Combined Monte Research Articles

Magnetocrystalline anisotropy imprinting of an antiferromagnet on an amorphous ferromagnet in FeRh/CoFeB heterostructures

Magnetic anisotropy is a fundamental key parameter of magnetic materials that determines their applications. For ferromagnetic materials, the magnetic anisotropy can be easily detected by using conventional magnetic characterization techniques. However, due to the magnetic compensated structure in antiferromagnetic materials, synchrotron measurements, such as X-ray magnetic linear dichroism, are often needed to probe their magnetic properties. In this work, we observed an imprinted fourfold magnetic anisotropy in the amorphous ferromagnetic layer of FeRh/CoFeB heterostructures. The MOKE and ferromagnetic resonance measurements show that the easy magnetization axes of the CoFeB layer are along the FeRh〈110〉 and FeRh〈100〉 directions for the epitaxially grown FeRh layer in the antiferromagnetic and ferromagnetic states, respectively. The combined Monte Carlo simulation and first-principles calculation indicate that the fourfold magnetic anisotropy of the amorphous CoFeB layer is imprinted due to the interfacial exchange coupling between the CoFeB and FeRh moments from the magnetocrystalline anisotropy of the epitaxial FeRh layer. This observation of imprinting the magnetocrystalline anisotropy of antiferromagnetic materials on easily detected ferromagnetic materials may be applied to probe the magnetic structures of antiferromagnetic materials without using synchrotron methods.

Thermo-mechanical-microstructural simulation of double-pass welding process in a TWIP steel by FE formulation and probabilistic model

This research work developed a decoupled thermo-mechanical-microstructural (TMM) numerical framework to simulate a multi-pass welding process. The numerical framework was applied to evaluate the effect of operating parameters on the weldability of a twinning induced plasticity (TWIP) steel considering metallurgical defects and the weld joint’s mechanical properties. The thermo-mechanical model was solved numerically using a finite element model (FEM). After that, the simulation of the thermo-microstructural field was performed through a combined probabilistic approach Monte Carlo (MC)-Voronoi tessellation. The staggered solution approach and the optimized FE macro-scale mesh further improved the convergence and reduced computing time. The correlation of TMM model estimations with thermal history measurements and mechanical and metallographic characterizations helped explain the variation of post-welding mechanical properties. The nature of residual stresses in the TWIP steel joint was correlated with the heat flux in the critical weld regions. The thermal gradients were also correlated with the weld regions that underwent grain growth and grain size reduction. The grain growth simulation performed by the MC-Voronoi model was in good agreement with the hardness reduction in the heat-affected zone (HAZ). The grain size distribution in the HAZ produced an unexpected tensile elongation.

Characterizing moisture uptake and plasticization effects of water on amorphous amylose starch models using molecular dynamics methods

Dynamics and thermophysical properties of amorphous starch were explored using molecular dynamics (MD) simulations. Using the OPLS3e force field, simulations of short amylose chains in water were performed to determine force field accuracy. Using well-tempered metadynamics, a free energy map of the two glycosidic angles of an amylose molecule was constructed and compared with other modern force fields. Good agreement of torsional sampling for both solvated and amorphous amylose starch models was observed. Using combined grand canonical Monte Carlo (GCMC)/MD simulations, a moisture sorption isotherm curve is predicted along with temperature dependence. Concentration-dependent activation energies for water transport agree quantitatively with previous experiments. Finally, the plasticization effect of moisture content on amorphous starch was investigated. Predicted glass transition temperature (Tg) depression as a function of moisture content is in line with experimental trends. Further, our calculations provide a value for the dry Tg for amorphous starch, a value which no experimental value is available.

A Ti-MOF Decorated With a Pt Nanoparticle Cocatalyst for Efficient Photocatalytic H2 Evolution: A Theoretical Study.

Pt nanoparticles (NPs) are often used as cocatalysts to enhance the photocatalytic hydrogen production catalyzed by the metal organic framework (MOF) materials. The catalytic efficiency of many Pt/MOF systems can be greatly improved when Pt NPs are used as cocatalysts. In this work, the Pt/20%-MIL-125-(SCH3)2 was chosen as the template material to understand the functional role of a Pt metal cocatalyst in the catalytic process. Experimentally, the catalytic activity of Pt/20%-MIL-125-(SCH3)2 is more than 100 times that of the system without the help of Pt NPs. Firstly, we proposed a searching algorithm, which is based on the combined Monte Carlo (MC) method and principal component analysis (PCA) algorithm, to find that the most probable adsorption site of the Pt13 nanocluster loaded on the (001) surface of 20%-MIL-125-(SCH3)2. Next, by using density functional theory (DFT) and time-dependent density functional theory (TDDFT) methods, we revealed that the accumulation of some positive charges on the Pt13 cluster and proton adsorbed on the Pt13 cluster, which can promote the separation of photogenerated electrons and holes, thus improving the photocatalytic efficiency. This work not only provides a method to obtain the adsorption configuration of metal clusters on various MOFs but also provides a new insight into increasing photocatalytic efficiency for H2 production in Pt/MOF systems.

Very sharp diffraction peak in nonglass-forming liquid with the formation of distorted tetraclusters

Understanding the liquid structure provides information that is crucial to uncovering the nature of the glass-liquid transition. We apply an aerodynamic levitation technique and high-energy X-rays to liquid (l)-Er2O3 to discover its structure. The sample densities are measured by electrostatic levitation at the International Space Station. Liquid Er2O3 displays a very sharp diffraction peak (principal peak). Applying a combined reverse Monte Carlo – molecular dynamics approach, the simulations produce an Er–O coordination number of 6.1, which is comparable to that of another nonglass-forming liquid, l-ZrO2. The atomic structure of l-Er2O3 comprises distorted OEr4 tetraclusters in nearly linear arrangements, as manifested by a prominent peak observed at ~180° in the Er–O–Er bond angle distribution. This structural feature gives rise to long periodicity corresponding to the sharp principal peak in the X-ray diffraction data. A persistent homology analysis suggests that l-Er2O3 is homologically similar to the crystalline phase. Moreover, electronic structure calculations show that l-Er2O3 has a modest band gap of 0.6 eV that is significantly reduced from the crystalline phase due to the tetracluster distortions. The estimated viscosity is very low above the melting point for l-ZrO2, and the material can be described as an extremely fragile liquid.

The representation of sediment source group tracer distributions in Monte Carlo uncertainty routines for fingerprinting: An analysis of accuracy and precision using data for four contrasting catchments.

Previous studies comparing sediment fingerprinting un‐mixing models report large differences in their accuracy. The representation of tracer concentrations in source groups is perhaps the largest difference between published studies. However, the importance of decisions concerning the representation of tracer distributions has not been explored explicitly. Accordingly, potential sediment sources in four contrasting catchments were intensively sampled. Virtual sample mixtures were formed using between 10 and 100% of the retrieved samples to simulate sediment mobilization and delivery from subsections of each catchment. Source apportionment used models with a transformed multivariate normal distribution, normal distribution, 25th–75th percentile distribution and a distribution replicating the retrieved source samples. The accuracy and precision of model results were quantified and the reasons for differences were investigated. The 25th–75th percentile distribution produced the lowest mean inaccuracy (8.8%) and imprecision (8.5%), with the Sample Based distribution being next best (11.5%; 9.3%). The transformed multivariate (16.9%; 17.3%) and untransformed normal distributions (16.3%; 20.8%) performed poorly. When only a small proportion of the source samples formed the virtual mixtures, accuracy decreased with the 25th–75th percentile and Sample Based distributions so that when <20% of source samples were used, the actual mixture composition infrequently fell outside of the range of uncertainty shown in un‐mixing model outputs. Poor performance was due to combined random Monte Carlo numbers generated for all tracers not being viable for the retrieved source samples. Trialling the use of a 25th–75th percentile distribution alongside alternatives may result in significant improvements in both accuracy and precision of fingerprinting estimates, evaluated using virtual mixtures. Caution should be exercised when using a normal type distribution, without exploration of alternatives, as un‐mixing model performance may be unacceptably poor.

Combined multi-objective optimization and robustness analysis framework for building integrated energy system under uncertainty

The optimal design of building integrated energy system is sensitive to the variation of uncertain parameters. For addressing the tradeoff of uncertainty and optimality-robustness, this study proposes a combined multi-objective optimization and robustness analysis framework for optimal design of building integrated energy system. The proposed framework includes two parts. In the optimization part, on the basis of scenario generation for capturing the uncertainties of renewable energy sources and energy demands, two-stage multi-objective stochastic mixed-integer nonlinear programming is conducted to optimize the system‘s economic and environmental objectives. Two decision-making methods are introduced to identify the final optimum solution from the obtained Pareto frontier. In the robustness-analysis part, a combined Monte Carlo simulation and optimization method is implemented to verify the robustness of the optimal solutions. The two parts of the framework are integrated to investigate the case of a hotel in Beijing, China. The results indicate that compared with the stochastic model, the deterministic model underestimates the annual total cost. Achieving economic and environmental optimum is conflicting and needs a trade-off through decision making. Moreover, in the robustness analysis, an acceptable robustness value is identified, considering both the selected objectives and the operation constraints’ probability of failure. The Shannon-entropy-based final optimum solution exhibits the best comprehensive performance, with an annual total cost of $695 × 103/year, an annual carbon emissions of 2100 tons/year, and an 8.81% probability of failure.

C2H4 and C2H6 adsorption-induced structural variation of pillared-layer CPL-2 MOF: A combined experimental and Monte Carlo simulation study

Coordination pillared-layer metal-organic frameworks (CPL-MOFs), such as CPL-2, are interesting versatile and porous materials with the potential for gas adsorption and separation. CPL-2 shows the unusual and gradual linker rotation upon the adsorption of ethylene (C2H4) and ethane (C2H6), leading to a fully reversible adsorption isotherm specifically under the conditions studied. Grand canonical Monte Carlo (GCMC) simulations showed that it is impossible to accommodate the experimentally observed loadings of C2H4 and C2H6 in CPL-2 using the crystallographic structure reported in the literature. According to the simulation findings, the pore expansion might be initiated by the clockwise 4,4'-bipyridine (bpy) pillar linker rotation. The pillar rotation leads to the enlarged pore volume, rendering additional adsorption sites, which are not present in the pristine structure. In situ synchrotron PXRD experiments for C2H4 and C2H6 adsorption on CPL-2 confirmed the occurrence of pore expansion in CPL-2 MOF. The combined experimental and simulation study shows for the first time that the linker rotation in CPL-2 can result in a adsorption isotherm without hysteresis. This work developed a real insight into the nature of pillared-layer MOFs, and the revealed structural changes could be potentially exploited to enhance alkene and alkane working capacities of such microporous materials.

Adsorption of CO and desorption of CO2 interacting with Pt (111) surface: a combined density functional theory and Kinetic Monte Carlo simulation

The adsorption of CO and desorption of CO2 interacting with the Pt (111) surface was investigated using Kinetic Monte Carlo (kMC) simulation. The processes involved an elementary oxidation/reduction reaction (ORR). In comparison with standard density functional theory (DFT), kMC can simulate systems at practical time scale since it is concerned with the elementary reactions of the CO and O2 molecules adsorbed in the surface of the Pt system. The DFT results provide reliable estimates for adsorption and desorption energy barriers. The standard Arrhenius' equation serves as a working model to define the temperature dependence of individual elementary reaction rates (k). By incorporating the proper k obtained from DFT calculations into the kMC simulations, the study was able to reproduce acceptable result in agreement with practical microscopic reaction step occurring in the exhaust of gasoline engines. Thus, the kMC provides useful insight in the involved ORR steps in the interaction of CO and O2 with Pt. The ORR is sensitive to O–O dissociation compared with CO adsorption

Bayesian combined forecasts and Monte Carlo simulations to improve inflation rate predictions in Romania

In this paper we applied the regression approach and Bayesian inference to obtain more accurate forecasts of the inflation rate in the case of the Romanian economy. The necessity of using the most accurate forecasts for the inflation rate is required by the realisation of economic criteria for the accession to the eurozone and by the inflation targeting strategy of the National Bank of Romania. Considering the assumption that simple econometric models provide better forecasts than complex models, in this paper we combined various forecasts from individual models using as prior information the expectations of experts. The empirical findings for Romanian inflation rate forecasts over the horizon of 2016-2018 indicated that a fixed effects model performed better than other simple models (autoregressive moving average model, dynamic model, simple and multiple linear model, VAR, Bayesian VAR, simultaneous equations model). The Bayesian combined forecasts that used experts’ predictions as priors, with a shrinkage parameter tending to infinity, improved the accuracy of all predictions using individual models, outperforming also naive forecasts and zero and equal weights forecasts. However, predictions based on Monte Carlo simulation outperformed all the scenarios in terms of the mean error and mean absolute error.

A DFT and KMC based study on the mechanism of the water gas shift reaction on the Pd(100) surface.

We present a combined density functional theory (DFT) and Kinetic Monte Carlo (KMC) study of the water gas shift (WGS) reaction on the Pd(100) surface. We propose a mechanism comprising both the redox and the associative pathways for the WGS within a single framework, which consists of seven core elementary steps, which in turn involve splitting of a water molecule followed by the production of an H-atom and an OH-species on the Pd(100) surface. In the following steps, these intermediates then recombine with each other and with CO leading to the evolution of CO2, and H2. Seven other elementary steps, involving the diffusion and adsorption of the surface intermediate species are also considered for a complete description of the mechanism. The geometrical and electronic properties of each of the reactants, products, and the transition states of the core elementary steps are presented. We also discuss the analysis of Bader charges and spin densities for the reactants, transition states and the products of these elementary steps. Our study indicates that the WGS reaction progresses simultaneously via the direct oxidation and the carboxyl paths on the Pd(100) surface.

Realistic microstructure evolution of complex Ta-Nb-Hf-Zr high-entropy alloys by simulation techniques

Over last 15 years high-entropy alloys (HEAs) and complex concentrated alloys (CCAs) have gained much appreciation for their numerous superior properties. In this paper we have shown a novel simulation methodology to realistically predict the nanometer level local structural features of complex Ta0.25Nb0.25Hf0.25Zr0.25 HEA. This involves prediction of the morphology of the short-range clustering (SRCs), their quantitative atomic composition at the nano level and the thermodynamic aspects. An alloy structure model containing 11664 atoms was created and this was subjected to structure evolution at 1800 °C. The structure evolution technique is based on a combined hybrid Monte Carlo and molecular dynamics (MC/MD) approach. The simulated results from this work are further validated against experiments and material characterizations reported in literature and done by high-resolution transmission electron micrograph (HRTEM) for the nano-level microstructure, atom probe tomography (APT) for the local chemical compositions and X-ray diffraction at synchrotron sources for the local lattice relaxation effects. This work qualitatively and quantitatively reproduces the materials characterization results reasonably well from the developed simulation methodologies. The structure evolution methods as described in this work are based on independent computer simulations and does not involve any manual intervention for input based on experiments on evolving SRCs. This work shows the potential of utilizing MC/MD based computational methods to reduce the number of costly experimental characterizations and accelerate the pace for materials development.

Similarity in ruthenium damage induced by photons with different energies: From visible light to hard X-rays

We performed combined experimental and computational research on damage processes in ruthenium thin films induced by femtosecond lasers with various photon energies. We present an experiment with an optical laser at normal incidence conditions and compare it with previously reported experiments at grazing incidence conditions with XUV and hard X-ray photons, covering a large range of photon energies. Analysis of ablation craters in Ru shows very similar crater morphology and depth of about 10–20 nm for all considered irradiation conditions. Simulations of light-matter interactions are performed with our combined Monte Carlo and two-temperature hydrodynamics approach. The simulation results show that the primal cause of eventual ablation is Auger decay of core-shell holes created after absorption of XUV and hard X-ray photons in the vicinity of ruthenium surface. They lead to the creation of many low-energy electrons which consequently release the absorbed energy near the surface, resembling the optical irradiation case. Similar absorbed energy distributions in the top part of ruthenium induce a similar thermo-mechanical response and, therefore, similar ablation process. Our results suggest that such mechanism is universal in a wide range of photon energies at grazing incidence conditions, when the photon absorption depth is smaller than the photoelectrons range.

Evaluation of optoacoustic response with a combined Monte Carlo optical and acoustic simulation approach

Optoacoustic, or photoacoustic, imaging combines the penetration capabilities of ultrasound imaging with the contrast mechanism of optical absorption related to the photoacoustic effect. To enable modeling of photoacoustic measurements and imaging applications, the problem can be divided into modeling of the optical photon propagation and the resulting acoustic wave propagation. In highly scattering media such as soft tissues, Monte Carlo (MC) methods are used to evaluate photon propagation, absorption and the subsequent generation of a heat source that produces the photoacoustic effect. Acoustic wave equations are then used to model the propagation of the sound in the medium. However, if the appropriate physics could be modeled with a single tool, there would be advantages of consistency in spatial and temporal domains as well as easier integration of the optical and acoustic simulations. We propose using MC methods for optical photon propagation and for the acoustic wave propagation. The simulations are split into two stages for the optical photon propagation and the acoustic phonon propagation. We describe how the same MC framework is used to model photon propagation and acoustic phonon propagation. We will then demonstrate this new combined MC framework in models of photoacoustic problems in homogeneous and heterogeneous cases. These results will be compared with results from using k-Wave models for the acoustic wave propagation. The correspondence between k-Wave the acoustic MC model are shown to be in good agreement.

A combined variational and diagrammatic quantum Monte Carlo approach to the many-electron problem

Two of the most influential ideas developed by Richard Feynman are the Feynman diagram technique and his variational approach. Here we show that combining both, and introducing a diagrammatic quantum Monte Carlo method, results in a powerful and accurate solver to the generic solid state problem, in which a macroscopic number of electrons interact by the long range Coulomb repulsion. We apply it to the quintessential problem of solid state, the uniform electron gas, which is at the heart of the density functional theory success in describing real materials, yet it has not been adequately solved for over 90 years. Our method allows us to calculate numerically exact momentum and frequency resolved spin and charge response functions. This method can be applied to a number of moderately interacting electron systems, including models of realistic metallic and semiconducting solids.

Wind Energy Generation Assessment at Specific Sites in a Peninsula in Malaysia Based on Reliability Indices

This paper presents a statistical analysis of wind speed data that can be extremely useful for installing a wind generation as a stand-alone system. The main objective is to define the wind power capacity’s contribution to the adequacy of generation systems for the purpose of selecting wind farm locations at specific sites in Malaysia. The combined Sequential Monte Carlo simulation (SMCS) technique and the Weibull distribution models are employed to demonstrate the impact of wind power in power system reliability. To study this, the Roy Billinton Test System (RBTS) is considered and tested using wind data from two sites in Peninsular Malaysia, Mersing and Kuala Terengganu, and one site, Kudat, in Sabah. The results showed that Mersing and Kudat were best suitable for wind sites. In addition, the reliability indices are compared prior to the addition of the two wind farms to the considered RBTS system. The results reveal that the reliability indices are slightly improved for the RBTS system with wind power generation from both the potential sites.

Effect of collagenase\u2013gelatinase ratio on the mechanical properties of a collagen fibril: a combined Monte Carlo\u2013molecular dynamics study

Loading in cartilage is supported primarily by fibrillar collagen, and damage will impair the function of the tissue, leading to pathologies such as osteoarthritis. Damage is initiated by two types of matrix metalloproteinases, collagenase and gelatinase, that cleave and denature the collagen fibrils in the tissue. Experimental and modeling studies have revealed insights into the individual contributions of these two types of MMPs, as well as the mechanical response of intact fibrils and fibrils that have experienced random surface degradation. However, no research has comprehensively examined the combined influences of collagenases and gelatinases on collagen degradation nor studied the mechanical consequences of biological degradation of collagen fibrils. Such preclinical examinations are required to gain insights into understanding, treating, and preventing degradation-related cartilage pathology. To develop these insights, we use sequential Monte Carlo and molecular dynamics simulations to probe the effect of enzymatic degradation on the structure and mechanics of a single collagen fibril. We find that the mechanical response depends on the ratio of collagenase to gelatinase—not just the amount of lost fibril mass—and we provide a possible mechanism underlying this phenomenon. Overall, by characterizing the combined influences of collagenases and gelatinases on fibril degradation and mechanics at the preclinical research stage, we gain insights that may facilitate the development of targeted interventions to prevent the damage and loss of mechanical integrity that can lead to cartilage pathology.

Investigating CO2 Sorption in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn) through Computational Studies

A combined Monte Carlo (MC) simulation and periodic density functional theory (DFT) study of CO2 sorption was performed in SIFSIX-3-M (M = Fe, Co, Ni, Cu, Zn), a family of hybrid ultramicroporous m...

Regulating Second-Harmonic Generation by van der Waals Interactions in Two-dimensional Lead Halide Perovskite Nanosheets.

The flexible organic amine cations on the interfaces of two-dimensional (2D) hybrid organic-inorganic perovskite nanosheets could form relaxed structures, which would lead to exotic optoelectronic properties but are hard to understand. Here, the unusual interfacial relaxation of nanosheets exfoliated from an orthorhombic 2D lead halide perovskite, [(C6H5CH2NH3)2]PbCl4, is interrogated via ultrafast second-harmonic generation (SHG) spectroscopy. The in-plane SHG intensity anisotropy of these nanosheets is found to decrease with reducing layer thickness. Combined first-principles calculations and Monte Carlo simulations reveal that the induced second-order polarization arises primarily from the (C6H5CH2NH3)+ cations; and these organic amine cations form significantly reorganized conformations with decreasing nanosheet thickness due to weakened van der Waals interactions. Because the orientations of organic components at the interface determine their electric properties and specifically the dipolar susceptibility, the resulting structure leads to striking changes in the SHG properties.

Validation of combined Monte Carlo and photokinetic simulations for the outcome correlation analysis of benzoporphyrin derivative-mediated photodynamic therapy on mice.

.We compare previously reported benzoporphyrin derivative (BPD)-mediated photodynamic therapy (PDT) results for reactive singlet oxygen concentration (also called singlet oxygen dose) on mice with simulations using a computational device, Dosie™, that calculates light transport and photokinetics for PDT in near real-time. The two sets of results are consistent and validate the use of the device in PDT treatment planning to predict BPD-mediated PDT outcomes in mice animal studies based on singlet oxygen dose, which showed a much better correlation with the cure index than the conventional light dose.