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Researcher
- Adam M Guss
- Rama K Vasudevan
- Josh Michener
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Liangyu Qian
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Andrzej Nycz
- Austin L Carroll
- Isaiah Dishner
- Jeff Foster
- John F Cahill
- Kashif Nawaz
- Kuntal De
- Serena Chen
- Stephen Jesse
- Udaya C Kalluri
- Xiaohan Yang
- Alex Walters
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Benjamin Lawrie
- Biruk A Feyissa
- Bogdan Dryzhakov
- Brian Fricke
- Carrie Eckert
- Chengyun Hua
- Chris Masuo
- Christopher Rouleau
- Clay Leach
- Costas Tsouris
- Debangshu Mukherjee
- Debjani Pal
- Gabor Halasz
- Gerald Tuskan
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilenne Del Valle Kessra
- Ilia N Ivanov
- Ivan Vlassiouk
- Jamieson Brechtl
- Jay D Huenemann
- Jewook Park
- Jiaqiang Yan
- Joanna Tannous
- Jong K Keum
- Kai Li
- Kyle Davis
- Kyle Gluesenkamp
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Paul Abraham
- Petro Maksymovych
- Radu Custelcean
- Saban Hus
- Sai Mani Prudhvi Valleti
- Steven Randolph
- Sumner Harris
- Utkarsh Pratiush
- Vilmos Kertesz
- Vincent Paquit
- William Alexander
- Yang Liu
- Zhiming Gao

ORNL has developed bacterial strains that can utilize a common plastic co-monomer as a feedstock. This will help enable modern, petroleum-derived plastics to be converted into value-added chemicals.

Due to a genes unique nucleotide sequences acquired through horizontal gene transfer, the gene has a transcriptional repressor activity and innate enzymatic role.

We have developed bacterial strains that can convert sustainable feedstocks and waste feedstocks into chemical precursors for next generation plastics.

A novel molecular sorbent system for low energy CO2 regeneration is developed by employing CO2-responsive molecules and salt in aqueous media where a precipitating CO2--salt fractal network is formed, resulting in solid-phase formation and sedimentation.

ORNL has identified a panel of novel nylon hydrolases with varied substrate and product selectivity.

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.

In scientific research and industrial applications, selecting the most accurate model to describe a relationship between input parameters and target characteristics of experiments is crucial.

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