Thermal Processing and Interactions of Ethyl Formate in Model Astrophysical Ices Containing Water and Ethanol

Salter, Tara L.; Wootton, L. H.; Brown, Wendy A.

doi:10.1021/acsearthspacechem.9b00091

Cited by 5 publications

(4 citation statements)

References 57 publications

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“…This approach works to evaluate the pre-exponential factor of atoms or small molecules such as Ar or N 2 . However, several experimental works have pointed out that bigger molecules may exhibit prefactor values several orders of magnitude higher than what is predicted by the previous formula, sometimes reaching 10 20 s –1 . ,,, This discrepancy originates from the fact that the previous formula neglects the rotational partition function of the desorbing molecules. Indeed, the pre-exponential factor reflects the entropic effect associated with the desorption kinetics; that is, in the transition state theory (TST), it can be written as where q ads and q ⧧ are single-particle partition functions for the adsorbed (initial) state and the transition state, respectively, calculated at the temperature T .…”

Section: Limitations and Frontiersmentioning

confidence: 80%

“…However, several experimental works have pointed out that bigger molecules may exhibit prefactor values several orders of magnitude higher than what is predicted by the previous formula, sometimes reaching 10 20 s −1 . 91,101,270,271 This discrepancy originates from the fact that the previous formula neglects the rotational partition function of the desorbing molecules. Indeed, the pre-exponential factor reflects the entropic effect associated with the desorption kinetics; that is, in the transition state theory (TST), it can be written as…”

Section: Limitations and Frontiersmentioning

confidence: 99%

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Thermal Desorption of Interstellar Ices: A Review on the Controlling Parameters and Their Implications from Snowlines to Chemical Complexity

Minissale

Aikawa

Bergin

et al. 2022

ACS Earth Space Chem.

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The evolution of star-forming regions and their thermal balance are strongly influenced by their chemical composition, which, in turn, is determined by the physicochemical processes that govern the transition between the gas phase and the solid state, specifically icy dust grains (e.g., particle adsorption and desorption). Gas–grain and grain–gas transitions as well as formation and sublimation of interstellar ices are thus essential elements of understanding astrophysical observations of cold environments (e.g., prestellar cores) where unexpected amounts of a large variety of chemical species have been observed in the gas phase. Adsorbed atoms and molecules also undergo chemical reactions that are not efficient in the gas phase. Therefore, the parametrization of the physical properties of atoms and molecules interacting with dust grain particles is clearly a key aspect to interpret astronomical observations and to build realistic and predictive astrochemical models. In this consensus evaluation, we focus on parameters controlling the thermal desorption of ices and how these determine pathways toward molecular complexity and define the location of snowlines, which ultimately influence the planet formation process. We review different crucial aspects of desorption parameters both from a theoretical and experimental points of view. We critically assess the desorption parameters (the binding energies, E b, and the pre-exponential factor, ν) commonly used in the astrochemical community for astrophysically relevant species and provide tables with recommended values. The aim of these tables is to provide a coherent set of critically assessed desorption parameters for common use in future work. In addition, we show that a nontrivial determination of the pre-exponential factor ν using transition state theory can affect the binding energy value. The primary focus is on pure ices, but we also discuss the desorption behavior of mixed, that is, astronomically more realistic, ices. This allows discussion of segregation effects. Finally, we conclude this work by discussing the limitations of theoretical and experimental approaches currently used to determine the desorption properties with suggestions for future improvements.

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Section: Limitations and Frontiersmentioning

confidence: 80%

Section: Limitations and Frontiersmentioning

confidence: 99%

Thermal Desorption of Interstellar Ices: A Review on the Controlling Parameters and Their Implications from Snowlines to Chemical Complexity

Minissale

Aikawa

Bergin

et al. 2022

ACS Earth Space Chem.

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“…While TPD has been successful in determining the BEs for many molecules that are of astrochemical relevance (e.g. Brown & Bolina 2007;Burke et al 2015a;Smith & Kay 2018;Behmard et al 2019;Salter et al 2019), there are limitations to experimental BE investigations with this and other techniques. Experiments are time consuming and the focus is usually on the scientifically most impactful systems.…”

Section: Introductionmentioning

confidence: 99%

Predicting binding energies of astrochemically relevant molecules via machine learning

Villadsen

Ligterink

Andersen

2022

A&A

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Context. The behaviour of molecules in space is to a large extent governed by where they freeze out or sublimate. The molecular binding energy is therefore an important parameter for many astrochemical studies. This parameter is usually determined with time-consuming experiments, computationally expensive quantum chemical calculations, or the inexpensive yet relatively inaccurate linear addition method. Aims. In this work, we propose a new method for predicting binding energies (BEs) based on machine learning that is accurate, yet computationally inexpensive. Methods. We created a machine-learning (ML) model based on Gaussian process regression (GPR) and trained it on a database of BEs of molecules collected from laboratory experiments presented in the literature. The molecules in the database are categorised by their features, such as mono- or multilayer coverage, binding surface, functional groups, valence electrons, and H-bond acceptors and donors. Results. We assessed the performance of the model with five-fold and leave-one-molecule-out cross validation. Predictions are generally accurate, with differences between predicted binding energies and values from the literature of less than ±20%. We used the validated model to predict the binding energies of 21 molecules that were recently detected in the interstellar medium, but for which binding energy values are unknown. We used a simplified model to visualise where the snow lines of these molecules would be located in a protoplanetary disk. Conclusions. This work demonstrates that ML can be employed to accurately and rapidly predict BEs of molecules. Machine learning complements current laboratory experiments and quantum chemical computational studies. The predicted BEs will find use in the modelling of astrochemical and planet-forming environments.

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“…20 s −1 91,101,269,270. This discrepancy originates from the fact that the previous formula neglects the rotational partition function of the desorbing molecules.…”

mentioning

confidence: 98%

Thermal desorption of interstellar ices. A review on the controlling parameters and their implications fromsnowlines to chemical complexity

Minissale¹,

Aikawa²,

Bergin³

et al. 2022

Preprint

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The evolution of star-forming regions and their thermal balance are strongly influenced by their chemical composition, that, in turn, is determined by the physicochemical processes that govern the transition between the gas phase and the solid state, specifically icy dust grains (e.g., particles adsorption and desorption). Gas-grain and grain-gas transitions as well as formation and sublimation of interstellar ices are thus essential elements of understanding astrophysical observations of cold environments (e.g., pre-stellar cores) where unexpected amounts of a large variety of chemical species have been observed in the gas phase. Adsorbed atoms and molecules also undergo chemical reactions which are not efficient in the gas phase. Therefore the parameterization of the physical properties of atoms and molecules interacting with dust grain particles is clearly a key aspect to interpret astronomical observations and to build realistic and predictive astrochemical models. In this consensus evaluation, we focus on parameters controlling the thermal desorption of ices and how these determine pathways towards molecular complexity and define the location of snowlines, which ultimately influence the planet formation process.We review different crucial aspects of desorption parameters both from a theoretical and experimental point of view. We critically assess the desorption parameters (the binding energies E b and the pre-exponential factor ν) commonly used in the astrochemical community for astrophysically relevant species and provide tables with recommended values. The aim of these tables is to provide a coherent set of critically assessed desorption parameters for common use in future work. In addition, we show that a non-trivial determination of the pre-exponential factor ν using the Transition State Theory can affect the binding energy value. The primary focus is on pure ices, but we also discuss the desorption behavior of mixed, i.e. astronomically more realistic ices. This allows discussion of segregation effects. Finally, we conclude this work by discussing the limitations of theoretical and experimental approaches currently used to determine the desorption properties with suggestions for future improvements.

show abstract

Thermal Processing and Interactions of Ethyl Formate in Model Astrophysical Ices Containing Water and Ethanol

Cited by 5 publications

References 57 publications

Thermal Desorption of Interstellar Ices: A Review on the Controlling Parameters and Their Implications from Snowlines to Chemical Complexity

Thermal Desorption of Interstellar Ices: A Review on the Controlling Parameters and Their Implications from Snowlines to Chemical Complexity

Predicting binding energies of astrochemically relevant molecules via machine learning

Thermal desorption of interstellar ices. A review on the controlling parameters and their implications fromsnowlines to chemical complexity

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