Scalable surface that mimics nature developed
Duke University engineers have developed a scalable soft surface that relies on electromagnetic actuation, mechanical modeling and machine learning to form new configurations.
Quantum computing phase changes show tipping point
Researchers at Duke University and the University of Maryland have used the frequency of measurements on a quantum computer to get a glimpse into the quantum computing phenomena of phase changes – something analogous to water turning to steam.
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.
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.
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.
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.
Machine learning shapes microwaves for a computer’s eyes
Researchers have developed a method to identify objects using microwaves that improves accuracy while reducing the associated computing time and power requirements.
Hyperspectral cameras designed to improve agricultural practices
A Duke University researcher is working on developing a small, inexpensive hyperspectral camera to enable worldwide precision agricultural practices thanks to a recently-awarded fellowship.
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.
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.
Smart robotic system developed to sniff out pollution and toxic leaks
Duke University researchers are using the physics of airflows to locate gaseous leaks more quickly in complex scenarios for processing and chemical applications. See video.