Since DNA and solvent molecules are unambiguously identifiable, we were interested to determine if the added element types would increase the specificity of learning the chemical environments around atoms and improve the accuracy of the model. As detailed in Computational Methods, element types are encoded as input features in the neural network graphs. In the "distinct waters" model, the number of element types is increased from seven to nine (H, C, N, O, P, Mg, and Cl for the general model, plus HW and OW as distinct water molecule element types).