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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Sergei V Kalinin
- Stephen Jesse
- Vlastimil Kunc
- Adam Siekmann
- Ahmed Hassen
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Bogdan Dryzhakov
- Dan Coughlin
- Hong Wang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Hyeonsup Lim
- Jamieson Brechtl
- Jewook Park
- Jim Tobin
- Josh Crabtree
- Kai Li
- Kashif Nawaz
- Kevin M Roccapriore
- Kim Sitzlar
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Merlin Theodore
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Ondrej Dyck
- Saban Hus
- Steven Guzorek
- Steven Randolph
- Subhabrata Saha
- Vipin Kumar
- Vivek Sujan
- Yongtao Liu

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.

Through the use of splicing methods, joining two different fiber types in the tow stage of the process enables great benefits to the strength of the material change.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

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.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.

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.