Prediction of new Ti-N phases using machine learned interatomic potential

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Offline navigation is a lifeline for travelers, adventurers, and everyday commuters. We demand speed, accuracy, and the flexibility to tailor routes to our specific needs. For years, OsmAnd has championed powerful, feature-rich offline maps that fit in your pocket. But as maps grew more detailed and user demands for complex routing increased, our trusty A* algorithm, despite its flexibility, started hitting a performance wall. How could we deliver a 100x speed boost without bloating map sizes or sacrificing the deep customization our users love?

Source: Computational Materials Science, Volume 267

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«Они как слон в посудной лавке»Политолог Дмитрий Суслов — о Совете мира, стратегии Дональда Трампа и будущем конфликта на Украине28 января 2026

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Baroness Kidron told Nick Robinson a ban social media for under 16-year-olds was "not a silver bullet".