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Register a new userEquations of state for ruthenium and rhodium
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Ru and Rh are interesting cases for comparing equations of state (EOS), because most general purpose EOS are semi-empirical, relying heavily on shock data, and none has been reported for Ru. EOS were calculated for both elements using all-electron atom-in-jellium theory, and cold compression curves were calculated for the common crystal types using the multi-ion pseudopotential approach. Previous EOS constructed for these elements used Thomas-Fermi (TF) theory for the electronic behavior at high temperatures, which neglects electronic shell structure; the atom-in-jellium EOS exhibited pronounced features from the excitation of successive electron shells. Otherwise, the EOS matched surprisingly well, especially considering the lack of experimental data for Ru. The TF-based EOS for Ru may however be inaccurate in the multi-terapascal range needed for some high energy density experiments. The multi-ion calculations predicted that the hexagonal close-packed phase of Ru remains stable to at least 2.5 TPa and possibly 10 TPa, and that its c/a should gradually increase to the ideal value. A method was devised to estimate the variation in Debye temperature from the cold curve, and thus estimate the ion-thermal EOS without requiring relatively expensive dynamical force calculations, in a form convenient for adjusting EOS or phase boundaries. The Debye temperature estimated in this way was similar to the result from atom-in-jellium calculations. We also predict the high-pressure melt loci of both elements.
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Equations of state (EOS) calculated from a computationally efficient atom-in-jellium treatment of the electronic structure have recently been shown to be consistent with more rigorous path integral Monte Carlo (PIMC) and quantum molecular dynamics (QMD) simulations of metals in the warm dense matter regime. Here we apply the atom-in-jellium model to predict wide-ranging EOS for the cryogenic liquid elements nitrogen, oxygen, and fluorine. The principal Hugoniots for these substances were surprisingly consistent with available shock data and Thomas-Fermi (TF) EOS for very high pressures, and exhibited systematic variations from TF associated with shell ionization effects, in good agreement with PIMC, though deviating from QMD and experiment in the molecular regime. The new EOS are accurate much higher in pressure than previous widely-used models for nitrogen and oxygen in particular, and should allow much more accurate predictions for oxides and nitrides in the liquid, vapor, and plasma regime, where these have previously been constructed as mixtures containing the older EOS.
Nowadays different experimental techniques, such as single molecule or relaxation experiments, can provide dynamic properties of biomolecular systems, but the amount of detail obtainable with these methods is often limited in terms of time or spatial resolution. Here we use state-of-the-art computational techniques, namely atomistic molecular dynamics and Markov state models, to provide insight into the rapid dynamics of short RNA oligonucleotides, in order to elucidate the kinetics of stacking interactions. Analysis of multiple microsecond-long simulations indicates that the main relaxation modes of such molecules can consist of transitions between alternative folded states, rather than between random coils and native structures. After properly removing structures that are artificially stabilized by known inaccuracies of the current RNA AMBER force field, the kinetic properties predicted are consistent with the timescales of previously reported relaxation experiments.
The process of RNA base fraying (i.e. the transient opening of the termini of a helix) is involved in many aspects of RNA dynamics. We here use molecular dynamics simulations and Markov state models to characterize the kinetics of RNA fraying and its sequence and direction dependence. In particular, we first introduce a method for determining biomolecular dynamics employing core-set Markov state models constructed using an advanced clustering technique. The method is validated on previously reported simulations. We then use the method to analyze extensive trajectories for four different RNA model duplexes. Results obtained using D. E. Shaw research and AMBER force fields are compared and discussed in detail, and show a non-trivial interplay between the stability of intermediate states and the overall fraying kinetics.
Recent path-integral Monte Carlo and quantum molecular dynamics simulations have shown that computationally efficient average-atom models can predict thermodynamic states in warm dense matter to within a few percent. One such atom-in-jellium model has typically been used to predict the electron-thermal behavior only, although it was previously developed to predict the entire equation of state (EOS). We report completely atom-in-jellium EOS calculations for Be, Al, Si, Fe, and Mo, as elements representative of a range of atomic number and low-pressure electronic structure. Comparing the more recent method of pseudo-atom molecular dynamics, atom-in-jellium results were similar: sometimes less accurate, sometimes more. All these techniques exhibited pronounced effects of electronic shell structure in the shock Hugoniot which are not captured by Thomas-Fermi based EOS. These results demonstrate the value of a hierarchical approach to EOS construction, using average-atom techniques with shell structure to populate a wide-range EOS surface efficiently, complemented by more rigorous 3D multi-atom calculations to validate and adjust the EOS.
The open-source library, irbasis, provides easy-to-use tools for two sets of orthogonal functions named intermediate representation (IR). The IR basis enables a compact representation of the Matsubara Greens function and efficient calculations of quantum models. The IR basis functions are defined as the solution of an integral equation whose analytical solution is not available for this moment. The library consists of a database of pre-computed high-precision numerical solutions and computational code for evaluating the functions from the database. This paper describes technical details and demonstrates how to use the library.
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