Monte Carlo Computer Simulations Research Articles

Molecular Simulation Studies of Pharmaceutical Pollutant Removal (Rosuvastatin and Simvastatin) Using Novel Modified-MOF Nanostructures (UIO-66, UIO-66/Chitosan, and UIO-66/Oxidized Chitosan).

The ubiquitous presence of pharmaceutical pollutants in the environment significantly threatens human health and aquatic ecosystems. Conventional wastewater treatment processes often fall short of effectively removing these emerging contaminants. Therefore, the development of high-performance adsorbents is crucial for environmental remediation. This research utilizes molecular simulation to explore the potential of novel modified metal-organic frameworks (MOFs) in pharmaceutical pollutant removal, paving the way for the design of efficient wastewater treatment strategies. Utilizing UIO-66, a robust MOF, as the base material, we developed UIO-66 functionalized with chitosan (CHI) and oxidized chitosan (OCHI). These modified MOFs' physical and chemical properties were first investigated through various characterization techniques. Subsequently, molecular dynamics simulation (MDS) and Monte Carlo simulation (MCS) were employed to elucidate the adsorption mechanisms of rosuvastatin (ROSU) and simvastatin (SIMV), two prevalent pharmaceutical pollutants, onto these nanostructures. MCS calculations demonstrated a significant enhancement in the adsorption energy by incorporating CHI and OCHI into UIO-66. This increased ROSU from -14,522 to -16,459 kcal/mol and SIMV from -17,652 to -21,207 kcal/mol. Moreover, MDS reveals ROSU rejection rates in neat UIO-66 to be at 40%, rising to 60 and 70% with CHI and OCHI. Accumulation rates increase from 4 Å in UIO-66 to 6 and 9 Å in UIO-CHI and UIO-OCHI. Concentration analysis shows SIMV rejection surges from 50 to 90%, with accumulation rates increasing from 6 to 11 Å with CHI and OCHI in UIO-66. Functionalizing UIO-66 with CHI and OCHI significantly enhanced the adsorption capacity and selectivity for ROSU and SIMV. Abundant hydroxyl and amino groups facilitated strong interactions, improving performance over that of unmodified UIO-66. Surface functionalization plays a vital role in customizing the MOFs for pharmaceutical pollutant removal. These insights guide next-gen adsorbent development, offering high efficiency and selectivity for wastewater treatment.

A method of calculating weighted values of objective traits for BLUP of breeding values to achieve relative desired changes.

A method of calculating weighted values for objective traits from the phenotypic records of all animals in a population was devised as an alternative to the conventional method of calculating weighted values from a family selection index. The genetic improvement of this method was verified by Monte Carlo computer simulation. A base population consisting of 10 males and 50 females, and five separate generations, other than the base population that had been randomly selected, was bred for two traits with different heritabilities. The breeding values of animals in generation five were estimated using the bivariate BLUP method. The three different weighted values obtained from this method and two conventional methods for estimated breeding values of the objective traits were used to estimate aggregate breeding values for selection. The results showed that selection using weighted values calculated from all animals in a population resulted in a greater response to selection, especially when the genetic correlation between the two traits was positive, than selection using other conventional methods. The use of the method devised in this study was expected to result in a greater genetic improvement than the conventional family selection index method for pig breeding programs applied in closed herds in Japan.

Prediction of response to truncated selection based on BLUP of breeding values and its prediction accuracy.

Three methods of predicting the response to truncated selection based on BLUP of breeding values (BVs) were compared under conditions in which the phenotypic values for the progenies of selected animals were not available. The following methods were used to predict the response to selection: (1) based on the mean of estimated breeding values (EBV) in the candidate population for selection ( ), (2) based on the variance of EBV in the candidate population for selection ( ), and (3) based on diagonal elements of the inverse matrix on the left-hand side of the mixed model equation ( ). The deviation of the average BV of the selected animals from the average BV of the candidate population for selection was taken as the true response to selection. The pedigree information and phenotypic values used for comparison were generated by Monte Carlo computer simulation. The results showed that had the smallest absolute mean error and had the smallest root-mean-square error. We concluded that it is desirable to use or to predict the response to truncated selection based on BLUP of BVs. However, in the population where selection is ongoing, the prediction accuracy of selection response is likely to be affected by the distortion of the distribution and the Bulmer effect for .

Thermodynamic properties of fluids with Mie n − m potentials and application to tune effective Mie potentials for simple real fluids

ABSTRACT Monte Carlo computer simulations have been performed to obtain the equation of state and internal energy of fluids with Mie n − m potentials, with m = 6 and n = 9, 12 and 15, for different supercritical temperatures and densities covering most of the fluid phase. These data have been used to test the performance of a third-order perturbation theory with the first three perturbation terms determined from computer simulation, giving rise to a very good agreement between theory and simulation. Next, the theory has been used to tune effective two-body Mie n − 6 potentials for the real fluids Ne, Ar, Kr, Xe and C H 4 at supercritical temperatures for wide range of densities and pressures. It has been shown that the theory is able to accurately fit the experimental data for the energy and pressure of these fluids within the temperature and density ranges considered. This theory might be useful to obtain the equation of state and the internal energy of real molecular fluids within the context of the SAFT-VR Mie theory.

Monte Carlo Simulation of Percolation Phenomena for Direct Current in Large Square Matrices

In this study, an in-depth analysis of the percolation phenomenon for square matrices with dimensions from L = 50 to 600 for a sample number of 5 × 104 was performed using Monte Carlo computer simulations. The percolation threshold value was defined as the number of conductive nodes remaining in the matrix before drawing the node interrupting the last percolation channel, in connection with the overall count of nodes within the matrix. The distributions of percolation threshold values were found to be normal distributions. The dependencies of the expected value (mean) of the percolation threshold and the standard deviation of the dimensions of the matrix were determined. It was established that the standard deviation decreased with the increase in matrix dimensions, ranging from 0.0262253 for a matrix with L = 50 to 0.0044160 for L = 600, which is almost six-fold lower. The mean value of the percolation threshold was practically constant and amounted to approximately 0.5927. The analysis involved not only the spatial distributions of nodes interrupting the percolation channels but also the overall patterns of node interruption in the matrix. The distributions revealed an edge phenomenon within the matrices, characterized by the maximum concentration of nodes interrupting the final percolation channel occurring at the center of the matrix. As they approached the edge of the matrix, their concentration decreased. It was established that increasing the dimensions of the matrix slowed down the rate of decrease in the number of nodes towards the edge. In doing so, the area in which values close to the maximum occurred was expanded. Based on the approximation of the experimental results, formulas were determined describing the spatial distributions of the nodes interrupting the last percolation channel and the values of the standard deviation from the matrix dimensions. The relationships obtained showed that with increasing matrix dimensions, the edge phenomenon should gradually disappear, and the percolation threshold standard deviation values caused by it will tend towards zero.

Analysis of Uneven Distribution of Nodes Creating a Percolation Channel in Matrices with Translational Symmetry for Direct Current

In this study, the phenomenon of node percolation was tested using the Monte Carlo computer simulation method for square matrices with dimensions L = 55, 101 and 151. The number of samples for each matrix was 5 × 106. The spatial distributions of the coordinates of the nodes creating the percolation channel were determined, and maps of the density distribution of these nodes were created. It has been established that in matrices with finite dimensions, an edge phenomenon occurs, consisting of a decrease in the concentration of nodes creating a percolation channel as one approaches the edge of the matrix. As the matrix dimensions increase, the intensity of this phenomenon decreases. This expands the area in which values close to the maximum occur. The length distributions of the left and right clusters of non-conducting nodes were determined for the situation when the next randomly selected node connects them and thus reaches the percolation threshold. It was found that clusters whose dimensions are close to half of the matrix dimensions are most likely to occur. The research shows that both the values of the standard deviation of the percolation threshold and the intensity of the edge phenomenon are clearly related to the dimensions of the matrices and decrease as they increase.

Investigations into the Influence of Matrix Dimensions and Number of Iterations on the Percolation Phenomenon for Direct Current

The paper presents studies of the site percolation phenomenon for square matrixes with dimensions L = 55, 101 and 151 using the Monte Carlo computer simulation method. The number of iterations for each matrix was 5 × 106. An in-depth analysis of the test results using the metrological approach consisting of determining the uncertainty of estimating the results of iterations with statistical methods was performed. It was established that the statistical distribution of the percolation threshold value is a normal distribution. The coefficients of determination for the simulation results in approximations of the percolation threshold using the normal distribution for the number of iterations 5 × 106 are 0.9984, 0.9990 and 0.9993 for matrixes with dimensions 55, 101 and 151, respectively. The average value of the percolation threshold for relatively small numbers of iterations varies in a small range. For large numbers of iterations, this value stabilises and practically does not depend on the dimensions of the matrix. The value of the standard deviation of the percolation threshold for small numbers of iterations also fluctuates to a small extent. For a large number of iterations, the standard deviation values reach a steady state. Along with the increase in the dimensions of the matrix, there is a clear decrease in the value of the standard deviation. Its value is about 0.0243, about 0.01 and about 0.012 for matrixes with dimensions 55, 101 and 151 for the number of iterations 5 × 106. The mean values of the percolation threshold and the uncertainty of its determination are (0.5927046 ± 1.1 × 10−5), (0.5927072 ± 7.13 × 10−6) and (0.5927135 ± 5.33 × 10−6), respectively. It was found that the application of the metrological approach to the analysis of the percolation phenomenon simulation results allowed for the development of a new method of optimizing the determination and reducing the uncertainty of the percolation threshold estimation. It consists in selecting the dimensions of the matrix and the number of iterations in order to obtain the assumed uncertainty in determining the percolation threshold. Such a procedure can be used to simulate the percolation phenomenon and to estimate the value of the percolation threshold and its uncertainty in matrices with other matrix shapes than square ones.

Phase behaviour of semiflexible lattice polymers in poor-solvent solution: Mean-field theory and Monte Carlo simulations.

We study a solution of interacting semiflexible polymers with curvature energy in poor-solvent conditions on the d-dimensional cubic lattice using mean-field theory and Monte Carlo computer simulations. Building upon past studies on a single chain, we construct a field-theory representation of the system and solve it within a mean-field approximation supported by Monte Carlo simulations in d = 3. A gas-liquid transition is found in the temperature-density plane that is then interpreted in terms of real systems. Interestingly, we find this transition to be independent of the bending rigidity. Past classical Flory-Huggins and Flory mean-field results are shown to be particular cases of this more general framework. Perspectives in terms of guiding experimental results towards optimal conditions are also proposed.

Spatial Organization of Slit-Confined Melts of Ring Polymers with Nonconserved Topology: A Lattice Monte Carlo Study.

We present Monte Carlo computer simulations for melts of semiflexible randomly knotted and randomly concatenated ring polymers on the fcc lattice and in slit confinement. Through systematic variation of the slit width at fixed melt density, we explore the influence of confinement on single-chain conformations and interchain interactions. We demonstrate that confinement makes chains globally larger and more elongated while enhancing both contacts and knottedness propensities. As for multichain properties, we show that ring-ring contacts decrease with the confinement, yet neighboring rings overlap more as confinement grows. These aspects are accompanied by a marked decrease in the links formed between pairs of neighboring rings. In connection with the quantitative relation between links and entanglements in polymer melts recently established by us [Ubertini M. A.; Rosa A.Macromolecules2023, 56, 3354-3362], we propose that confinement can be used to set polymer networks that act softer under mechanical stress and suggest a viable experimental setup to validate our results.

Orientation texturing and static magnetic response of multi-core particle containing limited number of superparamagnetic nanocores

In this paper, we study the orientational texturing and static magnetization of a small multi-core particle (MCP) that includes a few immobilized superparamagnetic particles (SPPs). We focus on the consideration of the MCPs containing 7 and 8 SPPs, which are located randomly or at the nodes of a simple cubic lattice. The results are obtained using Monte Carlo computer simulations. It is shown that intensive dipole–dipole interaction leads to the formation of an orientational texturing of the SPP’s magnetic moments, which strongly depends on the location of the SPPs inside the MCP. The magnetization laws of MCPs are compared with the continuous medium magnetostatics. For strongly interacting SPPs there is a big difference between the simulation results for the magnetization of the MCPs with cubic structure and the magnetization of continuous system of SPPs located in simple cubic lattice. The magnetization of the MCP for each specific random location of the SPPs also differs from the magnetization of continuous media of SPP gas, however, the average value of the MCP magnetization coincides with the continuous media magnetostatics.

Brownian dynamics simulations and Ornstein-Zernike equation for charged fluids using the Wolf potential

From a computational point of view, a promising description for charged-stabilized fluids is the so-called Wolf method, which is faster than the standard Ewald summation technique. Using Monte Carlo computer simulations, it was recently shown that the static correlation functions of strong electrolytes obtained with the Wolf potential satisfy the Stillinger–Lovett sum rules, which are a consequence of perfect screening, and are directly related to the local electroneutrality condition and the electrostatic screening within the Debye–Hückel regime. In this contribution, the Wolf potential is adapted to Brownian dynamics simulations to study both the structural and dynamical properties of charged fluids. In addition, we have solved the Ornstein-Zernike equation with the Wolf potential using the HNC closure relation. The resulting radial distributions agree well with the simulation data and previous results obtained with the Ewald technique. Simulation results using Brownian dynamics for weakly charged colloidal dispersions and asymmetric electrolytes are presented. The results include mean square displacement, self-intermediate scattering, and shear relaxation function, with no consideration of hydrodynamic interactions. Including the Wolf potential in Brownian dynamics simulations opens up the possibility of studying interesting transport phenomena in the low Reynolds and Peclet regime, even in those cases where hydrodynamic interactions become relevant.

How Heterogeneity Affects Cooperative Communications within Single Nanocatalysts.

Catalysis remains one of the most essential methods in chemical research and industry. Recent experiments have discovered an unusual phenomenon of catalytic cooperativity, when a reaction at one active site can stimulate reactions at neighboring sites within single nanoparticles. While theoretical analysis established that the transport of charged holes is responsible for this phenomenon, it does not account for inhomogeneity in the structural and dynamic properties of single nanocatalysts. Here, we investigate the effect of heterogeneity on catalytic communications by extending a discrete-state stochastic framework to random distributions of the transition rates. Our explicit calculations of spatial and temporal properties of heterogeneous systems in comparison with homogeneous systems predict that the strength of cooperativity increases, while the communication lifetimes and distances decrease. Monte Carlo computer simulations support theoretical calculations, and microscopic arguments to explain these observations are also presented. Our theoretical analysis clarifies some important aspects of molecular mechanisms of catalytic processes.

Zinc carboxylate optimization strategy for extending Al-air battery system's lifetime

Although Al-air batteries are expected to be the candidates for energy conversion systems in renewable energy market due to the higher energy density, richer reserves, and lighter mass of Al metal, the anode self-discharge is seen as a notorious issue that seriously sacrifices battery durability and stability. Herein, we propose zinc carboxylate inhibition of anode self-discharge for enhancing Al-air battery's lifetime, where the ionized Zn2+ induces a Zn guard on Al surface, and the hydrolysate RCOOH dominates an adsorption layer on the outer surface of Zn, ensuring a double protection for metal anode by means of advanced “one stone two birds” strategy. The results show that the typical zinc carboxylates improve the absolute anticorrosion efficiency of anode greatly, especially the maximum of 92.24% after zinc malate optimization. Furthermore, battery capacity and anode efficiency are as high as 2685.20 mAh g−1 and 90.11% at 20 mA cm−2 respectively. The cyclic discharge lifetime of system (0.12 g fuel) exceeds 19.01 h, which is 1.72 times longer than traditional optimization. Finally, the optimization mechanism is revealed based on Monte Carlo simulation and density functional theory calculation, which the double CO groups in the hydrolysate of zinc malate dominates the harmonious interaction between RCOOH adsorption layer and active metals, exhibiting a high-energy efficiency and long-lifetime Al-air battery power system.

Molecular thermodynamic model for O-(2-hydroxyethyl) cellulose (HEC) intrinsic viscosity

We present a coarse-grained model for O-(2-hydroxyethyl) cellulose (HEC) in order to obtain its intrinsic viscosity by applying three theoretical models and Monte Carlo computer simulations (MC). Results are based on a previous experimental study for this substance at neutral conditions and at pH 4.5, at temperatures of 25∘C and 40∘C (Martínez-Richa, 2012 [3]). The MC primitive model consists of spherocylinder particles whose aspect ratio was determined for 13 samples of HEC of different molecular weights. We consider the Onsager, Simha and Kuhn-Kuhn models, in order to relate the intrinsic viscosity with the aspect ratio of the particles.

Impact of shield location on staff and caregiver dose rates for I-131 radiopharmaceutical therapy patients

The goal of this study is to investigate the effect of the location and width of a single lead shield on the dose rate of staff and caregivers in a hospital room with an I-131 patient. The best orientation of the patient and caregiver relative to the shield was determined based on minimizing staff and caregiver radiation dose rates. Shielded and unshielded dose rates were simulated using a Monte Carlo computer simulation and validated using real-world ionisation chamber measurements. Based on a radiation transport analysis using an adult voxel phantom published by the International Commission on Radiological Protection, placing the shield near the caregiver yielded the lowest dose rates. However, this strategy reduced the dose rate in only a tiny area of the room. Furthermore, positioning the shield near the patient in the caudal direction provided a modest dose rate reduction while shielding a large room area. Finally, increased shield width was associated with decreasing dose rates, but only a four-fold dose-rate reduction was observed for standard width shields. The recommendations of this case study may be considered as potential candidate room configurations where radiation dose rates are minimized, however these findings must be weighed against additional clinical, safety, and comfort considerations.

Measurements of Zγ+jets differential cross sections in pp collisions at sqrt{s} = 13 TeV with the ATLAS detector

Differential cross-section measurements of Zγ production in association with hadronic jets are presented, using the full 139 fb−1 dataset of sqrt{s} = 13 TeV proton–proton collisions collected by the ATLAS detector during Run 2 of the LHC. Distributions are measured using events in which the Z boson decays leptonically and the photon is usually radiated from an initial-state quark. Measurements are made in both one and two observables, including those sensitive to the hard scattering in the event and others which probe additional soft and collinear radiation. Different Standard Model predictions, from both parton-shower Monte Carlo simulation and fixed-order QCD calculations, are compared with the measurements. In general, good agreement is observed between data and predictions from MATRIX and MiNNLOPS, as well as next-to-leading-order predictions from MadGraph5_aMC@NLO and Sherpa.

Tuning TiO2 suspension stability with poly(α-alkyl carboxylic acids) via side chain length and chain stereochemistry

Effects of hydrophobicity and stereochemistry of poly(α-alkyl carboxylic acids) on the properties of TiO2 suspensions were studied with experimental and in silico methods. Zeta potential measurements show that the addition of the more hydrophilic poly(acrylic acid) (PAA) to TiO2 suspensions shifts the isoelectric point of the nanoparticles towards lower pH the most, followed by poly(methacrylic acid) (PMA) and poly(ethacrylic) acid (PEA). Stereochemistry has a less pronounced effect on suspension stability, except at low pH, where isotactic PMA (iPMA) is not soluble in water. Dynamic light scattering measurements show that the aggregate size of the nanoparticles correlates well with their zeta potential and the aggregates are largest at the isoelectric point of the nanoparticles. Molecular dynamics (MD) and Monte Carlo (MC) computer simulations were used to study the interaction of polyacids with the surface of nanoparticles. MD simulations show that PAA forms the largest amount of hydrogen bonds with TiO2, followed by PMA. PEA forms very low numbers of hydrogen bonds with the nanoparticle surface. MC simulations were used to study the effect of pKa of COOH groups of polyacids on their adsorption on TiO2. It was found that even small differences in pKa between the polyacids have a strong effect.

Effect of Polydispersity on the Structural and Magnetic Properties of a Magnetopolymer Composite.

When using magnetopolymer composites in high-precision industrial and biomedical technologies, the problem of predicting their properties in an external magnetic field arises. In this work, we study theoretically the influence of the polydispersity of a magnetic filler on a composite's equilibrium magnetization and on the orientational texturing of magnetic particles formed during polymerization. The results are obtained using rigorous methods of statistical mechanics and Monte Carlo computer simulations in the framework the bidisperse approximation. It is shown that by adjusting the dispersione composition of the magnetic filler and the intensity of the magnetic field at which the sample's polymerization occurs, it is possible to control the composite's structure and magnetization. The derived analytical expressions determine these regularities. The developed theory takes into account dipole-dipole interparticle interactions and therefore can be applied to predict the properties of concentrated composites. The obtained results are a theoretical basis for the synthesis of magnetopolymer composites with a predetermined structure and magnetic properties.

Monte Carlo Computer Simulation Method for Solving the Problem of Particle Passage through Matter

The Monte Carlo method is compared with the deterministic methods based on the solution of the transport equation and the molecular dynamics methods. The capabilities of commonly used general-purpose programs (SRIM, PENELOPE, MCNP, FLUKA, and GEANT4) for Monte Carlo simulation of the processes of particle passage through matter are analyzed. Possible ways for further development of the Monte Carlo method are discussed.

Neutron gamma analysis of soil carbon: Post-irradiation physicochemical effects

In-situ soil carbon measurements would be beneficial when assessing carbon (C) sequestration practices and associated C credits. Neutron gamma analysis, which registers gamma rays that appear due to neutron irradiation, is a tool that can be used for such assessments. However, questions regarding post-effects of neutron irradiation on soil remain unexplored. Temporal post-irradiation effects (neutron flux 2⋅107 neutron/s, neutron energy 14 MeV) on soil chemical and physical attributes were investigated using a previously constructed pulsed fast-thermal neutron-gamma analysis system. Neutron and gamma dose rate distributions during stationary irradiation using this system and Monte-Carlo computer simulations were found to be in agreement; a stationary 1 h irradiation period (conservative or worse-case scenario) was utilized in these scenarios. Physical effects of activating new radioactive isotopes were experimentally determined by assessing changes in the post-irradiated soil gamma spectra (“hot background”) over time; additional soil radioactivity decreased to natural background levels within ∼1 h. Radiolytic decomposition estimates of soil water and soil organic material (primarily cellulosic residue), based on received dose loads and known radiation-chemical yields of water and organic material, were practically negligible. Results indicate that adsorbed radiation doses in scanning mode would be 500 to 1000 times less than in static mode. Thus, neutron gamma analysis does not impact physicochemical aspects of soil health and can be used for soil elemental content determinations without additional radiation safety concerns.