Structural properties of methanol–water binary mixtures within the quantum cluster equilibrium model
文献信息
A.-M. Kelterer, W. M. F. Fabian
Density functional theory (B3LYP-D3, M06-2X) has been used to calculate the structures, interaction energies and vibrational frequencies of a set of 93 methanol–water clusters of different type (cubic, ring, spiro, lasso, bicyclic), size and composition. These interaction energies have been used within the framework of the Quantum Cluster Equilibrium Theory (QCE) to calculate cluster populations as well as thermodynamic properties of binary methanol–water mixtures spanning the whole range from pure water to pure methanol. The necessary parameters amf and bxv of the QCE model were obtained by fitting to experimental isobars of MeOH–H2O mixtures with different MeOH content. The cubic and spiro motifs dominate the distribution of methanol–water clusters in the mixtures with a maximum of mixed clusters at x(MeOH) = 0.365. Reasonable agreement with experimental data as well as earlier molecular dynamics simulations was found for excess enthalpies HE, entropies SE as well as Gibbs free energies of mixing GE. In contrast, heat capacities Cp and CEp showed only poor agreement with experimental data.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.














