EMIT Lab

The EMIT lab’s mission (Engineering Materials for Transformative Technologies) is to conduct advanced manufacturing research aimed at lowering the carbon footprint, primarily in the aerospace, automobile, and energy industries. This will be achieved by increasing the material and energy efficiency of manufacturing processes, improving operational efficiency during the product’s use phase, and enabling transformative technologies such as nuclear fusion, high-efficiency turbine systems, and rocket engines.

Towards this mission, our primary focus is on developing a deeper understanding of process-structure-property relationships through both physics-based and statistical modeling, as well as multiscale and multimodal characterization. This knowledge is applied across our metal additive manufacturing projects to develop strategies for real-time monitoring, process optimization, and control, with the goal of creating adaptable, high-quality metal manufacturing processes for improved part performance and consistency.

Faculty

Sneha Prabha Narra

Assistant Professor, Mechanical Engineering

Courtesy appointment, Materials Science & Engineering

My academic journey has led to the establishment of the EMIT lab, where I work at the intersection of mechanical and materials engineering to advance manufacturing. I use manufacturing as a vehicle to explore diverse disciplines, continuously expanding my understanding of manufacturing as well as the new areas we venture into. As an instructor and research advisor, my primary goal is to create an engaging environment that sparks independent exploration and empowers students to challenge existing ideas—including my own.

Office

304 Scaife Hall

Email

snarra@andrew.cmu.edu

Google Scholar

Sneha Prabha Narra

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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.

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Projects

Part geometry effects on AM defects and microstructure

Part geometry is a key variable in additive manufacturing, manifesting in the form of varying deposition temperatures and thermal cycles during fabrication. Depending on the geometry, the deposition temperature increases, and the overall thermal cycles experienced by the material can cause notable phase transformations. Thus, there is a need to characterize the defects and microstructure resulting from higher deposition temperatures and thermal cycles when fabricating heat-constricting part geometries. This work focuses on establishing process windows as a function of deposition temperature and quantifying the effects of part thermal cycles on the microstructure and properties of as-fabricated and heat-treated Inconel 718.

This project, focused on laser powder bed fusion AM, is being carried out by William Frieden Templeton in collaboration with the University of Pittsburgh, with support from NASA.

Understanding oxide evolution in the melt pool via modeling and experimentation

Oxide dispersion-strengthened (ODS) alloys contain a high number density of nanoscale oxide particles, offering exceptional creep strength in high-temperature applications. Previous work on additively manufactured ODS alloys focused on experimental approaches, resulting in undesirable microstructural characteristics (low dispersoid number density and deleterious micron-scale inclusions). To gain insight into processing-microstructure relationships, this project integrates thermo-kinetic modeling with laser powder bed fusion experiments, enabling the development of processing strategies to increase dispersoid number density and eliminate inclusions. This work is conducted by Nathan Wassermann (co-advised by Alan McGaughey) with the support of the NDSEG Fellowship.

In-situ melt pool monitoring with two-color thermal imaging

In-situ melt pool temperatures and cooling conditions are critical in determining bead quality, solidification microstructure, and resulting properties. However, a major challenge in measuring temperatures with current thermal cameras is the need for spectral emissivity. In this work, we use a commercial color camera to apply a novel two-color method that reliably measures dynamic melt pool temperatures. Furthermore, we relate these measurements to properties such as hardness, thus enabling part property prediction. This in-situ temperature monitoring technique can be used for real-time process adjustments and provides high-quality temperature data that can be used for model calibration efforts.

This work, focused on the wire arc additive manufacturing process, is carried out by Gala Solis, co-advised by Jon Malen, with the support of the Manufacturing Futures Institute and the Army Research Laboratory.

Optimal control of property distributions in metal AM

Spatially varying heat input in AM processes provides both opportunities and challenges for process planning. Traditional heuristic methods and grid-based process mapping struggle with highly transient scenarios and varying part geometries, and are not suited to directly optimizing outcomes. To overcome this challenge, we are investigating an alternative approach based on formulating AM processes in state-space and solving for process plans using numerical trajectory optimization.

We are applying this planning approach to two different AM processes: electron beam powder bed fusion (EB-PBF) and wire arc additive manufacturing (WAAM). In both cases, we seek to control both the melting conditions and part-scale thermal conditions and final property outcomes. We solve both cases using a unified set of tools for additive manufacturing optimal control (ADDOPT) that we have developed, and demonstrate the solutions with experimental validation.

This project is being carried out by Mikhail Khrenov, with funding provided by the National Science Foundation’s Graduate Research Fellowship and the CMU Manufacturing Futures Institute.

Electron beam powder bed fusion process development

The electron beam offers unprecedented control over beam movement in addition to the flexibility to use higher deposition temperatures. For instance, we can steer the beam with velocities up to 4 km/s and deliver beam power as high as 6 kW. The focus of this work is on developing process strategies that utilize these unique capabilities to tailor the melting and solidification conditions, as well as work with alloys that are traditionally challenging to use in laser-based AM processes. This research is being performed by Jacob McCauley and Mikhail Khrenov in collaboration with William Frieden Templeton.

Feedback control of wire arc additive manufacturing

Wire Arc Additive Manufacturing (WAAM) allows for the economical manufacture of complex metal parts from high-strength alloys. However, variations in the process arising from changing conditions and environmental disturbances can introduce inconsistencies into the as-built geometry, microstructure, and resulting properties.

To mitigate these issues and realize the full potential of WAAM, we are developing closed-loop control approaches to ensure part quality. This includes monitoring melt pool geometry, solidification conditions, and global temperatures, and using appropriate control laws to adjust process parameters to track the desired deposition profile. Where necessary, we are also developing additional degrees of actuation for the process to allow for greater control over more variables simultaneously.

This project is being carried out by Lauren Fitzwater, Michelle Hobdari, River Sepinuck, and Moon Tan in collaboration with Mikhail Khrenov and Gala Solis.

Statistical models for linking defects to fatigue in AM

Due to the occurrences of porosity throughout, Laser Powder Bed Fusion manufactured components often suffer from degradation and increased variance in fatigue properties. In this work, we use X-ray Micro Computed Tomography porosity data to establish a robust, fatigue-based process window where components fabricated at parameters within this process window exhibit consistently superior fatigue performance for a given part geometry. Additionally, we seek to capture the variance in fatigue performance using porosity distributions, which allows for a streamlined path to certification for Laser Powder Bed Fusion components for fatigue applications. This work was supported by the NASA University Leadership Initiative and is currently being supported by the NASA Space Technology Research Institute grant entitled Institute for Model-Based Quality and Certification of Additive Manufacturing (IMQCAM). This project is being carried out by Justin Miner.

Multi-scale and multi-modal characterization to support model based qualification

Defects and microstructure play a critical role in determining the fatigue behavior of a material. This project primarily focuses on multi-scale and multi-modal characterization of laser powder bed fusion manufactured Inconel 718 to investigate porosity, grain structure, and secondary phases/precipitates in as-fabricated and post-processed material. This information will provide comprehensive experimental datasets to support process and material modeling efforts, as well as provide inputs to the micromechanical modeling of fatigue and fracture. This work is currently being supported by the NASA Space Technology Research Institute grant entitled Institute for Model-Based Quality and Certification of Additive Manufacturing (IMQCAM). This project is being carried out by David Reyes (co-advised by Tony Rollett).

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Research team

Jiangce Chen

Post-Doctorate

Email

jiangcec@andrew.cmu.edu

LinkedIn Profile

Mikhail Khrenov

Doctorate

Email

mkhrenov@andrew.cmu.edu

LinkedIn Profile

Jacob McCauley

Doctorate

Email

jacobmcc@andrew.cmu.edu

Linkedin profile

Justin Miner

Doctorate

Email

jpminer@andrew.cmu.edu

LinkedIn Profile

David Reyes

Doctorate

Co-Advisor

Anthony Rollett

Email

jreyesor@andrew.cmu.edu

LinkedIn Profile

Gala Cassiel Solis

Doctorate

Co-Advisor

Jonathan Malen

Email

gsolis@andrew.cmu.edu

LinkedIn Profile

William Frieden Templeton

Doctorate

Email

wfrieden@andrew.cmu.edu

LinkedIn Profile

Nathan Wassermann

Doctorate

Co-Advisor

Alan McGaughey

Email

nwasserm@andrew.cmu.edu

Portfolio

Zhonghao Wei

Masters

Email

zhonghaw@andrew.cmu.edu

LinkedIn Profile

Lauren Fitzwater

Undergraduate

Email

lgf@andrew.cmu.edu

LinkedIn Profile

Michelle Hobdari

Undergraduate

Email

mhobdari@andrew.cmu.edu

LinkedIn Profile

Moon Tan

Undergraduate

Email

yuetnint@andrew.cmu.edu

LinkedIn Profile

River Sepinuck

Undergraduate

Email

rsepinuc@andrew.cmu.edu

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Join us

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!

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Courses

Course	Course Name	Location	Units	Semester Offered
24-632	Special Topics: Additive Manufacturing Processing and Product Development	Pittsburgh	12	Fall
24-633	Additive Manufacturing Laboratory	Pittsburgh	12	Spring
24-651	Material Selection for Mechanical Engineers	Pittsburgh	12	Spring

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Media mentions

the Manufacturing Futures Institute

CMU student, professor, and alumnus receive ICAM awards

International Conference on Advanced Manufacturing awardees were recognized for contributions to advanced manufacturing research.

the Manufacturing Futures Institute

AI generates missing parts of temperature distribution

Researchers have found a way to reconstruct the complete temperature profile in real time using only the partial data available from in situ sensors used in additive manufacturing.

CMU Engineering

NASA mentor guides student’s career trajectory

Campus research experience, NASA internship, and advice from a mentor propel material science and engineering student, Lauren Fitzwater, to pursue a minor in additive manufacturing.

CMU Engineering

Undergraduates present research at Meeting of the Minds 2024

Engineering undergraduate students had a wonderful showing at Meeting of the Minds, displaying posters, giving presentations, and demonstrating projects they have worked on this past academic year.

See More Mentions

CMU Engineering

These defects are not to be mistaken as scratches

Shrinkage porosity, a common defect in metal castings, has been identified in laser powder bed fusion additive manufacturing.

CMU Engineering

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 Engineering

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.

CMU Engineering

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.

CMU Engineering

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.

Mechanical Engineering

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.

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Alumni

Graduate students

• Colin Ancalmo, master's student, currently a Ph.D. student at Carnegie Mellon University
• Kevin Chou, master's student, currently at Resilient Lifescience
• Hanshen Yu, June 2020-June 2023, currently a Ph.D. student at WPI
• Tharun Reddy, master's student, Aug 2021 - May 2023, currently a Ph.D. student at Stanford University
• Ryan Utz, master's student, Aug 2021 - May 2023
• Yao Xu, Ph.D. student, Aug 2018 – May 2022, co-advised with Professor Brajendra Mishra, currently working for Mattson Technology
• Mahya Shahabi, Graduate student researcher, Aug 2019 – May 2021, currently working for Ambri
• Prajwal Bharadwaj, Graduate student researcher, January 2021 – May 2021, currently a Ph.D. student at WPI
• Krishnan Giridharan, master's student, October 2019 – May 2021, currently an associate engineer at Rivian
• Dylan McKillip, master's student, August 2019 – May 2020, currently a test engineer at Brooks Automation

Undergraduate students

• Jorge Castano, mechanical engineering class of 2025 (CMU)
• Ian MacLachlan, mechanical engineering class of 2022 (CMU), currently Advanced Manufacturing Technician at CMU MFI
• 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)
• Samantha 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)

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