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Researcher
- Andrzej Nycz
- Ali Passian
- Chris Masuo
- Amit Shyam
- Hsuan-Hao Lu
- Joseph Lukens
- Nicholas Peters
- Peter Wang
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- Gyoung Gug Jang
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- Akash Jag Prasad
- Alexander I Wiechert
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- Alice Perrin
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- Andres Marquez Rossy
- Beth L Armstrong
- Brandon Miller
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- Calen Kimmell
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
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- Craig A Bridges
- Debangshu Mukherjee
- Emilio Piesciorovsky
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- Md Inzamam Ul Haque
- Mina Yoon
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- Nicholas Richter
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- Ramanan Sankaran
- Raymond Borges Hink
- Riley Wallace
- Ritin Mathews
- Ryan Dehoff
- Sheng Dai
- Sunyong Kwon
- Varisara Tansakul
- Vimal Ramanuj
- Vincent Paquit
- Vivek Sujan
- Vladimir Orlyanchik
- Wenjun Ge
- Xiaohan Yang
- Ying Yang

Materials produced via additive manufacturing, or 3D printing, can experience significant residual stress, distortion and cracking, negatively impacting the manufacturing process.

ORNL's fully on-chip CMOS-fabricated integrated photonic circuit can generate polarization or frequency entangled photons for use in quantum communications and networking.

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.

Photonic hyperentanglement involves pairs of photons entangled in multiple degrees of freedom (DoF), which hold promise for quantum communication protocols. However, the frequency DoF has received less attention due to constraints in evaluating such hyperentangled states.

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.

Ceramic matrix composites are used in several industries, such as aerospace, for lightweight, high quality and high strength materials. But producing them is time consuming and often low quality.

This disclosure presents a framework to identify critical conditions that an autonomous driving system will encounter on its mission.