Startup’s nuclear-inspired cooling system could make data centers more sustainable
Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI.
Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI.
Student-led expeditions use distributed instruments to observe auroral structures and probe space plasma in real-world conditions.
Fellowship honors contributions of immigrants to American society by awarding $90,000 in funding for graduate studies.
MIT Energy Initiative symposium maps a path to tap the planet’s heat-rich rocks for clean power at scale.
Two faculty and six additional alumni win top APS awards and prizes; four faculty and 12 additional alumni named APS Fellows.
The devices represent a key step toward practical quantum sensing, with applications in biomedical sensing, materials characterization, and more.
Graduate engineering program is No. 1 in the nation; MIT Sloan is No. 6.
Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.
A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.
Sophia Henneberg, assistant professor in the Department of Nuclear Science and Engineering, is developing stellarators to harness fusion energy.
Master's student Taylor Hampson is modeling the behavior of an unconventional rocket engine that will heat propellant using nuclear energy.
The program recognizes outstanding mentorship of graduate students.
In his 10 years at MIT, Loureiro helped illuminate the physics occurring at the center of fusion vacuum chambers and at the edges of the universe.
Nuclear waste continues to be a bottleneck in the widespread use of nuclear energy, so doctoral student Dauren Sarsenbayev is developing models to address the problem.
MIT researchers found a way to predict how efficiently materials can transport protons in clean energy devices and other advanced technologies.