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Among lattice configurations of densely packed hard ellipses, Monte Carlo simulations are used to identify the so-called parallel and diagonal lattices as the two favorable states. The free energies of these two states are computed for several system sizes employing the Einstein crystal method. An accurate calculation of the free energy difference between the two states reveals the parallel lattice as the state with the lowest free energy. The origin of the entropic difference between the two states is further elucidated by assessing the roles of the translational and rotational degrees of freedom. [ABSTRACT FROM AUTHOR]

Refractory high-entropy alloys are under consideration for applications where materials are subjected to high temperatures and levels of radiation, such as in the fusion power sector. However, at present, their scope is limited because they are highly brittle at room temperature. One suggested route to mitigate this issue is by alloying with Ti. In this theoretical study, using a computationally efficient linear-response theory based on density functional theory calculations of the electronic structure of the disordered alloys, we study the nature of atomic short-range order in these multi-component materials, as well as assessing their overall phase stability. Our analysis enables direct inference of phase transitions in addition to the extraction of an atomistic, pairwise model of the internal energy of an alloy suitable for study via, e.g., Monte Carlo simulations. Once Ti is added into either the NbMoTaW or VNbMoTaW system, we find that there is competition between chemical phase ordering and segregation. These results shed light on observed chemical inhomogeneity in experimental samples, as well as providing fundamental insight into the physics of these complex systems. [ABSTRACT FROM AUTHOR]

Vapor–liquid equilibria and thermodynamic properties of saturated argon and krypton were calculated by semi-classical Monte Carlo simulations with the NpT + test particle method using ab initio potentials for the two-body and nonadditive three-body interactions. The NpT + test particle method was extended to the calculation of second-order thermodynamic properties, such as the isochoric and isobaric heat capacities or the speed of sound, of the saturated liquid and vapor by using our recently developed approach for the systematic calculation of arbitrary thermodynamic properties in the isothermal–isobaric ensemble. Generally, the results for all simulated properties agree well with experimental data and the current reference equations of state for argon and krypton. In particular, the results for the vapor pressure and for the density and speed of sound of the saturated liquid and vapor agree with the most accurate experimental data for both noble gases almost within the uncertainty of these data, a level of agreement unprecedented for many-particle simulations. This study demonstrates that the vapor–liquid equilibrium and thermodynamic properties at saturation of a pure fluid can be predicted by Monte Carlo simulations with high accuracy when the intermolecular interactions are described by state-of-the-art ab initio pair and nonadditive three-body potentials and quantum effects are accounted for. [ABSTRACT FROM AUTHOR]

Functional thin films of nanoscale metal pillars in oxide or nitride matrices known as vertically aligned nanocomposite (VAN) have gained much interest owing to their unique strain-coupled and highly anisotropic properties. So far, the deposition of these films has been explored mostly experimentally. In this work, a density functional theory (DFT)-based kinetic Monte Carlo simulation model using Bortz–Kalos–Lebowitz algorithm was developed to understand the growth of VAN films deposited by pulsed laser technique on mismatching substrates. The model has been parameterized and applied to understand the kinetics of growth thin films consisting of Au pillars in CeO2 matrix deposited on SrTiO3 substrates. The effects of pulsed laser deposition (PLD) conditions including the pulse frequency, deposition flux, and substrate temperature were explored. The simulations indicate that the Au pillar size and shape exhibit significant dependence on the PLD conditions. Namely, increasing the temperature increases the average pillar size and lowers the pillar density, and vice versa. In addition, the simulations revealed that increasing the deposition rate results in lowering the average pillar size and increasing the density. Particularly, the DFT results suggest that Au pillar size can be tuned during the initial growth of the first monolayer due to the significantly low activation barrier. Our analysis showed that the relationship between the average pillar size and pillar density is influenced by the kinetics. Furthermore, autocorrelation analysis showed that pillars self-organize in quasi-ordered patterns at certain windows of the deposition conditions, which is attributed to the complex nature of the chemical interactions in the system, the kinetics, and the deposition parameters. [ABSTRACT FROM AUTHOR]

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

Upon impact, the free surface of a solid metal may eject a cloud of fast and fine particles. Photon Doppler Velocimetry (PDV) is one of the optical diagnostics used to characterize these ejecta. Although the technique provides a direct way to estimate the particle velocities in the single scattering regime, it has been shown that multiple scattering cannot be neglected in real ejecta. Here, we derive a model for PDV measurements starting from the first principles of wave scattering. We establish rigorously the relationship between the specific intensity and the measured signal, as well as the Radiative Transport Equation (RTE) that describes the evolution of the specific intensity upon scattering and absorption in dynamic ejecta, including the effects of inelastic scattering and inhomogeneities in the optical properties. We also establish rigorously the connection between the Monte Carlo scheme used for numerical simulations and the solution to the RTE. Using numerical simulations, we demonstrate the crucial contribution of multiple scattering to PDV spectrograms as well as the effect of statistical inhomogeneities in particle size distribution. These results could substantially impact the analysis of ejecta by PDV. [ABSTRACT FROM AUTHOR]

We present a computational framework for reliably determining the frequency-dependent intermolecular and intramolecular nuclear magnetic resonance (NMR) dipole–dipole relaxation rates of spin 1/2 nuclei from Molecular Dynamics (MD) simulations. This approach avoids the alterations caused by the well-known finite-size effects of translational diffusion. Moreover, a procedure is derived to control and correct for effects caused by fixed distance-sampling cutoffs and periodic boundary conditions. By construction, this approach is capable of accurately predicting the correct low-frequency scaling behavior of the intermolecular NMR dipole–dipole relaxation rate and thus allows for the reliable calculation of the frequency-dependent relaxation rate over many orders of magnitude. Our approach is based on the utilization of the theory of Hwang and Freed for the intermolecular dipole–dipole correlation function and its corresponding spectral density [L.-P. Hwang and J. H. Freed, J. Chem. Phys. 63, 4017–4025 (1975)] and its combination with data from MD simulations. The deviations from the Hwang and Freed theory caused by periodic boundary conditions and sampling distance cutoffs are quantified by means of random walker Monte Carlo simulations. An expression based on the Hwang and Freed theory is also suggested for correcting those effects. As a proof of principle, our approach is demonstrated by computing the frequency-dependent intermolecular and intramolecular dipolar NMR relaxation rates of 1H nuclei in liquid water at 273 and 298 K based on the simulations of the TIP4P/2005 model. Our calculations are suggesting that the intermolecular contribution to the 1H NMR relaxation rate of the TIP4P/2005 model in the extreme narrowing limit has previously been substantially underestimated. [ABSTRACT FROM AUTHOR]

This work presents a 3D quantum mechanics based model to address the physics at band structure crossing/anti-crossing points in full band Monte Carlo (FBMC) simulations. The model solves the Krieger and Iafrate (KI) equations in real time using pre-computed coefficients at k -points spatially sampled within the first Brillouin zone. Solving the KI equations in real time makes this model applicable for all electric fields, which enables its use in FBMC device simulations. In this work, a two-level refinement scheme is used to aggressively sample regions in proximity to band crossings for accurate solutions to the KI equations and coarsely sample everywhere else to limit the number of k -points used. The presented sampling method is demonstrated on the band structure of silicon but is effective for the band structure of any semiconductor material. Next, the adaptation of the fully quantum KI model into the semi-classical FBMC method is discussed. Finally, FBMC simulations of hole transport in 4H silicon carbide with and without the KI model are performed. Results along different crystallographic directions for a wide range of electric fields are compared to previously published simulation and experimental values. [ABSTRACT FROM AUTHOR]

Determining fluid pressure in Monte Carlo simulations can be a challenging task due to the reduced arsenal of computational tools available to perform such measurements. In addition, none of these tools is general enough to calculate the equilibrium pressure for a wide variety of models. The Gibbs–Duhem method, for example, is a very useful option, but only for pure (one component) systems. To enrich this arsenal, we propose here a direct method to calculate pressure in the canonical ensemble, which could easily be extended to mixtures at low densities. In analogy with the Widom method, our approach is based on the free energy variation with volume, described in terms of the removal of an empty or particle-occupied lattice column. We tested our approach for the lattice gas model and compared the results with exact Onsager solutions. Furthermore, the appearance of thermodynamic instabilities (loops) in the pressure isotherms during the phase transition and their relationship with interface effects are discussed. Finally, a phase diagram is obtained from these isotherms using the Hill construction. [ABSTRACT FROM AUTHOR]

Simulations of soft materials often adopt low-resolution coarse-grained (CG) models. However, the CG representation is not unique and its impact upon simulated properties is poorly understood. In this work, we investigate the space of CG representations for ubiquitin, which is a typical globular protein with 72 amino acids. We employ Monte Carlo methods to ergodically sample this space and to characterize its landscape. By adopting the Gaussian network model as an analytically tractable atomistic model for equilibrium fluctuations, we exactly assess the intrinsic quality of each CG representation without introducing any approximations in sampling configurations or in modeling interactions. We focus on two metrics, the spectral quality and the information content, that quantify the extent to which the CG representation preserves low-frequency, large-amplitude motions and configurational information, respectively. The spectral quality and information content are weakly correlated among high-resolution representations but become strongly anticorrelated among low-resolution representations. Representations with maximal spectral quality appear consistent with physical intuition, while low-resolution representations with maximal information content do not. Interestingly, quenching studies indicate that the energy landscape of mapping space is very smooth and highly connected. Moreover, our study suggests a critical resolution below which a "phase transition" qualitatively distinguishes good and bad representations. [ABSTRACT FROM AUTHOR]

Proton exchange reactions are of key importance in many processes in water. However, it is nontrivial to achieve reliable barrier heights for multiple proton exchanges and complexation energies in hydrogen-bonded systems theoretically. Performance of the fixed-node diffusion quantum Monte Carlo (FN-DMC) with the single-Slater–Jastrow trial wavefunction on total energies, barrier heights of multiple proton exchanges, and complexation energies of small water, ammonia, and hydrogen fluoride clusters is investigated in this study. Effects of basis sets and those of locality approximation (LA), T-move approximation (T-move), and determinant localization approximation (DLA) schemes in dealing with the nonlocal part of pseudopotentials on FN-DMC results are evaluated. According to our results, diffuse basis functions are important in achieving reliable barrier heights and complexation energies with FN-DMC, although the cardinal number of the basis set is more important than diffuse basis functions on total energies of these systems. Our results also show that the time step bias with DLA and LA is smaller than T-move; however, the time step bias of DMC energies with respect to time steps using the T-move is roughly linear up to 0.06 a.u., while this is not the case with LA and DLA. Barrier heights and complexation energies with FN-DMC using these three schemes are always within chemical accuracy. Taking into account the fact that T-move and DLA are typically more stable than LA, FN-DMC calculations with the T-move or DLA scheme and basis sets containing diffuse basis functions are suggested for barrier heights of multiple proton exchanges and complexation energies of hydrogen-bonded clusters. [ABSTRACT FROM AUTHOR]

An extension of a first-principle combined Monte Carlo method is proposed in this work to obtain the secondary electron emission characteristics of anisotropic crystal Al2O3. Unlike isotropic crystal Cu, density functional theory calculations reveal that the q-dependent energy loss function of Al2O3 in all directions is different. Therefore, an interpolation algorithm is introduced in the Monte Carlo method to determine the loss of energy and inelastic mean free path of electrons. The simulation results are in good agreement with experimental data. This method can be further used to simulate the secondary emission yield of other anisotropic crystal materials. [ABSTRACT FROM AUTHOR]

Within aerosol-rich environments, efficient simulation of frequency-modulated continuous wave (FMCW) laser detector echo characteristics is crucial. Conventional methods often need more efficiency. To address this, we propose a photon matrix-based approach for simulating intricate photon scattering processes, enhancing simulation accuracy. This study focuses on short-range FMCW laser detection under aerosol interference, assessing performance via signal-to-noise ratio (SNR). We analyze the impact of amplitude modulation coefficient and photon count on SNR. Surprisingly, the photon count minimally affects SNR, while the amplitude modulation coefficient significantly influences it. These findings shed light on optimizing FMCW laser detection in aerosol-laden environments. Attention to the amplitude modulation coefficient can notably enhance SNR and overall detection efficiency. [ABSTRACT FROM AUTHOR]

Absolute measurements of solid-material compressibility by magnetically driven shockless dynamic compression experiments to multi-megabar pressures have the potential to greatly improve the accuracy and precision of pressure calibration standards for use in diamond anvil cell experiments. To this end, we apply characteristics-based inverse Lagrangian analysis (ILA) to 11 sets of ramp-compression data on pure platinum (Pt) metal and then reduce the resulting weighted-mean stress–strain curve to the principal isentrope and room-temperature isotherm using simple models for yield stress and Grüneisen parameter. We introduce several improvements to methods for ILA and quasi-isentrope reduction, the latter including calculation of corrections in wave speed instead of stress and pressure to render results largely independent of initial yield stress while enforcing thermodynamic consistency near zero pressure. More importantly, we quantify in detail the propagation of experimental uncertainty through ILA and model uncertainty through quasi-isentrope reduction, considering all potential sources of error except the electrode and window material models used in ILA. Compared to previous approaches, we find larger uncertainty in longitudinal stress. Monte Carlo analysis demonstrates that uncertainty in the yield-stress model constitutes by far the largest contribution to uncertainty in quasi-isentrope reduction corrections. We present a new room-temperature isotherm for Pt up to 444 GPa, with 1-sigma uncertainty at that pressure of just under ± 1.2 % ; the latter is about a factor of three smaller than uncertainty previously reported for multi-megabar ramp-compression experiments on Pt. The result is well represented by a Vinet-form compression curve with (isothermal) bulk modulus K 0 = 270.3 ± 3.8 GPa, pressure derivative K 0 ′ = 5.66 ± 0.10 , and correlation coefficient R K 0 , K 0 ′ = − 0.843. [ABSTRACT FROM AUTHOR]

The performance of Hamiltonian Monte Carlo simulations crucially depends on both the integration timestep and the number of integration steps. We present an adaptive general-purpose framework to automatically tune such parameters based on a local loss function that promotes the fast exploration of phase space. We show that a good correspondence between loss and autocorrelation time can be established, allowing for gradient-based optimization using a fully differentiable set-up. The loss is constructed in such a way that it also allows for gradient-driven learning of a distribution over the number of integration steps. Our approach is demonstrated for the one-dimensional harmonic oscillator and alanine dipeptide, a small protein commonly used as a test case for simulation methods. Through the application to the harmonic oscillator, we highlight the importance of not using a fixed timestep to avoid a rugged loss surface with many local minima, otherwise trapping the optimization. In the case of alanine dipeptide, by tuning the only free parameter of our loss definition, we find a good correspondence between it and the autocorrelation times, resulting in a > 100 fold speedup in the optimization of simulation parameters compared to a grid search. For this system, we also extend the integrator to allow for atom-dependent timesteps, providing a further reduction of 25% in autocorrelation times. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the properties of transition metal (TM)-doped α - G a 2 O 3 using first-principles calculations and Monte Carlo simulations. α - G a 2 O 3 is a wide-bandgap semiconductor material with enhanced performance and lower fabrication costs on sapphire substrates compared to β - G a 2 O 3 . Doping with TMs can modify electrical transport, optical absorption, and magnetic properties, yet theoretical studies on this are scarce. Our study focused on V, Cr, Mn, and Fe impurities. We introduced a newly proposed scheme for efficiently determining the ground-state defect configuration during structural relaxation. We adopt a recent, novel image charge correction method to accurately calculate formation enthalpy and thermodynamic transition levels for spin-polarized transition metal ion doping, without employing the empirical dielectric constant. Results showed Cr ions tend to neutral substitutional Ga, while V, Mn, and Fe impurity ions tend to carry a negative charge in common n-type α - G a 2 O 3 . Magnetic moments and spin-splitting impurity levels primarily arise from transition metal impurities and their d orbitals. We used the generalized four-state method to calculate exchange interaction constants between substitution lattice sites and identified (anti) ferromagnetic couplings at specific distances in a 120-atom supercell, which are negligible in total energy calculations. Monte Carlo simulations indicated a Curie temperature of 360 K in n-type α - G a 2 O 3 : Mn system with 12.5% doping, suggesting intrinsic ferromagnetic ordering based on the Heisenberg model. Our study contributes to understanding TM-doped α - G a 2 O 3 electronic structure and magnetic properties through improved methodologies. The approach can be applied in research involving other TM-doped oxides or wide-bandgap semiconductors. [ABSTRACT FROM AUTHOR]

In this work, we studied the free-carrier transport properties and space-charge formation/polarization in a CdZnTe bar-shaped radiation detector using the Laser-Induced Transient Current technique. We found out that a steady-state space charge ranging from 8 × 108 to 2.1 × 109 cm−3 is formed throughout the detector at about 0.5 s following biasing. The measured current waveforms were modeled by Monte Carlo simulations after taking into account the electric and weighting fields inside the detector and shielding box. Modeling of the unpolarized waveforms revealed an exceptionally high electron mobility-lifetime product μ e τ e ≥ 0.095 c m 2 V − 1 . The observed formation of positive space charge in the biased detector and linear scaling of the current waveform shapes on applied bias revealed that the detector polarization is attributed to carrier injection at the anode. Measurements in pulsed and DC bias in modified electrode geometry proved the surface-charge formation. [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]

Statistical monitoring of warranty claims data using dynamic probability control limits has been shown to be effective in early detection of unforeseen reliability problems that emerge at the design and manufacturing phases. As the discrepancy between abnormal patterns and the normal pattern in aggregate warranty claims is usually small (especially at the early stage), we develop two new dynamic monitoring schemes that adopt CUSUM-type and EWMA-type statistics, named DyCUSUM and DyEWMA, respectively, to better address the warranty claims monitoring problem. Three effective algorithms – that is, the Monte Carlo simulation, Markov chain, and near-enumeration algorithms – are proposed to progressively determine control limits for the two schemes. In particular, comparison studies show that the near-enumeration algorithm can attain a higher approximation accuracy with a lower computational burden and is thus recommended. In-depth simulation experiments are then conducted to assess the performance of the schemes. We find that the DyEWMA scheme has superior and robust detection performance in various situations, whereas the DyCUSUM scheme is less effective and could even be ineffective in certain cases, compared with a Shewhart-type counterpart. Some specific suggestions are also provided to facilitate implementation of the proposed monitoring schemes. Improved schemes by combining the moving window approach to mitigate the 'inertia' problem is further discussed. Finally, a real case study is presented. [ABSTRACT FROM AUTHOR]

Scaling is common in empirical accounting research. It is often done to mitigate heteroscedasticity or the influence of firm size on parameter estimates. However, Barth and Clinch conclude that common diagnostic tools are ineffective in detecting various scale effects. Using analytic results and Monte Carlo simulations, we show that common forms of scaling, when misapplied, induce substantial spurious correlation via biased parameter estimates. Researchers, when uncertain about the exact functional form of scale effect, are typically better off dealing with both heteroscedasticity and the influence of larger firms using techniques other than scaling. [ABSTRACT FROM AUTHOR]

This paper highlights the tight relationship between the picking and packing processes in warehouse management and the need to consider them as an integrated problem. The study describes and models this integrated problem as a mixed-integer programming model, to optimise overall labour costs by determining the assignment of the subsets of orders, i.e. batches, for picking and packing. To address the issue of model complexity, the paper presents a statistical-based framework for generating approximate models and selecting the optimal one through examination. Based on the examination results, a pair-swapping heuristic is additionally proposed to be combined as a hybrid algorithm. Numerical experiments based on a real-world case demonstrate the effectiveness of the framework-proposed and selected hybrid algorithm by comparison with other framework-proposed approximate models, a solver, and existing heuristics. Our findings indicate that the combined usage of integrated picking and packing processes planning and the hybrid algorithm proposed and selected within the statistical-based framework can effectively reduce the cost of warehouse management. [ABSTRACT FROM AUTHOR]

The effects of tensile strain and contact transmissivity on the performance limits of monolayer molybdenum disulfide ( MoS 2) nanoscale n-channel MOSFETs are studied using a semi-classical Monte Carlo method. Density functional theory calculations were performed to parametrize the electronic band structure of MoS 2 subject to tensile and shear strain. Tensile strain decreases the bandgap, increases the inter-valley band-edge energy separation between the light-mass K-valleys and heavier-mass Q-valleys, and decreases the K-valley effective mass in a way that depends on the direction and the amount of the applied strain. Biaxial tensile strain and uniaxial tensile strain along the x- or y-directions are found to have the largest effect. In bulk materials, low-field phonon-limited electron mobility is enhanced, peak and saturation drift velocities are increased, and high-field negative differential resistance becomes more pronounced. Both 200 and 15 nm gate length MoS 2 MOSFETs with end-contacts with ideal (unity) and more realistic (significantly sub-unity) contact interface transmissivity were simulated. These MoS 2 devices exhibited substantial sensitivity to strain with ideal contact transmissivity, and more so for the 15 nm quasi-ballistic device scale than 200 nm long-channel devices. However, the results showed much less strain sensitivity for devices with more realistic contact transmissivities, which may be good or bad depending on whether strain-insensitive or strain-sensitive performance is desired for a particular application and may be possible to modify with improved contact geometries. [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]

We derive a hierarchy of equations, which allow a general n-body distribution function to be measured by test-particle insertion of between 1 and n particles. We apply it to measure the pair and three-body distribution functions in a simple fluid using snapshots from Monte Carlo simulations in the grand canonical ensemble. The resulting distribution functions obtained from insertion methods are compared with the conventional distance-histogram method: the insertion approach is shown to overcome the drawbacks of the histogram method, offering enhanced structural resolution and a more straightforward normalization. At high particle densities, the insertion method starts breaking down, which can be delayed by utilizing the underlying hierarchical structure of the insertion method. Our method will be especially useful in characterizing the structure of inhomogeneous fluids and investigating closure approximations in liquid state theory. [ABSTRACT FROM AUTHOR]

While the influence of various fabrication parameters during deposition on the ferroelectricity of hafnium oxide has been extensively studied, the effect of different atmospheres on the actual switching process has not yet been investigated. In this work, we characterized the ferroelectric properties of undoped hafnium oxide prepared by reactive sputtering under three different atmospheres: dry oxygen/nitrogen, wet nitrogen, and vacuum conditions. We found a significant correlation between dry and wet atmospheres and resulting polarization. Specifically, we observed a direct effect on ferroelectric switching when the film was exposed to dry atmospheres and vacuum, resulting in a higher electric field necessary to initialize the wake-up effect due to an initial imprint effect. Increasing the amount of wet nitrogen during switching decreased the imprint and lowered the necessary voltage required for the wake up. We present a simple model that explains and discusses the incorporation of moisture and its resulting consequences on the ferroelectric properties of hafnium oxide. Additionally, kinetic Monte Carlo simulations showed that the addition of protons to the oxide thin film leads to a lowering of the potential and to a redistribution of protons and oxygen vacancies, which reduces the initial imprint. [ABSTRACT FROM AUTHOR]

The aggregation of dipolar chains driven by thermal fluctuations in an external strong (electric or magnetic) field is investigated theoretically. We discover a new simple electrostatic mechanism that rationalizes the counter-intuitive lateral coalescence of dipolar chains. There, we first demonstrate that two bent dipolar chains can either attract or repel each other depending if they possess similar or opposite curvatures, respectively. Upon bending, dipolar chains become the siege of polarization-induced local charges that in turn lead to quadrupolar couplings. This striking feature is then exploited to understand our conducted Monte Carlo simulations at finite temperature where thermal fluctuations cause local curvatures in the formed dipolar chains. The related quadrupolar attractive mode with correlated chain-curvatures is clearly identified in the simulation snapshots. Our findings shed new light on a longstanding problem in soft matter and related areas. [ABSTRACT FROM AUTHOR]

We study the prospects of using quantum Monte Carlo techniques (QMC) to optimize the electronic wavefunctions and atomic geometries of gold compounds. Complex gold nanoclusters are widely studied for diverse biochemical applications, but the dynamic correlation and relativistic effects in gold set the bar high for reliable, predictive simulation methods. Here we study selected ground state properties of few-atom gold clusters by using density functional theory (DFT) and various implementations of the variational Monte Carlo (VMC) and diffusion Monte Carlo. We show that the QMC methods mitigate the exchange-correlation (XC) approximation made in the DFT approach: the average QMC results are more accurate and significantly more consistent than corresponding DFT results based on different XC functionals. Furthermore, we use demonstrate structural optimization of selected thiolated gold clusters with between 1 and 3 gold atoms using VMC forces. The optimization workflow is demonstrably consistent, robust, and its computational cost scales with nb, where b < 3 and n is the system size. We discuss the implications of these results while laying out steps for further developments. [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]

Pseudopotential locality errors have hampered the applications of the diffusion Monte Carlo (DMC) method in materials containing transition metals, in particular oxides. We have developed locality error free effective core potentials, pseudo-Hamiltonians, for transition metals ranging from Cr to Zn. We have modified a procedure published by some of us in Bennett et al. [J. Chem. Theory Comput. 18, 828 (2022)]. We carefully optimized our pseudo-Hamiltonians and achieved transferability errors comparable to the best semilocal pseudopotentials used with DMC but without incurring in locality errors. Our pseudo-Hamiltonian set (named OPH23) bears the potential to significantly improve the accuracy of many-body-first-principles calculations in fundamental science research of complex materials involving transition metals. [ABSTRACT FROM AUTHOR]

The ab initio path integral Monte Carlo (PIMC) method is one of the most successful methods in statistical physics, quantum chemistry and related fields, but its application to quantum degenerate Fermi systems is severely hampered by an exponential computational bottleneck: the notorious fermion sign problem. Very recently, Xiong and Xiong [J. Chem. Phys. 157, 094112 (2022)] have suggested to partially circumvent the sign problem by carrying out simulations of fictitious systems guided by an interpolating continuous variable ξ ∈ [−1, 1], with the physical Fermi- and Bose-statistics corresponding to ξ = −1 and ξ = 1. It has been proposed that information about the fermionic limit might be obtained by calculations within the bosonic sector ξ > 0 combined with an extrapolation throughout the fermionic sector ξ < 0, essentially bypassing the sign problem. Here, we show how the inclusion of the artificial parameter ξ can be interpreted as an effective penalty on the formation of permutation cycles in the PIMC simulation. We demonstrate that the proposed extrapolation method breaks down for moderate to high quantum degeneracy. Instead, the method constitutes a valuable tool for the description of large Fermi-systems of weak quantum degeneracy. This is demonstrated for electrons in a 2D harmonic trap and for the uniform electron gas (UEG), where we find excellent agreement (∼ 0.5 %) with exact configuration PIMC results in the high-density regime while attaining a speed-up exceeding 11 orders of magnitude. Finally, we extend the idea beyond the energy and analyze the radial density distribution (2D trap), as well as the static structure factor and imaginary-time density–density correlation function (UEG). [ABSTRACT FROM AUTHOR]

This study presents a new equation of state (EOS) for charged hard sphere fluids that incorporates ion-ion association. The EOS is developed using the Debye–Hückel (DH) theory, reference cavity approximation, and Wertheim's theory. Predictive accuracy is evaluated by comparing the model's predictions with Monte Carlo simulations for various charged hard-sphere fluids. The assessment focuses on mean ionic activity coefficient, individual ionic activity coefficient, and osmotic coefficients. The results demonstrate good agreement between the model and simulations, indicating its success for different electrolyte systems. Incorporating ion-ion association improves accuracy compared to the DH theory. The importance of the cavity function and ion-dipole interactions is emphasized in accurately representing structural properties. Overall, the developed EOS shows promising predictive capabilities for charged hard sphere fluids, providing validation and highlighting the significance of ion-ion association in thermodynamic predictions of electrolyte solutions. [ABSTRACT FROM AUTHOR]

We have developed the polyatomic extension of the established [M. Gustafsson, J. Chem. Phys. 138, 074308 (2013)] classical theory of radiative association in the absence of electronic transitions. The cross section and the emission spectrum of the process is calculated by a quasiclassical trajectory method combined with the classical Larmor formula which can provide the radiated power in collisions. We have also proposed a Monte Carlo scheme for efficient computation of ro-vibrationally quantum state resolved cross sections for radiative association. Besides the method development, the global potential energy and dipole surfaces for H + CN collisions have been calculated and fitted to test our polyatomic semiclassical method. [ABSTRACT FROM AUTHOR]

Dissociative adsorption onto a surface introduces dynamic correlations between neighboring sites not found in non-dissociative absorption. We study surface coverage dynamics where reversible dissociative adsorption of dimers occurs on a finite linear lattice. We derive analytic expressions for the equilibrium surface coverage as a function of the number of reactive sites, N, and the ratio of the adsorption and desorption rates. Using these results, we characterize the finite size effect on the equilibrium surface coverage. For comparable N's, the finite size effect is significantly larger when N is even than when N is odd. Moreover, as N increases, the size effect decays more slowly in the even case than in the odd case. The finite-size effect becomes significant when adsorption and desorption rates are considerably different. These finite-size effects are related to the number of accessible configurations in a finite system where the odd-even dependence arises from the limited number of accessible configurations in the even case. We confirm our analytical results with kinetic Monte Carlo simulations. We also analyze the surface-diffusion case where adsorbed atoms can hop into neighboring sites. As expected, the odd-even dependence disappears because more configurations are accessible in the even case due to surface diffusion. [ABSTRACT FROM AUTHOR]

A theoretical investigation of positron scattering from phosphorus-containing compounds (viz., PH 3 , P 2 H 4 , PCl 3 , PF 3 , PBr 3 , POF 3 , POCl 3 , and H 2 PO 4) is reported in this article. The quantum mechanical potential scattering approach is utilized to calculate integral elastic, excitation, momentum transfer, direct ionization, positronium formation, total ionization, inelastic, differential, and total cross sections on a fine energy grid from 1 to 5000 eV. The ionization contribution in the inelastic scattering is estimated using the complex scattering potential-ionization contribution technique. Prior research on positron collisions with these targets is scarce; as a result, the purpose of this study is to make up, at least in part, for this deficiency in cross-section data. In addition to being pertinent to positron transport analyses, such as Monte Carlo methods, the current results should be useful to benchmark the accuracy and validity of positron molecule collision computations and, more significantly, to compare these calculations with related electron scattering outcomes. Furthermore, the calculated cross sections of PH 3 are compared with NH 3 and other phosphorus-containing compounds. The analysis makes it abundantly evident that the atoms on the periphery of a molecule have a substantially larger impact on the scattering process than the central atom. To analyze the scattering dynamics of positrons and their anti-particle electrons, a comparative study of cross sections of H 2 PO 4 and H 2 SO 4 is also presented. For most of these targets, positron calculations are carried out for the first time. [ABSTRACT FROM AUTHOR]

We report a method to predict equilibrium concentration profiles of hard ellipses in nonuniform fields, including multiphase equilibria of fluid, nematic, and crystal phases. Our model is based on a balance of osmotic pressure and field mediated forces by employing the local density approximation. Implementation of this model requires development of accurate equations of state for each phase as a function of hard ellipse aspect ratio in the range k = 1–9. The predicted density profiles display overall good agreement with Monte Carlo simulations for hard ellipse aspect ratios k = 2, 4, and 6 in gravitational and electric fields with fluid–nematic, fluid–crystal, and fluid–nematic–crystal multiphase equilibria. The profiles of local order parameters for positional and orientational order display good agreement with values expected for bulk homogeneous hard ellipses in the same density ranges. Small discrepancies between predictions and simulations are observed at crystal–nematic and crystal–fluid interfaces due to limitations of the local density approximation, finite system sizes, and uniform periodic boundary conditions. The ability of the model to capture multiphase equilibria of hard ellipses in nonuniform fields as a function of particle aspect ratio provides a basis to control anisotropic particle microstructure on interfacial energy landscapes in diverse materials and applications. [ABSTRACT FROM AUTHOR]

To improve the performance of Cu(In,Ga)Se2 thin-film photovoltaic devices, a robust understanding of the dominant diffusion pathways of the alloy species In and Ga is needed. Here, the most probable defect complexes and mechanisms for In and Ga diffusion are identified with the aid of density functional theory. The binding energies and migration barriers for these complexes are calculated in bulk CuInSe2 and CuGaSe2. Analytic models and kinetic lattice Monte Carlo simulations are employed to predict the diffusivity of In and Ga under variations in composition and temperature. We find that a model based on coulombic interactions between group III antisites and vacancies on the Cu-sublattice produces results that match well with experiment. [ABSTRACT FROM AUTHOR]

Orientation-dependent integral equation theory (ODIET) was applied to the rose water model. Structural and thermodynamic properties of water modeled with the rose model were calculated using ODIET and compared to results from orientation-averaged integral equation theory (IET) and Monte Carlo simulations. Rose water model is a simple two-dimensional water model where molecules of water are represented as Lennard–Jones disks with explicit hydrogen bonding potential in form of rose functions. Orientational dependency significantly improves IET, as the thermodynamic results obtained using ODIET are significantly more in agreement with results calculated using MC than in the case of the orientationally averaged version. At high temperatures, the agreement between the simulation and theory is quantitative; however, when temperatures lower, a slight deviation between results obtained with different methods appear. ODIET correctly predicts the radial distribution function; moreover, ODIet also enables the calculation of angular distributions. While the angular distributions obtained with ODIET are in qualitative agreement with distributions from MC simulations, the height of the peaks in angular distributions differs between methods. Using results from ODIET, the spatial distribution of water molecules was constructed, which aids in the interpretation of other structural properties. ODIET was also used to calculate fractions of molecules with different number of hydrogen bonds, which is in the agreement with the simulations. Overall, use of ODIET significantly improves the obtained results in comparison to standard IET. [ABSTRACT FROM AUTHOR]

An efficient multivariate single control chart to simultaneously monitor 'location or mean' and 'scale or variabilities', based on individual observations of multiple quality characteristics (MQC), is a continuous research endeavour. Compared to rational subgroups, time-ordered individual sample observations of MQC are common in manufacturing. However, few researchers proposed parametric and nonparametric multivariate control charts to monitor individual observations in this context. The proposed parametric approach has limited applicability due to the restrictive distribution assumption of MQC. In addition, most of the suggested parametric or nonparametric approaches recommend multiple charts to monitor process 'location' and 'scale' parameters simultaneously. Multiple charts can increase the control complexities and overall false-alarm-rate. MQC can also have significant nonlinear correlation structures and follow unknown or nonnormal distributions in real-life scenarios. Single parametric or nonparametric multivariate charts for individual observations can exhibit poor performance in such situations. In this study, an adaptive Mahalanobis depth and k-nearest neighbour (k-NN) rule-based r-AMD chart is proposed and verified to address the lacuna mentioned above. Monte-Carlo simulation studies are used to evaluate the performance of the r-AMD chart. Four real-life manufacturing scenarios are also considered to validate the suitability and superiority of r-AMD over the existing 'r-MD' and other competing charts. [ABSTRACT FROM AUTHOR]

An extension of a first-principle combined Monte Carlo method is proposed in this work to obtain the secondary electron emission characteristics of anisotropic crystal Al2O3. Unlike isotropic crystal Cu, density functional theory calculations reveal that the q-dependent energy loss function of Al2O3 in all directions is different. Therefore, an interpolation algorithm is introduced in the Monte Carlo method to determine the loss of energy and inelastic mean free path of electrons. The simulation results are in good agreement with experimental data. This method can be further used to simulate the secondary emission yield of other anisotropic crystal materials. [ABSTRACT FROM AUTHOR]

Manufacturing companies strive to identify and manage the effects of unexpected disruptions (risks) on their production processes, which affect their performance and resilience. In this study, we propose a decision framework to capture the impact of interconnected risk sources, on the efficiency of manufacturing companies. The proposed framework utilises a novel mixed-integer linear programming (MILP) model to minimize the time of satisfying the orders while it considers the risk associated with suppliers and manufacturers. The MILP model considers the relationships among (i) material and suppliers and (ii) work centers to measure the propagation of risks throughout the production system. The proposed framework also utilises the Monte Carlo simulation to calculate the associated likelihood of delay and the distribution of the delivery time of orders. To show the complication of the propagation of risk, two distinct scenarios are compared. The first scenario considers zero risks, while the second one assigns probabilistic risk to the suppliers and work centers. The results highlight the magnitude and the complexity of the risk propagation from various interconnected sources through the production system. It also identifies the most vulnerable components of the production system affected more by various types of risk. [ABSTRACT FROM AUTHOR]

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose-response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient [Formula: see text] are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient [Formula: see text] are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for [Formula: see text] that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient [Formula: see text] are substantially upwardly biased.

A lattice-based version of the aggregation-volume-bias Monte Carlo method that was introduced recently has allowed for the extension of the calculation of the nucleation free energies from liquid clusters to solid clusters. Here, it was used to calculate the nucleation free energies of both bcc and fcc clusters formed by Lennard–Jones particles. Under the simulation conditions considered in this study, a cross-over of the thermodynamic stability from the bcc to the fcc structure was observed directly from the free energy results. In addition, the free energies obtained for both types of clusters were used to extrapolate bulk phase information, including chemical potential and surface tension, which revealed that bcc clusters are favored due to the lower surface tension. These results corroborate a recent classical density functional theory study. This work also demonstrates that this approach can be used to predict the entire thermodynamic landscape (i.e., free energies for clusters of different structures and sizes, including an infinitely large cluster, which is the bulk phase), which is important to answer fundamental questions related to crystallization such as the origin of polymorphism. [ABSTRACT FROM AUTHOR]

Determining the role of non-native interactions in folding dynamics, kinetics, and mechanisms is a classic problem in protein folding. More recently, this question has witnessed a renewed interest in light of the hypothesis that knotted proteins require the assistance of non-native interactions to fold efficiently. Here, we conduct extensive equilibrium and kinetic Monte Carlo simulations of a simple off-lattice C-alpha model to explore the role of non-native interactions in the thermodynamics and kinetics of three proteins embedding a trefoil knot in their native structure. We find that equilibrium knotted conformations are stabilized by non-native interactions that are non-local, and proximal to native ones, thus enhancing them. Additionally, non-native interactions increase the knotting frequency at high temperatures, and in partially folded conformations below the transition temperatures. Although non-native interactions clearly enhance the efficiency of transition from an unfolded conformation to a partially folded knotted one, they are not required to efficiently fold a knotted protein. Indeed, a native-centric interaction potential drives the most efficient folding transition, provided that the simulation temperature is well below the transition temperature of the considered model system. [ABSTRACT FROM AUTHOR]

Many-Body eXpansion (MBX) is a C++ library that implements many-body potential energy functions (PEFs) within the "many-body energy" (MB-nrg) formalism. MB-nrg PEFs integrate an underlying polarizable model with explicit machine-learned representations of many-body interactions to achieve chemical accuracy from the gas to the condensed phases. MBX can be employed either as a stand-alone package or as an energy/force engine that can be integrated with generic software for molecular dynamics and Monte Carlo simulations. MBX is parallelized internally using Open Multi-Processing and can utilize Message Passing Interface when available in interfaced molecular simulation software. MBX enables classical and quantum molecular simulations with MB-nrg PEFs, as well as hybrid simulations that combine conventional force fields and MB-nrg PEFs, for diverse systems ranging from small gas-phase clusters to aqueous solutions and molecular fluids to biomolecular systems and metal-organic frameworks. [ABSTRACT FROM AUTHOR]

Polycrystalline thin films are widely used for devices and energy-related applications, such as power electronics, solar cells, and thermal management of devices. In many cases, large-scale crystallization during thin-film growth is challenging, so columnar grains are often found in metal and semiconductor thin films. These rough columnar grain boundaries may also have different phonon specularities from that for typically smoother top/bottom film surfaces. A simple analytical model to separately treat these boundaries and interfaces for phonon scattering is currently unavailable, although the in-plane thermal transport is critical to heat spreading within thin-film devices. In this paper, we extend the effective medium formulation from three-dimensional polycrystalline bulk materials to columnar-grained thin films. The model predictions agree well with those given by frequency-dependent phonon Monte Carlo simulations, considering varied phonon specularity at top/bottom film surfaces and grain-boundary phonon transmissivity. The analytical model is further used to analyze the existing data on polycrystalline ZnO thin films with columnar grains. [ABSTRACT FROM AUTHOR]

This paper is concerned with a theoretical analysis of the behavior of optically excited spin currents in bilayer and multilayer systems of ferromagnetic and normal metals. As the propagation, control, and manipulation of the spin currents created in ferromagnets by femtosecond optical pulses is of particular interest, we examine the influence of different thicknesses of the constituent layers for the case of electrons excited several electronvolts above the Fermi level. Using a Monte-Carlo simulation framework for such highly excited electrons, we first examine the spatiotemporal characteristics of the spin current density driven in a Fe layer, where the absorption profile of the light pulse plays an important role. Further, we examine how the combination of light absorption profile, spin-dependent transmission probabilities, and iron layer thickness affects spin current density in a Fe/Au bilayer system. For high-energy electrons studied here, the interface and secondary electron generation have a small influence on spin transport in the bilayer system. However, we find that spin injection from one layer to another is most effective within a certain range of iron layer thicknesses. [ABSTRACT FROM AUTHOR]

We study the interaction between heterogeneously charged surfaces in an electrolyte solution by employing classical Density Functional Theory (cDFT) and Monte Carlo simulations. We observe a consistent behavior between cDFT and Monte Carlo simulations regarding force curves and two-dimensional density profiles. Armed with the validated cDFT, we explore the system's behavior under parameters that are challenging to simulate directly. Our findings include the impacts of domain size, domain charge, domain charge configuration, and bulk electrolyte concentration on the osmotic pressure. Remarkably, the force curve is more sensitive to the domain size for an asymmetric configuration than a symmetry configuration; the bulk concentration weakly influences the force curve independent of the system configurations. [ABSTRACT FROM AUTHOR]

Anion exchange is a facile, post-synthetic method to tune the emission wavelength of colloidal cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite nanocrystals. While colloidal nanocrystals can exhibit size-dependent phase stability and chemical reactivity, the role of size in the mechanism of anion exchange in CsPbX3 nanocrystals has not been elucidated. We used single-particle fluorescence microscopy to monitor the transformation of individual CsPbBr3 nanocrystals to CsPbI3. By systematically varying the size of the nanocrystals and the concentration of substitutional iodide, we observed that smaller nanocrystals exhibit longer transition times in their fluorescence trajectories, while larger nanocrystals undergo a more abrupt transition during anion exchange. Monte Carlo simulations were used to rationalize the size-dependent reactivity, in which we varied how each exchange event affects the probability for further exchange. Greater cooperativity for simulated ion exchange leads to shorter transition times to complete the exchange. We propose that size-dependent miscibility between CsPbBr3 and CsPbI3 at the nanoscale controls the reaction kinetics. Smaller nanocrystals maintain a homogeneous composition during anion exchange. As the nanocrystal size increases, variations in the octahedral tilting patterns of the perovskite crystals lead to different structures for CsPbBr3 and CsPbI3. Thus, an iodide-rich region must first nucleate within larger CsPbBr3 nanocrystals, which is followed by rapid transformation to CsPbI3. While higher concentrations of substitutional anions can suppress this size-dependent reactivity, the inherent differences in reactivity between nanocrystals of different sizes are important to consider when scaling up this reaction for applications in solid-state lighting and biological imaging. [ABSTRACT FROM AUTHOR]

The x-ray spectrum of a flash radiography source based on wire-shorted rod-pinch diode (RPD) is measured by an absorption spectrometer and calculated by the Geant4 Monte-Carlo code. The RPD is driven by a two-stage linear transformer driver (charging voltage ±45 kV per stage), which delivers ∼300 kA current within ∼200 ns on a short-circuit inductive load (∼30 nH). The spectrometer consists of LiF thermoluminescence dosimeters and metal filters of different materials and thicknesses, and the spectrum is reconstructed based on the Geant4 simulated dosimeter responses to various photon energies through different filters. The measured spectrum reaches an endpoint photon energy of ∼130 keV. The radiation characteristics of the RPD in the experiment are also modeled in Geant4 using measured voltage and current waveforms, and the results show an overestimation in photon number and endpoint energy (∼147 keV) compared to the measured spectrum, which indicates that during the bremsstrahlung process, the effective electron current is ∼27% of the total current, and the effective voltage is ∼12% lower than the directly reconstructed resistive voltage. A rough agreement is found between the spectra results and the non-relativistic Bethe–Heitler model with Sommerfeld correction; therefore, the analytic result can serve as an initial guess for spectrum reconstruction methods such as the perturbation method. [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]