Monte Carlo Theory Research Articles

Enhancing the natural gas upgrading and acetylene extraction performance of stable zirconium-organic frameworks PCN-605 by ligand functionalization

Exploring stable adsorbents for efficient separation of C2H2 and CO2 from CH4 is of great significance to meet the requirements of natural gas upgrading and high-purity C2H2 production. Despite excellent structure stability and large surface area/pore volume, low adsorbate affinity and co-adsorption of mixtures in zirconium-organic frameworks (Zr-MOFs) seriously limit their applications in gas separation. To overcome these limitations, we designed a series of stable adsorbents based on Zr-based PCN-605 by replacing two H atoms from two central ligand-aromatic rings with different functional groups (–F, –OH, –NH2, –SO3H, and –SO3Ag), which are expected to gain steric hindrance effect and charge-tuning effect in varying degrees. The adsorption and separation performances of C2H2/CH4 and CO2/CH4 in PCN-605 materials were theoretically investigated by combining grand canonical Monte Carlo and density functional theory. Thereinto, PCN-605-SO3Ag shows the largest selectivity of C2H2/CH4 (1031.5) and CO2/CH4 (271.1) under molar ratio 1:99 at 298 K, or increased by 43.3 and 11.9 times, as against the parent PCN-605. This improvement is attributed to a good synergism of steric hindrance effect with charge-tuning effect exerted by –SO3Ag, which modifies not only the pore surface structure but also the charge distribution, favoring special three-way adsorption to recognize C2H2, strengthening CO2 affinity with –SO3Ag, but suppressing CH4 uptake, etc. This work highlights the effect of precise surface-structure and charge-distribution control by ligand functionalization on C2H2/CH4 and CO2/CH4 separation in PCN-605 materials, and provides a feasible strategy to design function-oriented Zr-MOF adsorbents for applications of natural gas upgrading and C2H2 extraction.

The use of Monte Carlo simulation to evaluate the optical properties of polyester fabric treated with titanium dioxide nanopigments

AbstractThe current study utilises Monte Carlo simulation and Mie scattering theory to estimate the reflectance spectra of fabric coated with titanium dioxide nanopigments of various diameters and concentrations. Image processing was carried out and experimental data were gathered to evaluate the performance of Monte Carlo simulation. The distribution and location of the nanopigments on the surface of fabric were determined using the Monte Carlo method. Reflection of the fabric was calculated based on Monte Carlo simulation with the partitive mixing method and Mie theory. According to the experimental and simulation results, the reflectance of coated samples was increased by increasing the concentration and number of titanium dioxide nanoparticles. There was a good match between the results obtained by Monte Carlo simulation and the experimental results. For coated samples (dTiO2: 500 nm), the root mean square error between measured and predicted reflectance by the Monte Carlo and partitive mixing method and by Monte Carlo and Mie theory was 0.022 and 0.0078, respectively. The results indicate that the performance of the Monte Carlo and Mie method was better than that of the Monte Carlo and partitive mixing method. According to t‐test analysis, there was no statistically significant difference between the experimental data and Monte Carlo simulation.

Point defect formation energies in graphene from diffusion quantum Monte Carlo and density functional theory

Density functional theory (DFT) is widely used to study defects in monolayer graphene with a view to applications ranging from water filtration to electronics to investigation of radiation damage in graphite moderators. To assess the accuracy of DFT in such applications, we report diffusion quantum Monte Carlo (DMC) calculations of the formation energies of some common and important point defects in monolayer graphene: monovacancies, Stone-Wales defects, and silicon substitutions. We find that standard DFT methods underestimate monovacancy formation energies by around 1 eV. The disagreement between DFT and DMC is somewhat smaller for Stone-Wales defects and silicon substitutions. We examine vibrational contributions to the free energies of formation for these defects, finding that vibrational effects are non-negligible. Finally, we compare the DMC atomization energies of monolayer graphene, monolayer silicene, and bulk silicon, finding that bulk silicon is significantly more stable than monolayer silicene by 0.7522(5) eV per atom.

Interplay of magnetic field and trigonal distortion in the honeycomb Γ model: Occurrence of a spin-flop phase

In candidate Kitaev materials, the off-diagonal $\Gamma$ and $\Gamma'$ interactions are identified to come from the spin-orbit coupling and trigonal distortion, respectively. They have generated intense research efforts because of their intimate relation to the field-induced magnetically disordered state reported in $\alpha$-RuCl$_3$. Theoretically, while a plethora of field-induced phases has been proposed in the honeycomb lattice, a stable intermediate phase that can survive in a wide parameter region regardless of the underlying phases is still lacking. Here we focus on the interplay of an out-of-plane magnetic field and a symmetry-allowed $\Gamma'$ term due to trigonal distortion in the dominant antiferromagnetic $\Gamma$ region. By using multifaceted approaches ranging from classical Monte Carlo and semiclassical spin-wave theory to density-matrix renormalization group, we identify an intriguing spin-flop phase in the presence of magnetic field and antiferromagnetic $\Gamma'$ interaction, before it eventually enters into a fully polarized state. As the $\Gamma'$ interaction approaches the size of $\Gamma$ one, the $\Gamma$-$\Gamma'$ model maps to the easy-axis XXZ antiferromagnet, where the spin-flop phase can be understood as a superfluid phase in the extended Bose-Hubbard model. Our finding thus demonstrates an exciting path from the honeycomb $\Gamma$ model towards a $U(1)$-symmetric XXZ antiferromagnet in a magnetic field.

Theoretical Study of the Isotope and Homologue Effects on Nuclear Magnetic Shielding in Water and Hydrogen Sulfide Molecules

Abstract The hydrogen/deuterium isotope and oxygen/sulfur homologue effects on the absolute nuclear magnetic shielding constants were theoretically analyzed for five 17O-water isotopologues and five hydrogen sulfide isotopologues. Using both ab initio calculations and anharmonic vibrational structure calculations based on vibrational quantum Monte Carlo theory, we confirmed that the changes in the atomic charges are strongly correlated with the enhancements of the absolute nuclear magnetic shielding constants.

Quantifying the evolutionary mechanism of COVID-19 impact on international construction multi-projects: a risk driver perspective

Purpose The purpose of this paper is to quantify the evolutionary mechanism of coronavirus disease 2019 (COVID-19) impact on international construction multi-projects.Design/methodology/approach From three concepts of complexity, stressor and detractor risks, a multi-project simulation model under COVID-19 outbreak is proposed to study the characteristics of contingency with three peaks of ordered and disordered states. Specially, COVID-19 brings forth mitigation fee, epidemic prevention fee, holdup fee and schedule delay fee of multi-projects. By integrating parametric model, Monte Carlo and chaos theory, a comparative analysis of its contingency with or without COVID-19 is conducted. Summarizing the simulated results, their total contingencies at certain risk tolerance are obtained at two status of static at one-time point and dynamic over time. Meanwhile, some major risks including detractors, complexities and stressors are screened out for mitigation, especially for epidemic prevention and control. Eventually, the real case is illustrated to demonstrate its validity.Findings It provides a quantitative analysis framework for the impact of epidemic, a once-in-a-century black swan event with a long tail, on construction multi-projects.Practical implications It conduct an effective model to quantify impacts of COVID-19 on international construction multi-projects for implementing effective counter-measures, which lay foundation for claims among different stakeholders.Originality/value The term of detractor risk is applied to describe COVID-19 and quantify its impact upon international construction multi-projects. Further, a hybrid model by integrating parametric model and Monte Carlo in type I/II model is proposed to simulate their contingencies at disordered states. Finally, the simulated outcomes of these models are used to guide effective risk control to meet the requirements by the client.

Molecular Simulation on Competitive Adsorption Differences of Gas with Different Pore Sizes in Coal.

Micropores are the primary sites for methane occurrence in coal. Studying the regularity of methane occurrence in micropores is significant for targeted displacement and other yield-increasing measures in the future. This study used simplified graphene sheets as pore walls to construct coal-structural models with pore sizes of 1 nm, 2 nm, and 4 nm. Based on the Grand Canonical Monte Carlo (GCMC) and molecular dynamics theory, we simulated the adsorption characteristics of methane in pores of different sizes. The results showed that the adsorption capacity was positively correlated with the pore size for pure gas adsorption. The adsorption capacity increased with pressure and pore size for competitive adsorption of binary mixtures in pores. As the average isosteric heat decreased, the interaction between the gas and the pore wall weakened, and the desorption amount of CH4 decreased. In ultramicropores, the high concentration of CO2 (50–70%) is more conducive to CH4 desorption; however, when the CO2 concentration is greater than 70%, the corresponding CH4 adsorption amount is meager, and the selected adsorption coefficient SCO2/CH4 is small. Therefore, to achieve effective desorption of methane in coal micropores, relatively low pressure (4–6 MPa) and a relatively low CO2 concentration (50–70%) should be selected in the process of increasing methane production by CO2 injection in later stages. These research results provide theoretical support for gas injection to promote CH4 desorption in coal pores and to increase yield.

The Investigation of Hydrogen Adsorption in MOF NU‐1501 with Different Metal Doping using Molecular Simulations

AbstractMetal‐organic frameworks with high surface areas are currently being widely used for in‐depth studies on hydrogen storage with the aim of discussing the difficulties created by environmental degradation caused by the burning of fossil fuels. Understanding the effect of varied metal ion doping on adsorption position and energy is crucial to understanding the adsorption process. The adsorption behavior of NU‐1501‐Al and NU‐1501‐Fe was investigated using a combination of Grand Canonical Monte Carlo and Density Functional Theory in this study. The calculations reveal that aluminum has a larger charge than iron and higher adsorption energy. As the loading increases, hydrogen is primarily adsorbed by metal atoms and the carbon atoms of the metal‐benzene ring are connected to metal‐oxygen atoms. The research hopes to provide molecular‐level insights into the adsorption behavior of porous materials doped with different metals, which could be used to screen materials that improve gas adsorption, separation, and other expansion characteristics.

Creating Optimal Pockets in a Clathrochelate-Based Metal-Organic Framework for Gas Adsorption and Separation: Experimental and Computational Studies.

The rational design and synthesis of robust metal-organic frameworks (MOFs) based on novel organic building blocks are fundamental aspects of reticular chemistry. Beyond simply fabricating new organic linkers, however, it is important to elucidate structure-property relationships at the molecular level to develop high-performing materials. In this work, we successfully targeted a highly porous and robust cage-type MOF (NU-200) with an nbo-derived fof topology through the deliberate assembly of a cyclohexane-functionalized iron(II)-clathrochelate-based meta-benzenedicarboxylate linker with a Cu2(CO2)4 secondary building unit (SBU). NU-200 exhibited an outstanding adsorption capacity of xenon and a high ideal adsorbed solution theory (IAST) predicted selectivity for a 20/80 v/v mixture of xenon (Xe)/krypton (Kr) at 298 K and 1.0 bar. Our extensive computational simulations with grand canonical Monte Carlo (GCMC) and density functional theory (DFT) on NU-200 indicated that the MOF's hierarchical bowl-shaped nanopockets surrounded by custom-designed cyclohexyl groups─instead of the conventionally believed open metal sites (OMSs)─played a crucial role in reinforcing Xe-binding affinity. The optimally sized pockets firmly trapped Xe through numerous supramolecular interactions including Xe···H, Xe···O, and Xe···π. Additionally, we validated the unique pocket confinement effect by experimentally and computationally employing the similarly sized probe, sulfur dioxide (SO2), which provided significant insights into the molecular underpinnings of the high uptake of SO2 (11.7 mmol g-1), especially at a low pressure of 0.1 bar (8.5 mmol g-1). This work therefore can facilitate the judicious design of organic building blocks, producing MOFs featuring tailor-made pockets to boost gas adsorption and separation performances.

Excitonic-insulator instability and Peierls distortion in one-dimensional semimetals

The charge density wave instability in one-dimensional semimetals is usually explained through a Peierls-like mechanism, where the coupling of electrons and phonons induces a periodic lattice distortion along certain modes of vibration, leading to a gap opening in the electronic band structure and to a lowering of the symmetry of the lattice. In this work, we study two prototypical Peierls systems: the one-dimensional carbon chain and the monatomic hydrogen chain with accurate ab initio calculations based on quantum Monte Carlo and hybrid density functional theory. We demonstrate that in one-dimensional semimetals at $T=0$, a purely electronic instability can exist independently of a lattice distortion. It is induced by spontaneous formation of low energy electron-hole pairs resulting in the electronic band gap opening, i.e., the destabilization of the semimetallic phase is due to an excitonic mechanism.

Fractional and composite excitations of antiferromagnetic quantum spin trimer chains

Using quantum Monte Carlo, exact diagonalization, and perturbation theory, we study the spectrum of the S = 1/2 antiferromagnetic Heisenberg trimer chain by varying the ratio g = J2/J1 of the intertrimer and intratrimer coupling strengths. The doublet ground states of trimers form effective interacting S = 1/2 degrees of freedom described by a Heisenberg chain. Therefore, the conventional two-spinon continuum of width ∝ J1 when g = 1 evolves into to a similar continuum of width ∝ J2 when g → 0. The intermediate-energy and high-energy modes are termed doublons and quartons which fractionalize with increasing g to form the conventional spinon continuum. In particular, at g ≈ 0.716, the gap between the low-energy spinon branch and the high-energy band with mixed doublons, quartons, and spinons closes. These features should be observable in inelastic neutron scattering experiments if a quasi-one-dimensional quantum magnet with the linear trimer structure and J2 < J1 can be identified. Our results may open a window for exploring the high-energy fractional excitations.

Efficient Xe/Kr separation on two Metal-Organic frameworks with distinct pore shapes

Adsorptive separation of xenon (Xe) from krypton (Kr) is challenging owing to their low concentrations and similar physical properties. Herein, we report two metal–organic frameworks (MOFs) assembled from the same aliphatic ligand (trans-1, 4-cyclohexanedicarboxylic acid, H2CDC), but showing distinct pore shapes. The rhombus pores on Al-CDC show a narrower pore aperture of 4.5 Å × 6.0 Å, contracting to the pseudo-square pores (5.8 Å × 6.8 Å) on Cu-CDC. As a result, Al-CDC exhibits a high Xe adsorption capacity (2.45 mmol g−1) and Xe/Kr selectivity (10.7) at 298 K and 1.0 bar. The confined pore space and abundant saturated C-H groups provide stronger van der Waals interactions toward Xe, which is disclosed by the Grand Canonical Monte Carlo (GCMC) and Density Functional Theory (DFT) calculations. Dynamic breakthrough experiments further confirm their industrial application potential and stable reusability.

Electrochemical studies and molecular simulations on the use of molybdic acid for stabilization of AISI 304 stainless steel passive film in sulfuric acid medium

In this work, the corrosion of AISI 304 stainless steel (SS) in the absence and presence of different concentrations of molybdic acid was investigated using potentiodynamic polarization, open circuit potential (OCP) measurements, electrochemical impedance spectroscopy (EIS), Mott-Schottky analysis (MS) and theoretical simulations including molecular dynamics (MD), Monte Carlo (MC), and density functional theory (DFT). Although it is obvious that the use of molybdate ions can improve the anti-corrosion properties of austenitic SS, there are fewer comprehensive reports which has been devoted to “investigation of electrochemical properties of passive film” and/or “theoretical studies using molecular-scale simulations”. Therefore, the present study focused on examining these two issues. The results of potentiodynamic polarization showed that molybdic acid not only can reduce the corrosion rate but also decrease the critical current density (icrit) for passive film formation. MS analysis revealed the donor density in the passive film was increased up to 6.6 × 1020 cm−3 by increasing the molybdic acid concentration to 0.02 mM. The computational studies associated with MD and MC simulations showed that the adsorption energy of molybdic acid, as an inhibitor on steel surface, is −35.4 and −98.3 kcal mol−1, respectively. Moreover, the HOMO and LUMO energies and the energy difference between them were calculated by DFT simulation.

Multi-objective optimization of alkali/alkaline earth metals doped graphyne for ultrahigh-performance CO2 capture and separation over N2/CH4

Adsorbents with excellent CO2 capture and separation performances are critical in reducing the excessive CO2 concentration in the atmosphere. Herein, alkali/alkaline earth metals doped graphynes (AMn-GYs, AM = Li, Na, K, Mg and Ca; GY = graphyne; n = 0.5, 1, and 2) were evaluated by employing grand canonical Monte Carlo and density functional theory approaches. The results showed that AMs were strongly bonded on GY with binding energies of −0.09 to −2.52 eV and diffusion barriers of 5.20–16.32 eV. Electronic structure analyses proved that there was a strong covalent bond, large charge transfer, and distinct orbital overlap characters between the AMs and GY, thus constructing a stable and feasible gas adsorption environment. Among all structures, AM1-GYs with one AM doping in a GY unit cell displayed the best CO2 adsorption behavior. Thereafter, Li1/Na1/K1-GY with a pore size of 6.60 Å and Mg1/Ca1-GY with a pore size of 6.50 Å were screened as the potential adsorbents. In comparison, the best performing Ca1-GY had an ultra-high CO2 adsorption capacity of 9.01 mmol/g at 298 K and 1 bar, which was superior to most of the previously reported adsorbents. At 298 K and 1 bar, the CO2 selectivity over N2/CH4 for Ca1-GY reached 2246 and 5602, respectively. Interaction and gas distribution analysis confirmed that comparing to other AM1-GYs, Ca1-GY has a stronger affinity with CO2 and larger isosteric heat differences between CO2 and other gases, rendering Ca1-GY to possess excellent adsorption capacity and selectivity.

A comprehensive wind speed prediction system based on Monte Carlo and artificial intelligence algorithms

Wind energy has strong volatility and intermittent. Accurate wind speed prediction can not only improve the safety of the system, but also optimize dispatch and reduce economic losses. However, previous studies tend to ignore the influence of virtual components and lack effective identification of wind speed characteristics and a robust interval prediction scheme, resulting in poor results. To bridge these gaps, this paper proposes an energy theory method to solve the problem of modal over-decomposition. The study also combines effective modal recognition, uses different prediction methods according to modal characteristics and proposes a set of new optimization algorithms to improve nonlinear prediction capabilities. Finally, based on Monte Carlo theory, a set of interval prediction schemes that can adapt to different error characteristics are proposed. Under the verification of wind speed data in Changma, China and Sotavento, Spain. The mean absolute percentage error of wind speed deterministic prediction reaches 4.22% and 5.82%, respectively. The coverage rate of wind speed uncertainty prediction meets different confidence requirements, and the average interval width is still less than 2.5 m/s at 90% confidence. The results show that the forecasting system proposed in this paper is significantly better than all the comparative forecasting schemes, which can reduce the risk of fluctuations and improve the stability and safety of the wind power system.

Nitrogen‐rich melamine cyanurate derived hollow porous carbon microspheres prepared through CuCl2 activation for VOCs adsorption

AbstractNitrogen‐enriched porous carbon material with large specific surface area is of great demand in various applications. Herein, CuCl2 is adapted as a mild activator to transform the mixture of soybean meal and melamine cyanurate into a novel type of nitrogen‐enriched hollow porous carbon microspheres with well‐defined hierarchically structure. Excitingly, this mild activation agent not only helps generating porous structure, but also helps increasing the nitrogen content (mainly pyrrolic‐N) of products. The product NPC‐800‐4 exhibits the highest specific surface area (1672.45 m2 g−1) while a pretty high nitrogen content (13.09 at%). The NPC‐800‐4 sample performs the largest toluene and acetone adsorption capacity (818.46 mg g−1 and 758.87 mg g−1 respectively). Furthermore, Grand canonical Monte Carlo (GCMC) and density functional theory (DFT) calculations prove that the introduction of nitrogen functional groups can heighten the polarity of carbon framework and the electrostatic interaction, thus enhance the acetone adsorption capacity.

A Time-Varying Coupling Analysis of Expressway Traffic Volume and Manufacturing PMI

This study investigates the time-varying coupling relationship between expressway traffic volume and manufacturing purchasing manager index (PMI). First, for the traffic volume and manufacturing PMI time-series data, unit root stability test and Johansen cointegration test are applied to determine the stability of single sequence and the long-term stable correlation between variables, respectively. Then, a time-varying vector autoregressive model (TVP-VAR) is developed to quantify the time-varying correlation between variables. The time-varying parameters of TVP-VAR are estimated using the Markov chain Monte Carlo (MCMC) theory. Finally, the model is validated using examples from China. In the numeric example, three variables, i.e., expressway car traffic volume, expressway truck traffic volume, and manufacturing PMI, are selected for analysis. Results show that there is a positive interaction between expressway traffic volume (both car and truck) and manufacturing PMI. Express traffic volume slowly promotes the development of manufacturing industry. However, with the reform policy of road freight structure in China, the promotion effect of truck traffic on manufacturing PMI in the past two years has decreased significantly. Moreover, as affected by the China demand-led economic development model in recent years, the stimulus effect of manufacturing PMI on expressway passenger traffic volume has increased year by year. And, while the expressway freight structure remains stable, truck traffic volume is hardly affected by fluctuations in manufacturing PMI. These research results are helpful for policy makers to understand the time-varying coupling relationship between expressway traffic volume and manufacturing development and finally to improve the expressway management level.

An applied methodology for tolerance design based on concurrent engineering

Abstract. Tolerance design is an important part of the product development and manufacturing process. Studies show that using a reliable and efficient tolerance design method can effectively improve product quality and reduce manufacturing costs. Although numerous studies have been carried out in the area of tolerance analysis, combining the tolerance analysis with the concurrent engineering theory has been rarely studied so far. In order to resolve this shortcoming, a comprehensive tolerance design methodology based on concurrent engineering was proposed in the present study to shorten the product development cycle, improve product quality, and reduce manufacturing costs. To this end, experts from different engineering fields were employed to form a concurrent engineering team that works together. The tolerance design activities were divided into seven stages, including design requirements definition, dimension chain identification, initial geometric dimensioning and tolerancing, variation analysis, release technical specification, validation, and continuous improvement. Then the detailed work process of each stage is presented. Based on the Monte Carlo theory and 3D computer-aided tolerance software, a variation analysis framework was proposed. Finally, the gap between taillight and bodyside was considered a test case, and a specific operation method of tolerance design using this framework is expounded. In the studied cases, the calculated and measured mean value of the gap was 1.5 and 1.5368 mm, respectively, indicating the simulation error of 2.5 %. The obtained results show that the gap tolerance by the proposed method is consistent with the tolerance fluctuation in actual production.

Magnetic properties of NbSi2N4, VSi2N4, and VSi2P4 monolayers

The recent demonstration of MoSi2N4 and its exceptional stability to air, water, acid, and heat has generated intense interest in this family of two-dimensional materials. Among these materials, monolayers of NbSi2N4, VSi2N4, and VSi2P4 are semiconducting, easy-plane ferromagnets with negligible in-plane magnetic anisotropy. They, thus, satisfy a necessary condition for exhibiting a dissipationless spin superfluid mode. The Curie temperatures of monolayer VSi2P4 and VSi2N4 are determined to be above room temperature based on Monte Carlo and density functional theory calculations. The magnetic moments of VSi2N4 can be switched from in-plane to out-of-plane by applying tensile biaxial strain or electron doping.

Phase diagram of the anisotropic triangular lattice Hubbard model

In a recent study [Phys. Rev. X 10, 021042 (2020)], we showed using large-scale density matrix renormalization group (DMRG) simulations on infinite cylinders that the triangular lattice Hubbard model has a chiral spin liquid phase. In this work, we introduce hopping anisotropy in the model, making one of the three distinct bonds on the lattice stronger or weaker compared with the other two. We implement the anisotropy in two inequivalent ways, one which respects the mirror symmetry of the cylinder and one which breaks this symmetry. In the full range of anisotropy, from the square lattice to weakly coupled one-dimensional chains, we find a variety of phases. Near the isotropic limit we find the three phases identified in our previous work: metal, chiral spin liquid, and 120$^\circ$ spiral order; we note that a recent paper suggests the apparently metallic phase may actually be a Luther-Emery liquid, which would also be in agreement with our results. When one bond is weakened by a relatively small amount, the ground state quickly becomes the square lattice N\'{e}el order. When one bond is strengthened, the story is much less clear, with the phases that we find depending on the orientation of the anisotropy and on the cylinder circumference. While our work is to our knowledge the first DMRG study of the anisotropic triangular lattice Hubbard model, the overall phase diagram we find is broadly consistent with that found previously using other methods, such as variational Monte Carlo and dynamical mean field theory.