Monte Carlo simulation and free energies of mixed oxidenanoparticles

Literature Information

Publication Date 2013-03-20
DOI 10.1039/C3CP50388G
Impact Factor 3.676
Authors

John A. Purton, Stephen C. Parker, Neil L. Allan


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Abstract

A Monte Carlo Exchange technique is used to study the thermodynamic properties of MgO–MnO nanoparticles ranging in size from 1728 to 21 952 ions. The solubility of Mg2+ is much greater in MnO than the reverse, reflecting the difference in size between the two cations. The solubility, for a given temperature, diminishes with nanoparticle size. As the Mn concentration is progressively increased the Mn2+ ions occupy the corners, edges and then surface sites of the nanoparticle before entering subsurface layers. We do not observe any pronounced ordering of the cations within the body of the nanoparticles themselves. The enthalpies of forming ternary nanoparticles from particles of MgO and MnO of the same size vary with the size of the nanoparticle and become more positive for a given concentration as the particle size increases. Free energies of mixing of the two end-member nanoparticles have been determined using the semigrand ensemble. The consolute temperature (the temperature above which there is complete miscibility) increases non-linearly with the size of the nanoparticle by approximately 70% over the size range considered.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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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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