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Researcher
- Omer Onar
- Subho Mukherjee
- Mostak Mohammad
- Vandana Rallabandi
- Vivek Sujan
- Erdem Asa
- Shajjad Chowdhury
- Burak Ozpineci
- Emrullah Aydin
- Jon Wilkins
- Adam Siekmann
- Blane Fillingim
- Brian Post
- Gui-Jia Su
- Isabelle Snyder
- Lauren Heinrich
- Peeyush Nandwana
- Sudarsanam Babu
- Thomas Feldhausen
- Veda Prakash Galigekere
- Yousub Lee
- Alexander I Wiechert
- Ali Riza Ekti
- Costas Tsouris
- Debangshu Mukherjee
- Gs Jung
- Gyoung Gug Jang
- Lingxiao Xue
- Md Inzamam Ul Haque
- Nishanth Gadiyar
- Olga S Ovchinnikova
- Radu Custelcean
- Rafal Wojda
- Ramanan Sankaran
- Vimal Ramanuj
- Wenjun Ge

This disclosure introduces an innovative tool that capitalizes on historical data concerning the carbon intensity of the grid, distinct to each electric zone.

This disclosure introduces an innovative tool that capitalizes on historical data concerning the carbon intensity of the grid, distinct to each electric zone.

Technologies directed to an integrated on-board charger for dual motor based electric vehicle power train are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

This invention proposes a Honeycomb-DD coupling structure that addresses the shortcomings of the conventional honeycomb coil array and gathering the advantage of DD and honeycomb designs advantages in a single design.

Wireless charging systems need to operate at high frequency, at or near resonance, to maximize power transfer distance and efficiency. High voltages appear across the inductors and capacitors. The use of discrete components reduces efficiency, increases system complexity.

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

ORNL has developed a revolutionary system for wirelessly transferring power to electric vehicles and energy storage systems, enabling efficient, contactless charging.