LangToMo uses a diffusion model to generate text-conditioned pixel motion from a single frame and a lightweight mapping to convert that motion into robot actions, beating several prior flow- and video-based methods on manipulation benchmarks.
Superconducting nitridized-aluminum thin films
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abstract
We report the direct observation of superconductivity in nitridized-aluminum thin films. The films are produced by sputtering deposition of aluminum in a controlled mixture of nitrogen diluted in argon. The concentration of applied nitrogen directly determines the properties of the superconducting thin films. We observe samples displaying critical temperatures up to 3.38$\pm$0.01K and resilience to in-plane magnetic fields well above 1T, with good reproducibility of the results. This work represents an unambiguous demonstration of tunable superconductivity in aluminum-based nitridized thin films. Our results put forward nitridized aluminum as a promising material to be employed in superconducting quantum circuits for quantum technology applications.
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Pixel Motion as Universal Representation for Robot Control
LangToMo uses a diffusion model to generate text-conditioned pixel motion from a single frame and a lightweight mapping to convert that motion into robot actions, beating several prior flow- and video-based methods on manipulation benchmarks.