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With inspiration from “Tetris,” MIT researchers develop a better radiation detector
The device, based on simple tetromino shapes, could determine the direction and distance of a radiation source, with fewer detector pixels.
Researchers harness 2D magnetic materials for energy-efficient computing
NSE’s Thanh Nguyen and Mingda Li with an MIT team precisely controlled an ultrathin magnet at room temperature, which could enable faster, more efficient processors and computer memories.
MIT engineers develop a way to determine how the surfaces of materials behave
Prof Bilge Yildiz and colleagues devised a machine-learning-based method to investigate how materials behave at their surfaces. The approach could help in developing compounds or alloys for use as catalysts, semiconductors, or battery components.
Making more magnetism possible with topology
Researchers have been working for years to understand the electron topology and magnetism in certain semimetals have been frustrated by the fact that the materials only display magnetic properties if they are cooled to just a few degrees above absolute zero. A...
Ericmoore Jossou joins NSE and EECS in summer 2023
Jossou is one of eleven new faculty members join six of the School of Engineering's academic departments and institutes.
The task of magnetic classification suddenly looks easier
Knowing the magnetic structure of crystalline materials is critical to many applications, including data storage, high-resolution imaging, spintronics, superconductivity, and quantum computing. Information of this sort, however, is difficult to come by. Although magnetic structures can be obtained from neutron diffraction and...
Simulating neutron behavior in nuclear reactors
Amelia Trainer applied to MIT because she lost a bet. As part of what the fourth year NSE doctoral student labels her “teenage rebellious phase,” Trainer was quite convinced she would just be wasting the application fee were she to submit an...
New hardware offers faster computation for artificial intelligence, with much less energy
Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.
Quantum sensor can detect electromagnetic signals of any frequency
MIT engineers expand the capabilities of these ultrasensitive nanoscale detectors, with potential uses for quantum computing and biological sensing.
How can we reduce the carbon footprint of global computing?
Workshop hosted by MIT’s Climate and Sustainability Consortium, MIT-IBM Watson AI Lab, and the MIT Schwarzman College of Computing highlights how new approaches to computing can save energy and help the planet.