Molecular Origin of the Sign Preference of Ion- Induced Heterogeneous Nucleation in a Complex Ionic Liquid–Diethylene Glycol System

Abstract

Heterogeneous nucleation on charged seeds has been shown to frequently prefer a given sign of electrical charge (anion or cation), at constant seed size and (apparent) chemical composition. For some systems, this sign preference can be readily understood in terms of individual chemical interactions. However, experiments are in general unable to provide satisfying molecular-level explanations for the sign preference of chemically complex systems. Here, we experimentally demonstrate a positive sign preference for charged ionic liquid seeds (CILS) with diethylene glycol vapor (DEG) and explain the physicochemical origins of this preference via quantum chemical calculations. The computational results show that all enthalpies and free energies for adsorption of DEG onto the CILS clusters are lower for the positively charged seeds compared to those for the negatively charged seeds. The main reason for this difference is the stronger hydrogen bonds in the cationic clusters originating from the ability of imidazolium-based cations to act as hydrogen bond acceptors.

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning

“…Neither the binding energy nor the reactivity (e.g., proton transfer) alone is sufficient to determine how straightforward the CS process is for a given clustering system. Over several years, JKCS has been used to study various clusters and their properties. ,,,,,,− Based on these studies, we present typical examples of molecular cluster properties that complicate CS compared to a reference case of a nonreactive, one-component, crystal-like cluster with a single low-energy configuration, formed from rigid, closed-shell monomers with only one conformer. This reference case can be, for example, a water cluster at a very low temperature, that is, an ice crystal.…”

“…Diethylene glycol around ionic-liquid clusters. 109 Multiple conformers were introduced at the beginning of CS. With no proton transfer present, interactions were well described by DFT methods with large basis sets.…”

Reduced seed-material dependence of a condensation particle counter

“…However, persisting research efforts yielded a substantial decrease in the minimum detectable size by choosing specific working fluids. Those results hint that activation efficiencies are profoundly influenced by specific interaction between the chemical composition of the seed particle and the molecular constitution of the vapor (Krämer et al, 2000;Keshavarz et al, 2020;Toropainen et al, 2021). Employing the practical criteria for working fluids outlined in Magnusson et al (2003) and Iida et al (2009), propylene glycol is a suitable substance since it is non-hazardous and has a dynamic viscosity below 50 mPa•s at room temperature.…”

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning

“…Over several years, JKCS has been used to study various clusters and their properties. 3,6,44,46,54,62,[100][101][102][103][104][105][106][107][108][109][110][111][112][113] Based on these studies, we present typical examples of molecular cluster properties that complicate CS compared to a reference case of a nonreactive, one-component, crystal-like cluster with a single low-energy configuration, formed from rigid, closed-shell monomers with only one conformer. This reference case can be, for example, a water cluster at a very low temperature, i.e., an ice crystal.…”