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A new potential energy surface (PES) and dynamical study are presented of thereactive process between H2CO + OH towards the formation of HCO + H2O and HCOOH+ H. In this work a source of spurious long range interactions in symmetryadapted neural network (NN) schemes is identified, what prevents their directapplication for low temperature dynamical studies. For this reason, a partitionof the PES into a diabatic matrix plus a NN many body term has been used fittedwith a novel artificial neural networks scheme that prevents spuriousasymptotic interactions. Quasi-classical trajectory and ring polymer moleculardynamics (RPMD) studies have been carried on this PES to evaluate the rateconstant temperature dependence for the different reactive processes, showing agood agreement with the available experimental data. Of special interest is theanalysis of the previously identified trapping mechanism in the RPMD study,which can be attributed to spurious resonances associated to excitations of thenormal modes of the ring polymer.

Neural Network Potential Energy Surface for the low temperature Ring Polymer Molecular Dynamics of the H2CO + OH reaction