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Bimetallic nanoclusters have a wide range of uses, and Re-W has been shown to be a catalyst due to its good properties, so it is crucial to study Re-W nanoclusters at the microscopic scale in order to obtain better-performing Re-W nanoclusters. This research investigates the diffusion and structural modification of Re on the surfaces of W nanoclusters at high temperatures. The EAM potential function is employed in this work to explain the interaction between Re and W, and the LAMMPS (large-scale atom/polar massively parallel simulation) package is used for the simulation. We observed the diffusion phenomenon in our investigation by depositing Re atoms on the surface of the W nanoclusters. The findings demonstrate that there are differences in the exchange energy barriers between the Re and W atoms at various locations. At the intersection of the faces, the more (110) faces there are, the lower the exchange energy barrier between the Re and W atoms. During diffusion, the mechanisms of vacancy formation and migration were investigated. The results of the analysis demonstrate that the formation and migration of these vacancies are facilitated by the presence of Re atoms. Furthermore, we noticed that the lattice structure changed throughout the entire deposition process. This observation offers a theoretical direction for producing Re-W bimetallic nanoclusters with a little lattice distortion. [ABSTRACT FROM AUTHOR]

Abstract Human liver-type phosphofructokinase 1 (PFKL) has been shown to regulate glucose flux as a scaffolder arranging glycolytic and gluconeogenic enzymes into a multienzyme metabolic condensate, the glucosome. However, it has remained elusive of how phase separation of PFKL is governed and initiates glucosome formation in living cells, thus hampering to understand a mechanism of glucosome formation and its functional contribution to human cells. In this work, we developed a stochastic model in silico using the principle of Langevin dynamics to investigate how biological properties of PFKL contribute to the condensate formation. The significance of an intermolecular interaction between PFKLs, an effective concentration of PFKL at a region of interest, and its own self-assembled filaments in formation of PFKL condensates and control of their sizes were demonstrated by molecular dynamics simulation using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Such biological properties that define intracellular dynamics of PFKL appear to be essential for phase separation of PFKL, which may represent an initiation step for the formation of glucosome condensates. Collectively, our computational study provides mechanistic insights of glucosome formation, particularly an initial stage through the formation of PFKL condensates in living human cells.

Molecular descriptors characterize the biological, physical, and chemical properties of molecules and have long been used for understanding molecular interactions and facilitating materials design. Some of the most robust descriptors are derived from geometrical representations of molecules, called 3-dimensional (3D) descriptors. When calculated from molecular dynamics (MD) simulation trajectories, 3D descriptors can also capture the effects of operating conditions such as temperature or pressure. However, extracting 3D descriptors from MD trajectories is non-trivial, which hinders their wide use by researchers developing advanced quantitative-structure-property-relationship models using machine learning. Here, we describe a suite of open-source Python-based post-processing routines, called PyL3dMD, for calculating 3D descriptors from MD simulations. PyL3dMD is compatible with the popular simulation package LAMMPS and enables users to compute more than 2000 3D molecular descriptors from atomic trajectories generated by MD simulations. PyL3dMD is freely available via GitHub and can be easily installed and used as a highly flexible Python package on all major platforms (Windows, Linux, and macOS). A performance benchmark study used descriptors calculated by PyL3dMD to develop a neural network and the results showed that PyL3dMD is fast and efficient in calculating descriptors for large and complex molecular systems with long simulation durations. PyL3dMD facilitates the calculation of 3D molecular descriptors using MD simulations, making it a valuable tool for cheminformatics studies.

Endothelial cell monolayers line the inner surfaces of blood and lymphatic vessels. They are continuously exposed to different mechanical loads, which may trigger mechanobiological signals and hence play a role in both physiological and pathological processes. Computer-based mechanical models of cells contribute to a better understanding of the relation between cell-scale loads and cues and the mechanical state of the hosting tissue. However, the confluency of the endothelial monolayer complicates these approaches since the intercellular cross-talk needs to be accounted for in addition to the cytoskeletal mechanics of the individual cells themselves. As a consequence, the computational approach must be able to efficiently model a large number of cells and their interaction. Here, we simulate cytoskeletal mechanics by means of molecular dynamics software, generally suitable to deal with large, locally interacting systems. Methods were developed to generate models of single cells and large monolayers with hundreds of cells. The single-cell model was considered for a comparison with experimental data. To this end, we simulated cell interactions with a continuous, deformable substrate, and computationally replicated multistep traction force microscopy experiments on endothelial cells. The results indicate that cell discrete network models are able to capture relevant features of the mechanical behaviour and are thus well-suited to investigate the mechanics of the large cytoskeletal network of individual cells and cell monolayers. [ABSTRACT FROM AUTHOR]

Steel is the most versatile engineering and construction material. Construction, power, automobiles, infrastructure, manufacturing and various different industrial sectors are using steel as their most important raw material. It is also the most recycled metal material on earth. But steel is having a major problem of rusting when exposed to water. Interaction of steel products with water is almost unavoidable in majority of the cases like automobiles, construction, water pipes, etc. Thus a detailed atomistic study of steel with water is required to understand the corrosion behaviour. At the atomic scale, Fe, Cr, and Ni are the major alloying elements of steel and highly reactive with water which results in corrosion and degradation of both surface and bulk properties. Therefore, we have used reactive molecular dynamics simulation (RMDS) to investigate reactivity of water with Fe–Cr–Ni substrate. We have carried out large number of simulations at different initial conditions and found that water molecules split into H and OH. Further, OH predominantly reacts with Cr and forms chromium oxide compounds over the Fe–Cr–Ni substrate. In the next step, variation in potential energy and mean square displacement have been used for quantitative characterization of reaction between water and Fe–Cr–Ni substrate. This study can provide detailed perspective towards the corrosion behaviour of steel in humid environment. [ABSTRACT FROM AUTHOR]

Abstract Developing high-performance anode materials remains a significant challenge for clean energy storage systems. Herein, we investigated the (MXene/MoSe2@C) heterostructure hybrid nanostructure as a superior anode material for application in lithium, sodium, and potassium ion batteries (LIBs, SIBs, and PIBs). Moreover, the anode structure’s stability was examined via the open-source Large-scale atomic/molecular massively Parallel Simulator code. Our results indicated that the migration of SIBs toward the anode material is significantly greater than other ions during charge and discharge cycles. Therefore, SIBs systems can be competitive with PIBs and LIBs systems. In addition, the average values of the potential energies for the anode materials/ions complexes are about ~ − 713.65, ~ − 2030.41, and ~ − 912.36 kcal mol−1 in systems LIBs, SIBs, and PIBs, respectively. This study provides a rational design strategy to develop high-performance anode materials in SIBs/PIBs/LIBs systems, which can be developed for other transition metal chalcogenide-based composites as a superior anode of alkali metal ion battery storage systems.

Granular matter takes many paths to pack in natural and industrial processes. The path influences the packing microstructure, particularly for frictional grains. We perform discrete element modeling simulations of different paths to construct packings of frictional spheres. Specifically, we explore four stress-controlled protocols implementing packing expansions and compressions in various combinations thereof. We characterize the eventual packed states through their dependence of the packing fraction and coordination number on packing pressure, identifying non-monotonicities with pressure that correlate with the fraction of frictional contacts. These stress-controlled, bulk-like particle simulations access very low-pressure packings, namely, the marginally stable limit, and demonstrate the strong protocol dependence of frictional granular matter. [ABSTRACT FROM AUTHOR]

Crystallographic models of TiZrVMo HEAs were established here for six distinct grain sizes ranging from 7.4 to 23.5 nm. A consistent rise in tensile stress maxima is observed with diminishing grain size. Remarkably, the TiZrVMo composition demonstrates its optimal performance at a grain size of 12.4 nm. During tensile processes, TiZrVMo displays pronounced atomic plane slip and an increase in intra-grain dislocations, indicating significant plastic deformation. Conversely, TiZrV3Mo exhibits limited slip and localized stress, signifying a lower degree of plasticity. This research unveils the intricate interplay of grain boundary phenomena, dislocation behavior, and atomic plane slip, thereby shedding light on the mechanical properties of HEAs. [ABSTRACT FROM AUTHOR]

In this study, we have investigated numerous influential factors such as length, diameter, impurity introduction, and vacancy defects on the thermal conductivity of carbon nanotubes (CNTs). These investigations were conducted through molecular dynamics simulations using the large-scale atomic/molecular massively parallel simulator (LAMMPS). It is observed that longer CNTs tend to exhibit heightened thermal conductivity, a consequence of the increased support for phonon vibration modes that facilitate efficient thermal transport. Furthermore, CNTs with larger diameters display superior thermal characteristics owing to reduced phonon scattering effects. The introduction of boron doping reduces CNTs thermal conductivity by approximately 3% with the inclusion of 6% boron atoms, whereas nitrogen doping increases it by a similar margin. These doping effects hold great potential for optimizing the performance of MEMS and NEMS devices. This duality in doping offers a versatile means to fine-tune the thermal conductivity of CNTs, enabling effective heat management in micro/nanodevices. By strategically modulating thermal conductivity, we can optimize the heat transfer properties of CNT-based materials and devices. This optimization is of utmost importance in ensuring efficient heat dissipation and averting thermal-induced issues, such as overheating, performance degradation, or failure. Additionally, this paper explores how vacancy defects impact the thermal conductivity of CNTs. By varying the vacancy concentration from 1 to 6%, a decrease in thermal conductivity of approximately 2% to 4% was observed in both SWCNTs and DWCNTs. These results emphasize the pivotal role of defects in perturbing the efficient phonon transport mechanisms in CNTs and suggest the potential for customizing CNTs with specific defect concentrations to enhance their suitability for thermoelectric devices and thermal insulation materials. [ABSTRACT FROM AUTHOR]

Catalysts with dual functions in hydrogen production and storage are desired for the low-cost technology. In the preceding view, we used reactive force molecular dynamics to demonstrate how effective the Fe–Al core-shell structure is at breaking up water molecules and storing hydrogen free radicals via thermochemical water splitting. The results show that at T ∼600 K, water molecules begin to dissociate in the presence of a Fe–Al catalyst, releasing OH and H free radicals. It is worth noting that the produced OH free radicals are bonded to the Al-shell, whereas the H free radicals move to the Fe-core and stores via chemical bond. Interestingly, at T < 1200 K, there is no Fe–O bond. This could be due to Al having a higher oxidation potential than Fe, causing OH free radicals to preferentially associate with the Al-shell. Furthermore, at 2000K < T > 3000 K, the number of Fe–H bonds decreases while the number of H–H bonds increases, indicating that the stored H atom desorbs and forms an H 2 molecule. Temperature can thus be used to monitor the ability of Fe–Al catalysts to dissociate water, store hydrogen, and produce hydrogen. This research shows that developing core-shell type catalysts can provide an effective solution for hydrogen generation, storage, and transportation. • Fe–Al core-shell catalysts are efficient for dissociation of water molecules at T∼600 K. • Water dissociates into OH and H free radicals. • OH radical bonded to the Al-shell (Al–OH), whereas H radical bonded to Fe-core (Fe–H). • At temperature 2000K < T > 3000 K, Fe–H bonds dissociate and H 2 molecule generates. [ABSTRACT FROM AUTHOR]

Fluid dynamics is a ubiquitous problem that arises in different branches of science and industry. It is usually tackled by numerically solving continuum Navier-Stokes type equations. Molecular dynamics has been not a feasible tool to approach fluid dynamics until very recently due to its disproportional computational complexity for relevant system sizes. In this paper, we propose a new type of boundary conditions for molecular dynamics simulations of stationary fluid flows and present its possible GPU-based implementations in OpenMM and LAMMPS. We examine the performance and scalability of the proposed implementations. The benchmarking results show promising performance that makes it possible to reach turbulence in atomistic models of stationary fluid flows using modern supercomputers. [ABSTRACT FROM AUTHOR]

Several knowledge gaps on the properties and behavior of hydrogen must be closed to realize its widespread use as a clean fuel and reduction agent. A challenge in this regard is that hydrogen and its mixtures are influenced by quantum effects, in particular at low temperatures. We have implemented new pair potentials into the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) package that semi-classically account for quantum effects. They are called Feynman–Hibbs corrected Mie potentials (Mie–FH) of first and second order. In the literature, these potentials have been shown to accurately represent the thermodynamic properties of hydrogen, deuterium, helium, neon and their mixtures at temperatures above 20 K. We verify the correctness of the LAMMPS implementation by comparing to results from independent Monte Carlo simulations. The computational efficiency of the implementation is assessed for system sizes ranging from several thousands to one billion particles, highlighting the suitability of the implementation for large-scale simulations. The LAMMPS implementation paves the way for new applications, such as studying the transport properties of hydrogen mixtures, or investigating hydrogen confined in porous media.

Being the first part of a two-part series, published in this issue of the journal, this paper combines a brief overview of theoretical and experimental studies, as well as the results of atomistic simulations of surface melting in bulk bodies and nanoparticles with presentation of our own molecular dynamics results. We have studied the patterns and mechanisms of surface melting in metal nanoparticles (gold, silver, copper, lead and nickel). The patterns and mechanisms of this phenomenon were studied in most detail on gold and silver nanoparticles. It has been established that the effect of surface premelting is characteristic for nanoparticles of all the above metals, although with decreasing particle size this effect manifests itself to a lesser extent. In addition, our molecular dynamics results do not confirm theoretical predictions of some authors about the existence of a quite definite characteristic (critical) radius of nanoparticles, below which the effect of surface melting is completely absent.

In this study, the wetting and spreading behavior of AgCuTi ternary alloys on Fe substrate was investigate using a molecular dynamics (MD) modeling method. Modeling indicates that precursor films consisted of single-layer atoms are formed and that the wetting and spreading morphologies of the molten droplets on various crystal surfaces are distinct. Diffusive processes play a key role in the formation of the precursor film, and the droplet spreading morphology is correlated critically with the atomic arrangement of the substrate. The droplet spreading process can be divided into two stages of rapid and slow spreading, and there is an obvious interdiffusion phenomenon close to the solid-liquid contact line. The rate at which droplets spread quickens as the temperature rises. Furthermore, the spreading and diffusion capacities of various elements vary, and these properties are closely related to their chemical reactivity.

Semiconductor electronics is transforming computing, communication, energy harvesting, automobiles, biotechnology, and other electronic device landscapes. This transformation has been brought about by the ability to sense, receive, manipulate, and transmit data from the diverse systems of vertical stacks of semiconductor layers and microdevices. Though the discrete design details of each semiconductor may be extremely complex, the fundamental processing steps of each semiconductor device align well with the photolithography procedure. When these semiconductor layers are stacked using photolithography, the signal noise between the device features and layers is restricted by passivation or dielectric insulation provided by SiO2 layers. Depending on the type of functionality and the data-sensing mechanism of the semiconductors used, SiO2 layers have an intended fitness for their purpose. The purpose of SiO2 layers can be summarized as the encapsulation of the semiconductor device, making part of the semiconductor layer inert, i.e., passivated, creating a hard mask to negate the impact of subsequent processes like ion implantation or diffusion, insulating a part of the layer as in an intermetallic dielectric or gate dielectric, and improving adhesion of the subsequent deposition. The functionality of the adhesion of SiO2 is by far a less-studied area. The adhesive characteristics of SiO2 for subsequent deposition and the thickness of SiO2 affect stress distribution. Stresses due to SiO2 thin films, which can range from a few nanometers to a few microns thick depending on the functionality, are modeled in this research. The stresses in SiO2 films may cause delamination or discontinuity, affecting the performance and reliability of the optical or semiconductor devices they are built into. The classical molecular dynamics (MD) simulation technique was employed to investigate the stress characteristics of deposited films by leveraging the outcomes of atomistic modeling. A cluster made of fused silica was employed as a substrate. For the simulation of the SiO2 deposition process, silicon atoms with high energies and low-energy oxygen atoms were injected. This model was carefully controlled to ensure the stoichiometric conditions. In this analysis, we used the open-source code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) and the Ovito (Open Visualization) tool. The research in this paper focuses on SiO2 thin-film simulation to validate analytical and experimental stress. [ABSTRACT FROM AUTHOR]

Pyrochlore oxides ( A 2 B 2 O 7) are potential nuclear waste substrate materials due to their superior radiation resistance properties. We performed molecular dynamics simulations to study the structural properties and displacement cascades in ytterbium titanate pyrochlore ( Yb 2 Ti 2 O 7 ) and high-entropy alloys (HEPy), e.g., YbYTiZr O 7 , YbGdTiZr O 7 , and Yb 0.5 Y 0.5 Eu 0.5 Gd 0.5 TiZr O 7 . We computed lattice constants (LC) ( a o ) and threshold displacement energy (Ed). Furthermore, the calculation for a o and ionic radius ( r i o n i c ) were performed by substituting a combination of cations at the A and B sites of the original pyrochlore structure. Our simulation results have demonstrated that the lattice constant is proportional to the ionic radius, i.e., a o   α   r i o n i c . Moreover, the effect of displacement cascades of recoils of energies 1 keV, 2 keV, 5 keV, and 10 keV in different crystallographic directions ([100], [110], [111]) was studied. The number of defects is found to be proportional to the energy of incident primary knock-on atoms (PKA). Additionally, the E d of pyrochlore exhibits anisotropy. We also observed that HEPy has a larger E d as compared with Yb 2 Ti 2 O 7 . This establishes that Yb 2 Ti 2 O 7 has characteristics of lower radiation damage resistance than HEPy. Our displacement cascade simulation result proposes that HEPy alloys have more tendency for trapping defects. This work will provide atomic insights into developing substrate materials for nuclear waste applications. [ABSTRACT FROM AUTHOR]

Stimuli-responsive hydrogels are a class of hydrogels that undergo reversible changes in their physical or chemical properties in response to specific external stimuli. The pH is a critical environmental stimulus for stimuli-responsive hydrogels. When the pH of the surrounding environment changes, it can lead to significant alterations in the properties of the hydrogel, such as swelling behavior, mechanical strength, etc. So, understanding how pH affects the swelling behavior and mechanical properties of these hydrogels is crucial to optimize their performance in biomedical applications. Therefore, in the present study, the effect of pH on the swelling process, mechanical and thermal attributes of polyacrylamide hydrogel structure were studied using molecular dynamics simulation and LAMMPS software. The results reveal that as the pH increased from 2 to 11, the structural volume increased from 342,583 to Å3. The increase in the volume of the structure was in terms of the increase in atomic fluctuations by increasing the pH, and consequently, it led to more swelling. The mechanical properties show that the ultimate strength and Young’s modulus of the sample increase from 0.0298 to 0.0007 to 0.0359 and 0.0012 MPa, respectively. The reason for the increase in these parameters was that by increasing the pH, the attraction force among different components of the PAM hydrogel structure increased. This issue led to an increase in the stability of the nanostructure. Finally, the thermal properties showed that thermal conductivity increased from 0.51 to 0.62 W/m K by increasing pH to 11. The findings may lead to the development of pH-responsive hydrogels with enhanced properties, offering more effective and tailored solutions for biomedical applications.

Granular matter takes many paths to pack in natural and industrial processes. The path influences the packing microstructure, particularly for frictional grains. We perform discrete element modeling simulations of different paths to construct packings of frictional spheres. Specifically, we explore four stress-controlled protocols implementing packing expansions and compressions in various combinations thereof. We characterize the eventual packed states through their dependence of the packing fraction and coordination number on packing pressure, identifying non-monotonicities with pressure that correlate with the fraction of frictional contacts. These stress-controlled, bulk-like particle simulations access very low-pressure packings, namely, the marginally stable limit, and demonstrate the strong protocol dependence of frictional granular matter.

The main uses of bullets are as projectiles in firearms for military, law enforcement, and civilian purposes. However, bullets have significant industrial applications beyond their role in weaponry, such as precision drilling, cutting, and shaping of hard materials. Steel bullets have a very resistant structure and will not be damaged if exposed to corrosion. Other applications that are resistant to strike and projectiles, such as the automotive and aerospace industries, are based on fibers or fabrics with high toughness and tensile strength, such as Kevlar and p -aramid fibers, which are impregnated with some thermoplastic or thermoset polymers. Therefore, in the upcoming research, the impact of external force (EF) with various values (0.1, 0.2, 0.3, 0.4, and 0.5 V/Å) on the strength of Kevlar nanofibers reinforced with silicon dioxide (SiO2) nanoparticles and ethylene glycol (EG) has been investigated using LAMMPS software. EG and SiO2 nanoparticles with 10 and 2 vol% were added to Kevlar fabrics, creating a shear thickening fluid (STF) nanocomposite. The energy parameters of the interaction between the particles, collision velocity, and the center of mass have been calculated. The findings of the research indicate an increase in the interaction energy from 111271.85 to 154351.15 kcal/mol, an increase in the collision velocity from 0.7046 to 1.5812 Å/fs and an increase in the center of mass from 0.62671 to 1.1670 Å due to the EF applied from 0.2 to 0.4 (kcal/mol)/Å. These results show EF should be optimized in actual cases for the collision process to occur effectively.

Abstract Molecular descriptors characterize the biological, physical, and chemical properties of molecules and have long been used for understanding molecular interactions and facilitating materials design. Some of the most robust descriptors are derived from geometrical representations of molecules, called 3-dimensional (3D) descriptors. When calculated from molecular dynamics (MD) simulation trajectories, 3D descriptors can also capture the effects of operating conditions such as temperature or pressure. However, extracting 3D descriptors from MD trajectories is non-trivial, which hinders their wide use by researchers developing advanced quantitative-structure–property-relationship models using machine learning. Here, we describe a suite of open-source Python-based post-processing routines, called PyL3dMD, for calculating 3D descriptors from MD simulations. PyL3dMD is compatible with the popular simulation package LAMMPS and enables users to compute more than 2000 3D molecular descriptors from atomic trajectories generated by MD simulations. PyL3dMD is freely available via GitHub and can be easily installed and used as a highly flexible Python package on all major platforms (Windows, Linux, and macOS). A performance benchmark study used descriptors calculated by PyL3dMD to develop a neural network and the results showed that PyL3dMD is fast and efficient in calculating descriptors for large and complex molecular systems with long simulation durations. PyL3dMD facilitates the calculation of 3D molecular descriptors using MD simulations, making it a valuable tool for cheminformatics studies. Graphical Abstract

BackgroundExposure to high-intensity X-ray irradiation induces numerous defects in the thin films of optical components applied to X-ray free-electron laser (XFEL) facilities. These defects result in structural damage to the material and degradation of macroscopic properties, thereby affecting its service life and significantly compromising the reliability and stability of XFEL facilities.PurposeThis paper aims to design and implement an automated irradiation simulation software based on Python called automatic irradiation simulation based on LAMMPS (AISL) to support the simulation research of XFEL radiation damage to materials using molecular dynamics methods.MethodsAISL was designed to facilitate high-throughput automated studies on XFEL radiation damage by exploring the process of radiation-induced defects and promoting the accumulation of data for radiation-resistant materials. This software package established an automated workflow pipeline for simulation tasks, encompassing aspects such as batch submission management, scheduling of simulation tasks, reliable storage of computational data, and post-processing of thermodynamic information. Additionally, the metadata was automatically recorded in a radiation damage simulation database based on MongoDB, so were the workflow information, and calculation result files of the simulation. Finally, the utilization of AISL in simulating radiation damage in metal thin films of XFEL optical components was demonstrated to verify the validation of AISL.Results & ConclusionsThe demonstration results indicate that AISL is an effective, user-friendly software for conducting high-throughput automated irradiation simulation studies. It significantly enhances the efficiency of material irradiation damage simulation calculations using LAMMPS.

Aerogels are formed from a lattice of interconnected nanoparticles with a nanometer space between them. These nanostructured materials, with very low density and high specific surfaces, show exceptional properties, so their applications in various fields are expanding. In the present study, the mechanical behavior of paraffin-reinforced silica aerogel was examined by the change in the stress-strain curve, ultimate strength (US), and Young's modulus (YM) at different initial temperatures of 300, 310, 320, 330, and 350 K by MD and LAMMPS. It is revealed that rising the initial temperature can affect the silica aerogel's mechanical properties and impair the structure's mechanical strength. By increasing the initial temperature from 300 to 350 K, the US and YM modules declined from 410.45 to 1073.13 to 351.36–661.4 MPa, respectively. Physically, this mechanical performance results from increased atomic oscillations inside the computational box. Therefore, it is concluded that the effect of temperature on silica's mechanical performance is important and used in various industries.

Copyright of Oilfield Chemistry is the property of Sichuan University, Oilfield Chemistry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Atomic oxygen (AO), which is one of the most predominant and conspicuous space environmental factors in the low earth orbit, leads to severe deterioration of polymeric materials in spacecraft. The AO flux density and ambient temperature vary while a craft orbits in space; thus, it is necessary to pay close attention to the flux density and temperature effects on the mechanism of the AO interaction with materials. In past years, polyimide has been widely used on spacecraft due to its excellent performance—that is the reason why we chose Upilex-S as the object for study. It was analyzed using the ReaxFF reactive force field molecular dynamics simulation, respectively from the aspect of impact-induced temperature variation, mass loss, reaction product and erosion yield. The results show that dense AO deposition on the surface impedes further erosion at low temperatures, and the AO interaction with Upilex-S is exacerbated as the ambient temperature increases. However, the accelerating rate is inversely proportional to the ambient temperature, which means the higher the ambient temperature is, the slower it increases. On the other hand, the interaction rate of AO induced to Upilex-S is aggravated as the flux density increases at the lower stage, while the interaction rate begins to drop as the flux density increases at the higher level. The AO erosion effect is a complicated process rather than a simple summation of single atomic oxygen interactions. Our study could be used as a technical reference for the wide usage of Upilex-S on spacecraft. [ABSTRACT FROM AUTHOR]

The present paper considers a mathematical model describing the time evolution of spin states and magnetic properties of a nanomaterial. We present the results of two variants of nanosystem simulations. In the first variant, cobalt with a structure close to the hexagonal close-packed crystal lattice was considered. In the second case, a cobalt nanofilm formed in the previously obtained numerical experiment of multilayer niobium–cobalt nanocomposite deposition was investigated. The sizes of the systems were the same in both cases. For both simulations, after pre-correction in the initial time stages, the value of spin temperature stabilized and tended to the average value. Also, the change in spin temperature occurred near the average value. The system with a real structure had a variable spin temperature compared to that of a system with an ideal structure. In all cases of calculations for cobalt, the ferromagnetic behavior was preserved. Defects in the structure and local arrangement of the atoms cause a deterioration in the magnetic macroscopic parameters, such as a decrease in the magnetization modulus.

The decline in oil production has led to the development of the Enhanced Oil Recovery (EOR) technology to increase oil production. Chemical injection is one of the methods in EOR by injecting surfactants or polymers into reservoir wells. To understand the properties and dynamics of surfactants and polymers at the nanoscale, computational studies using molecular dynamics simulation were carried out. In this study, surfactant Sodium Dodecyl Benzene Sulfonate (SDBS) and polymers such as Polyacrylamide (PAM) were used to investigate their effect on the oil-water interface system at the atomic level. Molecular dynamics simulation was carried out using Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to calculate the diffusion coefficient and Interface Formation Energy (IFE) value for the addition of the surfactant and polymers. The simulation results show that the addition of the surfactant and polymers affects the water-oil interface system differently. The diffusion coefficient results indicates that there are strong interactions between SDBS and dodecane with D of 0.01358. While for PAM, the interactions with water are more significant with D of 0.059. The results of the IFE calculation value also show that the addition of SDBS and PAM makes the water-oil interface system more stable with the negative IFE value of -197.51 and -13.13 Kcal/mol respectively. The results of this study will be used as a reference and a basis for designing new surfactants or polymers that will led to more oil recovery.

Polyimides are polymeric materials that are widely used in spacecraft applications owing to their unique properties. However, exposure to a low-Earth-orbit environment containing atomic oxygen (AO) results in the disintegration of polymeric materials on the surface of spacecraft, thereby affecting the lifespan. Along with the development of theoretical research, the reactive force-field (ReaxFF) interatomic potential has become a robust computational method for exploring, developing and optimizing the material properties. This study employs the ReaxFF reactive-force-field molecular dynamics simulation (ReaxFF MD) program to investigate and compare the performance of two typical polyimide materials, Kapton and Upilex-S, under the impact of AO. Various aspects such as variations in the temperature, mass loss, decomposition products, and damage propagation depth were examined. Although these materials have similar elemental composition (C/H/O/N), they have different structures. Our results indicate that AO is initially adsorbed on the surfaces of both Kapton and Upilex-S. The continuous impact of AO leads to chemical reactions between AO and Kapton/Upilex-S. Erosion proceeds from the surface toward the interior of the materials. Similar to the findings of Experiment 2 conducted by the Materials International Space Station, our results also reveal that Upilex-S exhibits a lower mass loss and erosion yield than Kapton under the same AO conditions. This difference is primarily attributed to the distinct molecular structures of both Kapton and Upilex-S. Our study could provide valuable technical support for the extensive application of Upilex-S in spacecraft.

Composite materials are gaining increasing attention from researchers worldwide due to their ability to offer tailored properties for various technical challenges. One of these promising fields is metal matrix composites, including carbon-reinforced metals and alloys. These materials allow for the reduction of density while simultaneously enhancing their functional properties. This study is focused on the Pt-CNT composite, its mechanical characteristics, and structural features under uniaxial deformation depending on temperature and mass fractions of carbon nanotube (CNT). The mechanical behavior of platinum reinforced with carbon nanotubes of diameters varying in the interval 6.62–16.55 Å under uniaxial tension and compression deformation has been studied by the molecular dynamics method. Simulations for tensile and compression deformations have been done for all specimens at different temperatures (viz. 300 K, 500 K, 700 K, 900 K, 1100 K, and 1500 K). The calculated mechanical characteristics allow us to conclude that, compared to pure platinum, the Young's modulus increased by about 60%. The results indicate that yield and tensile strength values decreases with increase in temperature for all simulation blocks. This increase was due to the inherent high axial rigidity of CNTs. In this work, these characteristics are calculated for the first time for Pt-CNT. It can be concluded that CNTs can be an effective reinforcing material for composites based on a metal matrix under tensile strain. [ABSTRACT FROM AUTHOR]

Employing the isothermal molecular dynamics and the embedded atom method, we simulated melting of metallic nanoparticles (Au, Ag, Cu, Ni, and Pb ones). In more detail, the results for Au and Ag nanoparticles are presented and discussed. At first, we analyzed the behavior of the temperature dependences for the potential (cohesive) term into the specific (per atom) internal energy and for the degree of crystallinity in the course of heating nanoparticles. We have found that the results obtained for nanoparticles of about 4 and 8 nm in size (containing 2093 and 20,113 atoms, respectively) demonstrate the continuous melting. Employing the dependence of the specific potential energy on the distance to the nanoparticle center of mass and the common neighbor analysis, we showed that the continuous melting occurs via the surface pre-melting mechanism. Then, we evaluated the self-diffusion coefficient in the surface disordered layers of Au and Ag nanoparticles and found that our results agree in order of magnitude (10−9 m2/s) with the values of the self-diffusion coefficient for the bulk Au and Ag melts at the corresponding bulk melting temperatures. Finally, combining in our molecular dynamics experiments continuous heating Au nanoparticles with annealing them at some constant selected temperatures, we have shown that the liquid nucleation and growth mechanism should be most adequate to the melting behavior of metallic nanoparticles. [ABSTRACT FROM AUTHOR]

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In this work, bimetallic Cu-Ag nanoparticles of five stoichiometric compositions of various sizes were studied by molecular dynamics method using a many body EAM potential. Regularities of the structure formation are established, their characteristic features are described. In particular, in compositions with 10, 70, and 90 at.% Cu content, after the melt cooling, typical fcc structures with intersecting atomic planes of the hcp phase are formed. In compositions of 30 and 50 at.% Cu, the fraction of identified phases does not exceed 20% of the total number of atoms. A tendency to the formation of a core-shell structure was revealed in the case of a high copper content, while in the case of a high silver content, a so-called onion structure is formed. Using the caloric curves of the potential term of the internal energy, the melting and crystallization temperatures were determined. It has been established that the concentration dependences of the melting temperature of bimetallic Cu-Ag nanoparticles have a minimum corresponding to the equiatomic composition for all sizes. For the crystallization temperature, both the concentration dependences and the size dependences are less pronounced, but the minimum value of the crystallization temperature also corresponds to the equiatomic composition for all sizes; with an increase in the size of bimetallic Cu-Ag nanoparticles, a slight increase in the crystallization temperature is observed.

Composite materials are gaining increasing attention from researchers worldwide due to their ability to offer tailored properties for various technical challenges. One of these promising fields is metal matrix composites, including carbon-reinforced metals and alloys. These materials allow for the reduction of density while simultaneously enhancing their functional properties. This study is focused on the Pt-CNT composite, its mechanical characteristics, and structural features under uniaxial deformation depending on temperature and mass fractions of carbon nanotube (CNT). The mechanical behavior of platinum reinforced with carbon nanotubes of diameters varying in the interval 6.62–16.55 Å under uniaxial tension and compression deformation has been studied by the molecular dynamics method. Simulations for tensile and compression deformations have been done for all specimens at different temperatures (viz. 300 K, 500 K, 700 K, 900 K, 1100 K, and 1500 K). The calculated mechanical characteristics allow us to conclude that, compared to pure platinum, the Young’s modulus increased by about 60%. The results indicate that yield and tensile strength values decreases with increase in temperature for all simulation blocks. This increase was due to the inherent high axial rigidity of CNTs. In this work, these characteristics are calculated for the first time for Pt-CNT. It can be concluded that CNTs can be an effective reinforcing material for composites based on a metal matrix under tensile strain.

The performance of sodium superionic conductor (NASICON)-type LiZr 2 (PO 4) 3 (LZP) solid electrolytes for Li-ion batteries is dependent on their ion transportation properties. Therefore, to achieve high stability, ionic conductivity, and good compatibility with Li, the LZP solid electrolyte has chosen and doped with Al to improve aforesaid properties. Also, the effect of the dopant on various parameters has been investigated via MD simulations and experimentally. In this study, molecular dynamics (MD) simulations were used to investigate the effect of Al doping on the ion transport properties of Li 1+ x Al x Zr 2− x (PO 4) 3 (LAZP, x = 0.0–1.0) solid electrolytes. A facile solid-state reaction was used to synthesize both pristine and Al-doped solid electrolytes and to estimate the effect of doping on the ionic conductivity and ion diffusion in LZP. Computational and experimental results provided strong evidence of improved ion conductivity and diffusion in LZP owing to the presence of the Al dopant. Furthermore, the computational results agreed well with the experimental results, thereby validating the computational model. A maximum ionic conductivity of σ Li = 2.77 × 10−5 S cm −1 (for x = 0.2) was obtained. Enhanced ionic conductivity was observed with Al dopants owing to the creation of interstitial Li ions through a reduction in grain boundary resistance. However, a further increase in the amount of dopant reduced the ionic conductivity of LZP owing to Li-ion trapping at the most stable and metastable sites around the Al insertions. Doped LZP solid electrolytes are suitable for use in energy storage devices because of their enhanced ionic conductivity compared to that of pristine LZP. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • Introduces Pizza3, a new simulation framework for food mechanics and deconstruction. • Overcomes finite-element limits for explicit microstructural representations in food. • Uses "food atoms" for versatile interactions in solid and liquid food phases. • Employs SPH for solids and artificial forces to model Newtonian liquid behaviors. • Validates Pizza3 with complex 3D cases, offering insights into in-mouth texture perception. Current mesh-based simulation approaches face significant challenges in continuously modeling the mechanical behaviors of foods through processing, storage, deconstruction, and digestion. This is primarily due to the limitations of continuum mechanics in dealing with systems characterized by free boundaries, substantial deformations, mechanical failures, and non–homogenized mechanical properties. The dynamic nature of food microstructure and the transformation of the food bolus, in relation to its composition, present formidable obstacles in computer-aided food design. In response, the Pizza3 project adopts an innovative methodology, utilizing an explicit microstructural representation to construct and subsequently deconstruct food products in a modular, Lego-like fashion. Central to this simulation approach are "food atoms", conceptualized from the principles of smoothed particle hydrodynamics. These units are significantly larger than actual atoms but are finely scaled to represent both solid and liquid states of food faithfully. In solid phases, food atoms interact via pairwise forces akin to bond-peridynamic methods, thus extending the capabilities of continuum mechanics to encompass large deformations and fracturing phenomena. For liquids, the model employs artificial conservative and dissipative forces, enabling the simulation of a variety of phenomena within the framework of partial compressibility. The interaction dynamics between rigid and soft objects and fluids are accurately captured through Hertzian contact mechanics, offering a versatile parameterization applicable to impermeable (but possibly penetrable) surfaces and enforcing no-slip conditions. The efficacy of this framework is showcased through the successful modeling of three time-dependent 3D scenarios, each rigorously validated against established analytical and experimental models. Advancing beyond these initial applications, the framework is further extended to more intricate cases inadequately addressed in current literature. This extension sheds light on the underlying mechanisms of in-mouth texture perception, offering new insights and tools for food engineering and design. [ABSTRACT FROM AUTHOR]