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Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute ...
Metal-organic frameworks (MOFs) are characterized by high porosity and structural versatility. They have enormous potential, ...
12h
Tech Xplore on MSNSustainable cooling film could slash building energy use by 20% amid rising global temperaturesAn international team of scientists has developed a biodegradable material that could slash global energy consumption without ...
Learn how important materials are for nuclear energy innovation. Discover how digital modeling is driving nuclear materials ...
University of Chicago electrochemist Chibueze Amanchukwu is working to create a more sustainable future. His lab uses AI and ...
Wafer-scale accelerators for AI applications can deliver far more computing power with much greater energy efficiency.
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Tech Xplore on MSNNew framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysisBingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...
To predict the energy yield of residential solar PV fleets based on limited information, Dutch researchers developed a probability-based mathematical model that provides rapid sky view factor (SVF) ...
High-entropy materials (HEMs) offer exceptional strength and stability, revolutionizing energy applications in batteries, fuel cells, and hydrogen storage.
South Australia’s electricity operator has accused mainland states of “unduly influencing” a roadmap plotting a shift to green energy, warning its plan to build a $3bn transmission project ...
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