Live Event: Thursday, November 12, 2020
Join experts at the roundtable for a discussion on the design of new alloys suited for metal additive manufacturing (AM), with a focus on computational approaches and experimental approaches. The topics will cover important aspects of processing and postprocessing in alloy design. In particular, the panelists will discuss high throughput experimental methods for the evaluation of alloys for AM, computational methods to design alloys amenable to AM processing and postprocessing constraints, and applications for new alloys in AM.
What You Will Learn
- Gain an understanding of the approaches being used to design alloys for AM
- Know the metallurgical considerations for phase formation/microstructural evolution during AM in the design of new alloys
- Learn why a need exists for new alloys in AM
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About the Speakers
Allison M. Beese
Associate Professor, Materials Science and Engineering and Mechanical Engineering, Pennsylvania State University
Allison Beese received her B.S. in Mechanical Engineering from Penn State. She then worked at Knolls Atomic Power Laboratory before entering graduate school. She earned her M.S. and Ph.D. degrees in Mechanical Engineering from MIT. She spent two years as a postdoctoral fellow at Northwestern University, and joined the Materials Science and Engineering Department at Penn State in 2013. Her group focuses on identifying processing-structure-property links in metals through experimental characterization of microstructures and mechanical properties. In turn, they work to develop appropriate computational models, that consider microstructure, to describe the large deformation and fracture behavior of these materials. She has received an NSF CAREER award, the 2018 TMS AIME Robert Lansing Hardy Award, the 2017 International Outstanding Young Researcher in Freeform and Additive Manufacturing award, and a 3M non-tenured faculty award.
Professor, University of the Bundeswehr Munich
"Experimental Methods for Alloy Prototyping for Additive Manufacturing"
Both processability and final properties of new or modified alloys for additive manufacturing are sometimes difficult to predict. Therefore, experimental approaches are very useful. Here I present some approaches that allow to prototype new alloy compositions without costly and time-consuming pre-alloyed powder atomization.
Eric Jägle studied materials science at the University of Stuttgart, Germany, receiving a Dipl.-Ing. degree with distinction in 2006. In 2006-2007, he spent one year at the University of Cambridge. In the M.Phil. course in Materials Modelling, he worked with H.K.D.H. Bhadeshia on simulating the origin of banding in hot-rolled steel. Afterwards, he returned to Stuttgart for his Ph.D. at the Max-Planck-Institut für Metallforschung (MPI for Metals Research) under the supervision of Prof. E. J. Mittemeijer. His work focused on the mesoscopic simulation of microstructure development during phase transformations, in particular during recrystallization. After receiving his Ph.D. in 2011 with distinction, he moved to the Max-Planck-Institut für Eisenforschung (MPI for Iron Research) in Düsseldorf, Germany. There, he worked as post-doctoral researcher in the department of Prof. D. Raabe on Atom Probe Tomography analysis of electrical steels, precipitation transformations and mechanical alloying. In 2015 he became leader of a newly-formed group in the same department working on alloys for Additive Manufacturing. The group focuses on various aspects of alloys used in AM such as particle reinforcement, in-process strengthening reactions, hot cracking behaviour, residual stress and in-process metal-gas reactions. The investigated materials include steels, Ni- and Al- based alloys and composites. In 2020, he moved to the Institute of Materials Science of the Bundeswehr University Munich as full professor, continuing his work on materials for additive manufacturing.
Manager of Design and Product Development, QuesTek Innovations LLC
"ICME-based Alloy Design and Optimization for Additive Manufacturing"
Traditional wrought and cast alloys are not optimized for processing via Additive Manufacturing, and in some cases may not be printable at all. Furthermore, while there is a growing interest in use of AM parts as-built or with minimal post processing, design of optimized AM post-processing (heat treatment, HIP, surface finish, etc.) is critical to achieving property objectives. By applying computational models to capture process-structure-property relationships specific to AM, QuesTek has designed alloys that are not just optimized for AM processing, but in fact harness unique AM process conditions to in some cases exceed performance of wrought material.
Dana Frankel received her Sc.B. in Materials Science from Brown University before spending time as a materials engineer at Intel, working in quality and reliability, failure analysis, and electron microscopy groups. She went on to earn her Ph.D. in Materials Science from Northwestern University where her research focused on the design of high strength, fatigue resistant low-Ni and Ni-free shape memory alloys for biomedical applications. After graduating, she joined QuesTek Innovations LLC as a Materials Design Engineer. At QuesTek she has worked across a wide variety of alloy systems including lightweight cast alloys, refractory alloys, high entropy alloys, cast iron and steels for structural and tool applications, and design and optimization of alloys tailored for additive manufacturing. As the manager of design and product development at QuesTek, she leads the Design group, oversees alloy design activities, and coordinates strategic development of QuesTek’s IP portfolio.
Materials Technology Director, GE Research
"Rapid Development of AM Alloys for Aerospace Applications"
“Rapid Development of AM Alloys for Aerospace Applications”
The presenter will talk about some of the unique challenges associated with additive materials for aerospace applications. He will additionally share some of the unique approaches GE has taken to accelerate the development of high-temperature additive alloys, and how the team at GE is using machine learning to drive process optimization.
Joseph Vinciquerra is an aerospace engineer with more than twenty years of advanced technology development experience. As materials technology director at GE Research, he leads a world-class team of technologists working to shape and deliver the future of materials and processing techniques for GE and its customers. His 200+ member team of research scientists and engineers work across metals, ceramics, composites, coatings, and compounds and bring exceptional depth in material behavior, characterization, inspection, and physical modeling.
Vinciquerra’s technical background is rooted in experimental fracture mechanics of composite materials, to which he has gone on to innovate in composite structures design, coatings development, and life methods. Prior to his current role, he led GE’s research and development efforts associated with additive manufacturing for aerospace applications. His current areas of interest reside at the intersection of material science and digital manufacturing, such as in additive manufacturing, and the use of artificial intelligence and machine learning to accelerate material discovery and process optimization.
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