Improved AIOMFAC model parameterisation of the temperature dependence of activity coefficients for aqueous organic mixtures
Notice bibliographique
Résumé
Abstract. This study presents a new, improved parameterisation of the temperature dependence of activity coefficients in the AIOMFAC (Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients) model applicable for aqueous as well as water-free organic solutions. For electrolyte-free organic and organic–water mixtures the AIOMFAC model uses a group-contribution approach based on UNIFAC (UNIversal quasi-chemical Functional-group Activity Coefficients). This group-contribution approach explicitly accounts for interactions among organic functional groups and between organic functional groups and water. The previous AIOMFAC version uses a simple parameterisation of the temperature dependence of activity coefficients, aimed to be applicable in the temperature range from ~ 275 to ~ 400 K. With the goal to improve the description of a wide variety of organic compounds found in atmospheric aerosols, we extend the AIOMFAC parameterisation for the functional groups carboxyl, hydroxyl, ketone, aldehyde, ether, ester, alkyl, aromatic carbon-alcohol, and aromatic hydrocarbon to atmospherically relevant low temperatures. To this end we introduce a new parameterisation for the temperature dependence. The improved temperature dependence parameterisation is derived from classical thermodynamic theory by describing effects from changes in molar enthalpy and heat capacity of a multi-component system. Thermodynamic equilibrium data of aqueous organic and water-free organic mixtures from the literature are carefully assessed and complemented with new measurements to establish a comprehensive database, covering a wide temperature range (~ 190 to ~ 440 K) for many of the functional group combinations considered. Different experimental data types and their processing for the estimation of AIOMFAC model parameters are discussed. The new AIOMFAC parameterisation for the temperature dependence of activity coefficients from low to high temperatures shows an overall improvement of 28% in comparison to the previous model version, when both versions are compared to our database of experimentally determined activity coefficients and related thermodynamic data. When comparing the previous and new AIOMFAC model parameterisations to the subsets of experimental data with all temperatures below 274 K or all temperatures above 322 K (i.e. outside a 25 K margin of the reference temperature of 298 K), applying the new parameterisation leads to 37% improvement in each of the two temperature ranges considered. The new parameterisation of AIOMFAC agrees well with a large number of experimental data sets. Larger model–measurement discrepancies were found particularly for some of the systems containing multi-functional organic compounds. The affected systems were typically also poorly represented at room temperature and further improvements will be necessary to achieve better performance of AIOMFAC in these cases (assuming the experimental data are reliable). The performance of the AIOMFAC parameterisation is typically better for systems containing relatively small organic compounds and larger deviations may occur in mixtures where molecules of high structural complexity such as highly oxygenated compounds or molecules of high molecular mass (e.g. oligomers) prevail. Nevertheless, the new parameterisation enables the calculation of activity coefficients for a wide variety of different aqueous/water-free organic solutions down to the low temperatures present in the upper troposphere.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».