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Researcher
- Tomonori Saito
- Omer Onar
- Ahmed Hassen
- Brian Post
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- Vlastimil Kunc
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- Som Shrestha
- Syed Islam
- Zhenzhen Yang
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- Bishnu Prasad Thapaliya
- David Nuttall
- Emrullah Aydin
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- Sudarsanam Babu
- Umesh N MARATHE
- William Carter
- Xiang Lyu
- Ying Yang
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- Zhiming Gao
- Adam Stevens
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- Ali Riza Ekti
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- Zhijia Du

Method for visualizing and interacting with ionizing radiation data using augmented reality. This code provides coupling radiation transport data with immersive augmented reality experiences for users in real-world environments.

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

CAN-D codebase takes as input a set of collected CAN data logs from a vehicle, and produces a .dbc with partial or full signal definitions. Once this .dbc file is produced it can be used to translate subsequent messages from that vehicle in real time or post-drive processing.

1) HMS Version 4 (HMS-4) is the current state-of the- art NDA system deployed in the field to support holdup measurements.

Generating energy models from scratch is a costly and time consuming task. A detailed energy model can have thousands of input parameters that are necessary for a complete simulation of a building. A solution to this problem is the AutoBEMGen framework.

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

The invention teaches a method for separating uranium and the transuranic actinides neptunium, plutonium, and americium from nitric acid solutions by co-crystallization upon lowering the temperature from 60 C to 20 C or lower.

Mechanism-Based Trait Inference in Plants Using Multiplex Networks, AI Agents, and Translation Tools
This system enables the modular design and optimization of complex plant traits by organizing genes and regulatory mechanisms into interpretable clades.