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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Sergei V Kalinin
- Stephen Jesse
- Alex Roschli
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Bogdan Dryzhakov
- Erin Webb
- Evin Carter
- Hoyeon Jeon
- Huixin (anna) Jiang
- Jamieson Brechtl
- Jeremy Malmstead
- Jewook Park
- Kai Li
- Kashif Nawaz
- Kevin M Roccapriore
- Kitty K Mccracken
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Mengdawn Cheng
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Oluwafemi Oyedeji
- Ondrej Dyck
- Paula Cable-Dunlap
- Saban Hus
- Soydan Ozcan
- Steven Randolph
- Tyler Smith
- Xianhui Zhao
- Yongtao Liu

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

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.

We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.

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.

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.