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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Olga S Ovchinnikova
- Sergei V Kalinin
- Stephen Jesse
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- An-Ping Li
- Andrew Lupini
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- Gs Jung
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- Md Inzamam Ul Haque
- Neus Domingo Marimon
- Ondrej Dyck
- Radu Custelcean
- Saban Hus
- Steven Randolph
- Yongtao Liu

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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

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.

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.

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