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A team of researchers has developed a new method using machine learning to accurately simulate the heat conduction properties of metal-organic frameworks (MOFs), which have unique structures and potential applications in hydrogen storage, gas storage, and CO2 and water sequestration. This method greatly accelerates the development and application of novel MOFs, which were previously difficult to simulate with traditional methods.