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Researcher
- Gurneesh Jatana
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
- James Szybist
- Jonathan Willocks
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Stephen M Killough
- Todd Toops
- Vincent Paquit
- Yeonshil Park
- Alexander I Wiechert
- Alexey Serov
- Benjamin Manard
- Bryan Maldonado Puente
- Charles F Weber
- Corey Cooke
- Costas Tsouris
- Debangshu Mukherjee
- Derek Splitter
- Dhruba Deka
- Gina Accawi
- Haiying Chen
- Joanna Mcfarlane
- Josh Michener
- Liangyu Qian
- Mark M Root
- Matt Vick
- Md Inzamam Ul Haque
- Melanie Moses-DeBusk Debusk
- Michael Kirka
- Nolan Hayes
- Obaid Rahman
- Olga S Ovchinnikova
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Serena Chen
- Sreshtha Sinha Majumdar
- Vandana Rallabandi
- William P Partridge Jr
- Xiang Lyu

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

We tested 48 diverse homologs of SfaB and identified several enzyme variants that were more active than SfaB at synthesizing the nylon-6,6 monomer.

High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.

Method to operate a compression ignition engine in dual fuel operation with premixed turbulent flame propagation from low to high loads.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

The invention discloses methods of using a reducing agent for catalytic oxygen reduction from CO2 streams, enabling the treated CO2 streams to meet the pipeline specifications.

An electrochemical cell has been specifically designed to maximize CO2 release from the seawater while also not changing the pH of the seawater before returning to the sea.

Lean-burn natural gas (NG) engines are a preferred choice for the hard-to-electrify sectors for higher efficiency and lower NOx emissions, but methane slip can be a challenge.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.