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Researcher
- Omer Onar
- Subho Mukherjee
- Brian Post
- Mostak Mohammad
- Vandana Rallabandi
- Peter Wang
- Vivek Sujan
- Andrzej Nycz
- Erdem Asa
- Shajjad Chowdhury
- Blane Fillingim
- Burak Ozpineci
- Chris Masuo
- Emrullah Aydin
- Jon Wilkins
- Sudarsanam Babu
- Thomas Feldhausen
- Adam Siekmann
- Ahmed Hassen
- Gui-Jia Su
- Isabelle Snyder
- J.R. R Matheson
- Joshua Vaughan
- Lauren Heinrich
- Peeyush Nandwana
- Veda Prakash Galigekere
- Yousub Lee
- Adam Stevens
- Alex Roschli
- Ali Riza Ekti
- Amit Shyam
- Brian Gibson
- Cameron Adkins
- Christopher Fancher
- Chris Tyler
- Craig Blue
- David Olvera Trejo
- Gordon Robertson
- Isha Bhandari
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- John Lindahl
- John Potter
- Liam White
- Lingxiao Xue
- Luke Meyer
- Michael Borish
- Nishanth Gadiyar
- Rafal Wojda
- Rangasayee Kannan
- Ritin Mathews
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Scott Smith
- Steven Guzorek
- Vlastimil Kunc
- William Carter
- William Peter
- Yukinori Yamamoto

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.

In additive printing that utilizes multiple robotic agents to build, each agent, or “arm”, is currently limited to a prescribed path determined by the user.

This invention discusses the methodology to calibrating a multi-robot system with an arbitrary number of agents to obtain single coordinate frame with high accuracy.

This disclosure introduces an innovative tool that capitalizes on historical data concerning the carbon intensity of the grid, distinct to each electric zone.

This disclosure introduces an innovative tool that capitalizes on historical data concerning the carbon intensity of the grid, distinct to each electric zone.

Technologies directed to an integrated on-board charger for dual motor based electric vehicle power train are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.