MIT undergraduate researchers Helena Merker, Harry Heiberger, and Linh Nguyen, and PhD student Tongtong Liu, exploit machine-learning techniques to determine the magnetic structure of materials.

Inaugural award goes to MIT condensed matter theory professors of physics.

Using machine learning and simple X-ray spectra, researchers can uncover compounds that might enable next-generation computer chips or quantum devices.

The findings could inform the design of practical superconducting devices.

MIT engineers expand the capabilities of these ultrasensitive nanoscale detectors, with potential uses for quantum computing and biological sensing.

An MIT team incorporates AI to facilitate the detection of an intriguing materials phenomenon that can lead to electronics without energy dissipation.

Researchers have developed a technique for making quantum computing more resilient to noise, which boosts performance.

National Science Foundation award will allow the VELION FIB-SEM to become a permanent instrument in MIT.nano’s characterization facility.

Using ultrathin materials to reduce the size of superconducting qubits may pave the way for personal-sized quantum devices.

The new qubits stay in “superposition” for up to 10 seconds, and could make a promising foundation for quantum computers.