RESUMO
We present a novel cluster analysis implemented in our open-source software TRAVIS and its application to realistic and complex chemical systems. The underlying algorithm is exclusively based on atom distances. Using a two-dimensional model system, we first introduce different cluster analysis functions and their application to single snapshots and trajectories including periodicity and temporal propagation. Using molecular dynamics simulations of pure water with varying system size, we show that our cluster analysis is size-independent. Furthermore, we observe a similar clustering behavior of pure water in classical and ab initio molecular dynamics simulations, showing that our cluster analysis is universal. In order to emphasize the application to more complex systems and mixtures, we additionally apply the cluster analysis to ab initio molecular dynamics simulations of the [C2C1Im][OAc] ionic liquid and its mixture with water. Using that, we show that our cluster analysis is able to analyze the clustering of the individual components in a mixture as well as the clustering of the ionic liquid with water.
Assuntos
Líquidos Iônicos , Líquidos Iônicos/química , Simulação de Dinâmica Molecular , Água/química , Software , Análise por ConglomeradosRESUMO
In this work, we present a new theory to treat multicomponent liquids based on quantum-chemically calculated clusters. The starting point is the binary quantum cluster equilibrium theory, which is able to treat binary systems. The theory provides one equation with two unknowns. In order to obtain another linearly independent equation, the conservation of mass is used. However, increasing the number of components leads to more unknowns, and this requires linearly independent equations. We address this challenge by introducing a generalization of the conservation of arbitrary quantities accompanied by a comprehensive mathematical proof. Furthermore, a case study for the application of the new theory to ternary mixtures of chloroform, methanol, and water is presented. Calculated enthalpies of vaporization for the whole composition range are given, and the populations or weights of the different clusters are visualized.
RESUMO
A characteristic feature of ionic liquids is their nanosegregation, resulting in the formation of polar and nonpolar domains. The influence of increasing the alkyl side chain on the morphology of ionic liquids has been the subject of many studies. Typically, the polar network (charged part of the cation and anion) constitutes a continuous subphase that partially breaks to allow the formation of a nonpolar domain with the increase of the alkyl chain. As the nonpolar network expands, the number of tails per aggregate increases until the ionic liquid percolates. In this work, we demonstrate how the complementary software packages TRAVIS and AGGREGATES can be employed in conjunction to gain insights into the size and morphology of the [CnC1Im]Cl family, with n ∈ {2, 4, 6, 8, 10, 12}. The combination of the two approaches rounds off the picture of the intricate arrangement and structural features of the alkyl chains.
RESUMO
While so far it has been possible to calculate vibrational spectra of mixtures at a particular composition, we present here a novel cluster approach for a fast and robust calculation of mole fraction dependent infrared and vibrational circular dichroism spectra at the example of acetonitrile/(R)-butan-2-ol mixtures. By assigning weights to a limited number of quantum chemically calculated clusters, vibrational spectra can be obtained at any desired composition by a weighted average of the single cluster spectra. In this way, peak positions carrying information about intermolecular interactions can be predicted. We show that mole fraction dependent peak shifts can be accurately modeled and, that experimentally recorded infrared spectra can be reproduced with high accuracy over the entire mixing range. Because only a very limited number of clusters is required, the presented approach is a valuable and computationally efficient tool to access mole fraction dependent spectra of mixtures on a routine basis.