Molecular simulation study of the microstructures and properties of pyridinium ionic liquid[HPy][BF_(4)]mixed with acetonitrile

The microstructures and thermodynamic properties of mixed systems comprising pyridinium ionic liquid[HPy][BF_(4)]and acetonitrile at different mole fractions were studied using molecular dynamics simulation in this work.The following properties were determined:density,self-diffusion coefficient,excess molar volume,and radial distribution function.The results show that with an increase in the mole fraction of[HPy][BF_(4)],the self-diffusion coefficient decreases.Additionally,the excess molar volume initially decreases,reaches a minimum,and then increases.The rules of radial distribution functions(RDFs)of characteristic atoms are different.With increasing the mole fraction of[HPy][BF_(4)],the first peak of the RDFs of HA1-F decreases,while that of CT6-CT6 rises at first and then decreases.This indicates that the solvent molecules affect the polar and non-polar regions of[HPy][BF_(4)]differently.

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

Numerical Simulation and Entropy Production Analysis of Centrifugal Pump with Various Viscosity

The fluid’s viscosity significantly affects the performance of a centrifugal pump.The entropy production method and leakage are employed to analyze the performance changes under various viscosities by numerical simulation and validated by experiments.The results showed that increasing viscosity reduces both the pump head and efficiency.In addition,the optimal operating point shifts to the left.Leakage is influenced by vortex distribution in the front chamber and boundary layer thickness in wear-ring clearance,leading to an initial increase and subsequent decrease in leakage with increasing viscosity.The total entropy production Spro,Total inside the pump rises with increasing viscosity.The different mechanisms dominate under varying conditions:Turbulent dissipation dominates at low viscosity.Under high-viscosity conditions,energy loss is primarily caused by direct dissipation Spro,D and wall entropy production Spro,W.This study provides a deeper and more objective understanding of the energy characteristics of centrifugal pumps handling fluids of various viscosity,potentially aiding in optimizing pump design and improving energy conversion efficiency.

Explosion resistance performance of reinforced concrete box girder coated with polyurea:Model test and numerical simulation

To study the anti-explosion protection effect of polyurea coating on reinforced concrete box girder,two segmental girder specimens were made at a scale of 1:3,numbered as G(without polyurea coating)and PCG(with polyurea coating).The failure characteristics and dynamic responses of the specimens were compared through conducting explosion tests.The reliability of the numerical simulation using LS-DYNA software was verified by the test results.The effects of different scaled distances,reinforcement ratios,concrete strengths,coating thicknesses and ranges of polyurea were studied.The results show that the polyurea coating can effectively enhance the anti-explosion performance of the girder.The top plate of middle chamber in specimen G forms an elliptical penetrating hole,while that in specimen PCG only shows a very slight local dent.The peak vertical displacement and residual displacement of PCG decrease by 74.8% and 73.7%,respectively,compared with those of specimen G.For the TNT explosion with small equivalent,the polyurea coating has a more significant protective effect on reducing the size of fracture.With the increase of TNT equivalent,the protective effect of polyurea on reducing girder displacement becomes more significant.The optimal reinforcement ratio,concrete strength,thickness and range of polyurea coating were also drawn.

Unveiling the crystallization mechanism of cadmium selenide via molecular dynamics simulation with machine-learning-based deep potential

Cadmium selenide(CdSe)is an inorganic semiconductor with unique optical and electronic properties that make it useful in various applications,including solar cells,light-emitting diodes,and biofluorescent tagging.In order to synthesize high-quality crystals and subsequently integrate them into devices,it is crucial to understand the atomic scale crystallization mechanism of CdSe.Unfortunately,such studies are still absent in the literature.To overcome this limitation,we employed an enhanced sampling-accelerated active learning approach to construct a deep neural potential with ab initio accuracy for studying the crystallization of CdSe.Our brute-force molecular dynamics simulations revealed that a spherical-like nu-cleus formed spontaneously and stochastically,resulting in a stacking disordered structure where the competition between hexagonal wurtzite and cubic zinc blende polymorphs is temperature-dependent.We found that pure hexagonal crystal can only be obtained approximately above 1430 K,which is 35 K below its melting temperature.Furthermore,we observed that the solidification dynamics of Cd and Se atoms were distinct due to their different diffusion coefficients.The solidification process was initiated by lower mobile Se atoms forming tetrahedral frameworks,followed by Cd atoms occupying these tetra-hedral centers and settling down until the third-shell neighbor of Se atoms sited on their lattice posi-tions.Therefore,the medium-range ordering of Se atoms governs the crystallization process of CdSe.Our findings indicate that understanding the complex dynamical process is the key to comprehending the crystallization mechanism of compounds like CdSe,and can shed lights in the synthesis of high-quality crystals.

Recent advances in protein conformation sampling by combining machine learning with molecular simulation

The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational biology.One of the most cutting-edge and important applications of ML is its integration with molecular simulations to improve the sampling efficiency of the vast conformational space of large biomolecules.This review focuses on recent studies that utilize ML-based techniques in the exploration of protein conformational landscape.We first highlight the recent development of ML-aided enhanced sampling methods,including heuristic algorithms and neural networks that are designed to refine the selection of reaction coordinates for the construction of bias potential,or facilitate the exploration of the unsampled region of the energy landscape.Further,we review the development of autoencoder based methods that combine molecular simulations and deep learning to expand the search for protein conformations.Lastly,we discuss the cutting-edge methodologies for the one-shot generation of protein conformations with precise Boltzmann weights.Collectively,this review demonstrates the promising potential of machine learning in revolutionizing our insight into the complex conformational ensembles of proteins.

Numerical Simulation of the Settling Flux of Biodeposition in a Bay with Cage Culture Through Similarity Theory and a Simplified Pollution Source

The settling flux of biodeposition affects the environmental quality of cage culture areas and determines their environmental carrying capacity.Simple and effective simulation of the settling flux of biodeposition is extremely important for determining the spatial distribution of biodeposition.Theoretically,biodeposition in cage culture areas without specific emission rules can be simplified as point source pollution.Fluent is a fluid simulation software that can simulate the dispersion of particulate matter simply and efficiently.Based on the simplification of pollution sources and bays,the settling flux of biodeposition can be easily and effectively simulated by Fluent fluid software.In the present work,the feasibility of this method was evaluated by simulation of the settling flux of biodeposition in Maniao Bay,Hainan Province,China,and 20 sampling sites were selected for determining the settling fluxes.At sampling sites P1,P2,P3,P4,P5,Z1,Z2,Z3,Z4,A1,A2,A3,A4,B1,B2,C1,C2,C3 and C4,the measured settling fluxes of biodeposition were 26.02,15.78,10.77,58.16,6.57,72.17,12.37,12.11,106.64,150.96,22.59,11.41,18.03,7.90,19.23,7.06,11.84,5.19 and 2.57 g d^(−1)m^(−2),respectively.The simulated settling fluxes of biodeposition at the corresponding sites were 16.03,23.98,8.87,46.90,4.52,104.77,16.03,8.35,180.83,213.06,39.10,17.47,20.98,9.78,23.25,7.84,15.90,6.06 and 1.65 g d^(−1)m^(−2),respectively.There was a positive correlation between the simulated settling fluxes and measured ones(R=0.94,P=2.22×10^(−9)<0.05),which implies that the spatial differentiation of biodeposition flux was well simulated.Moreover,the posterior difference ratio of the simulation was 0.38,and the small error probability was 0.94,which means that the simulated results reached an acceptable level from the perspective of relative error.Thus,if nonpoint source pollution is simplified to point source pollution and open waters are simplified based on similarity theory,the setting flux of biodeposition in the open waters can be simply and effectively simulated by the fluid simulation software Fluent.

Numerical simulations for radon migration and exhalation behavior during measuring radon exhalation rate with closed-loop method

Accurate measurements of the radon exhalation rate help identify and evaluate radon risk regions in the environment.Among these measurement methods,the closed-loop method is frequently used.However,traditional experiments are insufficient or cannot analyze the radon migration and exhalation patterns at the gas–solid interface in the accumulation chamber.The CFD-based technique was applied to predict the radon concentration distribution in a limited space,allowing radon accumulation and exhalation inside the chamber intuitively and visually.In this study,three radon exhalation rates were defined,and two structural ventilation tubes were designed for the chamber.The consistency of the simulated results with the variation in the radon exhalation rate in a previous experiment or analytical solution was verified.The effects of the vent tube structure and flow rate on the radon uniformity in the chamber;permeability,insertion depth,and flow rate on the radon exhalation rate and the effective diffusion coefficient on back-diffusion were investigated.Based on the results,increasing the inser-tion depth from 1 to 5 cm decreased the effective decay constant by 19.55%,whereas the curve-fitted radon exhalation rate decreased(lower than the initial value)as the deviation from the initial value increased by approximately 7%.Increasing the effective diffusion coefficient from 2.77×10^(-7) to 7.77×10^(-6) m^(2) s^(-1) made the deviation expand from 2.14 to 15.96%.The conclusion is that an increased insertion depth helps reduce leakage in the chamber,subject to notable back-diffusion,and that the closed-loop method is reasonably used for porous media with a low effective diffusion coefficient in view of the back-diffusion effect.The CFD-based simulation is expected to provide guidance for the optimization of the radon exhalation rate measurement method and,thus,the accurate measurement of the radon exhalation rate.

MicroMagnetic.jl:A Julia package for micromagnetic and atomistic simulations with GPU support

MicroMagnetic.jl is an open-source Julia package for micromagnetic and atomistic simulations.Using the features of the Julia programming language,MicroMagnetic.jl supports CPU and various GPU platforms,including NVIDIA,AMD,Intel,and Apple GPUs.Moreover,MicroMagnetic.jl supports Monte Carlo simulations for atomistic models and implements the nudged-elastic-band method for energy barrier computations.With built-in support for double and single precision modes and a design allowing easy extensibility to add new features,MicroMagnetic.jl provides a versatile toolset for researchers in micromagnetics and atomistic simulations.

Coupled CFD-DEM Numerical Simulation of the Interaction of a Flow-Transported Rag with a Solid Cylinder

A coupled Computational Fluid Dynamics-Discrete Element Method(CFD-DEM)approach is used to calculate the interaction of a flexible rag transported by a fluid current with a fixed solid cylinder.More specifically a hybrid Eulerian-Lagrangian approach is used with the rag being modeled as a set of interconnected particles.The influence of various parameters is considered,namely the inlet velocity(1.5,2.0,and 2.5 m/s,respectively),the angle formed by the initially straight rag with the flow direction(45°,60°and 90°,respectively),and the inlet position(90,100,and 110 mm,respectively).The results show that the flow rate has a significant impact on the permeability of the rag.The higher the flow rate,the higher the permeability and the rag speed difference.The angle has a minor effect on rag permeability,with 45°being the most favorable angle for permeability.The inlet position has a small impact on rag permeability,while reducing the initial distance between the rag an the cylinder makes it easier for rags to pass through.

Application of Patient Simulators Combined with Internet plus Scenario Simulation Teaching Models on Intravenous Infusion Nursing Education in China

Objective: To explore the effectiveness of applying patient simulators combined with Internet Plus scenario simulation teaching models on intravenous (IV) infusion nursing education, and to provide scientific evidence for the implementation of advanced teaching models in future nursing education. Methods: Enrolled 60 nurses who took the IV infusion therapy training program in our hospital from January 2022 to December 2023 for research. 30 nurses who were trained in traditional teaching models from January to December 2022 were selected as the control group, and 30 nurses who were trained with simulation-based teaching models with methods including simulated patients, internet, online meetings which can be replayed and scenario simulation, etc. from January to December 2023 were selected as the experimental group. Evaluated the learning outcomes based on the Competency Inventory for Nursing Students (CINS), Problem-Solving Inventory (PSI), comprehensive learning ability, scientific research ability, and proficiency in the theoretical knowledge and practical skills of IV infusion therapy. Nursing quality, the incidence of IV infusion therapy complications and nurse satisfaction with different teaching models were also measured. Results: The scientific research ability, PSI scores, CINS scores, and comprehensive learning ability of the experimental group were better than those of the control group (P 0.05), and their assessment results of practical skills, nursing quality of IV infusion therapy during training, and satisfaction with teaching models were all better than those of the control group with statistical significance (P < 0.05). The incidence of IV infusion therapy complications in the experimental group was lower than that in the control group, indicating statistical significance (P < 0.05). Conclusions: Teaching models based on patient simulators combined with Internet Plus scenario simulation enable nursing students to learn more directly and practice at any time and in any place, and can improve their proficiency in IV infusion theoretical knowledge and skills (e.g. PICC catheterization), core competencies, problem-solving ability, comprehensive learning ability, scientific research ability and the ability to deal with complicated cases. Also, it helps provide high-quality nursing education, improve the nursing quality of IV therapy, reduce the incidence of related complications, and ensure the safety of patients with IV therapy.

Modeling and Simulation of an Organic Photovoltaic Cell: ITO/MoO3/CARAPA/PCBM/Alq3/Al with SCAPS

Renewable energies are of major interest due to their inexhaustible and clean nature, with minimal impact on the environment. Numerous technological pathways exist in this field, each distinguished by the materials used and their implementation principles. However, the cost-efficiency ratio remains a significant challenge for researchers. Currently, organic materials are gaining popularity due to their relatively low cost. However, their performance, particularly in terms of conversion efficiency, still requires improvements. This study focuses on optimizing the organic photovoltaic cell ITO/MoO3/CARAPA/PCBM/Alq3/Al using SCAPS. Several parameters were considered, such as layer thickness, recombination center density, and doping, to improve the cell’s performance. The optimal parameters obtained include an efficiency of 3%, a fill factor of 81.67%, an open-circuit voltage of 1610 mV, and a short-circuit current of 2.28 mA/cm2. The study also revealed that doping the phenyl-C61-butyric acid methyl ester (PCBM) layer has a significant impact on efficiency and short-circuit current, improving these parameters up to a certain point before causing degradation due to increased recombination. Furthermore, high doping of the tri (8-hydroxyquinoline) aluminum (Alq3) layer improves performance up to a critical threshold, after which degradation is also observed. In contrast, doping the molybdenum trioxide (MoO3) layer does not have a notable impact on cell performance. Regarding the thickness of the active Carapaprocera (CARAPA) and PCBM layers, non-optimal values lead to a decrease in performance. Similarly, an optimal thickness of the Alq3 layer significantly improves efficiency. These results highlight the importance of parameter optimization to maximize the efficiency of organic solar cells.

A New Method with High Confidence for Validation of Computer Simulation Models of Flight Systems

Computer simulation models may by used to gain further information about missile performance variability. Model validation is an important aspect of the test program for a missile system. Validation provides a basis for confidence in the model's results and is a necessary step if the model is to be used to draw inference about the behavior of the real missile. This paper is a review of methods useful for validation of computer simulation models of missile systems and provides a new method with high degree of confidence for validation of computer simulation models of missile systems. Some examples of the use of the new method in validating computer simulation models are given.

Comparison Between Computer Simulation of Transport and Diffusion of Cloud Seeding Material Within Stratiform Cloud and the NOAA-14 Satellite Cloud Track

A precipitation enhancement operation using an aircraft was conducted from 1415 to 1549 LST 14 March 2000 in Shaanxi Province. The NOAA-14 satellite data received at 1535 LST soon after the cloud seeding shows that a vivid cloud track appears on the satellite image. The length, average width and maximum width of the cloud track are 301 km, 8.3 and 11 km, respectively. Using a three-dimensional numerical model of transport and diffusion of seeding material within stratiform clouds, the spatial concentration distribution characteristics of seeding material at different times, especially at the satellite receiving time, are simulated. The model results at the satellite receiving time are compared with the features of the cloud track. The transported position of the cloud seeding material coincides with the position of the track. The width, shape and extent of diffusion of the cloud seeding material are similar to that of the cloud track. The spatial variation of width is consistent with that of the track. The simulated length of each segment of the seeding line accords with the length of every segment of the track. Each segment of the cloud track corresponds to the transport and diffusion of each segment of the seeding line. These results suggest that the cloud track is the direct physical reflection of cloud seeding at the cloud top. The comparison demonstrates that the numerical model of transport and diffusion can simulate the main characteristics of transport and diffusion of seeding material, and the simulated results are sound and trustworthy. The area, volume, vidth, depth, and lateral diffusive rate corresponding to concentrations 1, 4, and 10 L-1are simulated in order to understand the variations of influencing range.

A COMPUTER CODE FASTOR-3D FOR TRANSIENT THREE-DIMENSIONAL SIMULATION ON FLOW AND HEAT TRANS-FER WITH POROSITY APPROXIMATION

Upon the conservation of mass, momentum and energy, volume fraction and surface penetrative rate were employed to modify the conservative equations to simulate the effect of blockages on fluid flows and heat transfer. These equations were solved numerically with the finite differential method and the primitive variable approach. This method uses staggered grid and pressure correction schemes. A computer code FASTOR3D integrated the aforementioned algorithm. The preliminary results have been compared with conventional benchmark solutions. With auxiliary software DV, the numerical results were visualized in colorful images to demonstrate the variation of flow patterns and temperature profiles during the transient process. The results of the simulation code for the fluid flows and heat transfer in the sodium pool of a fast breeder reactor are acceptable.

Breeding design in wheat by combining the QTL information in a GWAS panel with a general genetic map and computer simulation

A large amount of genome-wide association study(GWAS)panels together with quantitative-trait locus(QTL)information associated with breeding-targeted traits have been described in wheat(Triticum aestivum L.).However,the application of mapping results from a GWAS panel to conventional wheat breeding remains a challenge.In this study,we first report a general genetic map which was constructed from 44 published linkage maps.It permits the estimation of genetic distances between any two genetic loci with physical map positions,thereby unifying the linkage relationships between QTL,genes,and genomic markers from multiple genetic populations.Second,we describe QTL mapping in a wheat GWAS panel of 688 accessions,identifying 77 QTL associated with 12 yield and grain-quality traits.Because these QTL have known physical map positions,they could be mapped onto the general map.Finally,we present a design approach to wheat breeding by using known QTL information and computer simulation.Potential crosses between parents in the GWAS panel may be evaluated by the relative frequency of the target genotype,trait correlations in simulated progeny populations,and genetic gain of selected progenies.It is possible to simultaneously improve yield and grain quality by suitable parental selection,progeny population size,and progeny selection scheme.Applying the design approach will allow identifying the most promising crosses and selection schemes in advance of the field experiment,increasing predictability and efficiency in wheat breeding.

COMPUTER SIMULATION OF MISCIBILITY AND SELF-ASSEMBLY STRUCTURE FOR POLYMER-CONTAINING SYSTEMS WITH SPECIAL INTERACTIONS

The miscibility and structure of A-B copolymer/C homopolymer blends with special interactions were studied by aMonte Carlo simulation in two dimensions. The interaction between segment A and segment C was repulsive, whereas it wasattractive between segment B and segment C. In order to study the effect of copolymer chain structure on the morphologyand structure of A-B copolymer/C homopolymer blends, the alternating, random and block A-B copolymers were introducedinto the blends, respectively. The simulation results indicated that the miscibility of A-B block copolymer/C homopolymerblends depended on the chain structure of the A-B copolymer. Compared with alternating or random copolymer, the blockcopolymer, especially the diblock copolymer, could lead to a poor miscibility of A-B copolymer/C homopolymer blends.Moreover, for diblock A-B copolymer/C homopolymer blends, obvious self-organized core-shell smicture was observed inthe segment B composition region from 20% to 60%. However if diblock copolymer composition in the blends is less than40%, obvious self-organized core-shell structure could be formed in the B-segment component region from 10 to 90%.Furthermore, computer statistical analysis for the simulation results showed that the core sizes tended to increasecontinuously and their distribution became wider with decreasing B-segment component.

COMPUTER SIMULATION OF METHANE MIGRATION IN LONGWALL PANELS WITH DESCENSIONAL VENTLIATION

It is important to study the methane transport phenomenon in a longwall panel under descensional ventilation conditions. In this paper the gob area is divided into a number of nodes to represent the rectangular percolating elements. The connections between nodes (elements) become branches,so that a network can be formed. Using the mechanics of porous media fluid flow, the mathematical model of air and gas flows has been established. Based on the existing ground pressure theories,the porosity of the inhomogeneous porous media in the gob can be given. In computer simulation it is considered that air pressure and temperature are functions of position ; air density, viscosity, and natural ventilation pressure are functions of temperature,pressure and methane concentration,and the resistance varies with air density and viscosity. Finally,the calculation results are given to show the differences between ascensional and descensional ventilation methods.

Phase field simulation for non-isothermal solidification of multicomponent alloys coupled with thermodynamics database

In order to quantitively model the real solidification process of industrial multicomponent alloys, a non-isothermal phase field model was studied for multicomponent alloy fully coupled with thermodynamic and diffusion mobility database, which can accurately predict the phase equilibrium, solute diffusion coefficients, specific heat capacity and latent heat release in the whole system. The results show that these parameters are not constants and their values depend on local concentration and temperature. Quantitative simulation of solidification in multicomponent alloys is almost impossible without such parameters available. In this model, the interfacial region is assumed to be a mixture of solid and liquid with the same chemical potentials, but with different composition. The anti-trapping current is also considered in the model. And this model was successfully applied to industrial A1-Cu-Mg alloy for the free equiaxed dendrite solidification process.