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    Machine learning unlocks superior performance in light-driven organic crystals

    1 week ago

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    Researchers have developed a machine-learning workflow to optimize the output force of photo-actuated organic crystals. Using LASSO regression to identify key molecular substructures and Bayesian optimization for efficient sampling, they achieved a maximum blocking force of 37.0 mN—73 times more efficient than conventional methods.
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