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Google's AirDrop-like feature might finally come to the Pixel 9 - Professional coverage
InnovationSoftwareTechnology

Google’s AirDrop-like feature might finally come to the Pixel 9

According to GSM Arena, the latest Android Canary build for the Google Pixel 9 series now includes the system files…

Canonical's AI-Generated Code Was "Plain Wrong" - Professional coverage
ComputingInnovationSoftware

Canonical’s AI-Generated Code Was “Plain Wrong”

According to Phoronix, Canonical has been experimenting with AI to modernize its legacy Ubuntu Error Tracker, a system for reporting…

Nike Sells Off Its NFT Bet RTFKT, Trump Pushes $200B Mortgage Buy - Professional coverage
BusinessInnovationStartups

Nike Sells Off Its NFT Bet RTFKT, Trump Pushes $200B Mortgage Buy

According to Bloomberg Business, Nike Inc. has sold its digital products subsidiary RTFKT, pronounced "artifact," roughly one year after shuttering…

ResearchScience

Computational Breakthrough Predicts Viable Zeolite Structures with Near-Perfect Accuracy

A new computational workflow has successfully distinguished viable zeolite intergrowths from hypothetical ones with unprecedented accuracy. The method, validated by experimental synthesis, could accelerate the discovery of novel materials for industrial applications. This approach marks a significant advancement in materials science by combining high-throughput screening with physicochemical energy descriptors.

Revolutionary Computational Method for Zeolite Discovery

Scientists have developed a groundbreaking computational approach that reportedly distinguishes feasible from unfeasible zeolite intergrowths with near-perfect accuracy, according to research published in Nature Materials. The study demonstrates how high-throughput screening combined with energy descriptors can predict which zeolite pairs can form intergrown structures, potentially accelerating the discovery of new materials for catalysis and separation processes.