Calendar of Events

CDAC Webinar: Anthony D. Rollett

“High Energy X-ray Microscopy Insights into Additive Manufacturing“

Anthony D. Rollett , Department of Materials Science & Engineering , Carnegie Mellon University

 Wed, Sep 28, 1:00 pm CT

Zoom link:

https://uic.zoom.us/j/99098590328?pwd=Qkxia2ROdXVvSHRNUGdNaHN1Wjlodz09

Abstract: 

Additive manufacturing (AM), aka 3D printing, is a relatively new technology that has given rise to the “maker culture” and an intense interest in design. That has carried over into metals AM, which has jumped almost immediately into manufacturing of actual parts. In doing so it has liberated both alloy design because of high cooling rates and part design because of geometric flexibility. Complex components have been deployed that were previously inaccessible, e.g., heat exchangers. Nothing is ever as simple as it seems, however, and the reliability of parts that must carry load depends on the internal (micro-)structure, especially with respect to fatigue loading. This motivates detailed study of all aspects of materials microstructure ranging from defect structures to strain, all of which is ideally suited to the use of intense sources of high energy x-rays as only third generation light sources can deliver. Computed tomography (CT) has revealed the presence of porosity in AM metals examined to date and confirmed that appropriate process control can limit it. CT has also provided data on surface condition that links to fatigue performance.  High speed radiography reveals even more crucial details of how laser light generates vapor cavities (“keyholes”) that can deposit voids past a critical instability point. Solidification cracking has been imaged as it happens during the solidification process, which offers the possibility finding printing recipes for alloys previously considered off-limits to 3D printing. High speed, high resolution diffraction in stainless steel, alloy 718 and Ti-6Al-4V reveals unexpected solidification and precipitation sequences. Diffraction microscopy reveals the highly strained nature of printed metals and how microstructure and internal strain state evolves during subsequent annealing. Supporting all these activities is machine learning which is a pervasively useful tool.

PSC All-Hands Meeting
Oct 26, 10am