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candidates chosen due to its high melting point, good thermal conductivity and low erosion rate. However, transitioning to the long-term timescales and high reliability required for commercial fusion means
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solid materials such as tungsten have been the primary candidates chosen due to its high melting point, good thermal conductivity and low erosion rate. However, transitioning to the long-term timescales
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these processes at very different levels, from individual atoms up to full working devices. These scales are hard to connect to one another. AIM uses artificial intelligence and machine learning to bridge that gap
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-to-recycle plastics, flue gases, and brine) into valuable fuels, chemicals, and materials using solar-powered devices. The core challenge is simulating the chemistry of these processes at very different levels