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
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Srikanth Yoginath
- Yong Chae Lim
- Zhili Feng
- Chad Steed
- James J Nutaro
- Jian Chen
- Junghoon Chae
- Kyle Kelley
- Pratishtha Shukla
- Rangasayee Kannan
- Sudip Seal
- Travis Humble
- Wei Zhang
- Adam Stevens
- Ali Passian
- Annetta Burger
- Anton Ievlev
- Arpan Biswas
- Brian Post
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Dali Wang
- Debraj De
- Gautam Malviya Thakur
- Gerd Duscher
- Harper Jordan
- James Gaboardi
- Jesse McGaha
- Jiheon Jun
- Joel Asiamah
- Joel Dawson
- Kevin Sparks
- Liam Collins
- Liz McBride
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Nance Ericson
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Pablo Moriano Salazar
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sai Mani Prudhvi Valleti
- Samudra Dasgupta
- Sarah Graham
- Stephen Jesse
- Sudarsanam Babu
- Sumner Harris
- Todd Thomas
- Tomas Grejtak
- Utkarsh Pratiush
- Varisara Tansakul
- William Peter
- Xiuling Nie
- Yiyu Wang
- Yukinori Yamamoto

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

Dual-GP addresses limitations in traditional GPBO-driven autonomous experimentation by incorporating an additional surrogate observer and allowing human oversight, this technique improves optimization efficiency via data quality assessment and adaptability to unanticipated exp

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

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

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

Scanning transmission electron microscopes are useful for a variety of applications. Atomic defects in materials are critical for areas such as quantum photonics, magnetic storage, and catalysis.

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.