AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Large language models are increasingly used as reasoning components in AI-driven materials Co-Scientists, yet the reliability of the resulting verification pipeline remains unclear. Metal-organic frameworks (MOFs) provide a particularly challenging setting because structures may appear under different identifiers, synt...
Long-duration energy storage (LDES) can mitigate prolonged renewable--load imbalances during Dunkelflaute events, but existing studies rely on zonal or linearized DC network models and inadequately analyze the operational feasibility of the grid across a wide range of full-year renewable, load, and contingency scenario...
CatRetriever provides a scalable route for connecting catalyst generative models with physically plausible and adsorption energy compatible bulk catalyst discovery, and is extended into an adsorption energy targeted bulk discovery pipeline that combines bulk retrieval, generative search space expansion, and adsorption...
CatDiT is presented, a unified framework for inverse catalyst design that generates valid and novel structures ranging from intermetallic alloys to oxide surfaces and establishes CatDiT as a practical and scalable approach for property-directed catalyst inverse design and targeted catalyst generation.
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