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Code for graph neural network-based surrogate models used to predict reaction-related properties for reinforcement-learning-accelerated atomistic simulations.
Code used to train mean-first-passage-time/time-estimator models and run deep-reinforcement-learning-accelerated atomistic simulations of vacancy diffusion.
Abstract Light-activated drugs are a promising way to treat localized diseases for which existing treatments have severe side effects. However, their development is complicated by the set of photophysical and biological properties that must be simultaneously optimized. Here we used computational techniques to find a se...
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