The effect of ionic defect interactions on the hydration of yttrium-doped barium zirconate
文献情報
Fabian M. Draber
Hydrated acceptor-doped barium zirconate is a well-investigated proton conductor. In the analysis of most experimental studies, an ideal defect model is applied to fit the measured hydration data and obtain corresponding enthalpies and entropies. However, the data show a distinct deviation from ideal behaviour and thus defect interactions cannot be neglected. In the present contribution, the thermodynamics of water uptake into the yttrium-doped bulk material are investigated on the microscopic level with regards to ionic defect interactions. Metropolis Monte Carlo simulations using interaction models from first-principles energy calculations are applied to obtain an estimation of the free energy of interaction. The present results indicate that the ionic defect interactions are the primary reason for the non-ideality observed in experiments with varying yttrium fraction, proton fraction, and temperature. The activity coefficient quotients for the mass action law are obtained, which connect the ideal and real model and are of relevance to data evaluation and theoretical calculations.
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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.












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