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Our another work accepted by Adv Mat. Big Congratulations!
When heat flows in bulk samples and across an interface, thermal conductivity k and interfacial thermal conductance G are two crucial measurables. However, scalar quantities offer limited microscopic knowledge. Interestingly, k and G are microscopically…
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Our work accepted by Advanced Materials. Big congratulations!
The first step to study a topological material is to tell whether or not the material is topological. However, this step is nontrivial, often combining extensive calculations and sophisticated experiments. The work, led by Nina…
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Mingda becomes an MIT Recreation Ambassador. Congratulations!
Mingda has been selected to serve as an Ambassador at MIT Recreation to support the mission of “Enhancing the lives of our community,” and to “inspire others to participate in and discover the benefits of recreational…
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Thanh receives the best poster award at IXS2022. Congratulations!
Thanh has received the Best Poster Award at the 12th International Conference on Inelastic X-ray Scattering (IXS 2022). Congratulations!
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Nathan’s science policy article is published at Harvard SITN. Congratulations!
Competing Visions of Science Funding in Congress
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Mingda becomes the Class 1947 Career Development Professor. Congratulations!
Mingda has been selected to hold the Class of 1947 Career Development Professorship. The selection “comes in recognition of the outstanding contributions in education and research.” Congratulations and keep up good work.
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Nina’s thesis selected to publish at Springer Thesis. Congratulations!
Nina’s PhD Thesis “Machine Learning-Augmented Spectroscopies for Intelligent Materials Design” has been selected to publish as Springer Thesis series, which “recognizes outstanding PhD research” and “brings together a selection of the very best Ph.D. theses…
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Nathan receives the DOE SCGSR Award. Congratulations!
Nathan Drucker has been selected to receive the U.S. Department of Energy (DOE) Office of Science Graduate Student Research (SCGSR) award. Congratulations!
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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.
