DFT data for giant hardening response in AlMgZn(Cu) alloys

AiiDA calculations for the publication Giant hardening response in AlMgZn(Cu) alloys. This study presents a thermomechanical processing concept which is capable of exploiting the full indus- trial application potential of recently introduced AlMgZn(Cu) alloys. The beneficial linkage of alloy design and processing allows not only to satisfy the long-standing trade-off between high mechanical strength in use and good formability during processing but also addresses the need for economically feasible processing times. After an only 3-hour short pre-aging treatment at 100 °C, the two investigated alloys, based on commercial EN AW-5182 and modified with additions of Zn and Zn + Cu respectively, show high formability due to increased work-hardening. Then, these alloys exhibit a giant hardening response of up to 184 MPa to reach a yield strength of 410 MPa after a 20-minute short final heat treatment at 185 °C, i.e. paint-baking. This rapid hardening response strongly depends on the number density, size distribution and constitution of precursors acting as preferential nucleation sites for T-phase precursor precipitation during the final high-temperature aging treatment and is significantly increased by the addition of Cu. Minor deformation (2%) after pre-aging and before final heat treatment further enhances the development of hardening precipitates additionally by activating dislocation-supported nucleation and growth. Tensile testing, quantitative and analytical electron-microscopy methods, atom probe analysis and DFT calculations were used to characterize the alloys investigated in this work over the thermomechanical processing route. The influence of pre-strain on the hardening response and the role of Cu additions in early-stage cluster nucleation are discussed in detail and supported by in-situ STEM experiments and first-principles calculations.

Identifier
Source https://archive.materialscloud.org/record/2021.227
Metadata Access https://archive.materialscloud.org/xml?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:1181
Provenance
Creator Marchand, Daniel; William, Curtin
Publisher Materials Cloud
Publication Year 2021
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type Dataset
Discipline Materials Science and Engineering