Monte Carlo simulations of nanoconfined n-decane films

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Publication Date
DOI 10.1039/A903431E
Impact Factor 3.676
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Abstract

Grand canonical ensemble Monte Carlo simulations of thin films of fluid n-decane confined between two plane-parallel, structureless walls were performed using the configurational bias method. The results indicate that special attention has to be paid to the way in which configuration space is sampled. A key quantity in the study is the solvation pressure p(sz), which is a damped oscillatory function of wall separation sz. The intensity of these oscillations is a consequence of both the formation of discrete molecular layers in the fluid parallel with the walls and the presence of isolated n-decane chains interconnecting neighboring layers, in that one end of the chain belongs to one layer and the other end to its neighbor. By means of Derjaguin's approximation, the solvation force from p(sz), which is frequently measured in experiments employing the surface forces apparatus, was calculated. The solvation force exhibits damped oscillations superimposed on a repulsive component, an effect which is ascribed to the presence of chains interconnecting neighboring fluid layers.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
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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.

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