Ken Kingery

Ken Kingery, senior science communications specialist, Duke University


AI & Machine Learning June 13, 2023

Machine learning approach used in crystalline structures for solid-state batteries

Machine learning (ML) approach opens insights into an entire class of materials being pursued for solid-state batteries by Duke University researchers.

By Ken Kingery
Robotics April 27, 2022

How eye imaging technology could help robots and cars see better

Researchers from Duke University are applying lessons learned from decades of perfecting eye-imaging technologies to tomorrow’s autonomous systems sensor technologies.

By Ken Kingery
Courtesy: Duke University
Power Quality January 16, 2022

Next-generation batteries propelled by sodium ion enhancements

Duke University researchers have developed insights into the atomistic dynamics of emerging solid-state batteries to speed their evolution and move beyond lithium.

By Ken Kingery
Energy, Power September 23, 2020

Atomic dynamics help turn heat into electricity

An atomic mechanism that makes some thermoelectric materials efficient near high-temperature phase transition could help unlock better options for technologies reliant on transforming heat into electricity.

By Ken Kingery
Robotics July 14, 2020

Coordinating complex behaviors among hundreds of robots

Duke University researchers have developed an approach to designing motion plans for multiple robots grows "trees" in the search space to solve complex problems in a fraction of the time.

By Ken Kingery
AI & Machine Learning September 29, 2019

Machine learning model finds metamaterial designs for energy harvesting

Duke University electrical engineers are using machine learning to design dielectric metamaterials that absorb and emit specific frequencies of terahertz radiation, which could create new, sustainable types of thermal energy harvesters and lighting.

By Ken Kingery
Simulators, Optimizers May 26, 2019

Guiding vibration simulations for turbines

The Duke-led GUIde Consortium develops faster, more accurate simulations of turbine blade vibrations to help aeronautical engineers develop safer jet turbines with lower maintenance costs.

By Ken Kingery
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