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A team of researchers has developed a new method using machine learning to greatly improve simulations of metal-organic frameworks (MOFs), which have unique properties and potential applications in fields such as hydrogen and gas storage. This method greatly accelerates the development and application of novel MOFs, which were previously difficult to simulate accurately due to their complex structure and large size.