Search

Boltzmann's H-function H(t), often regarded as an analog of time-dependent entropy, holds a venerable place in the history of science. However, accurate numerical evaluation of H(t) for particles other than atoms is rare. To remove this lacuna, we generalize Boltzmann's H-function to a gas of molecules with orientational degrees of freedom and evaluate H(t) from the time-dependent joint probability distribution function f(p, L, t) for linear (p) and angular (L) momenta, evolving from an initial nonequilibrium state, by molecular dynamics simulations. We consider both prolate- and oblate-shaped particles, interacting via the well-known Gay–Berne potential and obtain the relaxation of the generalized molecular H(t) from initial (t = 0) nonequilibrium states. In the long-time limit, the H function saturates to its exact equilibrium value, which is the sum of translational and rotational contributions to the respective entropies. Both the translational and rotational components of H(t) decay nearly exponentially with time; the rotational component is more sensitive to the molecular shape that enters through the aspect ratio. A remarkable rapid decrease in the rotational relaxation time is observed as the spherical limit is approached, in a way tantalizingly reminiscent of Hu–Zwanzig hydrodynamic prediction with the slip boundary condition. In addition, we obtain H(t) analytically by solving the appropriate translational and rotational Fokker–Planck equation and obtain a modest agreement with simulations. We observe a remarkable signature of translation–rotation coupling as a function of molecular shape, captured through a physically meaningful differential term that quantifies the magnitude of translation–rotation coupling. [ABSTRACT FROM AUTHOR]

We consider a general assembly system that produces variations on a single product. Customers can choose to customize any aspect of the product which corresponds to one or more stages of the assembly system. We assume that demand for the original product and the demand for any customization at any stage are all random with known probability distributions. We model this problem as a multi-echelon inventory management problem. This problem has not been studied before. Allowing for customization at any stage in an assembly system makes this problem significantly more complex than similar problems considered in the past. To solve this problem, we 'split' the assembly line into two parallel assembly lines which we call uncommitted and committed lines. We show that the usual method of reducing the assembly system to a series is not possible in general. We develop a heuristic policy which can be used to then reduce the system into a series system. We also present numerical calculations which highlight the efficacy of the heuristic policy. [ABSTRACT FROM AUTHOR]

Single particle level microscopy of immobilized FAPbBr3 nanocrystals (NCs) has elucidated the involvement of different processes in their photoluminescence (PL) intermittency. Four different blinking patterns are observed in the data from more than 100 NCs. The dependence of PL decays on PL intensities brought out in fluorescence lifetime intensity distribution (FLID) plots is rationalized by the interplay of exciton- and trion-mediated recombinations along with hot carrier (HC) trapping. The high intensity-long lifetime component is attributed to neutral exciton recombination, the low intensity-short lifetime component is attributed to trion assisted recombination, and the low intensity-long lifetime component is attributed to hot carrier recombination. Change-point analysis (CPA) of the PL blinking data reveals the involvement of multiple intermediate states. Truncated power law distribution is found to be more appropriate than power law and lognormal distribution for on and off events. Probability distributions of PL trajectories of single NCs are obtained for two different excitation fluences and wavelengths (λex = 400, 440 nm). Trapping rate (kT) prevails at higher power densities for both excitation wavelengths. From a careful analysis of the FLID and probability distributions, it is concluded that there is competition between the HC and trion assisted blinking pathways and that the contribution of these mechanisms varies with excitation wavelength as well as fluence. [ABSTRACT FROM AUTHOR]

A preceding paper [M. Dhar, J. A. Dickinson, and M. A. Berg, J. Chem. Phys. 159, 054110 (2023)] shows how to remove additive noise from an experimental time series, allowing both the equilibrium distribution of the system and its Green's function to be recovered. The approach is based on nonlinear-correlation functions and is fully nonparametric: no initial model of the system or of the noise is needed. However, single-molecule spectroscopy often produces time series with either photon or photon-counting noise. Unlike additive noise, photon noise is signal-size correlated and quantized. Photon counting adds the potential for bias. This paper extends noise-corrected-correlation methods to these cases and tests them on synthetic datasets. Neither signal-size correlation nor quantization is a significant complication. Analysis of the sampling error yields guidelines for the data quality needed to recover the properties of a system with a given complexity. We show that bias in photon-counting data can be corrected, even at the high count rates needed to optimize the time resolution. Using all these results, we discuss the factors that limit the time resolution of single-molecule spectroscopy and the conditions that would be needed to push measurements into the submicrosecond region. [ABSTRACT FROM AUTHOR]

Amorphous alumina resistance random-access memory is a promising candidate as a next-generation nonvolatile memory. It is intriguing that the nonvolatile memory function emerges in only amorphous samples, unlike crystalline samples. We studied local structures of amorphous alumina samples and Al 2 O 3 polycrystalline using atomic pair distribution function measurements. We derived the Al–Al, O–O, and Al–O atomic distances for each sample. By comparing them, we revealed that the subtle difference in the local structure significantly influences the performance of a nonvolatile memory function. [ABSTRACT FROM AUTHOR]

This paper aims to propose a Novel Condition-based maintenance (CBM) decision aid model for optimising the maintenance of complex multi-component systems. As the degradation level of each component is assumed to be independent and stochastic, it follows a specific probability distribution determined from historical data of experimental observations and inspection. The main objective is to optimise the total cost for providing maintenance actions and reducing the excess of spare parts usage. The decision support model consists of determining measurements on components with the aim of estimating the instant of time of removing predictively one or a group of components before they fail. The measurement model includes the mean residual lifetime (MRL) and some extensions developed for this purpose. For demonstrating the pertinency of the proposed model, we use a preventive maintenance strategy for one-component systems and a grouping/opportunistic maintenance for multi-component systems. Besides, a numerical comparative study performing these measurements is carried out using several examples and a case study from Electric energy distribution systems. The solution is illustrated as a decision-making optimal model for optimising the maintenance operations' costs and the total number of spare parts. The numerical results and the comparison show the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

The influence of argon and helium on the rovibrational kinetics of carbon dioxide (CO2) and CO in low-temperature conversion plasma is investigated. With this objective, a combined experimental and computational study is conducted, applying quantum cascade laser infrared absorption spectroscopy to a pulsed DC CO2 glow discharge with varying noble gas admixture and modeling it with a two-term Boltzmann solver. Time-resolved rovibrational temperatures and dissociation fractions are presented, exhibiting an increase in rotational–vibrational non-equilibrium and an increasing CO2 conversion with argon (Ar) and helium (He) admixtures. Results are discussed in the context of energy transfer processes for collisions involving electrons, corroborated by electron-kinetic modeling, and heavy particle collisions. With noble gas addition, an increase in the electron number density, promoting excitation, and the high-energy tail of the electron energy distribution function are found. Penning ionization processes are proposed as an explanation for the increase in conversion, showing higher conversion for Ar due to the lower excitation thresholds and, therefore, larger state population. In the context of rovibrational kinetics, processes leading to the gain or loss of vibrational energy of CO2 are analyzed, pointing out subtle differences in, for example, relaxation rate coefficients between Ar and He. However, the cooling of the gas through conductive heat transfer is identified as the most important influence of the Ar and He admixture, as it keeps the relaxation rate for vibrational quenching low. [ABSTRACT FROM AUTHOR]

Experimental and numerical studies were performed on the vibrational energy relaxation in shock-heated CO/N2/Ar mixtures. A laser absorption technique was applied to the time-dependent rovibrational temperature time-history measurements. The vibrational relaxation data of reflected-shock-heated CO were summarized at 1720–3230 K. In shock-tube experiments, the rotational temperature of CO quickly reached equilibrium, whereas a relaxation process was found in the time-dependent vibrational temperature. For the mixture with 1.0% CO and 10.0% N2, the vibrational excitation caused a decrease in the macroscopic thermodynamic temperature of the test gas. In the simulations, the state-to-state (StS) approach was employed, where the vibrational energy levels of CO and N2 are treated as pseudo-species. The vibrational state-specific inelastic rate coefficients of N2–Ar collisions were calculated using the mixed quantum–classical method based on a newly developed three-dimensional potential energy surface. The StS predictions agreed well with the measurements, whereas deviations were found between the Schwartz–Slawsky–Herzfeld formula predictions and the measurements. The Millikan–White vibrational relaxation data of the N2–Ar system were found to have the most significant impact on the model predictions via sensitivity analysis. The vibrational relaxation data of the N2–Ar system were then modified according to the experimental data and StS results, providing an indirect way to optimize the vibrational relaxation data of a specific system. Moreover, the vibrational distribution functions of CO and N2 and the effects of the vibration–vibration–translation energy transfer path on the thermal nonequilibrium behaviors were highlighted. [ABSTRACT FROM AUTHOR]

Robust control of a quantum system is essential to utilize the current noisy quantum hardware to its full potential, such as quantum algorithms. To achieve such a goal, a systematic search for an optimal control for any given experiment is essential. The design of optimal control pulses requires accurate numerical models and, therefore, accurate characterization of the system parameters. We present an online Bayesian approach for quantum characterization of qutrit systems, which automatically and systematically identifies optimal experiments that provide maximum information on the system parameters, thereby greatly reducing the number of experiments that need to be performed on the quantum testbed. Unlike most characterization protocols that provide point-estimates of the parameters, the proposed approach is able to estimate their probability distribution. The applicability of the Bayesian experimental design technique was demonstrated on test problems, where each experiment was defined by a parameterized control pulse. In addition to this, we also present an approach for iterative pulse extension, which is robust under uncertainties in transition frequencies and coherence times, and shot noise, despite being initialized with wide uninformative priors. Furthermore, we provide a mathematical proof of the theoretical identifiability of the model parameters and present conditions on the quantum state under which the parameters are identifiable. The proof and conditions for identifiability are presented for both closed and open quantum systems using the Schrödinger equation and the Lindblad master equation, respectively. [ABSTRACT FROM AUTHOR]

The superadiabatic dynamical density functional theory (superadiabatic-DDFT) is a promising new method for the study of colloidal systems out-of-equilibrium. Within this approach, the viscous forces arising from interparticle interactions are accounted for in a natural way by explicitly treating the dynamics of the two-body correlations. For bulk systems subject to spatially homogeneous shear, we use the superadiabatic-DDFT framework to calculate the steady-state pair distribution function and the corresponding viscosity for low values of the shear-rate. We then consider a variant of the central approximation underlying this superadiabatic theory and obtain an inhomogeneous generalization of a rheological bulk theory due to Russel and Gast. This paper thus establishes for the first time a connection between DDFT approaches, formulated to treat inhomogeneous systems, and existing work addressing nonequilibrium microstructure and rheology in bulk colloidal suspensions. [ABSTRACT FROM AUTHOR]

We have applied path-integral molecular dynamics simulations to investigate the impact of nuclear quantum effects on the vibrational dynamics of water molecules at the water–air interface. The instantaneous fluctuations in the frequencies of the O–H stretch modes are calculated using the wavelet method of time series analysis, while the time scales of vibrational spectral diffusion are determined from frequency-time correlation functions and joint probability distributions. We find that the inclusion of nuclear quantum effects leads not only to a redshift in the vibrational frequency distribution by about 120 cm−1 for both the bulk and interfacial water molecules but also to an acceleration of the vibrational dynamics at the water–air interface by as much as 35%. In addition, a blueshift of about 45 cm−1 is seen in the vibrational frequency distribution of interfacial water molecules compared to that of the bulk. Furthermore, the dynamics of water molecules beyond the topmost molecular layer was found to be rather similar to that of bulk water. [ABSTRACT FROM AUTHOR]

This paper presents the design of a single-phase solid phononic crystal (PnC) structure featuring a regular hexagonal perforation pattern. The structure manifests three negative refraction bands, encompassing one for transverse waves and two for longitudinal waves, thereby enabling simultaneous control of shear and longitudinal waves. Due to the high symmetry of the triangular lattice, the equal frequency curves corresponding to the negative refraction band approach circular shapes, suggesting a nearly isotropic negative refraction effect. This negative refraction effect is achieved through specific mass resonance modes closely related to the porous structure designed in this paper. Initially, we analyze the band structure of the PnC, followed by designing the PnC plate structure to achieve negative refraction control for transverse waves at a frequency of 32.4 kHz, with a negative refraction index of −1. Additionally, negative refraction control for longitudinal waves is attained at frequencies of 44 and 64.54 kHz. Subsequently, we scrutinize the influence of various conditions on negative refraction, including different structural parameters, incident angles, and operating frequencies, while verifying the robustness of the designed phonon crystal structure. Leveraging the negative refraction characteristics of the structure, we construct an elastic wave lens to achieve perfect imaging of shear and longitudinal waves. Finally, employing finite element simulation and analyzing focusing imaging characteristics with different source positions, we validate that the results closely align with theoretical expectations. The solid PnC structure designed in this study holds significant potential for applications in the fields of elastic wave imaging. [ABSTRACT FROM AUTHOR]

Zinc germanium diphosphide (ZnGeP2) is a ternary semiconductor best known for its nonlinear optical properties. A primary application is optical parametric oscillators operating in the mid-infrared region. Controlled donor doping provides a method to minimize the acceptor-related absorption bands that limit the output power of these devices. In the present study, a ZnGeP2 crystal is doped with selenium during growth. Selenium substitutes for phosphorus and serves as a deep donor. Significant concentrations of native defects (zinc vacancies, germanium-on-zinc antisites, and phosphorous vacancies) are also present in the crystal. Electron paramagnetic resonance (EPR) is used to establish the atomic-level model for the neutral charge state of the selenium donor. The S = 1/2 signal from the neutral donors is produced at 6 K by illuminating with 633 nm light (electrons excited from doubly ionized Zn vacancies convert Se P + donors to Se P 0 donors). A g matrix, with principal values of 2.088, 2.203, and 1.904, is extracted from the angular dependence of the EPR spectrum. The principal-axis direction associated with the 1.904 principal value is close to a Se–Ge bond. This indicates an asymmetric distribution of unpaired spin density around the selenium ion and thus predicts the deep donor behavior. [ABSTRACT FROM AUTHOR]

This work is part of a prediction challenge that invited theoretical/computational chemists to predict the photochemistry of cyclobutanone in the gas phase, excited at 200 nm by a laser pulse, and the expected signal that will be recorded during a time-resolved megaelectronvolt ultrafast electron diffraction (MeV-UED). We present here our theoretical predictions based on a combination of trajectory surface hopping with XMS-CASPT2 (for the nonadiabatic molecular dynamics) and Born–Oppenheimer molecular dynamics with MP2 (for the athermal ground-state dynamics following internal conversion), coined (NA+BO)MD. The initial conditions were sampled from Born–Oppenheimer molecular dynamics coupled to a quantum thermostat. Our simulations indicate that the main photoproducts after 2 ps of dynamics are CO + cyclopropane (50%), CO + propene (10%), and ethene and ketene (34%). The photoexcited cyclobutanone in its second excited electronic state S 2 can follow two pathways for its nonradiative decay: (i) a ring-opening in S 2 and a subsequent rapid decay to the ground electronic state, where the photoproducts are formed, or (ii) a transfer through a closed-ring conical intersection to S 1 , where cyclobutanone ring opens and then funnels to the ground state. Lifetimes for the photoproduct and electronic populations were determined. We calculated a stationary MeV-UED signal [difference pair distribution function— Δ PDF (r) ] for each (interpolated) pathway as well as a time-resolved signal [ Δ PDF (r , t) and Δ I / I (s , t) ] for the full swarm of (NA+BO)MD trajectories. Furthermore, our analysis provides time-independent basis functions that can be used to fit the time-dependent experimental UED signals [both Δ PDF (r , t) and Δ I / I (s , t) ] and potentially recover the population of photoproducts. We also offer a detailed analysis of the limitations of our model and their potential impact on the predicted experimental signals. [ABSTRACT FROM AUTHOR]

Despite the importance of the one-particle picture provided by the orbital paradigm, a rigorous understanding of the spatial distribution of electrons in molecules is still of paramount importance to chemistry. Considerable progress has been made following the introduction of topological approaches, capable of partitioning space into chemically meaningful regions. They usually provide atomic partitions, for example, through the attraction basins of the electron density in the quantum theory of atoms in molecules (QTAIM) or electron-pair decompositions, as in the case of the electron localization function (ELF). In both cases, the so-called electron distribution functions (EDFs) provide a rich statistical description of the electron distribution in these spatial domains. Here, we take the EDF concept to a new fine-grained limit by calculating EDFs in the QTAIM ∩ ELF intersection domains. As shown in AHn systems based on main group elements, as well as in the CO, NO, and BeO molecules, this approach provides an exquisitely detailed picture of the electron distribution in molecules, allowing for an insightful combination of the distribution of electrons between Lewis entities (such as bonds and lone pairs) and atoms at the same time. Besides mean-field calculations, we also explore the impact of electron correlation through Hartree–Fock (HF), density functional theory (DFT) (B3LYP), and CASSCF calculations. [ABSTRACT FROM AUTHOR]

A new algorithm has been developed to simulate two-dimensional (2D) spectra with correlated anisotropic frequencies faster and more accurately than previous methods. The technique uses finite-element numerical integration on the sphere and an interpolation scheme based on the Alderman–Solum–Grant algorithm. This method is particularly useful for numerical calculations of joint probability distribution functions involving quantities with a parametric orientation dependence. The technique's efficiency also allows for practical least-squares fitting of experimental 2D solid-state nuclear magnetic resonance (NMR) datasets. The simulation method is illustrated for select 2D NMR methods, and a least-squares analysis is demonstrated in the extraction of paramagnetic shift and quadrupolar coupling tensors and their relative orientation from the experimental shifting-d echo 2H NMR spectrum of a NiCl2 · 2D2O salt. [ABSTRACT FROM AUTHOR]

We have observed that Variational Mode Decomposition (VMD) exhibits instability in the denoising and separation of noisy multitone signals. Specifically, minor changes in factors such as signal-to-noise ratio, frequency spacing, sampling rate, and probability distribution can significantly impact the decomposition results. To address this issue, we have developed the Dual-VMD-correlation algorithm. This algorithm effectively mitigates the impact of beat effects when harmonics of closely spaced frequencies are superimposed, enabling stable denoising of noisy multitone signals and the separation of each individual tone signal. The algorithm holds promise for applications in frequency-modulated continuous wave laser detection. It can address challenges related to denoising laser echo signals interfered with by aerosols and the difficulty in separating backscatter interference from the target reflected signal spectrum. [ABSTRACT FROM AUTHOR]

A scaling law for the osmotic pressure of quasi-two-dimensional polymer melts as a function of concentration is obtained, which shows fractal characteristics. Structural properties such as the chains' contour length and their inner-monomer pair distribution function display fractal scaling properties as well. These predictions are confirmed with mesoscale numerical simulations. The chains are swollen and highly entangled, yet Flory's exponent is always ν = 1/2. The melt can be considered a fluid of "blobs" whose size becomes renormalized in terms of the contour's length while the fractal dimension df increases monotonically between 5/4 and 2, as the monomer concentration is increased. The semidilute scaling of the pressure is recovered when df = 1. Our results agree with recent experiments and with numerical reports on quasi-2d melts. This work provides a new paradigm to study and interpret thermodynamic and structural data in low-dimensional polymer melts, namely as fractal macromolecular objects. [ABSTRACT FROM AUTHOR]

Before hydrates can be widely used in industry, we should better understand the problematic issues of hydrate nucleation, particularly its stochastic nature. Here, we report on measurements of the nucleation probability of mixed-gas hydrates in which the guest molecules are a mixture of methane and propane. For the pure cases, at a supersaturation near 1.0, we had previously measured an induction time for the methane hydrate of about 1 h, whereas for the propane hydrate, it was over one day. Using the same experimental setup, we examine here the nucleation probability for a mixture of 90% methane and 10% propane as the guest gas for a range of supersaturations. For the experiments, the temperature was 274 ± 0.5 K and the stirring rate was about 300 rpm. The experiments were repeated at least ten times under the same condition, exchanging the sample water every time. We define the nucleation probability at a given time as the fraction of trials that nucleated by that time and then determine the nucleation probability distribution. The resulting nucleation frequency is found to have a power-law relation to supersaturation. Then, we examine how the nucleation frequency is affected by the existence of ultrafine bubbles in the initial water. We find that the ultrafine bubbles increase the nucleation frequency but much less than that of typical changes in supersaturation. [ABSTRACT FROM AUTHOR]

We study heat exchange in temperature-biased metal–molecule–metal molecular junctions by employing the molecular dynamics simulator LAMMPS. Generating the nonequilibrium steady state with Langevin thermostats at the boundaries of the junction, we show that the average heat current across a gold–alkanedithiol–gold nanojunction behaves physically, with the thermal conductance value matching the literature. In contrast, the full probability distribution function for heat exchange, as generated by the simulator, violates the fundamental fluctuation symmetry for entropy production. We trace this failure back to the implementation of the thermostats and the expression used to calculate the heat exchange. To rectify this issue and produce the correct statistics, we introduce single-atom thermostats as an alternative to conventional many-atom thermostats. Once averaging heat exchange over the hot and cold thermostats, this approach successfully generates the correct probability distribution function, which we use to study the behavior of both the average heat current and its noise. We further examine the thermodynamic uncertainty relation in the molecular junction and show that it holds, albeit demonstrating nontrivial trends. Our study points to the need to carefully implement nonequilibrium molecular dynamics solvers in atomistic simulation software tools for future investigations of noise phenomena in thermal transport. [ABSTRACT FROM AUTHOR]

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. We recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory. [ABSTRACT FROM AUTHOR]

Chirality-selective vibrational sum frequency generation (chiral SFG) spectroscopy has emerged as a powerful technique for the study of biomolecular hydration water due to its sensitivity to the induced chirality of the first hydration shell. Thus far, water O–H vibrational bands in phase-resolved heterodyne chiral SFG spectra have been fit using one Lorentzian function per vibrational band, and the resulting fit has been used to infer the underlying frequency distribution. Here, we show that this approach may not correctly reveal the structure and dynamics of hydration water. Our analysis illustrates that the chiral SFG responses of symmetric and asymmetric O–H stretch modes of water have opposite phase and equal magnitude and are separated in energy by intramolecular vibrational coupling and a heterogeneous environment. The sum of the symmetric and asymmetric responses implies that an O–H stretch in a heterodyne chiral SFG spectrum should appear as two peaks with opposite phase and equal amplitude. Using pairs of Lorentzian functions to fit water O–H stretch vibrational bands, we improve spectral fitting of previously acquired experimental spectra of model β-sheet proteins and reduce the number of free parameters. The fitting allows us to estimate the vibrational frequency distribution and thus reveals the molecular interactions of water in hydration shells of biomolecules directly from chiral SFG spectra. [ABSTRACT FROM AUTHOR]

Planning decisions are generally subject to some level of uncertainty. In forestry, data describing the resources available have a major impact on operations performance and productivity. This paper aims to present a method to improve decision-making in the forest supply chain by taking supply uncertainty into account using the results of data quality assessments. The case study describes the operations planning process of a Canadian forest products company dealing with an uncertain volume of wood supply. Three approaches to constructing probability distributions based on data quality are tested. Each approach offers a different level of precision: (1) a frequency distribution of accuracy, (2) a normal distribution based on average accuracy, and (3) a normal distribution based on data quality classification. Using stochastic programming to plan transport and production shows that lower costs can be achieved with a general characterisation of the data accuracy. Not considering uncertainty when planning operations leads to a significant replanning transportation cost. Using classes of data quality to include uncertainty in operations planning contributes to reducing the transportation cost from $15.90/m3 down to $15.32/m3 representing 3.6%. [ABSTRACT FROM AUTHOR]

Extending the storage-recovery model, we propose a new strengthening model, premised on detailed evolution laws for both mobile and immobile dislocations, for metals under moderate to intense loading. These dislocation density evolution laws include the multiplication, storage under the effect of dislocation junctions, release of pinned dislocations, and annihilation by cross-slip. The storage-release description is derived from a simplified depiction of the probability distribution function of the dislocation length in dislocation networks. Although the model requires only few parameters to characterize the evolution of dislocation densities, remarkable agreement is found with available experimental data. From a theoretical study of the long-time behavior of the model, analytical expressions are provided to easily extract most of these parameters from experimental stress–strain curves in the quasi-static regime, whereas the parameter that governs the strength of the release process is adjusted from dynamic tensile tests. Their values so determined for polycrystalline tantalum allow the model to reproduce experimental plate-impact data with a very good match. [ABSTRACT FROM AUTHOR]

This study is concerned with a theory of two-step nucleation and growth of crystals in a metastable liquid. This mechanism is that crystalline nuclei formation occurs in dense liquid clusters suspended in the solution. These clusters contain higher solution concentration and viscosity, leading to a lower surface free energy barrier and faster phase transition route. The theory is based on growth laws of crystals during the two-step bulk phase transformation. At the initial stage, the crystals evolve in a diffusion-limited environment with almost unchanged supersaturation. At the second stage, they become larger, move beyond these clusters, and evolve in accordance with a hyperbolic tangent law. A generalized particle growth law joining the first and second stages is obtained by stitching the diffusion limited and hyperbolic tangent laws. On this basis, an integrodifferential model of the evolution of a polydisperse ensemble of crystals was formulated and solved. The crystal-size distribution function increases and the solution supersaturation remains practically unchanged until the particle size corresponds to a transition in the particle growth rate from a diffusion-limited branch to a hyperbolic tangent branch. This is followed by an increase in the crystal growth rate, a decrease in the distribution function and solution supersaturation. Then the distribution function increases up to the maximum size of crystals grown in the solution. A sufficiently long time interval of almost constant supersaturation and the N-shaped behavior of the distribution function are the consequences of a two-step nucleation and growth mechanisms. [ABSTRACT FROM AUTHOR]

Coarse-graining of fluids is challenging because fluid particles are unbound and diffuse long distances in time. One approach creates coarse-grain variables that group all particles within a region centered on specific points in space and accounts for the movement of particles among such regions. In our previous work, we showed that in many cases, potential interactions for such a scheme adopted a generalized quadratic form, whose parameters depend on means, variances, and correlation coefficients among the coarse-grain variables. In this work, we use statistical mechanics to derive analytic expressions for these parameters, using properties of the fluid, including pair distribution functions. These expressions are compared against simulation-derived values and shown to be in good agreement. This approach can be used to calculate a priori the potential for any homogeneous, simple fluid, without the need for fitting procedures or matching, thus increasing the ease of use of this coarse-grain scheme and creating a foundation for large-scale bottom-up simulations. Furthermore, these expressions provide a quantitative way of studying the boundary between discrete (atomic) and continuum models of fluids. [ABSTRACT FROM AUTHOR]

This paper investigates the optimization of the inner thermal layout in nanofluid-filled horizontal annular pipes under natural convection conditions. Two-dimensional models of annular pipes are established using a numerical simulation approach. Then, using this as the simulation tool, the layouts of single-, triple-, and quadruple-heat-source annular pipes are optimized. The coordinates of the inner cylinders are defined as the decision variables, and the average Nusselt number (Nu) on the cold wall surface as the objective function. For the single-cylinder model, both the Bayesian optimization algorithm (BOA) and the genetic algorithm (GA) derive the same results: an axisymmetric layout where the single heat source is positioned slightly above the axis of the annulus. However, the BOA takes much less computational time than the GA and, consequently, is chosen for cases with more complex geometry. The optimization layout of the three-cylinder model also shows an axisymmetric distribution, while the result for the four-cylinder model presents a centrally symmetric distribution. Compared to the original average Nu, the optimized ones are enhanced by 17.83%, 8.36%, and 6.18% for single-, triple-, and quadruple-heat-source annular pipes, respectively. The results of this study can be used for guiding the layout design and optimization of the nanofluid-filled exchangers with multi-inner heat sources. [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]

A one-dimensional implicit particle-in-cell/Monte Carlo collision simulation was employed to study the effects of a uniform weak magnetic field and negative direct-current (DC) voltage on a radio frequency capacitively coupled plasma (CCP). The simulation results indicate that the application of a magnetic field to RF/DC hybrid power-driven CCP discharge can increase the plasma density and cause it to exhibit an asymmetric distribution. When the magnetic field strength increases, pronounced striations can be observed within the DC sheath in the spatiotemporal plots of an electron heating rate and an ionization rate. This is attributed to the generation of a large number of secondary electrons by the DC electrode. These secondary electrons are accelerated by the sheath voltage and undergo E × B drift motion. When the energy of these electrons reaches the ionization threshold of an argon gas, ionization occurs. At this point, the electrons are still situated within the DC sheath, and hence, they repeatedly undergo this process until they exit the DC sheath. Additionally, the electron energy distribution function reveals that an increase in a magnetic field can cause a transition from stochastic heating to ohmic heating. The simulation results of magnetized CCP discharge under the influence of negative DC voltage show that increasing negative DC voltage can effectively improve plasma density. The application of negative DC voltage and magnetic field strength has similar effects on the heating stripe phenomenon. As the negative DC voltage increases, the striation phenomenon becomes more pronounced. [ABSTRACT FROM AUTHOR]

The probability of inserting, without overlap, a hard spherical particle of diameter σ in a hard-sphere fluid of diameter σ0 and packing fraction η determines its excess chemical potential at infinite dilution, μex(σ, η). In our previous work [R. L. Davidchack and B. B. Laird, J. Chem. Phys. 157, 074701 (2022)], we used Widom's particle insertion method within molecular dynamics simulations to obtain high precision results for μex(σ, η) with σ/σ0 ≤ 4 and η ≤ 0.5. In the current work, we investigate the behavior of this quantity at small σ. In particular, using the inclusion-exclusion principle, we relate the insertion probability to the hard-sphere fluid distribution functions and thus derive the higher-order terms in the Taylor expansion of μex(σ, η) at σ = 0. We also use direct evaluation of the excluded volume for pairs and triplets of hard spheres to obtain simulation results for μex(σ, η) at σ/σ0 ≤ 0.2247 that are of much higher precision than those obtained earlier with Widom's method. These results allow us to improve the quality of the small-σ correction in the empirical expression for μex(σ, η) presented in our previous work. [ABSTRACT FROM AUTHOR]

This study reports the test results of a two-stage stochastic linear programming (SLP) model with recourse using a user-friendly generic decision support system (DSS) in a North American steel company. This model has the flexibility to configure multiple material facilities, activities and storage areas in a multi-period and multi-scenario environment. The value of stochastic solution (VSS) with a real-world example has a potential benefit of US$ 24.61 million. Experiments were designed according to the potential joint probability distribution scenarios and the magnitude of demand variability. Overall, 144 SLP optimisation model instances were solved across four industries, namely, steel, aluminium, polymer and pharmaceuticals. The academic contribution of this research is two-fold: first, the potential contribution to profit in a steel company using an SLP model; and second, the optimisation empirical experiments confirm a pattern that the VSS and expected value of perfect information (EVPI) increase with the increase in demand variability. This study has implications for practicing managers seeking business solutions with prescriptive analytics using stochastic optimisation-based DSS. This study will attract more industry attention to business solutions, and the prescriptive analytics discipline will garner more scholarly and industry attention. [ABSTRACT FROM AUTHOR]

The current state of electron probe methods [including energy loss spectroscopy of inelastically scattered electrons (EELS)] is considered. The analysis concerning the issues of their application, challenges, and limitations is performed. Particular attention is paid to the fundamental limitations and the means to overcome those during electron probe methods' subsequent development for the study of composite nanostructured materials. It is emphasized that the emitted electron energy spectrum dispersion (or electron energy distribution function width) is one of the main factors limiting a further increase in EELS energy resolution, although the use of direct detection sensors and monochromators allows one to approach the physical limit of this method. Novel low-macroscopic-field electron emitters are synthesized and investigated. Their properties are analyzed and compared with previously obtained specimens. Both energy and temporal resolutions of an EEL system utilizing the suggested cathodes are estimated. The comparison of its characteristics with the corresponding parameters of classical facilities is performed. The obtained results indicate the possibility to achieving a significant growth in energy and temporal resolutions as well as a decrease in the detection threshold of chemical elements with trace concentrations while maintaining relatively high emission current density values. [ABSTRACT FROM AUTHOR]

Narrow bandgap p-type semiconducting metal oxide nanowires (NWs), such as copper oxide (CuO), have gained significant attention for their potential in the development of electrical nano-devices. Tailoring the mechanical and electrical properties of CuO NWs is crucial for optimizing their functionality in specific applications. In this study, we employ nanosecond laser irradiation to precisely modify the properties of individual CuO NWs by inducing point and line defects, including oxygen vacancies and dislocations. Through controlled laser irradiation, we observe a gradual enhancement in the concentration of oxygen vacancies within CuO NWs until reaching a saturation point. The accumulation of vacancies leads to a substantial residual stress, resulting in lattice distortion and misfit. This high residual stress serves as a catalyst for the nucleation of dislocations, subsequently leading to a meaningful enhancement in plasticity. Remarkably, the density of dislocations demonstrates a strong correlation with the duration of laser irradiation. Prolonged irradiation leads to a thermally activated restoration process, where the dislocation configuration transitions from a random distribution to ordered dislocation loops. Mechanical characterization tests indicate that pristine CuO NWs exhibit brittleness, while laser irradiation renders them ductile with improved plasticity. Furthermore, the laser processing of CuO NWs demonstrates an enhancement in their electrical conductivity and optical absorbance. [ABSTRACT FROM AUTHOR]

Modeling the ion concentration profile in nanochannel plays an important role in understanding the electrical double layer and electro-osmotic flow. Due to the non-negligible surface interaction and the effect of discrete solvent molecules, molecular dynamics (MD) simulation is often used as an essential tool to study the behavior of ions under nanoconfinement. Despite the accuracy of MD simulation in modeling nanoconfinement systems, it is computationally expensive. In this work, we propose neural network to predict ion concentration profiles in nanochannels with different configurations, including channel widths, ion molarity, and ion types. By modeling the ion concentration profile as a probability distribution, our neural network can serve as a much faster surrogate model for MD simulation with high accuracy. We further demonstrate the superior prediction accuracy of neural network over XGBoost. Finally, we demonstrated that neural network is flexible in predicting ion concentration profiles with different bin sizes. Overall, our deep learning model is a fast, flexible, and accurate surrogate model to predict ion concentration profiles in nanoconfinement. [ABSTRACT FROM AUTHOR]

This paper addresses an unrelated parallel machines scheduling problem with the need of additional resources during the processing of the jobs, as well as during the setups that machines need between the processing of any two jobs. This problem is highly complex, and therefore in this paper we propose several constructive heuristics to solve it. To improve the performance of these heuristics, we propose several variations, including randomisation with different probability distributions and a local search phase, having this way GRASP algorithms. The results of extensive experiments over randomly generated instances show several findings on the different parameters that characterise our constructive algorithms. In particular, we highlight the fact that non-uniform probability distributions might be advisable for choosing elements of a restricted candidate list in GRASP algorithms. [ABSTRACT FROM AUTHOR]

The efficiency of material supply for workstations using Automatic Guided Vehicles (AGVs) is largely determined by the performance of the AGV dispatching scheme. This paper proposes a new solution approach for the AGV dispatching problem (AGVDP) for material replenishment in a general manufacturing workshop where workstations are in a matrix layout, and where uncertainty in replenishment time of workstations and stochastic unloading efficiencies of AGVs are dynamic contextual factors. We first extend the literature proposing a mixed integer optimisation model with a delivery satisfaction soft constraint of material orders and two objectives: transportation costs and delivery time deviation. We then develop a new knowledge-guided estimation of distribution algorithm with delivery satisfaction evaluation for solving the model. Our algorithm fuses three knowledge-guided strategies to enhance optimisation capabilities at its respective execution stages. Comprehensive numerical experiments with instances built from a real-world scenario validate the proposed model and algorithm. Results demonstrate that the new algorithm outperforms three popular multi-objective evolutionary algorithms, a discrete version of a recent multi-objective particle swarm optimisation, and a multi-objective estimation of distribution algorithm. Findings of this work provide major implications for workshop management and algorithm design. [ABSTRACT FROM AUTHOR]

Single-molecule and related experiments yield time series of an observable as it fluctuates due to thermal motion. In such data, it can be difficult to distinguish fluctuating signal from fluctuating noise. We present a method of separating signal from noise using nonlinear-correlation functions. The method is fully nonparametric: No a priori model for the system is required, no knowledge of whether the system is continuous or discrete is needed, the number of states is not fixed, and the system can be Markovian or not. The noise-corrected, nonlinear-correlation functions can be converted to the system's Green's function; the noise-corrected moments yield the system's equilibrium-probability distribution. As a demonstration, we analyze synthetic data from a three-state system. The correlation method is compared to another fully nonparametric approach—time binning to remove noise, and histogramming to obtain the distribution. The correlation method has substantially better resolution in time and in state space. We develop formulas for the limits on data quality needed for signal recovery from time series and test them on datasets of varying size and signal-to-noise ratio. The formulas show that the signal-to-noise ratio needs to be on the order of or greater than one-half before convergence scales at a practical rate. With experimental benchmark data, the positions and populations of the states and their exchange rates are recovered with an accuracy similar to parametric methods. The methods demonstrated here are essential components in building a complete analysis of time series using only high-order correlation functions. [ABSTRACT FROM AUTHOR]

The structural properties of confined single-file hard-disk fluids are studied analytically by means of a mapping of the original system onto a one-dimensional mixture of non-additive hard rods, the mapping being exact in the polydisperse limit. Standard statistical-mechanical results are used as a starting point to derive thermodynamic and structural properties of the one-dimensional mixture, where the condition that all particles have the same chemical potential must be taken into account. Analytical results are then provided for the nth neighbor probability distribution function, the radial distribution function, and the structure factor, a very good agreement being observed upon comparison with simulation data from the literature. Moreover, we have analyzed the scaling form for the disappearance of defects in the zigzag configuration for high pressure and have obtained the translational correlation length and the structural crossover in the oscillation frequency for asymptotically large distances. [ABSTRACT FROM AUTHOR]

Stochastic pattern anomalies limit the shrinking of the size of nano-patterns in extreme-ultraviolet lithography at around 10 nm due to the discrete/probabilistic nature of photon–electron-reaction systems. We express the patterns and their anomalies as probability distributions and predict stochastic hotspots where the anomaly generation probabilities rise unexpectedly in arbitrary pattern features. Three-dimensional chemo-physical event distributions in pattern-exposed resist films are calculated by the fully coupled first-principles Monte Carlo simulation combined with the discrete development/etching models. The aggregates of molecular level solubility flipping (sub-cluster) well express spatial correlations in the observed anomalies. Spatial correlation in sub-cluster generation is not scaled and their impact increases with shrinking patterns. The correlation is squeezed near the pattern edge, inducing edge placement error, and it spreads in the areas between edges causing stochastic pattern defects. For materials with sub-cluster size not negligible compared to image size, the stochastic hotspots appear when the correlated area spreads in areas far from the edges adjacent to the higher probability region. Deep neural networks successfully predict the probability distributions of sub-clusters and anomaly generation in arbitrary pattern features without the Monte Carlo method. [ABSTRACT FROM AUTHOR]

In dispersion, nanoparticles can interact with the surrounding dispersion medium, such that an interfacial region with a structure differing from that of the bulk exists. Distinct nanoparticulate surfaces induce specific degrees of interfacial phenomena, and the availability of surface atoms is a crucial prerequisite for interfacial restructuring. Here, we investigate the nanoparticle–water interface of 0.5–10 wt. % aqueous iron oxide nanoparticle dispersions of 6 nm diameter in the presence of 6 vol. % ethanol with x-ray absorption spectroscopy (XAS) and atomic pair distribution function (PDF) analysis. The absence of surface hydroxyl-groups in XAS spectra is in accordance with the double-difference PDF (dd-PDF) analysis, due to a fully covered surface from the capping agent. The previously observed dd-PDF signal is not stemming from a hydration shell, as postulated in Thomä et al. [Nat Commun. 10, 995 (2019)], but from the residual traces of ethanol from nanoparticle purification. With this article, we provide an insight into the arrangement of EtOH solutes in water at low concentration. [ABSTRACT FROM AUTHOR]

In various types of many-particle systems, bidispersity is frequently used to avoid spontaneous ordering in particle configurations. In this study, the relation between bidispersity and disorder degree of particle configurations is investigated. By using magnetic dipole–dipole interaction, magnet particles are dispersed in a two-dimensional cell without any physical contact between them. In this magnetic system, bidispersity is introduced by mixing large and small magnets. Then, the particle system is compressed to produce a uniform particle configuration. The compressed particle configuration is analyzed by using Voronoi tessellation for evaluating the disorder degree, which strongly depends on bidispersity. Specifically, the standard deviation and skewness of the Voronoi cell area distribution are measured. As a result, we find that the peak of standard deviation is observed when the numbers of large and small particles are almost identical. Although the skewness shows a non-monotonic behavior, a zero skewness state (symmetric distribution) can be achieved when the numbers of large and small particles are identical. In this ideally random (disordered) state, the ratio between pentagonal, hexagonal, and heptagonal Voronoi cells becomes roughly identical, while hexagons are dominant under monodisperse (ordered) conditions. The relation between Voronoi cell analysis and the global bond orientational order parameter is also discussed. [ABSTRACT FROM AUTHOR]

In this paper, we take variable separation method to study Klein–Kramers (KK) equation. By choosing different eigenvalues and noise functions, we can get different probability density functions (PDFs) of KK equation. These PDFs contain not only normal distributions but also other distributions that correspond to anomalous diffusion phenomena. For example, power-law distribution, truncated Cauchy–Lorentz distribution, Weibull distribution, log-logistic distribution, Gamma distribution. We also show the 3D and 2D profiles of these PDFs to analyze the corresponding dynamic properties and illustrate the possible practical applications of these results. In addition, we also find some exact solutions that are not PDFs. They are also listed to ensure the completeness of the results and to illustrate the potential applications of these exact solutions. [ABSTRACT FROM AUTHOR]

A Ni x Co 1-x O/HCS catalyst with superior water-splitting is presented. High water-splitting reaction kinetics and enhanced durability were observed. The structure-function relationship was investigated with XPS, which demonstrated the presence of dominant Ni2+ and Co2+ species and a functionalized HCS support where nucleation of small metal oxide nanoparticles occurred. The PDF showed broadened Nickel/Cobalt-oxide bonds and expansion of the metal-metal pair distances. The alteration of the Metal-Oxide and Metal-Metal-Oxide bonds favored better HER and OER electrocatalysis, also as supported by DFT. EXAFS showed the existence of the bimetallic oxide catalyst and the stretching of the Ni–O bonds due to the coordination of the Ni–O with the Co. The composite exhibited higher activity and enhanced electrocatalytic mechanism towards water splitting through higher exchange current densities (0.615 and 0.886 mA cm−2) and low charge transfer resistance (14 and 10 Ω) respectively. Chronoamperometry proved the catalyst's stability during prolonged electrolysis. [Display omitted] • Successful preparation of homogeneously dispersed Ni x Co 1-x O nanoparticles supported on porous and graphitic hollow carbon spheres (HCS). • Characterization of materials demonstrated short-range order crystallinity of the Ni x Co 1-x O bimetallic transition metal oxides. • Pair distribution function (PDF), Extended x-ray absorption fine structure (EXAFS), and powder x-ray diffraction (PXRD) data elucidated the structure of the materials and proposed a mechanism attributed to the improved overall water splitting. • The small domain size of the bimetallic oxide catalysts and synergistic effects between Ni and Co oxides significantly contribute to the observed activity and durability of the catalysts. [ABSTRACT FROM AUTHOR]

We provide new constraints on the dark matter halo density profile of Milky Way (MW) dwarf spheroidal galaxies (dSphs) using the phase-space distribution function (DF) method. After assessing the systematics of the approach against mock data from the Gaia Challenge project, we apply the DF analysis to the entire kinematic sample of well-measured MW dwarf satellites for the first time. Contrary to previous findings for some of these objects, we find that the DF analysis yields results consistent with the standard Jeans analysis. In particular, in this study we rediscover (i) a large diversity in the inner halo densities of dSphs (bracketed by Draco and Fornax), and (ii) an anticorrelation between inner halo density and pericenter distance of the bright MW satellites. Regardless of the strength of the anticorrelation, we find that the distribution of these satellites in density versus pericenter space is inconsistent with the results of the high-resolution N -body simulations that include a disc potential. Our analysis motivates further studies on the role of internal feedback and dark matter microphysics in these dSphs. [ABSTRACT FROM AUTHOR]

A robust method for determining the electron temperature and density of atmospheric-pressure non-equilibrium argon plasmas is reported. The methodology is based on the analysis of the continuum and line spectra of the plasma. Assuming that the electron energy distribution function (EEDF) is expressed as a two-temperature generalized EEDF (GEEDF), the gamma value of the GEEDF is determined through a grid search of the continuum spectrum analysis given by the bremsstrahlung process, which minimizes the mean-squared logarithmic error (MSLE). In addition, the relationship between the gamma value and the electron temperature and density is determined. Utilizing this relationship, the electron temperature and density are determined by minimizing the MSLE between the excited-state densities obtained from the line spectrum analysis and numerically calculated using the collisional-radiative model. This methodology yielded results that satisfied both continuum and line spectrum analyses. In addition, the same analysis was conducted either by continuum spectrum analysis or by line spectrum alone to compare the results. [ABSTRACT FROM AUTHOR]