1,977 research outputs found

    Temperature dependent effective potential method for accurate free energy calculations of solids

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    We have developed a thorough and accurate method of determining anharmonic free energies, the temperature dependent effective potential technique (TDEP). It is based on \emph{ab initio} molecular dynamics followed by a mapping onto a model Hamiltonian that describes the lattice dynamics. The formalism and the numerical aspects of the technique are described in details. A number of practical examples are given, and results are presented, which confirm the usefulness of TDEP within \emph{ab initio} and classical molecular dynamics frameworks. In particular, we examine from first-principles the behavior of force constants upon the dynamical stabilization of body centered phase of Zr, and show that they become more localized. We also calculate phase diagram for 4^4He modeled with the Aziz \emph{et al.} potential and obtain results which are in favorable agreement both with respect to experiment and established techniques

    Electron affinity of liquid water.

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    Understanding redox and photochemical reactions in aqueous environments requires a precise knowledge of the ionization potential and electron affinity of liquid water. The former has been measured, but not the latter. We predict the electron affinity of liquid water and of its surface from first principles, coupling path-integral molecular dynamics with ab initio potentials, and many-body perturbation theory. Our results for the surface (0.8 eV) agree well with recent pump-probe spectroscopy measurements on amorphous ice. Those for the bulk (0.1-0.3 eV) differ from several estimates adopted in the literature, which we critically revisit. We show that the ionization potential of the bulk and surface are almost identical; instead their electron affinities differ substantially, with the conduction band edge of the surface much deeper in energy than that of the bulk. We also discuss the significant impact of nuclear quantum effects on the fundamental gap and band edges of the liquid

    Development of an Advanced Force Field for Water using Variational Energy Decomposition Analysis

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    Given the piecewise approach to modeling intermolecular interactions for force fields, they can be difficult to parameterize since they are fit to data like total energies that only indirectly connect to their separable functional forms. Furthermore, by neglecting certain types of molecular interactions such as charge penetration and charge transfer, most classical force fields must rely on, but do not always demonstrate, how cancellation of errors occurs among the remaining molecular interactions accounted for such as exchange repulsion, electrostatics, and polarization. In this work we present the first generation of the (many-body) MB-UCB force field that explicitly accounts for the decomposed molecular interactions commensurate with a variational energy decomposition analysis, including charge transfer, with force field design choices that reduce the computational expense of the MB-UCB potential while remaining accurate. We optimize parameters using only single water molecule and water cluster data up through pentamers, with no fitting to condensed phase data, and we demonstrate that high accuracy is maintained when the force field is subsequently validated against conformational energies of larger water cluster data sets, radial distribution functions of the liquid phase, and the temperature dependence of thermodynamic and transport water properties. We conclude that MB-UCB is comparable in performance to MB-Pol, but is less expensive and more transferable by eliminating the need to represent short-ranged interactions through large parameter fits to high order polynomials

    Molecular modeling for physical property prediction

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    Multiscale modeling is becoming the standard approach for process study in a broader framework that promotes computer aided integrated product and process design. In addition to usual purity requirements, end products must meet new constraints in terms of environmental impact, safety of goods and people, specific properties. This chapter adresses the use of molecular modeling tools for the prediction of physical property usefull for chemical engineering practice

    Connection between water’s dynamical and structural properties: Insights from ab initio simulations

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    Among all fluids, water has always been of special concern for scientists from a wide variety of research fields because of its rich behavior. In particular, some questions remain unanswered today regarding the temperature dependence of bulk and interfacial transport properties of supercooled and liquid water, for example, regarding the fundamentals of the violation of the Stokes–Einstein relation in the supercooled regime, or the subtle relation between structure and dynamical properties. We have studied the temperature dependence of the bulk transport properties from ab initio molecular dynamics based on density functional theory, down to the supercooled regime. We determined, from a selection of functionals, that the SCAN (strongly constrained and appropriately normed) functional best describes the experimental viscosity and self-diffusion coefficient, although we found disagreements at lower temperatures. For a limited set of temperatures, we also explored the role of nuclear quantum effects on water dynamics using ab initio molecular dynamics that was accelerated by a recently introduced machine learning approach. We then investigated the molecular mechanisms underlying the different functionals’ performance and assessed the validity of the Stokes–Einstein relation. We also explored the connection between structural properties and transport coefficients, verifying the validity of the excess entropy scaling relations for all functionals. These results pave the way for the prediction of the transport coefficients from the radial distribution function, thus helping to develop better functionals. In this respect, these results indicate the importance of describing the long-range features of the radial distribution function

    Development and application of force fields for molecular simulations

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    Simulationen weicher Materie umfassen ein breites Spektrum von Anwendungen, wie z. B. die Modellierung von BiomolekĂŒlen, Polymeren und Materialien fĂŒr die organische Elektronik. Um die LĂ€ngen- und Zeitskalen relevanter PhĂ€nomene zu erreichen, werden die Wechselwirkungen in diesen Systemen ĂŒblicherweise durch recheneffiziente analytische Kraftfelder berechnet. Ein Teil dieser Arbeit beschreibt eine Beispielanwendung fĂŒr die kraftfeldbasierte Modellierung von amorphen organischen Halbleitern. Der konventionelle Kraftfeldansatz fĂŒhrt jedoch Parameter ein, die aus fĂŒr das betrachtete MolekĂŒl geeigneten ParametersĂ€tzen zugewiesen werden mĂŒssen. Vor allem aufgrund der einfachen FunktionsausdrĂŒcke fĂŒr die nicht-kovalenten Wechselwirkungen erfordert das Verfahren zur Bestimmung dieser ParametersĂ€tze empirische Zielwerte, die nicht immer verfĂŒgbar sind. Bottom-up-AnsĂ€tze, wie z. B. Bottom-up-Kraftfelder mit festen FunktionsausdrĂŒcken oder Potentiale basierend auf neuronalen Netzen, zielen darauf ab, die experimentellen Daten durch Ergebnisse aus ab initio Rechnungen zu ersetzen. FĂŒr die Anwendung in umfangreichen Molekulardynamiksimulationen weisen diese Methoden noch offene Herausforderungen auf. Feste FunktionsausdrĂŒcke leiden unter einer begrenzten FlexibilitĂ€t, die ab initio PotentialenergieoberflĂ€che zu reproduzieren und erfordern manuelle Typdefinitionen, um die Anzahl der Parameter zu reduzieren. Potentiale, die auf neuronalen Netzen basieren, verbessern beide Aspekte, aber ihre hohen Rechenanforderungen begrenzen die zugĂ€nglichen LĂ€ngen- und Zeitskalen. In dieser Arbeit wird ein neuartiger Bottom-up-Ansatz zur Modellierung nicht-kovalenter Wechselwirkungen vorgestellt, der fĂŒr großskalige Simulationen konzipiert ist. Das Konzept effizienter additiver Wechselwirkungen wird mit der FlexibilitĂ€t kĂŒnstlicher neuronaler Netze fĂŒr die Interpolation verschiedener chemischer Zusammensetzungen und geometrischer Anordnungen kombiniert. Die Anwendung des Modells wird in Molekulardynamiksimulationen demonstriert, und der Vergleich der berechneten thermodynamischen Eigenschaften mehrerer kleiner organischer MolekĂŒle mit experimentellen Daten und konventionellen Kraftfeldern zeigt eine vielversprechende Vorhersageleistung. ZusĂ€tzlich bewahrt das Modell die Energiezerlegung in physikalisch motivierte Komponenten, die von der symmetrieangepassten Störungstheorie, die fĂŒr die ab initio Referenzrechnungen verwendet wird, bereitgestellt wird. Diese Trennbarkeit und die UnabhĂ€ngigkeit von empirischen Daten machen dieses Modell potenziell nĂŒtzlich fĂŒr zukĂŒnftige Materialdesign-Anwendungen
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