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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Kashif Nawaz
- Mingyan Li
- Sam Hollifield
- Stephen Jesse
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Bogdan Dryzhakov
- Brian Fricke
- Brian Weber
- Christopher Rouleau
- Costas Tsouris
- Debangshu Mukherjee
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Isaac Sikkema
- Ivan Vlassiouk
- Jamieson Brechtl
- Jewook Park
- Jong K Keum
- Joseph Olatt
- Kai Li
- Kevin Spakes
- Kunal Mondal
- Kyle Gluesenkamp
- Liam Collins
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Mary A Adkisson
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Oscar Martinez
- Radu Custelcean
- Saban Hus
- Sai Mani Prudhvi Valleti
- Steven Randolph
- Sumner Harris
- T Oesch
- Utkarsh Pratiush
- Zhiming Gao

Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.

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.

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.

This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.