The EMIT lab (Engineering MaterIals for Transformative technologies) at CMU run by Sneha Narra focuses on advancing metal additive manufacturing knowledge to manufacture light-weight organic designs and utilize novel, advanced materials. At a scientific level, our group studies the fundamentals of additive manufacturing processes, investigates the resulting material microstructure and properties, and develops process design paradigms. Our group’s mission is to lower the carbon footprint, primarily in aerospace, automobile, and energy industries. This will be achieved either through reduced material and/or operational usage or through enabling transformative technologies, such as nuclear fusion and high-efficiency turbine systems.
Sneha Narra’s academic training and experience has led to the establishment of the EMIT lab, working at the intersection of mechanical and materials science and engineering and leveraging data-driven methods to expand advanced manufacturing capabilities. As an instructor, Narra’s goal is to help her students learn effectively in a comfortable environment and spark interest in them to explore outside the classroom. Narra is passionate about mentoring and participates in outreach activities, educates students about professional development opportunities, and provides opportunities to conduct research in interdisciplinary topics.
Labs and facilities
NextManufacturing Center houses various fusion-based metal additive manufacturing equipment that our lab uses in our research work.
We utilize electron microscopy and x-ray facilities at the Materials Characterization Facility (MCF), to conduct material characterization work.
We have robotic wire arc additive manufacturing (WAAM) equipment in our lab at Mill 19. In the following video, Lincoln Electric’s WAAM machine deposits weld beads in a layer-by-layer manner to build 3D structures. WAAM allows engineers to produce large 3D structures relatively fast compared to alternate additive manufacturing processes and traditional manufacturing processes. Builds on the scale in the video, around 1ft x 1ft x 0.5 ft footprint, take around 15-20 hours when using a qualified process. In the video below, three build layers are shown at an increased speed.
Dynamic modeling, planning, and control for wire-Arc additive manufacturing
Wire-arc additive manufacturing (WAAM) allows the production of large scale parts that can economically replace forgings and castings with no need for fixed tooling. However, the process currently suffers from instabilities and uncontrolled variations in final microstructure and properties.
In order to address these issues, we are working to develop real-time monitoring techniques, physics-based and data-informed dynamical models, and planning and control techniques with which to optimize process outcomes.
This project is being carried out by Mikhail Khrenov, in collaboration with Jack Beuth and Chris Pistorius. Funding is provided by the Manufacturing Futures Institute and the National Science Foundation’s Graduate Research Fellowship.
Influence of thermal variations on defects and microstructure
Laser powder bed fusion is a layer-by-layer process where layers of metal powder are fused to previously deposited layers successively with a laser. This creates a possibility for process conditions to change during fabrication. For instance, parts with limited conduction paths to the base plate may build up heat during manufacturing–shifting recommended process window. Our group is designing experiments and conducting material characterization to understand the effect of temperature build up and thermal cycles on defects and microstructure.
This work is conducted by William Frieden Templeton in collaboration with Albert To at the University of Pittsburgh. Funding is provided by NASA.
AM for high-temperature alloys
Oxide dispersion strengthened (ODS) alloys contain a high number density of nano-scale oxide (e.g., yttria) particles, offering exceptional high-temperature creep strength and radiation resistance. These properties make ODS steels an attractive candidate for structural materials in next-generation nuclear fusion reactors; however, existing processing routes are flawed. In this project, molecular dynamics simulations are integrated with AM experiments to investigate the mechanisms of oxygen dissolution and oxide formation, with the goal of tuning alloy composition and AM processing conditions to control oxide characteristics. This work is conducted by Nathan Wassermann in collaboration with Alan McGaughey, an expert in molecular dynamics.
Two-color thermal imaging method for wire-arc additive manufacturing
Commonly used imaging methods in wire arc additive manufacturing have included the use of monochrome or infrared (IR) cameras. A major challenge in estimating temperatures from these cameras is the need for spectral emissivity. Using the novel two-color method with a commercial color camera allows us to get more accurate temperature measurements by reducing sensitivity to the variation in spectral emissivity. Images are captured with varying exposure times to generate a full thermal field of the weld pool. These measurements can then be used in in-process monitoring and model calibration/validation to further inform process parameter development and optimization.
This work is conducted by Gala Solis in collaboration with Jonathan Malen in the Department of Mechanical Engineering, funded by the Manufacturing Futures Institute and The National GEM Fellowship Consortium.
ML-accelerated thermal simulation for metal AM
This research aims to develop fast thermal simulation tools based on machine learning methods to 1) support close-loop temperature control in AM process, 2) monitor temperature history in part-scale for studying the process-structure-property relationships, 3) predict temperature history in the stages of process planning and part design.
Impact of powder stream characteristics on part quality
Laser directed energy deposition has industrial applications for near-net shape part production and part repair. Powder stream characteristics (powder mass flow rate, spot diameter) influence powder capture efficiency and deposited track dimensions. Traditional gas atomized powder feedstock has low-yield manufacturing and low in-process powder capture efficiencies (<50%), accounting for 20% of a total part cost. A gap remains for effectively using low-cost feedstocks at industrial mass flow rates (>50 mg/s). This work investigates how process inputs (powder size and morphology, carrier gas flow rate) correlate with powder stream characteristics, for selecting process inputs with improved part quality for low-cost feedstocks.
Defect-fatigue relationships in laser powder bed fusion
In additively manufactured parts, process-induced defects reduce mechanical performance. Specifically, premature crack initiation at these defects results in fatigue failure, which limits the mechanical lifetime of AM parts adversely, endangering safety. Therefore, probabilistic methods to estimate fatigue life are necessary for qualification of AM parts for fatigue-critical applications.
This research focuses on developing methods that integrate process-defect relationships through quantification and statistical modeling to establish defect distributions (size, shape, location, and interaction). By utilizing defect statistics we aim to predict fatigue life and risk of failure.
This research is conducted by Justin Miner as part of the NASA University Leadership Initiative (ULI) project.
Structure-property relationships in binder jet WC-Co
The goal of this project is to establish microstructural relationships to material properties for Binder Jet manufactured WC-Co. The Binder Jet Process, specifically, has been found to produce WC-Co parts with inferior mechanical properties when compared to their wrought counterparts. By understanding the microstructure-property relationship, this project aims provide insight into desired microstructural distributions in production.
Statistical learning is used to create an inferential model from micrograph data obtained from feature extraction and quantification which allows for accurate prediction of mechanical properties.
Gala Cassiel Solis
William Frieden Templeton
If you are interested in joining the EMIT Lab at CMU, please read the appropriate section below.
Undergraduates: Projects are advertised through the MechE newsletter as they are available. Please refer to this information for opportunities to join the lab or email Dr. Narra with the tag [Undergrad] in the subject if you are interested in whether new projects may be becoming available.
Graduate students: All graduate students (MS or Ph.D.) will only be considered through the official CMU application system. Please apply online. If you are an admitted MS student and would like to learn about available projects please refer to the MS Canvas page or email Dr. Narra with the tag [MS] in the subject.
Postdocs: No postdoc positions are available at this time.
We look forward to hearing from you!
President Biden Visit
On January 28th, our group participated in the Mill-19 facility tour and demonstrated the wire arc additive manufacturing process in our lab in collaboration with Lincoln Electric Additive Solutions. We discussed the benefits of metal additive manufacturing with the President of the United States. We are fortunate to be part of the additive manufacturing community and honored to represent our field during the President of the United States’ visit to CMU.
(Left - Right) William Templeton, Sneha Narra, President Biden. See President Biden’s tweet about the visit.
Graduate students currently advised at WPI
- Hanshen Yu, Ph.D. student, June 2020-present, co-advised with Professor Jamal Yagoobi
Mill 19 growing a digital backbone
Digital backbone at Mill 19 will make data readily available for advancing digital twin and AI-related manufacturing research.
CMU to Lead NASA Space Technology Research Institute
A new NASA Space Technology Research Institute (STRI) led by Carnegie Mellon University seeks to shorten the cycle required to design, manufacture, and test parts that can withstand the conditions of space travel through constructing models for qualification and certification.
A sweet way to teach kids about manufacturing
Sneha Prabha Narra uses hands-on activities to introduce engineering and additive manufacturing concepts to local grade school students.
Biden calls for investment in American innovation
President Biden touted the importance of advanced manufacturing innovation, robotics, 3D printing, and artificial intelligence during his recent visit to Mill 19.
Metal 3D printing across scales
New faculty member Sneha Prabha Narra is interested in utilizing recent advances in in-situ monitoring, process modeling, and fundamentals of welding to advance the use of wire arc additive manufacturing for new applications and materials.
- Tharun Reddy, master's student
- Ryan Utz, master's student
- Yao Xu, Ph.D. student, Aug 2018 – May 2022, co-advised with Professor Brajendra Mishra, currently working for Mattson Technology
- Mahya Shahabi, Aug 2019 – May 2021, currently a Ph.D. student at WPI
- Prajwal Bharadwaj, January 2021 – May 2021, currently a Ph.D. student at WPI
- Krishnan Giridharan, October 2019 – May 2021, currently an associate engineer at Rivian
- Dylan McKillip, August 2019 – May 2020, currently a test engineer at Brooks Automation
- Ian MacLachlan
- John Trainor, aerospace engineering class of 2021 (WPI), currently a design engineer at Triton Space Technologies, LLC
- Nathaniel Rutkowski, aerospace engineering class of 2021 (WPI), currently a propulsion engineer at Firehawk Aerospace
- Kaitlin Barron, mechanical engineering class of 2022 (WPI)
- Shannon O’Connor, mechanical engineering class of 2022 (WPI), NASA LaRC summer intern (additive manufacturing research), Summer and Fall 2021
- Caitlin Kean, mechanical engineering class of 2022 (WPI)
- Nathan Maldonado, mechanical engineering class of 2022 (WPI)
- Daniel Marsh, mechanical engineering class of 2022 (WPI)
- Adrianna Yuen, mechanical engineering class of 2024 (WPI)
- Samantah Castellano, mechanical engineering class of 2024 (CMU)
- Meenakshi Sundrum, mechanical engineering, engineering and public policy, class of 2024 (CMU)
- Brenna Slomsky, mechanical engineering class of 2024 (CMU)
- Charlotte Ng, materials science and engineering, engineering and public policy, class of 2024 (CMU)
- Ian Maclachlan