Portico: A program for the asymptotic classification of transition-state normal modes
Description
In molecular dissociation and fragmentation, some degrees of freedom that are vibrational at the saddle-point geometry correspond asymptotically to rotations or translations of the product fragments. Their correct classification as vibrational or roto-translational is essential in kinetic and statistical models that treat these degrees of freedom separately, but current assignments often rely on visual inspection or system-specific criteria. Here, we present Portico (Projection Onto Roto-Translational and Internal COordinates), a program for the automated classification of transition-state normal modes according to their asymptotic product character. First, Portico assigns the imaginary-frequency mode to the roto-translational sector by construction because it defines the reaction coordinate leading toward product separation. Second, Portico represents the transition-state normal modes in a mixed representation that combines internal coordinates selected to span the vibrational degrees of freedom of the isolated product fragments with rigid-body translational and rotational displacement vectors of those fragments. The components of each mode in this representation define a scalar weight, Ωi, which quantifies its roto-translational character. Since the total number of transition-state normal modes to be assigned to the roto-translational sector is fixed by the dimensionality of the dissociation channel, Portico completes this sector by ranking the real-frequency modes according to their Ωi values and selecting the required number of modes. The same analysis can also be applied at non-stationary geometries, where the gradient direction is projected out and plays the role of the reaction coordinate. The method applies to channels yielding atomic, linear, and nonlinear fragments and does not require propagation toward the asymptotic product region. Portico thus provides an objective and transferable tool for automated reaction analysis and statistical models of molecular fragmentation.