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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Anees Alnajjar
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Kyle Kelley
- Nageswara Rao
- Anton Ievlev
- Arpan Biswas
- Brian Sanders
- Craig A Bridges
- Gerald Tuskan
- Gerd Duscher
- Ilenne Del Valle Kessra
- Isaiah Dishner
- Jeff Foster
- Jerry Parks
- John F Cahill
- Josh Michener
- Liam Collins
- Liangyu Qian
- Mahshid Ahmadi-Kalinina
- Mariam Kiran
- Marti Checa Nualart
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Paul Abraham
- Sai Mani Prudhvi Valleti
- Sheng Dai
- Stephen Jesse
- Sumner Harris
- Utkarsh Pratiush
- Vilmos Kertesz
- Xiaohan Yang
- Yang Liu

The eDICEML digital twin is proposed which emulates networks and hosts of an instrument-computing ecosystem. It runs natively on an ecosystem’s host or as a portable virtual machine.

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

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

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.

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.

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

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.