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Achieving a fivefold speedup in solvation free energy calculations while maintaining accuracy could revolutionize computational chemistry practices.
Unlock spectroscopic and electronic observables in large-scale molecular simulations by learning the electron density directly, paving the way for more comprehensive and transferable machine-learned interatomic potentials.