journal article·2014-12

Surface precipitation on engineering alloys

Y. Chen, X.Y. Fang, Y. Brechet, C.R. Hutchinson

Acta Materialia· Volume 81
Publisher page

Abstract

Abstract It is well known that solid-state precipitation forms an important microstructural component of many engineering alloys and is used to help control the bulk mechanical properties. In this contribution, a thermal treatment process is introduced that can induce solid-state precipitation also on the surfaces of engineering alloys, resulting in patterned surfaces. The process requires only thermal treatments and could be integrated into existing thermal or thermomechanical processing schedules for engineering alloys—as a consequence, one of the advantages over existing surface treatment processes is that it is comparatively cheap. Three Al–Si-based alloys are used to demonstrate the key features of the surface precipitation process. Surface area coverage of 30% of Si particles, Si(Ge) core–shell particles, and Mg 2 Si particles on Al–Si, Al–Si–Ge and AA6061 alloys, respectively, are demonstrated. The kinetics of surface precipitation are studied using in situ hot-stage optical microscopy. The surface precipitation process brings together aspects of surface science and physical metallurgy and represents a fertile field for collaboration between these disciplines and for the investigation of surface precipitation, as a potential future surface treatment. The ability to cheaply pattern the surfaces of engineering alloys with compounds that may themselves exhibit interesting functional properties highlights an opportunity for alloy designers and functional materials researchers to collaborate for the long-term goal of functionalizing structural engineering alloys.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Aluminum Alloy Microstructure Properties · Aluminum Alloys Composites Properties · Magnesium Alloys: Properties and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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