Ensemble Monte Carlo Simulations Research Articles

Phase behavior analysis of methane confined in nanopores using molecular simulation

Interest in the phase behavior of hydrocarbons in shale reservoirs has grown in recent years. Petroleum fluid phase behavior has been observed to differ significantly between conventional reservoirs and shale reservoirs. Within shale reservoirs, notable surface-fluid interactions can lead to non-uniform molecule distribution and an alteration in fluid phase behavior, primarily caused by the existence of nano-scale porous materials. In this work, we study the phase behavior of methane in single cylindrical pore models. We apply the gauge Gibbs ensemble Monte Carlo (gauge-GEMC) simulation technique to investigate the phase behavior of methane in 4–10 nm single nanopores and calculate the saturation pressures at various temperatures using the grand canonical Monte Carlo (GCMC) simulation technique. A shift in the phase diagram has been found for methane in nanopores. As pore size decreases, the shift becomes more significant.

Enhanced non-equilibrium Peltier cooling through electron gas expansion: A Monte Carlo simulation study

We demonstrate enhanced Peltier cooling at the nanoscale using geometrical constriction. This nozzle structure leads to electron expansion under an applied bias, which in turn results in additional cooling. This extra cooling enhances the overall Peltier effect when the electrons are out of equilibrium with the lattice. An ensemble Monte Carlo simulation is used to demonstrate the non-equilibrium expansion of an electron gas using nanoscale trapezoidal geometric confinement. The proposed device operates under steady-state conditions, providing enhanced cooling compared to a one-dimensional flat geometry. We observe a five-fold increase in both the maximum cooling temperature and cooling power density, reaching more than 5 kW/cm2, when comparing the trapezoidal geometry to the regular flat geometry.

Molecular insights into methane hydrate dissociation: Role of methane nanobubble formation.

Understanding the underlying physics of natural gas hydrate dissociation is necessary for efficient CH4 extraction and in the exploration of potential additives in the chemical injection method. Silica being "sand" is already present inside the reservoir, making the silica nanoparticle a potential green additive. Here, molecular dynamics (MD) simulations have been performed to investigate the dissociation of the CH4 hydrate in the presence and absence of ∼1, ∼2, and ∼3nm diameter hydrophilic silica nanoparticles at 100bar and 310K. We find that the formation of a CH4 nanobubble has a strong influence on the dissociation rate. After the initial hydrate dissociation, the rate of dissociation slows down till the formation of a CH4 nanobubble. We find the critical concentration and size limit to form the CH4 nanobubble to be ∼0.04 molefraction of CH4 and ∼40 to 50 CH4 molecules, respectively. The solubility of CH4 and the chemical potential of H2O and CH4 are determined via Gibbs ensemble Monte Carlo simulations. The liquid phase chemical potential of both H2O and CH4 in the presence and absence of the nanoparticle is nearly the same, indicating that the effect of this additive will not be significant. While the formation of the hydration shell around the nanoparticle via hydrogen bonding confirms the strength of interactions between the water molecules and the nanoparticle in our MD simulations, the contact of the nanoparticle with the interface is infrequent, leading to no explicit effect of the nanoparticle on the dynamics of methane hydrate dissociation.

Analysis of carbon peak achievement at the provincial level in China: Construction of ensemble prediction models and Monte Carlo simulation

As China advances toward its carbon peaking goals, many regions face the challenge of balancing rapid economic growth with sustainable development. Evaluating carbon emissions at the provincial level is crucial for formulating effective strategies to achieve China's carbon peak targets. This study aims to construct an accurate model for predicting carbon emissions and to explore the evolution of these emissions across Chinese provinces, as well as their contributions to national carbon peak targets. Using the Environmental Kuznets Curve (EKC) theory, the 30 provinces were categorized into groups. An ensemble carbon emissions forecasting model was developed by integrating time-series models with multifactor models. Three scenarios were established within the framework of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Monte Carlo simulations were employed to explore potential pathways to achieve carbon peaks. The results indicate that China will reach its carbon emission peak between 2030 and 2031, with peak values expected to range between 11,499.65 and 11,629.51 Mt. Significant differences were observed among the provincial groups in their contributions to carbon peaking. Groups II and III are projected to peak in 2030 and 2022, respectively, while Groups I and IV face greater challenges, with peak years projected between 2032–2035 and 2031–2034, respectively. Four tiers with different emission reduction responsibilities were identified by comparing the peak times of the 30 provinces under the three scenarios, and optimal recommendations for achieving carbon peaks were proposed for each province. The accurate prediction models and Monte Carlo simulations provide reliable results for achieving carbon peak targets across Chinese provinces, offering a scientific basis for optimizing national carbon emission reduction policies.

Uncovering optimal carbon and boron nitride nanotube geometries for methane and hydrogen release

We screened 1651 carbon and boron nitride (BN) nanotubes to investigate methane release at 298 K and hydrogen release at 77 K through grand canonical ensemble Monte Carlo (GCMC) simulations. The effects of nanotube radius, density, and van der Waals spacing on the release quantities of these gases were explored. Our research shows that CH4 release in C(40,40) and BN(40,40) nanotubes reaches a high of 0.15 g/g, below the DOE's 0.5 g/g target. Similarly, the best nanotubes for volumetric release, C(21,9) and BN(18,18), peak at 175 cm³/cm³, below the DOE target of 330 cm³/cm³. This suggests that internal adsorption within isolated nanotubes is insufficient to meet DOE targets, highlighting the need for optimization of inter-tube van der Waals spacing. For H2, C(40,39) and BN(40,40) nanotubes are optimal for weight release, achieving up to 12.19% at a pressure of 8 MPa. This surpasses the 2025 DOE benchmark of 5.5 wt%. Meanwhile, C(28,7) and BN(24,24) nanotubes are most suitable for volumetric release. The C(28,7) nanotube, recommended for H2 storage, reaches a volumetric release quantity close to the DOE target of 0.04 kg/L at a van der Waals spacing of 1 nm. At pressures exceeding 2 MPa, the weight adsorption outside nanotubes accounts for 40–55% of the total, underscoring the pivotal role of extra-tube adsorption in gas storage capacity for both CH4 and H2. The results provide a foundation for the design of nanotube-based materials for efficient gas storage and release, with implications for clean energy applications.

Avoiding pitfalls in molecular simulation of vapor sorption: Example of propane and isobutane in metal-organic frameworks for adsorption cooling applications.

This study introduces recommendations for conducting molecular simulations of vapor adsorption, with an emphasis on enhancing the accuracy, reproducibility, and comparability of results. The first aspect we address is consistency in the implementation of some details of typical molecular models, including tail corrections and cutoff distances, due to their significant influence on generated data. We highlight the importance of explicitly calculating the saturation pressures at relevant temperatures using methods such as Gibbs ensemble Monte Carlo simulations and illustrate some pitfalls in extrapolating saturation pressures using this method. For grand canonical Monte Carlo (GCMC) simulations, the input fugacity is usually calculated using an equation of state, which often requires the critical parameters of the fluid. We show the importance of using critical parameters derived from the simulation with the same model to ensure internal consistency between the simulated explicit adsorbate phase and the implicit bulk phase in GCMC. We show the advantages of presenting isotherms on a relative pressure scale to facilitate easier comparison among models and with experiment. Extending these guidelines to a practical case study, we evaluate the performance of various isoreticular metal-organic frameworks (MOFs) in adsorption cooling applications. This includes examining the advantages of using propane and isobutane as working fluids and identifying MOFs with a superior performance.

Hydrogen adsorption in Si-LTA and LTA-4A zeolites: A Gibbs Ensemble Monte Carlo simulation study

Storing a targeted amount of hydrogen is one of the most challenging tasks. Several porous materials are being tested for the physisorption of hydrogen. We perform, NPT-Gibbs Ensemble Monte Carlo Simulation of hydrogen storage inside two zeolites: Si-LTA and LTA-4A. Classical three-site Silvera-Goldman potential is used to model hydrogen molecules. Gravimetric densities, radial distribution functions, adsorption enthalpies and specific regions for hydrogen are analyzed in detail in this study. Although number of hydrogen molecules stored in LTA-4A is more compared to Si-LTA, their gravimetric densities are comparable. At 77 K and 200 bar, almost 3 wt% of hydrogen can be stored in these zeolites. Introduction of sodium ions enhance the number of hydrogen molecules adsorbed in LTA-4A. Because of the presence of sodium ions at the windows of the cages, it can store these extra hydrogens inside it. It is also observed that for both these zeolites, preferred adsorption sites are always α-cages compared to the channels or β-cages. Replacement of silicon atoms with aluminium does not have any change on the uptake, but the presence of sodium counter ions increase the uptake. At low loading, enthalpies of adsorption are enhanced by 2 kJ/mol, because of the counter ions. Even though hydrogen uptake is less in these zeolites, we find important aspects of hydrogen adsorption in general which will help to devise porous materials with higher storing capabilities.

Effects of electric field and device size on the electron velocity in p-i-n GaAs semiconductor

This paper introduces the investigation of the influence of electric field and device size on the drift velocity of electrons in GaAs semiconductor using ensemble Monte Carlo simulation method under limited size conditions. We employed a GaAs diode device model with p-i-n structure, consisting of p-type and n-type semiconductor layers with uniform size of 20 nm, and a variable-sized intrinsic (i) semiconductor layer in between. We show that in the absence of external electric field, the damped velocity will diminish as the size of the (i) layer ranges from 100 nm to 800 nm. And the damped oscillation period of the electron velocity is a linear function of the device size. Additionally, by examining the maximum value of electron velocity under the influence of an external electric field, our observed results are consistent with those reported by Saraniti et al. (2002) [22] in low electric field below 50 kV/cm; while at higher electric fields, the maximum velocity gradually increased to a saturation value. Furthermore, the maximum velocity vmax is found to follow a simple logarithmic law as a function of i-layer size S as vmax=aln⁡(bS). The coefficients of this relation equation were derived using least-square approximation technique yielding a high determination coefficient R2 up to 0.998.

2D MoS2 under switching field conditions: Study of high-frequency noise velocity fluctuations

The transient high-frequency noise response of two-dimensional MoS2 under abrupt large signal switching field conditions is studied by means of an ensemble Monte Carlo simulator. Low-to-high and high-to-low transitions are analyzed at low (77 K) and room temperature, considering several underlying substrates. The incorporation of stochastic individual scattering events allows capturing the transient collective phonon–electron coupling, which is shown to be responsible for the appearance of an oscillatory behavior in the average velocity and energy at low temperature in the case of MoS2 on SiO2, hBN, and Al2O3. Activation and deactivation of surface polar phonon emissions in the low-to-high field switching process yield the appearance of a relevant peak in the power spectral density of velocity fluctuations in the THz range. The results show the important influence of the substrate type in the noise behavior of MoS2 at very high frequencies, which is critical for the design of future FET devices based on 2D TMD technology.

The Maximum Entropy Principle: General Extended Hydrodynamic Approach for Dynamic High-Field Transport in Monolayer Graphene

Within the maximum entropy principle, we present a general theory able to describe in a dynamical context the transport properties of hot carriers in monolayer graphene under electric fields of arbitrary strength. Therefore, we obtain a closed extended hyperbolic system of hydrodynamic (HD) equations in which all the unknown constitutive functions are completely determined. In particular, we consider the different scattering mechanisms used in the literature in the kinetic approaches. The closed extended HD system is applied to monolayer graphene at 300 K and is validated by comparing numerical calculations with ensemble Monte Carlo simulations.

Liquid-vapor equilibrium and critical point of parabolic-well fluids of variable width derived from Gibbs Ensemble Monte Carlo simulation

The vapor-liquid coexistence curve at equilibrium of parabolic-well (PW) fluids is computed by means of Monte Carlo simulations, for a selection of well-widths. The outcome is compared with results for corresponding curves of triangle-well (TW) and square-well (SW) fluids with the same range. It is found that, for a given width, the shape of the vapor-liquid coexistence curve in the case of the parabolic-well fluid is rather similar to the one of the triangular-well fluid and a little bit different to the one of the square-well fluid. It is also found that such vapor-liquid coexistence curve shifts towards higher temperatures as the width of the parabolic-well potential increases, always falling, for the same range in all cases, between the vapor-liquid coexistence curves corresponding to the other two potentials. In addition, it was observed that the reduced critical temperature matches the theoretical prediction of the Vliegenthart and Lekkerkerker (V-L) criterion only for the smaller well-width, the accuracy of such criterion decreasing substantially as the range increases.

Auto-calibration strategy for the equilibration phase of Gibbs ensemble Monte Carlo simulations

ABSTRACT This paper proposes simulation protocols in terms of an auto-calibration strategy for the parameterisation of Gibbs ensemble Monte Carlo simulations for Lennard–Jones fluids. The proposed simulation protocols have been deduced from various approaches proposed in literature and have been tested against pure LJ fluids and their mixtures. These simulation protocols are intended to reduce or avoid time-consuming pre-simulations by adjusting the trial move limits, the number of attempted transfers, or the probability of attempted transfer during the equilibration phase, and can serve as a starting point for simulating more complex molecules, beyond LJ-fluids. This new approach aims to adjust simulation parameters to ensure a sufficient amount of successful trial moves as suggested in literature. It is similar to a previously proposed trial move adjustment and can easily be implemented in existing simulation code. Abbreviations: BWR EoS: Benedict–Webb–Rubin equation of state; CBMC: Configurational-bias Monte Carlo; EoS: Equation of state; GEMC: Gibbs ensemble Monte Carlo; LJ: Lennard–Jones; M1; M2; M3: Abbreviations for the three simulated mixtures; MC: Monte Carlo; PAT: Probability of attempted transfer; TL: Translation within a box (GEMC move); TR: Transfer to the other box (GEMC move); t-PR EoS: Volume-translated Peng-Robinson equation of state

Machine Learning-Enabled Development of Accurate Force Fields for Refrigerants.

Hydrofluorocarbon (HFC) refrigerants with zero ozone-depleting potential have replaced chlorofluorocarbons and are now ubiquitous. However, some HFCs have high global warming potential, which has led to calls by governments to phase out these HFCs. Technologies to recycle and repurpose these HFCs need to be developed. Therefore, thermophysical properties of HFCs are needed over a wide range of conditions. Molecular simulations can help understand and predict the thermophysical properties of HFCs. The prediction capability of a molecular simulation is directly tied to the accuracy of the force field. In this work, we applied and refined a machine learning-based workflow to optimize the Lennard-Jones parameters of classical HFC force fields for HFC-143a (CF3CH3), HFC-134a (CH2FCF3), R-50 (CH4), R-170 (C2H6), and R-14 (CF4). Our workflow involves liquid density iterations with molecular dynamics simulations and vapor-liquid equilibrium (VLE) iterations with Gibbs ensemble Monte Carlo simulations. Support vector machine classifiers and Gaussian process surrogate models save months of simulation time and can efficiently select optimal parameters from half a million distinct parameter sets. Excellent agreement as evidenced by low mean absolute percent errors (MAPEs) of simulated liquid density (ranging from 0.3% to 3.4%), vapor density (ranging from 1.4% to 2.6%), vapor pressure (ranging from 1.3% to 2.8%), and enthalpy of vaporization (ranging from 0.5% to 2.7%) relative to experiments was obtained for the recommended parameter set of each refrigerant. The performance of each new parameter set was superior or similar to the best force field in the literature.

The Role of Thermalization in the Cooling Dynamics of Hot Carrier Solar Cells

The hot carrier solar cell (HCSC) concept has been proposed to overcome the Shockley Queisser limit of a single p–n junction solar cell by harvesting carriers before they have lost their surplus energy. A promising family of materials for these purposes is metal halide perovskites (MHP). MHPs have experimentally shown very long cooling times, the key requirement of a HCSC. By using ensemble Monte Carlo simulations, light is shed on why cooling times are found to be extended. This article concentrates on the role of thermalization in the cooling process. The role of carrier–phonon and carrier–carrier interactions in thermalization and cooling is specified, while showing how these processes depend on material parameters, such as the dielectric constant and effective mass. It is quantified how thermalization acts as a cooling mechanism via the cold background effect. The importance of a low degree of background doping is to achieve the observed extended cooling times. Herein, it is mapped out how perovskites should be tuned, their material parameters, carrier concentration, and purity, in order to realize a HCSC. It contributes to the debate on the cooling times in MHPs and the suitability of tin perovskites for HCSCs.

Alchemical Free Energy and Hamiltonian Replica Exchange Molecular Dynamics to Compute Hydrofluorocarbon Isotherms in Imidazolium-Based Ionic Liquids.

Ionic liquids (ILs) have shown promise for applications that leverage differential gas solubility in an IL solvent, e.g., gas separations. Although most available literature provides Henry's law constants, the ability to efficiently estimate full isotherms is important for engineering design calculations. Molecular simulation can be used as a tool to predict full isotherms of gas in ILs. However, particle insertions or deletions in a charge-dense IL medium and the sluggish conformational dynamics of ILs present two sampling challenges for these systems. We therefore devised a method that uses Hamiltonian replica exchange (HREX) molecular dynamics (MD) combined with alchemical free energy calculations to compute full solubility isotherms of two different hydrofluorocarbons (HFCs) in imidazolium-based IL binary mixtures. This workflow is significantly faster than the Gibbs ensemble Monte Carlo (GEMC) simulations which fail to deal with the slow conformational relaxation caused by the sluggish dynamics of ILs. Multiple free energy estimators, including thermodynamic integration, free energy perturbation, and multistate Bennett acceptance ratio method, provided consistent results. Overall, the simulated Henry's law constant, isotherm curvature, and solubility trends match experimental results reasonably well. We close by calculating the full solubility isotherms of two HFCs in IL mixtures that have not been reported in the literature, demonstrating the potential of this method to be used for solubility prediction and setting the stage for future computational screening studies that search for the "best" IL to separate azeotropic HFC mixtures.

Monte Carlo Simulations of Water Adsorption in Aluminum Oxide Rod-Based Metal–Organic Frameworks

Atmospheric water harvesting utilizing nanoporous sorbent materials with suitable adsorption characteristics has recently emerged as a potential solution for the global water crisis. Here, we probe the adsorption behavior of two high-performing Al(μ2-OH) rod-based metal–organic frameworks (MOFs), MOF-303 and MOF-333, using Gibbs ensemble Monte Carlo simulations. We find that simulations using nonpolarizable force fields and rigid framework structures optimized using periodic electronic structure calculations can achieve good agreement with experimental data for adsorption isotherms and isosteric heats of adsorption; however, for MOF-303, it is important to utilize a structure that accounts for the distortion associated with water adsorbed at the primary adsorption site.

The role of nonequilibrium LO phonons, Pauli exclusion, and intervalley pathways on the relaxation of hot carriers in InGaAs/InGaAsP multi-quantum-wells

Under continuous-wave laser excitation in a lattice-matched In0.53Ga0.47As/In0.8Ga0.2As0.44P0.56 multi-quantum-well (MQW) structure, the carrier temperature extracted from photoluminescence rises faster for 405 nm compared with 980 nm excitation, as the injected carrier density increases. Ensemble Monte Carlo simulation of the carrier dynamics in the MQW system shows that this carrier temperature rise is dominated by nonequilibrium LO phonon effects, with the Pauli exclusion having a significant effect at high carrier densities. Further, we find a significant fraction of carriers reside in the satellite L-valleys for 405 nm excitation due to strong intervalley transfer, leading to a cooler steady-state electron temperature in the central valley compared with the case when intervalley transfer is excluded from the model. Good agreement between experiment and simulation has been shown, and detailed analysis has been presented. This study expands our knowledge of the dynamics of the hot carrier population in semiconductors, which can be applied to further limit energy loss in solar cells.

Carrier mobility and high-field velocity in 2D transition metal dichalcogenides: degeneracy and screening

The effect of degeneracy and the impact of free-carrier screening on a low-field mobility and a high-field drift velocity in MoS2 and WS2 are explored using an in-house ensemble Monte Carlo simulator. Electron low field mobility increases to for MoS2 and to for WS2 when temperature decreases to and carrier concentration is around . In the case of holes, best mobility values were and , reached at similar temperature and carrier concentration conditions while at room temperature these fall to and for MoS2 and WS2, respectively. The carrier screening effect plays a major role at low fields, and low and intermediate temperatures, where a combination of large occupancy of primary valleys and carrier–phonon interactions dominated by relatively low energy exchange processes results in an enhanced screening of intrinsic scattering. For electrons, degeneracy yields to transport in secondary valleys, which plays an important role in the decrease of the low field mobility at high concentrations and/or at room temperature. The high-field drift velocity is not much affected by carrier screening because of an increased carrier scattering with surface optical polar phonons, favouring larger phonon wavevector interactions with small dielectric function values.

Development of an ensemble Monte Carlo simulator for high-power semiconductor devices with self-consistent electromagnetism and GPU implementation

The ensemble Monte Carlo (EMC) method is a powerful and widely used technique for modeling carrier transport in semiconductors in which one can easily take into account band structure and a variety of scattering mechanisms. In the usual implementations of EMC, the semiclassical electron dynamics is coupled self-consistently to the electrostatic field and this suffices for most devices. However, for high power, high current semiconductor device applications the electrostatic approximation is often not adequate and the full electromagnetic (EM) equations must be solved in fully-coupled fashion. We report on the development of a fully self-consistent, time-domain, EM-EMC simulator for two- and three-dimensional device simulations in which we also address a well known drawback of these methods, their computational intensiveness, by producing a GPU implementation.

Experimental and simulation study on the delayed release of CO in the initial stage of the low-temperature oxidation of coal

To investigate the delayed release characteristics of CO gas in the initial stage of the low-temperature oxidation of coal, closed oxygen consumption experiments were conducted on coal samples taken from the Hongqingliang coal mine, and the corresponding relationship between the CO concentration and time in the initial stage of the experimental reaction was analyzed. A physical adsorption model of the macromolecules in coal for O2 and CO was established, and the difference in the competitive adsorption between the CO and O2 gas molecules on the coal surface was analyzed from a microscopic perspective using the grand canonical ensemble Monte Carlo simulation. The results showed a delayed CO release phenomenon in the initial stage of the reaction in all the experiments, and the delayed time of CO release was negatively correlated with the temperature; the relationship between the adsorption amounts of CO and O2 in the molecular structure model of coal was CO > O2. With increasing temperature, the adsorption capacity of the two gases decreased. Under the same conditions, there was competitive adsorption of the mixture of CO and O2 by coal, with the adsorption capacity of CO being much greater than that of O2. The adsorption of CO gas molecules by coal played an inhibitory role in the release of CO gas in the initial oxidation stage. The study results are expected to help understand the CO generation characteristics in the goaf of coal seam working faces and thus prevent coal mine disasters.