The role of the pre-exponential factor on temperature programmed desorption spectra: A computational study of frozen species on interstellar icy grain mantles

TL;DR

This study investigates how different models of the pre-exponential factor influence temperature programmed desorption spectra for astrochemical ices, proposing computationally efficient methods for accurate parameter estimation.

Contribution

It compares existing pre-exponential factor models and introduces cost-effective strategies for including vibrational effects in astrochemical TPD simulations.

Findings

Tait and Campbell models yield TPD peaks within 30 K of each other.

Proposed methods avoid complex quantum calculations.

Inclusion of vibrational partition functions improves model accuracy.

Abstract

Temperature programmed desorption (TPD) is a well-known technique to study gas-surface processes, and it is characterized by two main quantities: the adsorbate binding energy and the pre-exponential factor. While the former has been well addressed in recent years by both experimental and computational methods, the latter remains somewhat ill-defined, and different schemes have been proposed in the literature for its evaluation. In the astrochemistry context, binding energies and pre-exponential factors are key parameters that enter microkinetic models for studying the evolution over time of the chemical species in the universe. In this paper, we studied, by computer simulations, the effect of different pre-exponential factor models using water, ammonia, and methanol adsorbed on amorphous and crystalline ices as test cases: specifically, the one most widely used by the astrochemical community (Herbst-Hasegawa), the models provided by Tait and Campbell, and an extension of the Tait formulation including the calculation of the vibrational partition function. We suggest the methods proposed by Tait and Campbell that provide TPD temperature peaks within 30 K of each other while avoiding demanding quantum mechanical calculations, as they are based on tabulated data. Finally, when the explicit inclusion of the vibrational partition function is needed, we propose a cost-effective strategy to include all the thermal contributions in the partition functions without the need for performing a full vibrational calculation of the whole system.