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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
- Stephen Jesse
- An-Ping Li
- Andrew Lupini
- Annetta Burger
- Anton Ievlev
- Arpan Biswas
- Benjamin Lawrie
- Bogdan Dryzhakov
- Brian Fricke
- Carter Christopher
- Chance C Brown
- Chengyun Hua
- Christopher Rouleau
- Costas Tsouris
- Debangshu Mukherjee
- Debraj De
- Gabor Halasz
- Gautam Malviya Thakur
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- James Gaboardi
- Jamieson Brechtl
- Jason Jarnagin
- Jesse McGaha
- Jewook Park
- Jiaqiang Yan
- Jong K Keum
- Kai Li
- Kevin Spakes
- Kevin Sparks
- Kyle Gluesenkamp
- Liam Collins
- Lilian V Swann
- Liz McBride
- Mahshid Ahmadi-Kalinina
- Mark Provo II
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Petro Maksymovych
- Radu Custelcean
- Rob Root
- Saban Hus
- Sai Mani Prudhvi Valleti
- Sam Hollifield
- Steven Randolph
- Sumner Harris
- Todd Thomas
- Utkarsh Pratiush
- Xiuling Nie
- Zhiming Gao

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.

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

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.