Check out the latest media coverage of Duke mechanical engineering and materials science research and education.
Duke MEMS in the News
Technology Networks Cancer News |
Brain Tumor Breakthrough Opens Avenue for New Drug Treatments
David Needham
New Books Network |
Time and Beauty: Why Time Flies and Beauty Never Dies
MEMS Professor Adrian Bejan joins a podcast to talk about his recent book, "Time and Beauty: Why Time Flies and Beauty Never Dies."
The Science Advisory Board |
Sound Waves Sort Extracellular Vesicles to Enable Liquid Biopsies, Regenerative Therapies
Tony Jun Huang uses sound waves to separate small extracellular vesicles (sEVs) from biofluids, laying the groundwork for the development of next-generation liquid biopsies and regenerative therapies.
The Atlantic |
The Transcendent Brain
Adrian Bejan offers an evolutionary explanation, based on the eye and the brain, as to why we find the golden ratio so appealing.
Popular Mechanics |
Want to Build the Perfect Bonfire? All You Need Is a Little Bit of Math
MEMS Professor Adrian Bejan has some advice on how to mathematically build the perfect bonfire.
US Department of Energy |
Uncovering the Atomic Mechanism Underpinning Heat Transport in Thermoelectric Materials
MEMS Professor Olivier Delaire is using neutrons to reveal remarkable atomic behavior in thermoelectric materials for more efficient conversion of heat into electricity.
Engineering and Technology |
Lab-Made Gel That Outperforms Cartilage Paves Way for Next-Gen Knee Operations
MEMS Professor Ken Gall works with campus collaborators on a gel-based cartilage substitute to relieve achy knees that’s even stronger and more durable than the real thing.
Popular Science |
A Self-Aware Robot Taught Itself How to Use Its Body
MEMS Professor Boyuan Chen lead a project that created a robot that could learn, through practice, what its own form can do
New Scientist |
Why Does Time Fly or Drag? How Emotions Warp Our Temporal Perceptions
MEMS Professor Adrian Bejan says the brain’s processing speed slows as we age – caused by the greater complexity of our neural networks that means signals travel greater distances.