Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate
(217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (128)
- User Facilities
(27)
Researcher
- Kyle Kelley
- Rama K Vasudevan
- Anees Alnajjar
- Sergei V Kalinin
- Stephen Jesse
- Adam Siekmann
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Bogdan Dryzhakov
- Craig A Bridges
- Hong Wang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Hyeonsup Lim
- Jamieson Brechtl
- Jewook Park
- Kai Li
- Kashif Nawaz
- Kevin M Roccapriore
- Liam Collins
- Mariam Kiran
- Marti Checa Nualart
- Maxim A Ziatdinov
- Nageswara Rao
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Ondrej Dyck
- Saban Hus
- Sheng Dai
- Steven Randolph
- Vivek Sujan
- Yongtao Liu

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

Electrochemistry synthesis and characterization testing typically occurs manually at a research facility.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.

This technology provides a device, platform and method of fabrication of new atomically tailored materials. This “synthescope” is a scanning transmission electron microscope (STEM) transformed into an atomic-scale material manipulation platform.

This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.