AI models are dreaming up the materials of the future
“Scientists looking to remove carbon dioxide (CO2) from the air cleanly and cheaply have long been interested in metal-organic frameworks, or MOFs: gigantic, sponge-like molecules that can be precisely engineered to capture the gas and then release it on command.
Made of metal ions held together by compounds containing carbon, MOFs come in a dizzying array of structures, each with its own distinct properties. A MOF capable of absorbing CO2 at a humid sea-level location, for example, will have a different structure from one that can operate in a dry, high-altitude climate. Sorting through the billions of possibilities to find the right MOF for the job is an almost impossible task for a human chemist. It is, however, a perfect task for an artificial-intelligence (AI) model.”
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A team of researchers in China has developed a 32-bit RISC-V processor using molybdenum disulfide (MoS2), a 2D semiconductor only one molecule thick. The processor, called RV32-WUJI, is limited in speed and efficiency, with a clock speed in the kilohertz range, but it can execute the full RISC-V 32-bit instruction set using nearly 6,000 transistors. MoS2 was chosen for its potential to be compatible with silicon manufacturing processes, though challenges included adjusting transistor performance without traditional doping techniques. (via ArsTechnica)
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