New 3D chips could make electronics faster and more energy-efficient
The low-cost, scalable technology can seamlessly integrate high-speed gallium nitride transistors onto a standard silicon chip.
The low-cost, scalable technology can seamlessly integrate high-speed gallium nitride transistors onto a standard silicon chip.
Researchers designed a tiny receiver chip that is more resilient to interference, which could enable smaller 5G “internet of things” devices with longer battery lives.
Longtime MIT electrical engineer receives SPIE Frits Zernike Award for Microlithography in recognition of outstanding accomplishments in microlithographic technology.
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
Faculty members and researchers honored in recognition of their scholarship, service, and overall excellence.
Nona Technologies exemplifies how J-WAFS has helped launch real-world solutions for global water and food challenges.
The results will help scientists visualize never-before-seen quantum phenomena in real space.
Researchers achieved a type of coupling between artificial atoms and photons that could enable readout and processing of quantum information in a few nanoseconds.
MIT engineers developed ultrathin electronic films that sense heat and other signals, and could reduce the bulk of conventional goggles and scopes.
MIT engineers developed an insect-sized jumping robot that can traverse challenging terrains and carry heavy payloads.
MIT researchers developed a photon-shuttling “interconnect” that can facilitate remote entanglement, a key step toward a practical quantum computer.
Agreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.
Rhombohedral graphene reveals new exotic interacting electron states.
MIT researchers developed a fiber computer and networked several of them into a garment that learns to identify physical activities.
Researchers developed a scalable, low-cost device that can generate high-power terahertz waves on a chip, without bulky silicon lenses.