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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Lawrence {Larry} M Anovitz
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Kashif Nawaz
- Stephen Jesse
- An-Ping Li
- Andrew G Stack
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Bogdan Dryzhakov
- Brian Fricke
- Christopher Rouleau
- Costas Tsouris
- Debangshu Mukherjee
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- Jamieson Brechtl
- Jewook Park
- Jong K Keum
- Juliane Weber
- Kai Li
- Kyle Gluesenkamp
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Peng Yang
- Radu Custelcean
- Saban Hus
- Sai Krishna Reddy Adapa
- Sai Mani Prudhvi Valleti
- Steven Randolph
- Sumner Harris
- Utkarsh Pratiush
- Zhiming Gao

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.

An efficient, eco-friendly metal extraction using ultrasonic leaching, ideal for lithium and magnesium recovery from minerals and waste.

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.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.