Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate
(29)
- Computing and Computational Sciences Directorate (39)
- Energy Science and Technology Directorate
(229)
- Fusion and Fission Energy and Science Directorate (24)
- Information Technology Services Directorate (3)
- Isotope Science and Enrichment Directorate (7)
- National Security Sciences Directorate (20)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(138)
- User Facilities (28)
Researcher
- Beth L Armstrong
- Jun Qu
- Venkatakrishnan Singanallur Vaidyanathan
- Alex Plotkowski
- Amir K Ziabari
- Amit Shyam
- Corson Cramer
- Diana E Hun
- James A Haynes
- Meghan Lamm
- Michael Kirka
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Soydan Ozcan
- Stephen M Killough
- Steve Bullock
- Sumit Bahl
- Tomas Grejtak
- Vincent Paquit
- Xianhui Zhao
- Alex Roschli
- Alice Perrin
- Ben Lamm
- Bryan Lim
- Bryan Maldonado Puente
- Christopher Ledford
- Corey Cooke
- David J Mitchell
- Erin Webb
- Ethan Self
- Evin Carter
- Gabriel Veith
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
- Halil Tekinalp
- James Klett
- Jeremy Malmstead
- John Holliman II
- Jordan Wright
- Jovid Rakhmonov
- Khryslyn G Araño
- Kitty K Mccracken
- Mark M Root
- Marm Dixit
- Matthew S Chambers
- Nancy Dudney
- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Oluwafemi Oyedeji
- Peeyush Nandwana
- Peter Wang
- Rangasayee Kannan
- Ryan Kerekes
- Sally Ghanem
- Sanjita Wasti
- Sergiy Kalnaus
- Shajjad Chowdhury
- Sunyong Kwon
- Tolga Aytug
- Trevor Aguirre
- Tyler Smith
- Ying Yang
- Yiyu Wang

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

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

Using all polymer formulations, the PIP densification is improved almost 70% over traditional preceramic polymers and PIP material leading to cost and times saving for densifying ceramic composites made from powder or fibers.

New demands in electric vehicles have resulted in design changes for the power electronic components such as the capacitor to incur lower volume, higher operating temperatures, and dielectric properties (high dielectric permittivity and high electrical breakdown strengths).