Author: Patricia DeLacey
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Conquering Disorder: Modeling a solid with liquid-like ion movement
A new method reveals copper selenide’s elusive electrical properties and vibrational patterns, moving towards thermoelectric generators, solid-state batteries or silent fridges.
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Simulated humanoid robots learn to hike rugged terrain autonomously
Now able to learn locomotion and navigation together, robots develop balanced gaits and safe routes.
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Winning the “Nobel Prize” of computing
The world-changing AI research of Andrew Barto (PhD CSE ’75).
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Nano-switch achieves first directed, gated flow of excitons
Moving excitons with light and a nano-ridge could help bridge optics and electronics, enabling new devices and faster, more efficient communication.
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Woven metamaterials inspired by baskets for stiff, resilient robots
Able to undergo repeated compressions without losing their shape, woven materials could form robots, exoskeletons, car parts, architectural components and more.
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First 3D look at ductility-boosting ‘twinning’ behavior in lightweight magnesium alloy
Piecing together the lightweight alloy’s complex mechanical properties moves towards use in cars to extend fuel economy.
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AI system discovers visual categories while adapting to new contexts
Open ad-hoc categorization approach combines language guidance with visual clustering to learn contextualized features for flexible image interpretation.
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A dual ion beam tests new steel under fusion energy-producing conditions
Researchers establish long-term helium trapping and swelling by titanium-carbide nanoparticles in a novel RAFM steel.
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Microrobots for targeted drug delivery
Fabricated with a gel side for carrying drugs and a magnetic side for steering, these microrobots can navigate complex biological environments like intestines.
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At-home melanoma testing: Skin patch test works in mice
A microneedle patch captures cancer biomarkers in the top-most layer of skin to detect melanoma in animal tissue samples.
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Improving AI models: Automated tool detects silent errors in deep learning training
TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, saving time and resources.
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Satellites reveal tropical wetland flooding did not cause methane surge
Human activity or other wetland factors like temperature or soil chemistry could be at play.