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“First-principles material modeling of solid-state electrolytes with the spinel structure”. Mees MJ, Pourtois G, Rosciano F, Put B, Vereecken PM, Stesmans A, Physical chemistry, chemical physics (2014). http://doi.org/10.1039/C3CP54610A
Abstract: Ionic diffusion through the novel (AlxMg1-2xLix)Al2O4 spinel electrolyte is investigated using first-principles calculations, combined with the Kinetic Monte Carlo algorithm. We observe that the ionic diffusion increases with the lithium content x. Furthermore, the structural parameters, formation enthalpies and electronic structures of (AlxMg1-2xLix)Al2O4 are calculated for various stoichiometries. The overall results indicate the (AlxMg1-2xLix)Al2O4 stoichiometries x = 0.2...0.3 as most promising. The (AlxMg1-2xLix)Al2O4 electrolyte is a potential candidate for the all-spinel solid-state battery stack, with the material epitaxially grown between well-known spinel electrodes, such as LiyMn2O4 and Li4+3yTi5O12 (y = 0...1). Due to their identical crystal structure, a good electrolyte-electrode interface is expected.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 4.123
Times cited: 8
DOI: 10.1039/C3CP54610A
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“Establishing uniform acceptance in force biased Monte Carlo simulations”. Neyts EC, Thijsse BJ, Mees MJ, Bal KM, Pourtois G, Journal of chemical theory and computation 8, 1865 (2012). http://doi.org/10.1021/ct2008268
Abstract: Uniform acceptance force biased Monte Carlo (UFMC) simulations have previously been shown to be a powerful tool to simulate atomic scale processes, enabling one to follow the dynamical path during the simulation. In this contribution, we present a simple proof to demonstrate that this uniform acceptance still complies with the condition of detailed balance, on the condition that the characteristic parameter lambda = 1/2 and that the maximum allowed step size is chosen to be sufficiently small. Furthermore, the relation to Metropolis Monte Carlo (MMC) is also established, and it is shown that UFMC reduces to MMC by choosing the characteristic parameter lambda = 0 [Rao, M. et al. Mol. Phys. 1979, 37, 1773]. Finally, a simple example compares the UFMC and MMC methods.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 5.245
Times cited: 20
DOI: 10.1021/ct2008268
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“Uniform-acceptance force-bias Monte Carlo method with time scale to study solid-state diffusion”. Mees MJ, Pourtois G, Neyts EC, Thijsse BJ, Stesmans A, Physical review : B : condensed matter and materials physics 85, 134301 (2012). http://doi.org/10.1103/PhysRevB.85.134301
Abstract: Monte Carlo (MC) methods have a long-standing history as partners of molecular dynamics (MD) to simulate the evolution of materials at the atomic scale. Among these techniques, the uniform-acceptance force-bias Monte Carlo (UFMC) method [ G. Dereli Mol. Simul. 8 351 (1992)] has recently attracted attention [ M. Timonova et al. Phys. Rev. B 81 144107 (2010)] thanks to its apparent capacity of being able to simulate physical processes in a reduced number of iterations compared to classical MD methods. The origin of this efficiency remains, however, unclear. In this work we derive a UFMC method starting from basic thermodynamic principles, which leads to an intuitive and unambiguous formalism. The approach includes a statistically relevant time step per Monte Carlo iteration, showing a significant speed-up compared to MD simulations. This time-stamped force-bias Monte Carlo (tfMC) formalism is tested on both simple one-dimensional and three-dimensional systems. Both test-cases give excellent results in agreement with analytical solutions and literature reports. The inclusion of a time scale, the simplicity of the method, and the enhancement of the time step compared to classical MD methods make this method very appealing for studying the dynamics of many-particle systems.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 3.836
Times cited: 31
DOI: 10.1103/PhysRevB.85.134301
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