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Researcher
- Diana E Hun
- Philip Boudreaux
- Som Shrestha
- Singanallur Venkatakrishnan
- Tomonori Saito
- Amir K Ziabari
- Bryan Maldonado Puente
- Mahabir Bhandari
- Nolan Hayes
- Philip Bingham
- Ryan Dehoff
- Sergiy Kalnaus
- Venugopal K Varma
- Vincent Paquit
- Zoriana Demchuk
- Achutha Tamraparni
- Adam Aaron
- Beth L Armstrong
- Catalin Gainaru
- Charles D Ottinger
- Georgios Polyzos
- Gina Accawi
- Gurneesh Jatana
- Jaswinder Sharma
- Karen Cortes Guzman
- Kuma Sumathipala
- Mark M Root
- Mengjia Tang
- Michael Kirka
- Nancy Dudney
- Natasha Ghezawi
- Obaid Rahman
- Peter Wang
- Shiwanka Vidarshi Wanasinghe Wanasinghe Mudiyanselage
- Stephen M Killough
- Zhenglai Shen

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

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

We developed and incorporated two innovative mPET/Cu and mPET/Al foils as current collectors in LIBs to enhance cell energy density under XFC conditions.

The incorporation of low embodied carbon building materials in the enclosure is increasing the fuel load for fire, increasing the demand for fire/flame retardants.

The traditional window installation process involves many steps. These are becoming even more complex with newer construction requirements such as installation of windows over exterior continuous insulation walls.

The co-processing of cathode and composite electrolyte for solid state polymer batteries has been developed. A traditional uncalendared cathode of e.g.

Concrete floor slab flatness and levelness are parameters often specified in construction documents that contractors must meet to ensure a high quality of construction. However, the measurement of these parameters is cumbersome and time-consuming.