A transferable machine learning potential trained on a new 3,119-configuration unrestricted CCSD(T) dataset outperforms DFT-trained potentials for gas-phase organic reaction barriers and forces.
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Reactive Chemistry at Unrestricted Coupled Cluster Level: High-throughput Calculations for Training Machine Learning Potentials
A transferable machine learning potential trained on a new 3,119-configuration unrestricted CCSD(T) dataset outperforms DFT-trained potentials for gas-phase organic reaction barriers and forces.