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. These findings could help develop remote-controlled actuators for medical devices and robotics, supporting applications such as minimally invasive surgery and precision drug delivery.
Read more: Machine learning unlocks superior performance in light-driven organic crystals
The human brain can learn through experience to filter out disturbing and distracting stimuli -- such as a glaring roadside billboard or a flashing banner on the internet. Scientists have used electroencephalography (EEG) to show that early visual processing in humans changes with repeated exposure.
Read more: The brain learns to filter out distracting stimuli over time