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
- Yong Chae Lim
- Zhili Feng
- Jian Chen
- Kyle Kelley
- Rangasayee Kannan
- Wei Zhang
- Adam Stevens
- Anton Ievlev
- Arpan Biswas
- Brian Post
- Brian Sanders
- Bryan Lim
- Dali Wang
- Gerald Tuskan
- Gerd Duscher
- Ilenne Del Valle Kessra
- Isaiah Dishner
- Jeff Foster
- Jerry Parks
- Jiheon Jun
- John F Cahill
- Josh Michener
- Liam Collins
- Liangyu Qian
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Paul Abraham
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sai Mani Prudhvi Valleti
- Sarah Graham
- Stephen Jesse
- Sudarsanam Babu
- Sumner Harris
- Tomas Grejtak
- Utkarsh Pratiush
- Vilmos Kertesz
- William Peter
- Xiaohan Yang
- Yang Liu
- Yiyu Wang
- Yukinori Yamamoto

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

Enzymes for synthesis of sequenced oligoamide triads and tetrads that can be polymerized into sequenced copolyamides.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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.

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.

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

A human-in-the-loop machine learning (hML) technology potentially enhances experimental workflows by integrating human expertise with AI automation.

The scanning transmission electron microscope (STEM) provides unprecedented spatial resolution and is critical for many applications, primarily for imaging matter at the atomic and nanoscales and obtaining spectroscopic information at similar length scales.