Canonical Ensemble Monte Carlo Simulations Research Articles

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.

Interfacial structure within thin films of decane isomers adsorbed on a metal substrate

Canonical-ensemble Monte Carlo simulations were used to examine the solid–liquid interfacial structure within neat and multicomponent solutions of decane isomers at 350 K. As seen both experimentally and computationally for many fluids, layering within the liquid film near the solid substrate was exhibited in all fluids examined here. The amount of branching within a molecule, though, limited the range of density oscillations, particularly for multicomponent fluids. Analysis of molecular orientation within the first layer showed a strong preference in most cases for molecules to adopt orientations that enhance the energy of adsorption. To this end, preferential absorption was observed in all fluid mixtures with n-decane present. For both n-decane and 2,2-dimethyloctane, whether neat or in solution, the preference for orientations that maximise interactions between the alkane backbone of the molecule and the substrate led to additional in-plane alignment between adjacent adsorbed molecules. In contrast, for 4-propylheptane little in-plane alignment or orientation preference was observed at the interface.

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.

The coexistence curve and surface tension of a monatomic water model.

We study the monatomic water model of Molinero and Moore the grand canonical ensemble Monte Carlo simulation. Measurements of the probability distribution of the number density obtained via multicanonical sampling and histogram reweighting provide accurate estimates of the temperature dependence of both the liquid-vapor coexistence densities and the surface tension. Using finite-size scaling methods, we locate the liquid-vapor critical point at Tc = 917.6K, ρc = 0.311gcm-3. When plotted in scaled variables, in order to test the law of corresponding states, the coexistence curve of monatomic water is close to that of real water. In this respect, it performs better than extended simple point charge (SPC/E), TIP4P, and TIP4P/2005 water.

Molecular structure characterization of middle-high rank coal via 13C NMR, XPS and FTIR spectroscopy

Elemental analysis, 13C nuclear magnetic resonance (NMR) spectroscopy, X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), combined with Grand Canonical ensemble Monte Carlo (GCMC) simulations and energy minimizations were used to establish the molecular structure model of middle-high coal rank accurately. The three-dimensional molecular structure models of middle-high coal rank (from the No. 6 Mine of Pingdingshan (PDS) Mining Area and the No. 4 Mine of Hebi (HB) Mining Area in Henan Province, Xiegou (XG) Mine, Changping (CP) Mine, and Sihe (SH) Mine in Shanxi Province, China) were optimized and constructed. The results showed that the structural arrangement is more orderly and compact with the increase of coal rank. The established molecular formulae for PDS, HB, XG, CP, and SH are respectively C69H43NO3, C166H93N3O8, C191H125N3O7, C169H105N3O7, and C221H123N3O7.

Parallel Prefetching for Canonical Ensemble Monte Carlo Simulations.

In order to enable large-scale molecular simulations, algorithms must efficiently utilize multicore processors that continue to increase in total core count over time with relatively stagnant clock speeds. Although parallelized molecular dynamics (MD) software has taken advantage of this trend in computer hardware, single-particle perturbations with Monte Carlo (MC) are more difficult to parallelize than system-wide updates in MD using domain decomposition. Instead, prefetching reconstructs the serial Markov chain after computing multiple MC trials in parallel. Canonical ensemble MC simulations of a Lennard-Jones fluid with prefetching resulted in up to a factor of 1.7 speedup using 2 threads, and a factor of 3 speedup using 4 threads. Strategies for maximizing efficiency of prefetching simulations are discussed, including the potentially counterintuitive benefit of reduced acceptance probabilities. Determination of the optimal acceptance probability for a parallel simulation is simplified by theoretical prediction from serial simulation data. Finally, complete open-source code for parallel prefetch simulations was made available in the Free Energy and Advance Sampling Simulation Toolkit (FEASST).

Parallel Prefetching for Canonical Ensemble Monte Carlo Simulations.

In order to enable large-scale molecular simulations, algorithms must efficiently utilize multi-core processors that continue to increase in total core count over time with relatively stagnant clock speeds. Although parallelized molecular dynamics (MD) software has taken advantage of this trend in computer hardware, single-particle perturbations with Monte Carlo (MC) are more difficult to parallelize than system-wide updates in MD using domain decomposition. Instead, prefetching reconstructs the serial Markov chain after computing multiple MC trials in parallel. Canonical ensemble simulations of a Lennard-Jones fluid with prefetching resulted in up to a factor of 1.7 speedup using 2 threads, and a factor of 3 speedup using 4 threads. Strategies for maximizing efficiency of prefetching simulations are discussed, including the potentially counter-intuitive benefit of reduced acceptance probabilities. Determination of the optimal acceptance probability for a parallel simulation is simplified by theoretical prediction from serial simulation data. Finally, complete open-source code for parallel prefetch simulations was made available in the Free Energy and Advance Sampling Simulation Toolkit (FEASST).

Electrical double layer in molten salts taking into account Lennard-Jones potential

Results are presented of canonical ensemble Monte Carlo simulations of molten salt electrical double layers. Electrode surface atoms and ions are modelled as soft spheres with the use of the Lennard-Jones potential. Ions and electrode atoms have the same diameter but differ in the applied energetic Lennard-Jones parameter values. The electrode surface consists of C (graphite), Hg or Pb atoms. The values of the applied parameters allow a comparison of the results obtained with those of real systems. The paper presents such results as: ion distributions, the mean electrostatic potential and differential capacitance. The differential capacitance values are collated with theoretical and experimental results. The capacitance curves obtained by simulations are flatter than experimental ones. The theoretical capacitance values, in contrast to the experimental ones, are smaller at the positive electrode potentials and this difference is due to the occurrence of chemical bonding between anions and electrode surface in experimental systems.

Size and charge correlations in spherical electric double layers: a case study with fully asymmetric mixed electrolytes within the solvent primitive model.

Size and charge correlations in spherical electric double layers are investigated through Monte Carlo simulations and density functional theory, through a solvent primitive model representation. A fully asymmetric mixed electrolyte is used for the small ions, whereas the solvent, apart from being a continuum dielectric, is also treated as an individual component. A partially perturbative density functional theory is adopted here, and for comparison, a standard canonical ensemble Monte Carlo simulation is used. The hard-sphere free energy is treated within a weighted density approach and the residual ionic contribution is estimated through perturbation around the uniform density. The results from both methods corroborate each other quantitatively over a wide range of physical parameters. The importance of structural correlations is envisaged through the size and charge asymmetry of the supporting electrolytes that includes the solvent as a component.

Investigation on Adsorption and Separation Behavior of Propane/Propene Mixtures in Zeolites.

Propane/propene separation is among the most energy-intensive separation processes in the petrochemical industry. Separation based on adsorption on a nanoporous material (e.g., zeolites) has spawned new ideas for this process. Therefore, we conducted grand canonical ensemble Monte Carlo simulations to investigate the adsorption and separation of propane and propene in one-dimensional (ATS, MOR, and AWO), two-dimensional (MWW, FER, and BOG) and three-dimensional (MFI, BEA, FAU) zeolites. The computation of pure components indicates that the adsorption capacity is affected by the zeolite pore diameter, dimensionality, and isosteric heat. For a given diameter, three dimensional zeolites exhibit better adsorption properties than two or one-dimensional zeolites. Zeolites with diameters ranging from 4.8 Å to 5.4 Å show high propane and propene affinity. In binary mixture simulations, the separation capacity of propane and propene increases with elevated pressure and decreased temperature. Among these zeolites, AWO exhibits the best separation performance due to its eight-ring window channel, which is consistent with experimental results. Thus, our results provide better understanding on propane and propene adsorption and separation in different zeolites, as well as insight into how production conditions could be upgraded.

Deep neural network learning of complex binary sorption equilibria from molecular simulation data.

We employed deep neural networks (NNs) as an efficient and intelligent surrogate of molecular simulations for complex sorption equilibria using probabilistic modeling. Canonical (N 1 N 2 VT) Gibbs ensemble Monte Carlo simulations were performed to model a single-stage equilibrium desorptive drying process for (1,4-butanediol or 1,5-pentanediol)/water and 1,5-pentanediol/ethanol from all-silica MFI zeolite and 1,5-pentanediol/water from all-silica LTA zeolite. A multi-task deep NN was trained on the simulation data to predict equilibrium loadings as a function of thermodynamic state variables. The NN accurately reproduces simulation results and is able to obtain a continuous isotherm function. Its predictions can be therefore utilized to facilitate optimization of desorption conditions, which requires a laborious iterative search if undertaken by simulation alone. Furthermore, it learns information about the binary sorption equilibria as hidden layer representations. This allows for application of transfer learning with limited data by fine-tuning a pretrained NN for a different alkanediol/solvent/zeolite system.

Lithium decoration of boron-doped hybrid fullerenes and nanotubes as a novel 3D architecture for enhanced hydrogen storage: A DFT study

A three dimensional (3D) dumbbell-like nanostructure composed by interconnected fullerenes and nanotubes with Lithium decoration and boron-doping (37Li@C139B31) has been proposed in virtue of density functional theory (DFT) and first-principles molecular dynamics (MD) simulations which shows excellent geometric and thermal stability. First-principles calculations are performed to investigate the hydrogen adsorption onto the 37Li@C139B31. The results indicate that B substitution can improve the metal binding and the average binding energy of 37 adsorbed Li atoms on the C139B31 (2.79 eV) is higher than the cohesive energy of bulk Li (1.63 eV) suppressing the clustering. Meanwhile, the H2 storage gravimetric density of 178H2@37Li@C139B31 reaches up to 15.9 wt% higher than the year 2020 target from the US department of energy (DOE). The average adsorption energy of H2 molecules falls in a desirable range of 0.18–0.27 eV. Moreover, grand canonical ensemble Monte Carlo (GCMC) simulations reveal that at room temperature the hydrogen gravimetric density (HGD) adsorbed on 37Li@C139B31 reaches up to 11.6 wt% at 100 bars higher than the DOE 2020 target. Our multiscale simulations indicate that our proposed nanostructure provides a promising medium for hydrogen storage.

Screening metal-organic frameworks for capturing radioactive gas Rn in indoor air.

The radioactive gas Rn in indoor air shows severe harm to the human body and even induces the occurence of lung cancer. Finding an excellent candidate that can efficiently and selectively adsorb Rn, is still a great challenge. In this work, we use the grand canonical ensemble Monte Carlo simulation to systematically investigate the selectivities of 23 different kinds of representative metal organic framework (MOFs) for Rn separation from the Rn/N2 and Rn/O2 mixtures at 298 K. Results indicate that ZIF-12, HKUST-1, IRMOF-62 and ZIF-11 are four kinds of excellent candidates for capturing Rn. In particular, the selectivities of ZIF-12 for Rn/N2 and Rn/O2 mixtures with Rn molar fraction XRn = 0.001 reach ∼2500 and 1200 at 1 atm and 298 K, respectively. Moreover, when the Rn concentration becomes smaller, the selectivity of ZIF-12 for Rn would increase significantly. In short, we found that ZIF-12 is indeed a very promising candidate for trapping radioactive Rn in indoor air.

The magnetization of dense aggregated dipolar fluids

The magnetization for dipolar fluids is studied treated separately at low and high external magnetic field. Canonical ensemble Monte Carlo simulations have been performed in dipolar hard sphere fluid in order to test these theoretical results. New expressions are introduced at low and high external field and ultimately the synthesized formula is given. The main difference in the structure of dipolar liquids at different external field is the average orientation of the formed chains. In case of infinitesimal external magnetic field there is no a well-specified direction, while at high enough external field actually the chains are parallel to this field. The present theory yields good result in the intermediate region as well where the most conspicuous failures are provided by the former theories.

Capture of CO2 in carbon nanotube bundles supported with room-temperature ionic liquids: A molecular simulation study

Novel gas adsorption properties by room-temperature ionic liquids (ILs) confined in carbon nanotube (CNT) bundles were ascertained using grand canonical ensemble Monte Carlo (GCMC) simulations in which the adsorption and separation of CO2 from CO2/N2 mixtures. The introduction of ILs into the CNT channels significantly enhances the adsorption of CO2, while it is not sensitive to N2 adsorption. This is due to the strong interaction between specific ILs in the CNTs and CO2 molecules. The presence of water showed a significant impact on the adsorption capacity of CO2 as well.

Competitive Adsorption Mechanism Study of CHClF2 and CHF3 in FAU Zeolite

Separating and recovering CHF3 and CHClF2 greenhouse gases from exhausted gases is quite important for avoiding adverse impacts to the environment. In synthesizing chlorofluorocarbons substitutes, faujasite (FAU) is proved to be effective in separating the hydrofluorocarbons. Grand canonical ensemble Monte Carlo simulations were used without precedent in analyzing the competitive adsorption mechanism of CHF3/CHClF2 in Na58Al58Si134O384 (58Al), Na88Al88Si104O384 (88Al), and Na96Al96Si96O384 (96Al) FAU zeolite model from infinite dilution to saturation adsorption, so as to explore the overall competitive relationship as the adsorption amount increases. As a result, it has been found that the sodium migration degree is affected by the guest–host effect in the 58A1 model. However, the sodium migration is not discovered in 88Al and 96Al models with diversified CHF3 or CHClF2 loadings. The preferred binding site in all FAU zeolite models involves CHClF2 and CHF3 anchored by cations in sites II and site III′. Ad...

Hybrid Monte Carlo with LAMMPS

We describe a strategy for performing canonical and isothermal-isobaric ensemble hybrid Monte Carlo (HMC) simulations with the widely-used Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics (MD) software package. The overall workflow for the HMC simulations is handled using an external Python driver script, which invokes LAMMPS’ library interface to perform numerically intensive tasks such as MD integration. We document several rigorous consistency checks that have been used to validate our HMC implementation. We also demonstrate that our approach can be readily extended to implement biased HMC sampling schemes for computing free energies. Codes and input files from the documented examples are available on the web.

All-silica zeolites screening for capture of toxic gases from molecular simulation

Abstract The exhaust gases, including SO2, NH3, H2S, NO2, NO, and CO, are principal air pollutants due to their severe harms to the ecological environment. Zeolites have been considered as good absorbent candidates to capture the six exhaust gases. In this work, we performed grand canonical ensemble Monte Carlo (GCMC) simulations to examine the capability of 95 kinds of all-silica zeolites in the removal of the six toxic gases, and to predict the adsorption isotherms of the six gases on all the zeolites. The simulation results showed that, H2S, NO, NO2, CO and NH3 are well-captured by zeolite structures with accessible surface area of 1600–1800 m2·g− 1 and pore diameter of 0.6–0.7 nm, such as AFY and PAU, while SO2 is well-adsorbed by zeolites containing larger accessible surface area (1700–2700 m2·g− 1) and pore diameter (0.7–1.4 nm) at room temperature and an atmospheric pressure. However, at saturated adsorption, zeolites RWY, IRR, JSR, TSC, and ITT are found to exhibit better abilities to capture these gases. Our study provides useful computational insights in choosing and designing zeolite structures with high performance to remove toxic gases for air purification, thereby facilitating the development and application of exhaust gas-processing technology in green industry.

Highly non-additive symmetric mixtures at a wall.

This paper discusses the results of the grand canonical ensemble Monte Carlo simulation of the wetting behavior of non-additive symmetric mixtures at non-selective walls. We have focused on the mixtures that exhibit closed immiscibility loops in the bulk, and the results obtained have demonstrated that such systems show a rather complex wetting behavior. In particular, such mixtures may exhibit a complete wetting at temperatures below the bulk demixing point, and an incomplete wetting at higher temperatures. Such a situation occurs when the adsorbed film remains mixed up to the bulk coexistence. However, close to the bulk tricritical point, being the onset of the continuous demixing transition (λ-line), a second wetting transition takes place. On the other hand, in the systems in which the adsorbed films undergo the demixing transition, a complete wetting may occur below as well as at and above the bulk demixing transition temperature. It has also been demonstrated that the wetting behavior depends strongly on the strength of the surface-fluid interaction.

Adsorption and separation of n/iso-pentane on zeolites: A GCMC study

Separation of branched chain hydrocarbons and straight chain hydrocarbons is very important in the isomerization process. Grand canonical ensemble Monte Carlo simulations were used to investigate the adsorption and separation of iso-pentane and n-pentane in four types of zeolites: MWW, BOG, MFI, and LTA. The computation of the pure components indicates that the adsorption capacity is affected by physical properties of zeolite, like pore size and structures, and isosteric heat. In BOG, MFI and LTA, the amount of adsorption of n-pentane is higher than iso-pentane, while the phenomenon is contrary in MWW. For a given zeolite, a stronger adsorption heat corresponds to a higher loading. In the binary mixture simulations, the separation capacity of n-and iso-pentane increases with the elevated pressure and the increasing iso-pentane composition. The adsorption mechanism and competition process have been examined. Preferential adsorption contributions prevail at low pressure, however, the size effect becomes important with the increasing pressure, and the relatively smaller n-pentane gradually competes successfully in binary adsorption. Among these zeolites, MFI has the best separation performance due to its high shape selectivity. This work helps to better understand the adsorption and separation performance of n- and iso-pentane in different zeolites and explain the relationship between zeolite structures and adsorption performance.