Churchillfulton0480

Numerical experiments suggest that our proposed methodology allows achieving accuracy that is comparable to other popular interpolation and machine learning techniques and requires significantly less time for model training than nonlinearly parameterized formulation.We survey the underlying theory behind the large-scale and linear scaling density functional theory code, conquest, which shows excellent parallel scaling and can be applied to thousands of atoms with diagonalization and millions of atoms with linear scaling. We give details of the representation of the density matrix and the approach to finding the electronic ground state and discuss the implementation of molecular dynamics with linear scaling. We give an overview of the performance of the code, focusing in particular on the parallel scaling, and provide examples of recent developments and applications.A hybrid configuration state function (CSF) and Slater determinant (SD) basis full configuration interaction (CI) program was developed to simultaneously take advantage of fast SD basis algorithms for σ = Hc formation and the smaller CI vector length and more robust convergence offered by a CSF basis. Graphical processing unit acceleration of the direct CSF-SD and SD-CSF basis transformation algorithms ensures that the combined transformation time per iteration relative to σ formation is small (∼15%). In addition to the obvious benefits of reducing the memory footprint of the CI vector, additional computational savings are demonstrated that rely directly on the size of the CI basis, in one particular case reducing the CI time-to-solution of a HF-CAS-(16,16)-CI/6-31G calculation of ethylene from 1954.79 s to 956 s by using a CSF basis, a 2.0× speedup.In this work, we have investigated the mono-variant relationship between the reduced viscosity and residual entropy in pure fluids and in binary mixtures of hydrocarbons and hydrocarbons with dissolved carbon dioxide. The mixtures considered were octane + dodecane, decane + carbon dioxide, and 1,3-dimethylbenzene (m-xylene) + carbon dioxide. The reduced viscosity was calculated according to the definition of Bell, while the residual entropy was calculated from accurate multi-parameter Helmholtz-energy equations of state and, for mixtures, the multi-fluid Helmholtz energy approximation. The mono-variant dependence of reduced viscosity upon residual molar entropy was observed for the pure fluids investigated, and by incorporating two scaling factors (one for reduced viscosity and the other for residual molar entropy), the data were represented by a single universal curve. To apply this method to mixtures, the scaling factors were determined from a mole-fraction weighted sum of the pure-component values. This simple model was found to work well for the systems investigated. The average absolute relative deviation (AARD) was observed to be between 1% and 2% for pure components and a mixture of similar hydrocarbons. Larger deviations, with AARDs of up to 15%, were observed for the asymmetric mixtures, but this compares favorably with other methods for predicting the viscosity of such systems. We conclude that the residual-entropy concept can be used to estimate the viscosity of mixtures of similar molecules with high reliability and that it offers a useful engineering approximation even for asymmetric mixtures.We present a method to invert a given density and find the Kohn-Sham (KS) potential in Density Functional Theory (DFT) that shares the density. Our method employs the concept of screening density, which is naturally constrained by the inversion procedure and thus ensures that the density being inverted leads to a smooth KS potential with correct asymptotic behavior. We demonstrate the applicability of our method by inverting both local and non-local (Hartree-Fock and coupled cluster) densities; we also show how the method can be used to mitigate the effects of self-interactions in common DFT potentials with appropriate constraints on the screening density.We studied the nonequilibrium transport of serially coupled double quantum dots connected to ferromagnetic electrodes. We demonstrated that the nonadiabatic part of the spin gauge field resulted in a current-induced Dzyaloshinskii-Moriya (DM) interaction effect in a double quantum dot and numerically confirmed this observation through the hierarchical equations of motion approach. We report that the spin current and the effective DM interaction are enhanced in the Kondo regime. We demonstrate that this enhancement occurs because the Kondo resonance, which is supposed to be suppressed by the local ferromagnetic exchange, is enhanced by the inter-dot coupling. This additional Kondo resonance channel increases the spin current. In addition, the impact of the spin-spin interaction and the Kondo effect on tunnel magnetoresistance is discussed. Our results offer a new approach for controlling the non-collinear spin interaction in double quantum dot devices.The structural evolution of the equilibrium and supercooled Cu46Zr54 liquids was investigated with a combination of elastic neutron scattering (with isotopic substitution) and synchrotron x-ray scattering studies. The partial pair correlation functions were determined over a wide temperature range (∼270 °C). These show that the Cu-Cu and Zr-Zr ordering increases as the temperature decreases, while the Cu-Zr ordering decreases. This surprising result is in contradiction with the results from molecular dynamics studies.We explicitly compute the non-equilibrium molecular dynamics of protons in the solid acid CsH2PO4 on the micrometer length scale via a multiscale Markov model The molecular dynamics/matrix propagation (MDM) method. Within the MDM approach, the proton dynamics information of an entire molecular dynamics simulation can be condensed into a single M × M matrix (M is the number of oxygen atoms in the simulated system). selleck chemicals Due to this drastic reduction in the complexity, we demonstrate how to increase the length and time scales in order to enable the simulation of inhomogeneities of CsH2PO4 systems at the nanometer scale. We incorporate explicit correlation of protonation dynamics with the protonation state of the neighboring proton sites and illustrate that this modification conserves the Markov character of the MDM method. We show that atomistic features such as the mean square displacement and the diffusion coefficient of the protons can be computed quantitatively from the matrix representation. Furthermore, we demonstrate the application potential of the scheme by computing the explicit dynamics of a non-equilibrium process in an 8 μm CsH2PO4 system during 5 ms.Monte Carlo simulations are a powerful tool to investigate the thermodynamic properties of atomic systems. In practice, however, sampling of the complete configuration space is often hindered by high energy barriers between different regions of configuration space, which can make ergodic sampling completely infeasible within accessible simulation times. Although several extensions to the conventional Monte Carlo scheme have been developed, which enable the treatment of such systems, these extensions often entail substantial computational cost or rely on the harmonic approximation. In this work, we propose an exact method called Funnel Hopping Monte Carlo (FHMC) that is inspired by the ideas of smart darting but is more efficient. Gaussian mixtures are used to approximate the Boltzmann distribution around local energy minima, which are then used to propose high quality Monte Carlo moves that enable the Monte Carlo simulation to directly jump between different funnels. We demonstrate the method's performance on the example of the 38 as well as the 75 atom Lennard-Jones clusters, which are well known for their double funnel energy landscapes that prevent ergodic sampling with conventional Monte Carlo simulations. By integrating FHMC into the parallel tempering scheme, we were able to reduce the number of steps required significantly until convergence of the simulation.Two-dimensional (2D) materials such as graphene, molybdenum sulfide, and hexagonal boron nitride are widely studied for separation applications such as water desalination. Desalination across such 2D nanoporous membranes is largely influenced by the bulk transport properties of water, which are, in turn, sensitive to the operating temperature. However, there have been no studies on the effect of temperature on desalination through 2D nanopores. We investigated water desalination through hydrogen functionalized graphene nanopores of varying pore areas at temperatures 275.0 K, 300.0 K, 325.0 K, and 350.0 K. The water flux showed a direct relation with the diffusion coefficient and an inverse relation with the hydrogen-bond lifetime. As a direct consequence, the water flux was found to be related to the temperature as per the Arrhenius equation, similar to an activated process. The results from the present study improve the understanding on water and ion permeation across nanoporous 2D materials at different temperatures. Furthermore, the present investigation suggests a kinetic model, which can predict the water and ion permeation based on the characteristics of the nanopore.Inspired by the possibility to experimentally manipulate and enhance chemical reactivity in helium nanodroplets, we investigate the effective interaction and the resulting correlations between two diatomic molecules immersed in a bath of bosons. By analogy with the bipolaron, we introduce the biangulon quasiparticle describing two rotating molecules that align with respect to each other due to the effective attractive interaction mediated by the excitations of the bath. We study this system in different parameter regimes and apply several theoretical approaches to describe its properties. Using a Born-Oppenheimer approximation, we investigate the dependence of the effective intermolecular interaction on the rotational state of the two molecules. In the strong-coupling regime, a product-state ansatz shows that the molecules tend to have a strong alignment in the ground state. To investigate the system in the weak-coupling regime, we apply a one-phonon excitation variational ansatz, which allows us to access the energy spectrum. In comparison to the angulon quasiparticle, the biangulon shows shifted angulon instabilities and an additional spectral instability, where resonant angular momentum transfer between the molecules and the bath takes place. These features are proposed as an experimentally observable signature for the formation of the biangulon quasiparticle. Finally, by using products of single angulon and bare impurity wave functions as basis states, we introduce a diagonalization scheme that allows us to describe the transition from two separated angulons to a biangulon as a function of the distance between the two molecules.The application of predictive and reliable modeling techniques for the simulation of charge transport in functional materials is an essential step for the development of advanced platforms for electronics, optoelectronics, and photovoltaics. In this context, kinetic Monte Carlo (KMC) methods have emerged as a valuable tool, especially for the simulation of systems where charge transport can be described by the hopping of charge carriers across localized quantum states, as, for example, in organic semiconductor materials. The accuracy, computational efficiency, and reliability of KMC simulations of charge transport, however, crucially depend on the methods and approximations used to evaluate electrostatic interactions arising from the distribution of charges in the system. The long-range nature of Coulomb interactions and the need to simulate large model systems to capture the details of charge transport phenomena in complex devices lead, typically, to a computational bottleneck, which hampers the application of KMC methods.