A faster experiment to find and study topological materials
Using machine learning and simple X-ray spectra, researchers can uncover compounds that might enable next-generation computer chips or quantum devices.
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Seeing an elusive magnetic effect through the lens of machine learning
An MIT team incorporates AI to facilitate the detection of an intriguing materials phenomenon that can lead to electronics without energy dissipation.
Fast-tracking the search for energy-efficient materials
Doctoral candidate Nina Andrejević combines spectroscopy and machine learning techniques to identify novel and valuable properties in matter.
A streamlined approach to determining thermal properties of crystalline solids and alloys
MIT research team finds machine learning techniques offer big advantages over standard experimental and theoretical approaches.
A cool advance in thermoelectric conversion
A quantum effect in topological semimetals demonstrated by MIT researchers could allow for the utilization of an untapped energy source.
Newly observed phenomenon could lead to new quantum devices
Exotic states called Kohn anomalies could offer clues to why some materials have the electronic properties they do.