Project Info
Automating the Analysis of 3D Printed Metals Microstructures
Aaron Stebner | astebner@mines.edu
This project is a large, collaborative effort between Mines, Lockheed Martin, Wolf Robotics, Carnegie Mellon, Oak Ridge, and other collaborators. The overall task is to deliver a 6-axis robotic laser welding additive manufacturing machine to the Navy that can qualify parts as they are being built, instead of taking years to qualify a part after it’s built.
This project will also support the development of a new high-throughput 3D X-ray Diffraction and Tomography beam line at the Advanced Photon Source of Argonne National Lab.
Critical technologies need to be developed for high throughput characterizations of 3D printed metals to support building a database sufficient for training machine learning models to use for real-time process optimization. These include X-ray tomography for characterizing porosity, mechanical testing, X-ray diffraction for characterizing phases, and microscopy for characterizing other microstructure aspects (weld pool sizes, cracks, precipitates, etc.).
This effort will have broader impact toward automating the ability for scientists to collect large amounts of high pedigree metals characterization data, improving their ability and lowering the barrier to scientific discovery, both in additive manufacturing, as well as materials science and engineering as a whole.
More Information
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1726375&HistoricalAwards=false
Grand Engineering Challenge: Engineer the tools of scientific discovery
Student Preparation
Qualifications
good to excellent programming abilities in Python, C++, and/or Matlab
some basic knowledge of metals and mechanical behavior of materials is a plus, but not required
Time Commitment
15/mo minimum, more is better
Skills/Techniques Gained
deep knowledge of materials microstructures and properties
software development
data compression, management, and processing
algorithm development
sampling
advanced materials characterization techniques
Mentoring Plan
The student will be paired with a senior graduate student or post doc who will have the ability to work with the student as much as needed
The student will have a review with myself and/or Prof. Kappes at least every other week to give a progress update and plan next steps
We have several subgroup meetings each week the student can attend to network and collaborate with others working on parallel/related efforts/aspects of our research programs