction from high resolution crystalline STEM images
- 5 August 2023
- Published by Elsevier in Ultramicroscopy
- Vol. 254, 113827
Direct motif extraction from high resolution crystalline STEM images