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This paper focuses on phase and aggregation behavior for linear chains composed of blocks of hydrophilic and hydrophobic segments. Phase and conformational transitions of patterned chains are relevant for understanding liquid–liquid separation of biomolecular condensates, which play a prominent role in cellular biophysics and for surfactant and polymer applications. Previous studies of simple models for multiblock chains have shown that, depending on the sequence pattern and chain length, such systems can fall into one of two categories: displaying either phase separation or aggregation into finite-size clusters. The key new result of this paper is that both formation of finite-size aggregates and phase separation can be observed for certain chain architectures at appropriate conditions of temperature and concentration. For such systems, a bulk dense liquid condenses from a dilute phase that already contains multi-chain finite-size aggregates. The computational approach used in this study involves several distinct steps using histogram-reweighting grand canonical Monte Carlo simulations, which are described in some level of detail. [ABSTRACT FROM AUTHOR]

Performing full-resolution atomistic simulations of nucleic acid folding has remained a challenge for biomolecular modeling. Understanding how nucleic acids fold and how they transition between different folded structures as they unfold and refold has important implications for biology. This paper reports a theoretical model and computer simulation of the ab initio folding of DNA inverted repeat sequences. The formulation is based on an all-atom conformational model of the sugar-phosphate backbone via chain closure, and it incorporates three major molecular-level driving forces—base stacking, counterion-induced backbone self-interactions, and base pairing—via separate analytical theories designed to capture and reproduce the effects of the solvent without requiring explicit water and ions in the simulation. To accelerate computational throughput, a mixed numerical/analytical algorithm for the calculation of the backbone conformational volume is incorporated into the Monte Carlo simulation, and special stochastic sampling techniques were employed to achieve the computational efficiency needed to fold nucleic acids from scratch. This paper describes implementation details, benchmark results, and the advantages and technical challenges with this approach. [ABSTRACT FROM AUTHOR]

We obtain the phase diagram of the hard core lattice gas with third nearest neighbor exclusion on the triangular lattice using Monte Carlo simulations that are based on a rejection-free flat histogram algorithm. In a recent paper [Darjani et al., J. Chem. Phys. 151, 104702 (2019)], it was claimed that the lattice gas with third nearest neighbor exclusion undergoes two phase transitions with increasing density with the phase at intermediate densities exhibiting hexatic order with continuously varying exponents. Although a hexatic phase is expected when the exclusion range is large, it has not been seen earlier in hard core lattice gases with short range exclusion. In this paper, by numerically determining the entropies for all densities, we show that there is only a single phase transition in the system between a low-density fluid phase and a high density ordered sublattice phase and that a hexatic phase is absent. The transition is shown to be first order in nature, and the critical parameters are determined accurately. [ABSTRACT FROM AUTHOR]

Polymer models describing the statistics of biomolecules under confinement have applications to a wide range of single-molecule experimental techniques and give insight into biologically relevant processes in vivo. In this paper, we determine the transverse position and bending correlation functions for a wormlike chain confined within slits and cylinders (with one and two confined dimensions, respectively) using a mean-field approach that enforces rigid constraints on average. We show the theoretical predictions accurately capture the statistics of a wormlike chain from Monte Carlo simulations in both confining geometries for both weak and strong confinement. We also show that the longitudinal correlation function is accurately computed for a chain confined to a slit and leverages the accuracy of the model to suggest an experimental technique to infer the (often unobservable) transverse statistics from the (directly observable) longitudinal end-to-end distance. [ABSTRACT FROM AUTHOR]

The study of the thermodynamics and structures of iron clusters has been carried on, focusing on small clusters and initial icosahedral and fcc-cuboctahedral structures. Two combined tools are used. First, energy intervals are explored by the Monte Carlo algorithm, called σ-mapping, detailed in the work of Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. In its flat histogram version, it provides the classical density of states, gp(Ep), in terms of the potential energy of the system. Second, the iron system is described by a potential which is called "corrected EAM" (cEAM), explained in the work of Basire et al. [J. Chem. Phys. 141, 104304 (2014), Paper II]. Small clusters from 3 to 12 atoms in their ground state have been compared first with published Density Functional Theory (DFT) calculations, giving a complete agreement of geometries. The series of 13, 55, 147, and 309 atom icosahedrons is shown to be the most stable form for the cEAM potential. However, the 147 atom cluster has a special behaviour, since decreasing the energy from the liquid zone leads to the irreversible trapping of the cluster in a reproducible amorphous state, 7.38 eV higher in energy than the icosahedron. This behaviour is not observed at the higher size of 309 atoms. The heat capacity of the 55, 147, and 309 atom clusters revealed a pronounced peak in the solid zone, related to a solid-solid transition, prior to the melting peak. The corresponding series of 13, 55, and 147 atom cuboctahedrons has been compared, underscoring the unstability towards the icosahedral structure. This unstability occurs clearly in several steps for the 147 atom cluster, with a sudden transformation at a transition state. This illustrates the concerted icosahedron-cuboctahedron transformation of Buckminster Fuller-Mackay, which is calculated for the cEAM potential. Two other clusters of initial fcc structures with 24 and 38 atoms have been studied, as well as a 302 atom cluster. Each one relaxes towards a more stable structure without regularity. The 38 atom cluster exhibits a nearly glassy relaxation, through a cascade of six metastable states of long life. This behaviour, as that of the 147 atom cluster towards the amorphous state, shows that difficulties to reach ergodicity in the lower half of the solid zone are related to particular features of the potential energy landscape, and not necessarily to a too large size of the system. Comparisons of the cEAM iron system with published results about Lennard-Jones systems and DFT calculations are made. The results of the previous clusters have been combined with that of Paper II to plot the cohesive energy Ec and the melting temperature Tm in terms of the cluster atom number Nat. The Nat1/3 linear dependence of the melting temperature (Pawlow law) is observed again for Nat > 150. In contrast, for Nat < 150, the curve diverges strongly from the Pawlow law, giving it an overall V-shape, with a linear increase of Tm when Nat goes from 55 to 13 atoms. Surprisingly, the 38 atom cluster is anomalously below the overall curve. [ABSTRACT FROM AUTHOR]

In a recent paper, we proposed the adaptive shift method for correcting undersampling bias of the initiator-full configuration interaction (FCI) quantum Monte Carlo. The method allows faster convergence with the number of walkers to the FCI limit than the normal initiator method, particularly for large systems. However, in its application to some systems, mostly strongly correlated molecules, the method is prone to overshooting the FCI energy at intermediate walker numbers, with convergence to the FCI limit from below. In this paper, we present a solution to the overshooting problem in such systems, as well as further accelerating convergence to the FCI energy. This is achieved by offsetting the reference energy to a value typically below the Hartree–Fock energy but above the exact energy. This offsetting procedure does not change the exactness property of the algorithm, namely, convergence to the exact FCI solution in the large-walker limit, but at its optimal value, it greatly accelerates convergence. There is no overhead cost associated with this offsetting procedure and is therefore a pure and substantial computational gain. We illustrate the behavior of this offset adaptive shift method by applying it to the N2 molecule, the ozone molecule at three different geometries (an equilibrium open minimum, a hypothetical ring minimum, and a transition state) in three basis sets (cc-pVXZ, X = D, T, Q), and the chromium dimer in the cc-pVDZ basis set, correlating 28 electrons in 76 orbitals. We show that in most cases, the offset adaptive shift method converges much faster than both the normal initiator method and the original adaptive shift method. [ABSTRACT FROM AUTHOR]

Wittkamper I et al. i studied the oxidation behavior of macroscopic Rh-Ga alloy SCALMS droplets and Rh-Ga model catalyst nanoparticles with low Rh content and found that thin oxide layers formed that were enriched with Rh.[18] Using computational methods, they concluded that Rh incorporation into the Ga SB 2 sb O SB 3 sb film occurs by substituting octahedrally coordinated Ga. The papers are roughly split, with half focused on SACs where the single metal atoms are supported on an oxide, while the other half focus on single-atom alloys. While the recent heterogeneous catalysis literature contains a vast number of reports of the synthesis and application of new single-atom catalysts, the field, in general, suffers from a distinct lack of fundamental understanding of the exact nature of the active sites and their operating mechanism. [Extracted from the article]

A variant of the hypothetical scanning (HS) method for calculating the absolute entropy and free energy of fluids is developed, as applied to systems of Lennard-Jones atoms (liquid argon). As in the preceding paper (Paper I), a probability P[sub i] approximating the Boltzmann probability of system configuration i, is calculated with a reconstruction procedure based on adding the atoms gradually to an initially empty volume, where they are placed in their positions at i; in this process the volume is divided into cubic cells, which are visited layer-by-layer, line-by-line. At each step a transition probability (TP) is calculated and the product of all the TPs leads to P[sub i]. At step k, k-1 cells have already been treated, where among them N[sub k] are occupied by an atom. A canonical metropolis Monte Carlo (MC) simulation is carried out over a portion of the still unvisited (future) volume thus providing an approximate representation of the N-N[sub k] as yet untreated (future) atoms. The TP of target cell k is determined from the number of visits of future atoms to this cell during the simulation. This MC version of HS, called HSMC, is based on a relatively small number of efficiency parameters; their number does not grow and their values are not changed as the number of the treated future atoms is increased (i.e., as the approximation improves); therefore, implementing HSMC for a relatively large number of future atoms (up to 40 in this study) is straightforward. Indeed, excellent results have been obtained for the free energy and the entropy. © 2003 American Institute of Physics. [ABSTRACT FROM AUTHOR]

In this paper, we report grand canonical Monte Carlo simulations performed to characterize the adsorption of four linear alcohol molecules, comprising between two and five carbon atoms (namely, ethanol, n-propanol, n-butanol, and n-pentanol) on crystalline ice in a temperature range typical of the Earth's troposphere. The adsorption details analyzed at 228 K show that, at low coverage of the ice surface, the polar head of the adsorbed molecules tends to optimize its hydrogen bonding with the surrounding water, whereas the aliphatic chain lies more or less parallel to the ice surface. With increasing coverage, the lateral interactions between the adsorbed alcohol molecules lead to the reorientation of the aliphatic chains that tend to become perpendicular to the surface; the adsorbed molecules pointing thus their terminal methyl group up to the gas phase. When compared to the experimental data, the simulated and measured isotherms show a very good agreement, although a small temperature shift between simulations and experiments could be inferred from simulations at various temperatures. In addition, this agreement appears to be better for ethanol and n-propanol than for n-butanol and n-pentanol, especially at the highest pressures investigated, pointing to a possible slight underestimation of the lateral interactions between the largest alcohol molecules by the interaction potential model used. Nevertheless, the global accuracy of the approach used, as tested under tropospheric conditions, opens the way for its use in modeling studies also relevant to another (e.g., astrophysical) context. [ABSTRACT FROM AUTHOR]

In a binary mixture, stripes refer to a one-dimensional periodicity of the composition, namely, a regular alternation of layers filled with particles of mostly one species. We have recently introduced [Munaò et al., Phys. Chem. Chem. Phys. 25, 16227 (2023)] a model that possibly provides the simplest binary mixture endowed with stripe order. The model consists of two species of identical hard spheres with equal concentration, which mutually interact through a square-well potential. In that paper, we have numerically shown that stripes are present in both liquid and solid phases when the attraction range is rather long. Here, we study the phase behavior of the model in terms of a density functional theory capable to account for the existence of stripes in the dense mixture. Our theory is accurate in reproducing the phases of the model, at least insofar as the composition inhomogeneities occur on length scales quite larger than the particle size. Then, using Monte Carlo simulations, we prove the existence of solid stripes even when the square well is much thinner than the particle diameter, making our model more similar to a real colloidal mixture. Finally, when the width of the attractive well is equal to the particle diameter, we observe a different and more complex form of compositional order in the solid, where each species of particle forms a regular porous matrix holding in its holes the other species, witnessing a surprising variety of emergent behaviors for a very basic model of interaction. [ABSTRACT FROM AUTHOR]

The exponential-6 (exp-6) potential is commonly used to model fluids at high densities. In this paper, I propose a new equation of state (EOS) in the form of an analytical expression for the excess Helmholtz free energy of an exp-6 fluid. The EOS is based on extensive Monte Carlo simulations and therefore combines the excellent accuracy of the simulations with the numerical efficiency of a polynomial expression. The mean relative error in compressibility factor and internal energy is 0.14% and 0.25% respectively, which is a significant improvement over statistical mechanical theories. The EOS was implemented into a thermochemical code in order to optimize gas parameters and evaluate its performance on pure gas data, shock compression and detonation properties. Predicted gas densities, heat capacities and speed of sound for pure gases were generally within experimental uncertainties at pressures up to 1 GPa and temperatures above 300 K. For polar molecules, a simple free energy correction was introduced which greatly improved accuracy at low temperature. Calculated shock Hugoniots showed excellent agreement with experimental values up to 150 GPa and 10 000 K, and the detonation performance was accurately predicted for a number of different types of explosives. [ABSTRACT FROM AUTHOR]

Hybrid methods that combine molecular dynamics methods capable of analyzing dynamics with Monte Carlo (MC) methods that can efficiently treat thermodynamically stable states are valuable for understanding complex chemical processes in which an equilibrium state is reached through many elementary processes. The hybrid MC (HMC) method is one such promising method; however, it often fails to sample configurations properly from the canonical multimodal distribution due to the rugged potential energy surfaces. In this paper, we extend the HMC method to overcome this difficulty. The new method, which is termed potential scaling HMC (PS-HMC), makes use of an artificially modulated trajectory to propose a new configuration. The trajectory is generated from Hamilton's equations, but the potential energy surface is scaled to be gradually flattened and then recovered to the original surface, which facilitates barrier-crossing processes. We apply the PS-HMC method to three kinds of molecular processes: the thermal motion of argon particles, butane isomerization, and an atom transfer chemical reaction. These applications demonstrate that the PS-HMC method is capable of correctly constructing the canonical ensemble with a multimodal distribution. The sampling efficiency and accepted trajectories are examined to clarify the features of the PS-HMC method. Despite the potential scaling, many reactive atom transfer trajectories (elementary processes) pass through the vicinity of the minimum energy path. Furthermore, we demonstrate that the method can properly imitate the relaxation process owing to the inherent configurational continuity. By comparing the PS-HMC method with other relevant methods, we can conclude that the new method is a unique approach for studying both the dynamic and thermodynamic aspects of chemical processes. [ABSTRACT FROM AUTHOR]

Theoretical analysis and computer simulations (Monte Carlo and numerical integration of differential equations) indicate that the statistical effect of a small number of reacting molecules is affected by transfer of reagent molecules between nanoreactors (droplets in this study). As a model reaction, a simple reversible association A + B ⇆ C was chosen, which was studied previously without reagent transfer processes. For sufficiently fast exchange of reactant molecules and a sufficiently high number of nanoreactors, the studied systems virtually do not differ from large volume systems if overall kinetics and thermodynamics of the chemical process are concerned. However, if either reagent molecule exchange is not fast or the number of exchanging nanoreactors is low, then the stochastic effect is clearly visible, influencing the kinetics of reaching reaction equilibrium. In systems with a low number of nanoreactors, the apparent (average) equilibrium constant is affected as well. The distribution of reactant molecules in the nanoreactors is governed by stochastic processes, dependent on stochastic rate constants of all processes, chemical as well as physical (transfer of molecules outside and into droplets). When accumulation of reactant molecules in the continuous phase cannot be neglected, then the partition coefficients of reactants between the continuous and dispersed phases have to be taken into account. Distributions of reactant molecules described in the paper for systems composed of few nanoreactors can be especially important for some biochemical processes in living cells or devised corresponding artificial reactors. If the reactant molecules predominate in a continuous phase, then the kinetics and overall conversion of reversible association may be significantly affected by the presence of the dispersed phase and its catalytic behavior can be observed. It has been shown that Monte Carlo simulations, applying a devised simple algorithm, give reliable results, allowing theoretical studies of nanoscale-droplet systems. [ABSTRACT FROM AUTHOR]

Small systems have higher surface area-to-volume ratios than macroscopic systems. The thermodynamics of small systems therefore deviates from the description of classical thermodynamics. One consequence of this is that properties of small systems can be dependent on the system's ensemble. By comparing the properties in grand canonical (open) and canonical (closed) systems, we investigate how a small number of particles can induce an ensemble dependence. Emphasis is placed on the insight that can be gained by investigating ideal gases. The ensemble equivalence of small ideal gas systems is investigated by deriving the properties analytically, while the ensemble equivalence of small systems with particles interacting via the Lennard-Jones or the Weeks–Chandler–Andersen potential is investigated through Monte Carlo simulations. For all the investigated small systems, we find clear differences between the properties in open and closed systems. For systems with interacting particles, the difference between the pressure contribution to the internal energy, and the difference between the chemical potential contribution to the internal energy, are both increasing with the number density. The difference in chemical potential is, with the exception of the density dependence, qualitatively described by the analytic formula derived for an ideal gas system. The difference in pressure, however, is not captured by the ideal gas model. For the difference between the properties in the open and closed systems, the response of increasing the particles' excluded volume is similar to the response of increasing the repulsive forces on the system walls. This indicates that the magnitude of the difference between the properties in open and closed systems is related to the restricted movement of the particles in the system. The work presented in this paper gives insight into the mechanisms behind ensemble in-equivalence in small systems, and illustrates how a simple statistical mechanical model, such as the ideal gas, can be a useful tool in these investigations. [ABSTRACT FROM AUTHOR]

Inelastic collisions of OH with an inert liquid perfluoropolyether (PFPE) surface have been studied experimentally. A pulsed molecular beam of OH with a kinetic energy distribution peaking at 35 kJ mol−1 was directed at a continually refreshed PFPE surface. OH molecules were detected state-selectively with spatial and temporal resolution by pulsed, planar laser-induced fluorescence. The scattered speed distributions were confirmed to be strongly superthermal, regardless of the incidence angle (0° or 45°). Angular scattering distributions were measured for the first time; their reliability was confirmed through extensive Monte Carlo simulations of experimental averaging effects, described in Paper II [A. G. Knight et al., J. Chem. Phys. 158, 244705 (2023)]. The distributions depend markedly on the incidence angle and are correlated with scattered OH speed, consistent with predominantly impulsive scattering. For 45° incidence, the angular distributions are distinctly asymmetric to the specular side but peak at sub-specular angles. This, along with the breadth of the distributions, is incompatible with scattering from a surface that is flat on a molecular scale. New molecular dynamics simulations corroborate the roughness of the PFPE surface. A subtle but unexpected systematic dependence of the angular distribution on the OH rotational state was found, which may be dynamical in origin. The OH angular distributions are similar to those for kinematically similar Ne scattering from PFPE and hence not strongly perturbed by OH being a linear rotor. The results here are broadly compatible with prior predictions from independent quasiclassical trajectory simulations of OH scattering from a model-fluorinated self-assembled monolayer surface. [ABSTRACT FROM AUTHOR]

The study of alloys using computational methods has been a difficult task due to the usually unknown stoichiometry and local atomic ordering of the different structures experimentally. In order to combat this, first-principles methods have been coupled with statistical methods such as the cluster expansion formalism in order to construct the energy hull diagram, which helps to determine if an alloyed structure can exist in nature. Traditionally, density functional theory (DFT) has been used in such workflows. In this paper, we propose to use chemically accurate many-body variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods to construct the energy hull diagram of an alloy system due to the fact that such methods have a weaker dependence on the starting wavefunction and density functional, scale similarly to DFT with the number of electrons, and have had demonstrated success for a variety of materials. To carry out these simulations in a high-throughput manner, we propose a method called Jastrow sharing, which involves recycling the optimized Jastrow parameters between alloys with different stoichiometries. We show that this eliminates the need for extra VMC Jastrow optimization calculations and results in significant computational cost savings (on average 1/4 savings of total computational time). Since it is a novel post-transition metal chalcogenide alloy series that has been synthesized in its few-layer form, we used monolayer GaSxSe1−x as a case study for our workflow. By extensively testing our Jastrow sharing procedure for monolayer GaSxSe1−x and quantifying the cost savings, we demonstrate how a pathway toward chemically accurate high-throughput simulations of alloys can be achieved using many-body VMC and DMC methods. [ABSTRACT FROM AUTHOR]

In a recent paper, Lucco Castello et al. (arXiv:2107.03537) provided an accurate parameterization of classical one-component plasma bridge functions that was embedded in a novel dielectric scheme for strongly coupled electron liquids. Here, this approach is rigorously formulated, its set of equations is formally derived, and its numerical algorithm is scrutinized. A systematic comparison with available and new path integral Monte Carlo simulations reveals a rather unprecedented agreement especially in terms of the interaction energy and the long wavelength limit of the static local field correction. [ABSTRACT FROM AUTHOR]

Results of Monte Carlo simulations of the electrode-molten salt interface are reported. The system was modeled by soft ions in contact with a soft wall using the Lennard-Jones potential restricted to the repulsion part. The soft wall was formed of C (graphite), Hg, and Pb atoms. Calculations were carried out for the parameter values which would permit making comparison with the real system. The paper presents information on physicochemical properties of the interfacial region, such as the ion singlet distribution functions, the mean electrostatic potential as a function of the distance from the electrode surface, and differential capacitance results as a function of the electrode charges. The differential capacitance curves have a flat and distorted bell shape which vary depending on the kind of the electrode material. The differential capacitance results are discussed and compared with the data obtained from ionic liquid simulations, density functional theory, and mean field calculations. [ABSTRACT FROM AUTHOR]

This paper reports the results of analysis of the electrical double layer (EDL) phenomenon in molten salts to provide information on the influence of short range interaction type on the shape of charge distribution and the effect of the charge distribution shape on capacitance values. A new method of analysis is proposed, which allows a quantitative discussion. It is assumed that EDL can be modelled as a number of capacitor plates connected in series. This paper reports the application of the proposed method in quantitative analysis of the molten salt capacitance data obtained for different short range potentials. The data to be analysed were obtained from the Monte Carlo simulations of the symmetrical molten salt electrolyte for the following short range interaction potentials: hard spheres, Lennard-Jones repulsions, and full Lennard-Jones. The new analysis method gives a more detailed understanding of EDL in molten salts and can become an inspiration for new researches in this field. [ABSTRACT FROM AUTHOR]

In order to better control the assembly of nanorods, knowledge of the pathways by which they form ordered structures is desirable. In this paper, we characterize crystal nucleation in suspensions of spherocylindrical rods with aspect ratio L/D = 2.3 in the presence of both small and large polymer depletants. Using a combination of Langevin dynamics and Monte Carlo simulations, together with biased sampling techniques, we show that the preferred pathway always involves the formation of monolayer assemblies irrespective of the volume fraction of the initial isotropic phase and the diameter of the depletants. This includes the previously neglected case of nucleation from the colloidal liquid phase and shows that the presence of depletion attraction can alter nucleation pathways even when the initial phase is dense. [ABSTRACT FROM AUTHOR]

In this paper, new Newton and Gauss–Newton methods for iterative coarse-graining based on integral equation theory are evaluated and extended. In these methods, the potential update is calculated from the current and target radial distribution function, similar to iterative Boltzmann inversion, but gives a potential update of quality comparable with inverse Monte Carlo. This works well for the coarse-graining of molecules to single beads, which we demonstrate for water. We also extend the methods to systems that include coarse-grained bonded interactions and examine their convergence behavior. Finally, using the Gauss–Newton method with constraints, we derive a model for single bead methanol in implicit water, which matches the osmotic pressure of the atomistic reference. An implementation of all new methods is provided for the open-source VOTCA package. [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations require barostats to be performed at a constant pressure. The usual recipe is to employ the Berendsen barostat first, which displays a first-order volume relaxation efficient in equilibration but results in incorrect volume fluctuations, followed by a second-order or a Monte Carlo barostat for production runs. In this paper, we introduce stochastic cell rescaling, a first-order barostat that samples the correct volume fluctuations by including a suitable noise term. The algorithm is shown to report volume fluctuations compatible with the isobaric ensemble and its anisotropic variant is tested on a membrane simulation. Stochastic cell rescaling can be straightforwardly implemented in the existing codes and can be used effectively in both equilibration and production phases. [ABSTRACT FROM AUTHOR]

In this second paper of a two part series, we present extensive benchmark results for two different inchworm Monte Carlo expansions for the spin-boson model. Our results are compared to previously developed numerically exact approaches for this problem. A detailed discussion of convergence and error propagation is presented. Our results and analysis allow for an understanding of the benefits and drawbacks of inchworm Monte Carlo compared to other approaches for exact real-time non-adiabatic quantum dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we provide a detailed description of the inchworm Monte Carlo formalism for the exact study of real-time non-adiabatic dynamics. This method optimally recycles Monte Carlo information from earlier times to greatly suppress the dynamical sign problem. Using the example of the spin- boson model, we formulate the inchworm expansion in two distinct ways: The first with respect to an expansion in the system-bath coupling and the second as an expansion in the diabatic coupling. The latter approach motivates the development of a cumulant version of the inchworm Monte Carlo method, which has the benefit of improved scaling. This paper deals completely with methodology, while Paper II provides a comprehensive comparison of the performance of the inchworm Monte Carlo algorithms to other exact methodologies as well as a discussion of the relative advantages and disadvantages of each. [ABSTRACT FROM AUTHOR]

The Gibbs ensemble molecular dynamics algorithm introduced in the preceding paper (paper I) [C. Bratschi and H. Huber, J. Chem. Phys. v126, 164104 (2007)] is applied to two recently published CO2 ab initio pair potentials, the Bock-Bich-Vogel and symmetry-adapted perturbation theory site-site potentials. The critical properties of these potentials are calculated for the first time. Critical values and points in the single and two-phase zones are compared with Monte Carlo results to demonstrate the accuracy of the molecular dynamics algorithm, and are compared with experiment to test the accuracy of the potentials. Pressure calculations in the liquid, gas, and supercritical states are carried out and are used to explain potential-related effects and systematic discrepancies. The best ab initio potential yields results in good agreement with experiment. [ABSTRACT FROM AUTHOR]

In this paper (paper I) and the following paper (paper II) [C. Bratschi, H. Huber, and D. J. Searles, J. Chem. Phys. 126, 164105 (2007)], a new molecular dynamics algorithm implementing the Gibbs ensemble will be presented and then on applied to the liquid-vapor coexistence curve for two ab initio CO2 potentials. In paper I, the Gibbs ensemble molecular dynamics algorithm using non-Hamiltonian molecular dynamics techniques is introduced. It is shown that states of the correct probability density function are sampled and the correct exchange probability is generated. The extended system Nosé-Hoover formalism is used to generate a constant temperature ensemble with equal pressures in the subsystems, combined with single particle transfers between the subsystems, over several time steps, to get equal chemical potentials. [ABSTRACT FROM AUTHOR]

The nonlinear viscoelastic behavior of the Fraenkel-chain model is studied with respect to the constitutive equation of the Rouse model. Distinctly different from the results of the Rouse model, the Fraenkel-chain model gives the following characteristic nonlinear behavior: (a) The two distinct dynamic modes in the relaxation modulus GS(t,λ)—as observed in the linear region reported in Paper I [Y.-H. Lin and A. K. Das, J. Chem. Phys. 126, 074902 (2007), preceding paper]—or in the first normal-stress difference function GΨ1(t,λ) are shown to have different strain dependences: strain hardening for the fast mode and strain softening for the slow mode. (b) The Lodge–Meissner relation GS(t,λ)=GΨ1(t,λ) holds over the whole time range, which has been shown both analytically and by simulation. (c) The second normal-stress difference is nonzero, being positive in the fast-mode region and negative in the slow-mode region. The comparisons between orientation and stress for all tensor components consistently confirm the strong correlation of the slow mode as well as its entropic nature with the segmental-orientation anisotropy as shown in the linear region studied in Paper I. A consequence of this correlation is the applicability of the stress-optical rule in the slow-mode region. This also leads to the expectation that the damping function h(λ)=GS(t,λ)/GS(t,λ→0) and the ratio between the first and second normal-stress differences, N2(t,λ)/N1(t,λ), are described by the orientation tensor which has the same form as that given by Doi and Edwards [J. Chem. Soc. Faraday Trans. 2 74, 1789 (1978); 74, 1802 (1978)] with independent-alignment approximation for an entangled system. The similarity between the slow mode of an entanglement-free Fraenkel-chain system and the terminal mode of an entangled polymer system as observed in the comparison of theory, simulation, and experiment suggests that the close correlation of the entropic nature of the mode with the orientation anisotropy—as of the Fraenkel segment or the primitive step in the Doi–Edwards theory—is a generally valid physical concept in polymer viscoelasticity. [ABSTRACT FROM AUTHOR]

In the preceding paper [A. E. Ismail, G. C. Rutledge, and G. Stephanopoulos J. Chem. Phys. (in press)] we introduced wavelet-accelerated Monte Carlo (WAMC), a coarse-graining methodology based on the wavelet transform, as a method for sampling polymer chains. In the present paper, we extend our analysis to consider excluded-volume effects by studying self-avoiding chains. We provide evidence that the coarse-grained potentials developed using the WAMC method obey phenomenological scaling laws, and use simple physical arguments for freely jointed chains to motivate these laws. We show that coarse-grained self-avoiding random walks can reproduce results obtained from simulations of the original, more-detailed chains to a high degree of accuracy, in orders of magnitude less time. [ABSTRACT FROM AUTHOR]

In Paper I of this series the formulations of the replica-exchange multicanonical algorithm and the multicanonical replica-exchange method for Monte Carlo versions have been presented. The effectiveness of these algorithms were then tested with the system of a penta peptide, Met-enkephalin, in the gas phase. In this article the detailed comparisons of performances of these algorithms together with the regular replica-exchange method are made, taking a more complex system of a 17-residue helical peptide. It is shown that these two new algorithms are more efficient than the regular replica-exchange method. [ABSTRACT FROM AUTHOR]

In this paper, we extend our analysis of lattice systems using the wavelet transform to systems for which exact enumeration is impractical. For such systems, we illustrate a wavelet-accelerated Monte Carlo (WAMC) algorithm, which hierarchically coarse-grains a lattice model by computing the probability distribution for successively larger block spins. We demonstrate that although the method perturbs the system by changing its Hamiltonian and by allowing block spins to take on values not permitted for individual spins, the results obtained agree with the analytical results in the preceding paper, and "converge" to exact results obtained in the absence of coarse-graining. Additionally, we show that the decorrelation time for the WAMC is no worse than that of Metropolis Monte Carlo (MMC), and that scaling laws can be constructed from data performed in several short simulations to estimate the results that would be obtained from the original simulation. Although the algorithm is not asymptotically faster than traditional MMC, the new algorithm executes several orders of magnitude faster than a full simulation of the original problem because of its hierarchical design. Consequently, the new method allows for rapid analysis of a phase diagram, allowing computational time to be focused on regions near phase transitions. [ABSTRACT FROM AUTHOR]

Global optimization is an active area of research in atomistic simulations, and many algorithms have been proposed to date. A prominent example is basin hopping Monte Carlo, which performs a modified Metropolis Monte Carlo search to explore the potential energy surface of the system of interest. These simulations can be very demanding due to the high-dimensional configurational search space. The effective search space can be reduced by utilizing grids for the atomic positions, but at the cost of possibly biasing the results if fixed grids are employed. In this paper, we present a flexible grid algorithm for global optimization that allows us to exploit the efficiency of grids without biasing the simulation outcome. The method is general and applicable to very heterogeneous systems, such as interfaces between two materials of different crystal structures or large clusters supported at surfaces. As a benchmark case, we demonstrate its performance for the well-known global optimization problem of Lennard-Jones clusters containing up to 100 particles. Despite the simplicity of this model potential, Lennard-Jones clusters represent a challenging test case since the global minima for some "magic" numbers of particles exhibit geometries that are very different from those of clusters with only a slightly different size. [ABSTRACT FROM AUTHOR]

Solute–solvent reduced density profiles of hard-sphere fluids were calculated by using several integral equation theories for liquids. The traditional closures, Percus–Yevick (PY) and the hypernetted-chain (HNC) closures, as well as the theories with bridge functions, Verlet, Duh–Henderson, and Kinoshita (named MHNC), were used for the calculation. In this paper, a one-solute hard-sphere was immersed in a one-component hard-sphere solvent and various size ratios were examined. The profiles between the solute and solvent particles were compared with those calculated by Monte Carlo simulations. The profiles given by the integral equations with the bridge functions were much more accurate than those calculated by conventional integral equation theories, such as the Ornstein–Zernike (OZ) equation with the PY closure. The accuracy of the MHNC–OZ theory was maintained even when the particle size ratio of solute to solvent was 50. For example, the contact values were 5.7 (Monte Carlo), 5.6 (MHNC), 7.8 (HNC), and 4.5 (PY), and the first minimum values were 0.48 (Monte Carlo), 0.46 (MHNC), 0.54 (HNC), and 0.40 (PY) when the packing fraction of the hard-sphere solvent was 0.38 and the size ratio was 50. The asymptotic decay and the oscillation period for MHNC–OZ were also very accurate, although those given by the HNC–OZ theory were somewhat faster than those obtained by Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

The problem of DNA-DNA interaction mediated by divalent counterions is studied using a generalized grand-canonical Monte-Carlo simulation for a system of two salts. The effect of the divalent counterion size on the condensation behavior of the DNA bundle is investigated. Experimentally, it is known that multivalent counterions have strong effect on the DNA condensation phenomenon. While tri- and tetra-valent counterions are shown to easily condense free DNA molecules in solution into toroidal bundles, the situation with divalent counterions is not as clear cut. Some divalent counterions like Mg+2 are not able to condense free DNA molecules in solution, while some like Mn+2 can condense them into disorder bundles. In restricted environment such as in two dimensional system or inside viral capsid, Mg+2 can have strong effect and able to condense them, but the condensation varies qualitatively with different system, different coions. It has been suggested that divalent counterions can induce attraction between DNA molecules but the strength of the attraction is not strong enough to condense free DNA in solution. However, if the configuration entropy of DNA is restricted, these attractions are enough to cause appreciable effects. The variations among different divalent salts might be due to the hydration effect of the divalent counterions. In this paper, we try to understand this variation using a very simple parameter, the size of the divalent counterions. We investigate how divalent counterions with different sizes can lead to varying qualitative behavior of DNA condensation in restricted environments. Additionally, a grand canonical Monte-Carlo method for simulation of systems with two different salts is presented in detail. [ABSTRACT FROM AUTHOR]

In this paper, a new theory is developed for the self-assembly of associating molecules confined to a single spatial dimension, but allowed to explore all orientation angles. The interplay of the anisotropy of the pair potential and the low dimensional space results in orientationally ordered associated clusters. This local order enhances association due to a decrease in orientational entropy. Unlike bulk 3D fluids which are orientationally homogeneous, association in 1D necessitates the self-consistent calculation of the orientational distribution function. To test the new theory, Monte Carlo simulations are performed and the theory is found to be accurate. It is also shown that the traditional treatment in first order perturbation theory fails to accurately describe this system. The theory developed in this paper may be used as a tool to study hydrogen bonding of molecules in 1D zeolites as well as the hydrogen bonding of molecules in carbon nanotubes. [ABSTRACT FROM AUTHOR]

We report on the properties of the physically consistent cluster used in a theory of homogeneous vapor-phase nucleation and defined by Ellerby, Weakliem, and Reiss (paper I of this series) and by Ellerby and Reiss (paper II of this series). Specifically, the free energy of formation of argon clusters and their radial density distributions are obtained from Monte Carlo simulations. Additionally a modified liquid drop theory is presented, and the results from this macroscopic theory are compared to the simulation results. Finally, we outline the development of a rate theory which utilizes the modified liquid drop theory. [ABSTRACT FROM AUTHOR]

We report on tests of the shifted potential (SP), gradient shifted force (GSF), and Taylor shifted force (TSF) real-space methods for multipole interactions developed in Paper I of this series, using the multipolar Ewald sum as a reference method. The tests were carried out in a variety of condensed-phase environments designed to test up to quadrupole-quadrupole interactions. Comparisons of the energy differences between configurations, molecular forces, and torques were used to analyze how well the real-space models perform relative to the more computationally expensive Ewald treatment. We have also investigated the energy conservation, structural, and dynamical properties of the new methods in molecular dynamics simulations. The SP method shows excellent agreement with configurational energy differences, forces, and torques, and would be suitable for use in Monte Carlo calculations. Of the two new shifted-force methods, the GSF approach shows the best agreement with Ewald-derived energies, forces, and torques and also exhibits energy conservation properties that make it an excellent choice for efficient computation of electrostatic interactions in molecular dynamics simulations. Both SP and GSF are able to reproduce structural and dynamical properties in the liquid models with excellent fidelity. [ABSTRACT FROM AUTHOR]

The thermodynamics of iron clusters of various sizes, from 76 to 2452 atoms, typical of the catalyst particles used for carbon nanotubes growth, has been explored by a flat histogram Monte Carlo (MC) algorithm (called the a -mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, gp(Ep) in the configurational space, in terms of the potential energy of the system, with good and well controlled convergence properties, particularly in the melting phase transition zone which is of interest in this work. To describe the system, an iron potential has been implemented, called "corrected EAM" (cEAM), which approximates the MEAM potential of Lee et al. [Phys. Rev. B 64, 184102 (2001)] with an accuracy better than 3 meV/at, and a five times larger computational speed. The main simplification concerns the angular dependence of the potential, with a small impact on accuracy, while the screening coefficients Sij are exactly computed with a fast algorithm. With this potential, ergodic explorations of the clusters can be performed efficiently in a reasonable computing time, at least in the upper half of the solid zone and above. Problems of ergodicity exist in the lower half of the solid zone but routes to overcome them are discussed. The solid-liquid (melting) phase transition temperature Tm is plotted in terms of -- 1/3 the cluster atom number Nat. The standard Nat -1/3 <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I. [ABSTRACT FROM AUTHOR]at <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I. [ABSTRACT FROM AUTHOR]

In this paper, equilibrium properties of structure II hydrates of hydrogen were determined from Monte Carlo simulations in the isothermal-isobaric Gibbs ensemble. Water and hydrogen molecules are described by the TIP4P/Ice and Silvera-Goldman models, respectively. The use of the Gibbs ensemble has many key advantages for the simulation of hydrates. By the separation of hydrogen vapor and hydrate phases into their own domains, coupled with transfer moves of hydrogen molecules between domains, cage occupancies were determined. Furthermore, the choice of this ensemble also allows equilibrium lattice constants and guest molecule chemical potentials to be straightforwardly estimated. Results for hydrogen mass fractions indicate reasonable agreement with prior simulation data and theoretical models, while detailed analysis of cage occupancy distributions and neighboring cage pair occupancy combinations gives valuable insight into the behavior of this hydrate at the inter-cage scale. These results will aid in the construction of theoretical models, for which knowledge of the occupancy of neighboring cages is of great importance. In support of previous experimental and theoretical works, we also find evidence of double occupancy of a few small cages inside of the hydrate stability zone, albeit at very high pressures; approximately 0.1% of small cages are doubly occupied at 300 MPa, for temperatures of 225 K and 250 K. [ABSTRACT FROM AUTHOR]

Consider the standard stochastic reaction network model where the dynamics is given by a continuous-time Markov chain over a discrete lattice. For such models, estimation of parameter sensitivities is an important problem, but the existing computational approaches to solve this problem usually require time-consuming Monte Carlo simulations of the reaction dynamics. Therefore, these simulation-based approaches can only be expected to work over finite time-intervals, while it is often of interest in applications to examine the sensitivity values at the steady-state after the Markov chain has relaxed to its stationary distribution. The aim of this paper is to present a computational method for the estimation of steady-state parameter sensitivities, which instead of using simulations relies on the recently developed stationary finite state projection algorithm [Gupta et al., J. Chem. Phys. 147, 154101 (2017)] that provides an accurate estimate of the stationary distribution at a fixed set of parameters. We show that sensitivity values at these parameters can be estimated from the solution of a Poisson equation associated with the infinitesimal generator of the Markov chain. We develop an approach to numerically solve the Poisson equation, and this yields an efficient estimator for steady-state parameter sensitivities. We illustrate this method using several examples. [ABSTRACT FROM AUTHOR]

We propose to couple a state-resolved rovibrational coarse-grain model to a stochastic particle method for simulating internal energy excitation and dissociation of a molecular gas. A coarse-grained model for a rovibrational reaction mechanism of an ab initio database developed at the NASA Ames Research Center for the N2–N system is modified based on variably spaced energy bins. The thermodynamic properties of the modified coarse-grained model allow us to closely match those obtained with the full set of rovibrational levels over a wide temperature range, while using a number of bins significantly smaller than the complete mechanism. The chemical-kinetic behavior of equally and variably spaced bin formulations is compared by simulating internal energy excitation and dissociation of nitrogen in an adiabatic, isochoric reactor. We find that the variably spaced formulation is better suited for reproducing the dynamics of the full database at conditions of interest in the Earth atmospheric entry. Also in this paper, we discuss the details of our particle method implementation for the uniform rovibrational collisional bin model and describe changes to the Direct Simulation Monte Carlo (DSMC) collision algorithm, which become necessary to accommodate our state-resolved reaction mechanism for excitation and dissociation reactions. The DSMC code is then verified against equivalent master equation calculations. In these simulations, state-resolved cross sections are used in analytical form. These cross sections verify micro-reversibility relations for the rovibrational bins and allow for fast execution of the DSMC code. In our verification calculations, we obtain very close agreement for the concentrations profiles of N and N2, as well as the translational and rovibrational mode temperatures obtained independently through both methods. In addition to macroscopic moments, we compare discrete internal energy populations predicted at selected time steps via DSMC and the master equations. We observe good agreement between the two sets of results within the limits imposed by statistical scatter, which is inherent to particle-based DSMC solutions. As future work, the rovibrational coarse-grain model coupled to the particle method will allow us to study 3D reentry flow configurations. [ABSTRACT FROM AUTHOR]

In this paper, we present a Monte Carlo simulation study on the structure of the electrical double layer around a spherical colloid surrounded by a binary electrolyte composed of spherical and non-spherical ions. Results are provided for the radial distribution functions between the colloid and ions, the orientation correlations between the colloid and non-spherical particles, and the integrated charge. Work is reported mainly for non-spherical particles modeled as spherocylinders, although a particular comparison is made between spherocylindrical particles and dimers. For the conditions investigated here, spherocylinders and dimers produce essentially the same structural information. Additionally, it is shown that spherocylinders mostly orient tangentially to the colloid at its surface; this preferred orientation disappears for larger distances. We also evidence that, near the colloid, the integrated charge attenuates monotonically when the macroparticle is highly charged, whereas for intermediate and low charged states of the colloid, the integrated charge can display charge reversal, overcharging, or both, with magnitudes that are sensitive to the salt concentration and to the localization of charge inside the spherocylinders. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) simulations give access to equilibrium structures and dynamic properties given an ergodic sampling and an accurate force-field. The force-field parameters are calibrated to reproduce properties measured by experiments or simulations. The main contribution of this paper is an approximate Bayesian framework for the calibration and uncertainty quantification of the force-field parameters, without assuming parameter uncertainty to be Gaussian. To this aim, since the likelihood function of the MD simulation models is intractable in the absence of Gaussianity assumption, we use a likelihood-free inference scheme known as approximate Bayesian computation (ABC) and propose an adaptive population Monte Carlo ABC algorithm, which is illustrated to converge faster and scales better than the previously used ABCsubsim algorithm for the calibration of the force-field of a helium system. The second contribution is the adaptation of ABC algorithms for High Performance Computing to MD simulations within the Python ecosystem ABCpy. This adaptation includes a novel use of a dynamic allocation scheme for Message Passing Interface (MPI). We illustrate the performance of the developed methodology to learn posterior distribution and Bayesian estimates of Lennard-Jones force-field parameters of helium and the TIP4P system of water implemented for both simulated and experimental datasets collected using neutron and X-ray diffraction. For simulated data, the Bayesian estimate is in close agreement with the true parameter value used to generate the dataset. For experimental as well as for simulated data, the Bayesian posterior distribution shows a strong correlation pattern between the force-field parameters. Providing an estimate of the entire posterior distribution, our methodology also allows us to perform the uncertainty quantification of model prediction. This research opens up the possibility to rigorously calibrate force-fields from available experimental datasets of any structural and dynamic property. [ABSTRACT FROM AUTHOR]

In the present paper, a generalized hybrid Monte Carlo method to generate the multicanonical ensemble has been developed, which is a generalization of the multicanonical hybrid Monte Carlo (HMC) method by Hansmann and co-workers [Chem. Phys. Lett. 259, 321 (1996)]. The generalized hybrid Monte Carlo (GHMC) method is an equations-of-motion guided Monte Carlo combined with partial momentum refreshment. We successfully applied our multicanonical GHMC to dense Lennard-Jones fluids and a coarse grained protein model. It is found that good computational efficiency can be gained in the case of the acceptance ratio around 60% for the models examined. While a large number of molecular dynamics (MD) steps in a single GHMC cycle is needed to yield good computational efficiency at a large mixing ratio of momenta with thermal noise vectors, corresponding to the original multicanonical HMC method, a small number of MD steps are enough to achieve good efficiency at a small mixing ratio. This property is useful to develop a composite algorithm combining the present GHMC method with other Monte Carlo moves. [ABSTRACT FROM AUTHOR]

In this paper we develop a thermodynamic perturbation theory for two site associating fluids which exhibit bond cooperativity (system energy is non-pairwise additive). We include both steric hindrance and ring formation such that the equation of state is bond angle dependent. Here, the bond angle is the angle separating the centers of the two association sites. As a test, new Monte Carlo simulations are performed, and the theory is found to accurately predict the internal energy as well as the distribution of associated clusters as a function of bond angle. [ABSTRACT FROM AUTHOR]

This paper deals with molecular simulation of the chemical potentials in aqueous electrolyte solutions for the water solvent and its relationship to chemical potential simulation results for the electrolyte solute. We use the Gibbs-Duhem equation linking the concentration dependence of these quantities to test the thermodynamic consistency of separate calculations of each quantity. We consider aqueous NaCl solutions at ambient conditions, using the standard SPC/E force field for water and the Joung-Cheatham force field for the electrolyte. We calculate the water chemical potential using the osmotic ensemble Monte Carlo algorithm by varying the number of water molecules at a constant amount of solute. We demonstrate numerical consistency of these results in terms of the Gibbs-Duhem equation in conjunction with our previous calculations of the electrolyte chemical potential. We present the chemical potential vs molality curves for both solvent and solute in the form of appropriately chosen analytical equations fitted to the simulation data. As a byproduct, in the context of the force fields considered, we also obtain values for the Henry convention standard molar chemical potential for aqueous NaCl using molality as the concentration variable and for the chemical potential of pure SPC/E water. These values are in reasonable agreement with the experimental values. [ABSTRACT FROM AUTHOR]

At physiological conditions, myriads of biomolecules (e.g., amino acids, peptides, and proteins) exist predominantly in the zwitterionic structural form and their biological functions will result in these conditions. However these geometrical structures are inaccessible energetically in the gas phase, and at this point, stabilization of amino-acids in physiological conditions is still under debate. In this paper, the electronic properties of a glycine molecule in the liquid environment were studied by performing a relaxation of the glycine geometry in liquid water using the free energy gradient method combined with a sequential quantum mechanics/molecular mechanics approach. A series of Monte Carlo Metropolis simulations of the glycine molecule embedded in liquid water, followed by only a quantum mechanical calculation in each of them were carried out. Both the local and global liquid environments were emphasized to obtain nuclear magnetic resonance (NMR) parameters for the glycine molecule in liquidwater. The results of the equilibrium structure in solution and the systematic study of the hydrogen bonds were used to discard the direct proton transfer from the carboxyl group to the ammonium group of the glycine molecule in water solution. The calculations of the Density Functional Theory (DFT) were performed to study the polarization of the solvent in the parameters of nuclear magnetic resonance of the glycine molecule in liquid water. DFT calculations predicted isotropic chemical changes on the H, C, N, andOatoms of glycine in liquidwater solution which agree with the available experimental data. [ABSTRACT FROM AUTHOR]

In this paper we investigate the solubility of a hard-sphere gas in a solvent modeled as an associating lattice gas. The solution phase diagram for solute at 5% is compared with the phase diagram of the original solute free model. Model properties are investigated both through Monte Carlo simulations and a cluster approximation. The model solubility is computed via simulations and is shown to exhibit a minimum as a function of temperature. The line of minimum solubility (TmS) coincides with the line of maximum density (TMD) for different solvent chemical potentials, in accordance with the literature on continuous realistic models and on the 'cavity' picture. [ABSTRACT FROM AUTHOR]

Precise knowledge of the static density response function (SDRF) of the uniform electron gas serves as key input for numerous applications, most importantly for density functional theory beyond generalized gradient approximations. Here we extend the configuration path integral Monte Carlo (CPIMC) formalism that was previously applied to the spatially uniform electron gas to the case of an inhomogeneous electron gas by adding a spatially periodic external potential. This procedure has recently been successfully used in permutation blocking path integral Monte Carlo simulations (PB-PIMC) of the warm dense electron gas [T. Dornheim et al., Phys. Rev. E 96, 023203 (2017)], but this method is restricted to low and moderate densities. Implementing this procedure into CPIMC allows us to obtain highly accurate finite temperature results for the SDRF of the electron gas at high to moderate densities closing the gap left open by the PB-PIMC data. In this paper, we demonstrate how the CPIMC formalism can be efficiently extended to the spatially inhomogeneous electron gas and present the first data points. Finally, we discuss finite size errors involved in the quantum Monte Carlo results for the SDRF in detail and present a solution how to remove them that is based on a generalization of ground state techniques. [ABSTRACT FROM AUTHOR]

We present a short overview of pressure calculation in molecular dynamics or Monte Carlo simulations. The emphasis is given to polarizable models in order to resolve the controversy caused by the paper of M. J. Louwerse and E. J. Baerends [Chem. Phys. Lett. 421, 138 (2006)] about pressure calculation in systems with periodic boundaries. We systematically derive expressions for the pressure and show that despite the lack of explicit pairwise additivity, the pressure formula for polarizable models is identical with that of nonpolarizable ones. However, a strict condition for using this formula is that the induced dipole should be in perfect mechanical equilibrium prior to pressure calculation. The perfect convergence of induced dipoles ensures conservation of energy as well. We demonstrate using more cumbersome but exact methods that the derived expressions for the polarizable model of water provide correct numerical results. We also show that the inaccuracy caused by imperfect convergence of the induced dipoles correlates with the inaccuracy of the calculated pressure. [ABSTRACT FROM AUTHOR]

We investigate the vibrational shift of beryllium oxide (BeO) in Xe matrix as well as in Ar matrix environments by mixed quantum-classical simulation and examine the origin of spectral shift in details. BeO is known to form strong chemical complex with single rare gas atom, and it is predicted from the gas phase calculations that vibrational frequencies are blueshifted by 78 cm-1 and 80 cm-1 upon formation of XeBeO and ArBeO, respectively. When the effects of other surrounding rare gas atoms are included by Monte Carlo simulations, it is found that the vibrational frequencies are redshifted by 21 cm-1 and 8 cm-1 from the isolated XeBeO and ArBeO complexes, respectively. The vibrational shift of XeBeO in Ar matrix is also calculated and compared with experimental data. In all simulations examined in this paper, the calculated vibrational frequency shifts from the isolated BeO molecule are in reasonable agreement with experimental values. The spectral shift due to the rare-gas-complex formation of RgBeO (Rg = Xe or Ar) is not negligible as seen in the previous studies, but it is shown in this paper that the effects of other surrounding rare gas atoms should be carefully taken into account for quantitative description of the spectral shifts and that these two effects are competing in vibrational spectroscopy of BeO in matrix environments. [ABSTRACT FROM AUTHOR]