LAMMPS Research Articles

Investigating the role of temperature and moisture on the degradation of 3D-printed polymethyl methacrylate dental materials through molecular dynamics simulations

This study aimed to comprehensively investigate the degradation behavior of 3D printed polymethyl methacrylate (PMMA) dental materials, with a specific focus on the influential factors of temperature and moisture, by employing molecular dynamics simulations. Owing to their aesthetic properties, 3D-printed PMMA dental materials play a pivotal role in dental applications. However, understanding their degradation mechanisms, particularly in the context of temperature and moisture variations, is crucial for their long-term durability. A Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) was utilized for the molecular dynamics simulations. The simulation setup included temperature variations from 300 to 600 K and relative humidity (RH) levels ranging from 20 to 100%. Various mechanical properties and structural changes were analyzed to determine the degradation behavior. Energetic profiling during equilibration and the subsequent temperature variations were studied. The spatial distribution of the mean squared displacement, non-bond energy, Young’s modulus, bending stress, and volume expansion coefficient of the particles were quantitatively analyzed, revealing temperature- and moisture-dependent trends. The study concluded that temperature and moisture significantly affected the degradation behavior of 3D-printed PMMA dental materials. Higher temperatures and increased humidity levels contribute to reduced mechanical strength and altered structural properties, emphasizing the importance of controlling environmental conditions during fabrication.

Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

Study on the Irradiation Evolution and Radiation Resistance of PdTi Alloys.

Medium-entropy alloys (MEAs) exhibit exceptional mechanical properties, thermal properties, and irradiation resistance, making them promising candidates for aerospace and nuclear applications. This study utilized molecular dynamics simulations to examine the defect behavior in PdTi alloys under various irradiation conditions. Simulations were performed using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) with the modified embedded-atom method (MEAM) potential to describe interatomic interactions. Various temperatures, primary knock-on atom (PKA) energies, and elemental ratios were tested to understand the formation and evolution of defects. The results show that compared to pure Pd, PdTi alloys with increased entropy exhibit significantly enhanced irradiation resistance at higher temperatures and PKA energies. This study explored the impact of different elemental ratios, including Pd, PdTi1.5, PdTi, and Pd1.5Ti. Findings indicate that increasing the Pd concentration enhances the alloy's irradiation resistance, improving mobility and recombination rates of defect clusters. A one-to-one Pd-to-Ti ratio demonstrated optimal performance. Temperature analysis revealed that at 300 K and 600 K, PdTi alloys exhibit excellent irradiation resistance at a PKA energy of 30 keV. However, as the temperature rises to 900 K, the irradiation resistance decreases slightly, and at 1200 K, the performance is likely to decline further. This study offers some useful insights into the irradiation evolution and radiation resistance of PdTi medium-entropy alloys, which may help inform their potential applications in the nuclear field and contribute to the further development of MEAs in this area.

Enhancing Mechanical Properties of Graphene/Aluminum Nanocomposites via Microstructure Design Using Molecular Dynamics Simulations.

This study explores the mechanical properties of graphene/aluminum (Gr/Al) nanocomposites through nanoindentation testing performed via molecular dynamics simulations in a large-scale atomic/molecular massively parallel simulator (LAMMPS). The simulation model was initially subjected to energy minimization at 300 K, followed by relaxation for 50 ps under the NPT ensemble, wherein the number of atoms (N), simulation temperature (T), and pressure (P) were conserved. After the model was fully relaxed, loading and unloading simulations were performed. This study focused on the effects of the Gr arrangement with a brick-and-mortar structure and incorporation of high-entropy alloy (HEA) coatings on mechanical properties. The findings revealed that Gr sheets (GSs) significantly impeded dislocation propagation, preventing the dislocation network from penetrating the Gr layer within the plastic zone. However, interactions between dislocations and GSs in the Gr/Al nanocomposites resulted in reduced hardness compared with that of pure aluminum. After modifying the arrangement of GSs and introducing HEA (FeNiCrCoAl) coatings, the elastic modulus and hardness of the Gr/Al nanocomposites were 83 and 9.5 GPa, respectively, representing increases of 21.5% and 17.3% compared with those of pure aluminum. This study demonstrates that vertically oriented GSs in combination with HEA coatings at a mass fraction of 3.4% significantly enhance the mechanical properties of the Gr/Al nanocomposites.

Assessment of machine learning models trained by molecular dynamics simulations results for inferring ethanol adsorption on an aluminium surface

Molecular dynamics (MD) simulations can reduce our need for experimental tests and provide detailed insight into the chemical reactions and binding kinetics. There are two challenges while dealing with MD simulations: one is the time and length scale limitations, and the latter is efficiently processing the massive amount of data resulting from the MD simulations and generating the proper reaction rates. In this work, we evaluated the use of regression machine learning (ML) methods to solve these two challenges by developing a framework for ethanol adsorption on an Aluminium (Al) slab. This framework comprises three main stages: first, an all-atom molecular dynamics model; second, ML regression models; and third, validation and testing. In stage one, the adsorption of ethanol molecules on the Al surface for various temperatures, velocities and concentrations is simulated using the large-scale atomic/molecular massively parallel simulator (LAMMPS) and ReaxFF. The outcome of stage one is utilised for training, testing, and validating the predictive models in stages two and three. We developed and evaluated 28 different ML models for predicting the number of adsorbed molecules over time, including linear regression, support vector machine (SVM), decision trees, ensemble, Gaussian process regression (GPR), neural network (NN) and Bayesian hyper-parameter optimisation models. Based on the results, the Bayesian-based GPR showed the highest accuracy and the lowest training time. The developed model can predict the number of adsorbed molecules for new cases within seconds, while MD simulations take a few weeks. This adsorption rate can then be used in macroscale simulations to tackle the time and length scale limitations. The proposed numerical framework has the potential to be generalised and, therefore, contribute to future low-cost binding reaction estimations, providing a valuable tool for industry and experimentalists.

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

This work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace reduced-order model for the canonical (NVT) and isobaric (NPT) ensembles. The symplectic reduced-order basis is randomized on the tangent space of the Stiefel manifold to provide topological relationships and capture model-form uncertainty. Using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), we assess the relevance of these stochastic reduced-order atomistic models on canonical problems involving a Lennard-Jones fluid and an argon crystal melt.

Computational insights into the structural, thermodynamic and transport properties of CaF2-MgF2 binary fluoride system at high temperatures

The structural, thermodynamic and transport properties of the CaF2-MgF2 molten salt system were investigated with ab initio molecular dynamics (AIMD), system-specific neural network interatomic potentials (NNIPs) and universal PreFerred Potentials (PFP). We trained an NNIP model using AIMD data as input and used this potential to efficiently simulate the interactions within a large supercell in a temperature range of 1273–1773 K. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code was employed to validate our trained NNIP model. The Matlantis software with universal PFP is also presented to prove its feasibility for MD calculations and can be considered as a useful alternative simulation tool for higher-order systems where existing potentials are not readily available. We calculated structural and thermodynamic properties including radial distribution function (RDF), angular distribution function (ADF), specific heat capacity, ionic self-diffusivity, and viscosity. Our results indicate that the system exhibited a high degree of structural disorder, with the Ca, Mg, and F ions forming a liquid solution. Using PFP, the positions of the first peak in RDFs for Ca-F and Mg-F pairs are only slightly left-shifted (<0.05 Å), and the estimated viscosity of the melt decreases from 4.613 mPa·s to 1.846 mPa·s with an increase in temperature from 1273 K to 1773 K, in agreement with the NNIP trained specifically for CaF2-MgF2. Our results provide valuable insights into the properties of the CaF2-MgF2 system at high temperatures and serve as predictive models for the development of new electrolytes that could be used for silicon epitaxy by adding silica.

Mechanistic insights into condensate formation of human liver-type phosphofructokinase by stochastic modeling approaches

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.

Atomistic and continuum Ascertainment of The crack tip stress fields in anisotropic elastic cubic media

The article provides a comparative analysis of stresses associated with the crack tip in an anisotropic elastic medium with cubic crystalline symmetry of elastic properties under mixed loading conditions obtained by two fundamentally different approaches: atomistic simulations and continuum fracture mechanics methods. The atomistic modelling approach is premised on the application of the molecular dynamics (MD) method implemented in the open source code program Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). The continuum mechanics approach is based on the classical elasticity theory of anisotropic media, in which the mechanical fields associated with the crack tip are represented by the crack tip stress and displacement series expansions generalizing the well-known classical asymptotical presentation of M. Williams to the case of anisotropic media. Using the MD method, a large series of computations of the loading of monocrystalline copper and aluminum plates with a face-centered cubic crystal lattice weakened by a central crack applying the embedded atom potential (EAM) was implemented. MD modeling is aimed at determining the atomic stresses and strains near the crack tip. The computed atomic stresses were compared with the stress field determined by the continuum elasticity theory of anisotropic media for crystal lattices with cubic symmetry of elastic properties. A comparative analysis was carried out for the angular dependencies of the stress and strain tensor components at various selected distances from the crack tip for the entire range of mixed deformation forms starting from pure tensile loading and ending with forms close to pure transverse shear. It is ascertained that the crack tip fields determined on the basis of two fundamentally different approaches, precisely, discrete and continuum, are completely consistent with each other. It is established that mathematical methods of continuum fracture mechanics can be applied to describe stress, strain and displacement fields at the atomic level.

Molecular Dynamics Study of Adhesion-Related Structural Properties for PVDF-HFP Polymer Binders

The current lithium-ion battery (LIB) market is expanding rapidly. Binders are essential to maintaining the high capacity and longevity of batteries. These binders can be classified into organic binders used for cathodes and aqueous binders used for anodes. Among them, Poly(vinylidene fluoride) (PVDF) binder is a representative organic binder that offers excellent electrochemical stability. To solve low adhesive force and weak mechanical strength of conventional PVDF binders, hexafluoropropylene (HFP) is added to improve these properties. However, the present poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP) binders still show lower adhesive force than other polymeric binders, and therefore further research works are necessary.In this study, we employ classical molecular dynamics (MD) simulations to investigate the structural properties of the PVDF-HFP copolymers. To create realistic disordered PVDF-HFP polymers, we develop a computational scheme that can randomly arrange the angles and sequences of the constituent polymer chains. By varying the ratio of randomly arranged PVDF-HFP copolymers to 0/100, 5/95, 10/90, 15/85, and 20/80, we build a solution model that mimics the HFP concentration of PVDF-HFP (0–20%, Sigma Aldrich) used in the actual experiments. N-methyl-2-pyrrolidone (NMP) used as solvents. To create a large-scale model, we utilize the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and set parameters by using OPLS force field. This allows us to build a simulation model containing approximately 40,000 atoms consisting of 10 PVDF-HFP polymers and 1500 NMP monomers.After creating the simulation model, approximately eight steps of molecular dynamics simulation are performed by referring to the process of making the actual polymer film. In this process, NMP molecules are evaporated to produce a polymer film consisting only of PVDF-HFP polymers. Then we perform the adhesion analysis by applying forces to five polymer film models with different composition ratios in various conditions. Throughout these processes, we find the characteristic changes depending on the composition ratio. Finally, we will present the possible routes that can lead to the enhanced adhesive properties of PVDF-HFP, which is a key requirement to the development of high performance binders.

Energy landscapes for clusters of hexapeptides.

We present the results for energy landscapes of hexapeptides obtained using interfaces to the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. We have used basin-hopping global optimization and discrete path sampling to explore the landscapes of hexapeptide monomers, dimers, and oligomers containing 10, 100, and 200 monomers modeled using a residue-level coarse-grained potential, Mpipi, implemented in LAMMPS. We find that the dimers of peptides containing amino acid residues that are better at promoting phase separation, such as tyrosine and arginine, have melting peaks at higher temperature in their heat capacity compared to phenylalanine and lysine, respectively. This observation correlates with previous work on the same uncapped hexapeptide monomers modeled using atomistic potential. For oligomers, we compare the variation in monomer conformations with radial distance and observe trends for selected angles calculated for each monomer. The LAMMPS interfaces to the GMIN and OPTIM programs for landscape exploration offer new opportunities to investigate larger systems and provide access to the coarse-grained potentials implemented within LAMMPS.

Mechanical properties of Si(1−x)–C(x): strength and stiffness of materials using LAMMPS molecular dynamics simulation

This study investigated the mechanical properties (elastic modulus, tensile strength, yield strength, and toughness) of different percent C of silicon carbide (SiC) using molecular dynamics simulations via the large-scale atomic/molecular massively parallel simulator (LAMMPS) with the uniaxial tensile test at four strain rates: 0.1, 0.5, 1.0, and 5.0 m s−1, using the Tersoff potential. The simulation uses 20 × 20 × 20 atoms (108.6 Å × 108.6 Å × 108.6 Å) of the diamond cubic structure of Si, then carbon atoms were placed randomly at 5% intervals from 0–50 percent C. Results show improved mechanical properties when increasing percent C until peaking at 25%, before decreasing. This is caused by the shortest bond length at 25 percent C from the increase of Si=C using the radial distribution function analysis. Increasing the strain rate generally improves the mechanical properties of the material. The deformation mechanism shows that increasing (decreasing) strain rate generally results in multiple (lesser) failure points with a ductile (brittle) fracture mode.

Elastic response of trabecular bone under compression calculated using the firm and floppy boundary lattice element method

Micro-Finite Element analysis (μFEA) has become widely used in biomechanical research as a reliable tool for the prediction of bone mechanical properties within its microstructure such as apparent elastic modulus and strength. However, this method requires substantial computational resources and processing time. Here, we propose a computationally efficient alternative to FEA that can provide an accurate estimation of bone trabecular mechanical properties in a fast and quantitative way. A lattice element method (LEM) framework based on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) open-source software package is employed to calculate the elastic response of trabecular bone cores. A novel procedure to handle pore-material boundaries is presented, referred to as the Firm and Floppy Boundary LEM (FFB-LEM). Our FFB-LEM calculations are compared to voxel- and geometry-based FEA benchmarks incorporating bovine and human trabecular bone cores imaged by micro Computed Tomography (μCT). Using 14 computer cores, the apparent elastic modulus calculation of a trabecular bone core from a μCT-based input with FFB-LEM required about 15 min, including conversion of the μCT data into a LAMMPS input file. In contrast, the FEA calculations on the same system including the mesh generation, required approximately 30 and 50 min for voxel- and geometry-based FEA, respectively. There were no statistically significant differences between FFB-LEM and voxel- or geometry-based FEA apparent elastic moduli (+24.3% or +7.41%, and +0.630% or -5.29% differences for bovine and human samples, respectively).

Dust Condensation of SiC, SiO in Asymptotic Giant Branch Stellar Winds-SiC Spectrum

We have chosen the Large Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code to calculate the coalescence of silicon carbide (SiC), silicon oxide dust (SiO) in the AGB stellar wind. LAMMPS is a classical molecular dynamics simulation code. At the same time, we consider the effect of temperature on the evolution of molecular dynamics. We also calculated the temperature change of non-spherical SiC, SiO dust coalescence. The condensation temperature range of SiC dust in the AGB stellar wind is [300–500]k and [900–1100]k for SiO. Finally, the infrared spectrum of SiC was calculated using Gaussian 16 software. The 77SiC, 70Si3C3, and 121Si3C3 models have clear characteristic peaks of infrared spectra responding at 5, 8.6, 11.3, 15, 19, and 37 μm.

The analysis of extension evolution law and damage behavior characteristic for line microcracks on Si3N4 bearing balls

To predict the relation between extension evolution law and damage of line microcracks on silicon nitride bearing balls. Firstly, the 3D point cloud features of line microcracks are obtained based on multi-image 3D reconstruction. Next, the point cloud diagram data is optimized to fit the molecular dynamics geometric model of line microcracks extension process. Then, according to the Si3N4 molecular dynamics deep learning potential, the molecular dynamics mechanical model is established. Finally, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is used to numerically solve the extension evolution of line microcracks. The experiment result shows that from the change analysis of single-layer surface mesh, the microcracks extension is concentrated in the central region of the indentation. The new microcracks spread along both sides of the original microcracks. After uniformly distributed load is applied to line microcracks, there is a phenomenon of concentrated swirling microcracks formation under the indentation region. By analyzing the atomic coordination number nephogram, the microcracks extension occurs when the proportion of amorphous atoms is up to 7 % during loading. And the plastic deformation occurs when the proportion of amorphous atoms is dropped to 6 % during unloading. In addition, in the process of indentation loading, plastic deformation and slip zone occur on Si3N4 bearing balls surface. However, the strain is accumulated in the middle region during unloading. The slip zone moves inward and becomes thin, and the elastic deformation partially is recovered.

Promoting nanoscale deformation twinning through FCC phase decomposition in AlCoCrFeMo0.05Ni2 high entropy alloy

The high temperature plasticity of AlCoCrFeMo0.05Ni2 high entropy alloy (HEA) is significantly enhanced after annealing. However, the specific mechanisms are not fully understood. In this study, a polycrystalline HEA model with dimensions of 18 nm×18 nm×26 nm was used to analyze stress mapping under uniaxial tension through Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Complemented by experimental results, one can see that the decomposition of the FCC phase promotes the formation of nanoscale deformation twins. The formation of deformation twinning is most likely one of the primary reasons for the substantial improvement in high temperature plasticity. The findings provide valuable insights for controlling the high temperature performance of the alloy.

Investigation of some thermal properties of iron and chromium-based core-shell nanowires

Fe and Cr based core–shell nanowires (CSNWs) are modeled as cylindrical structures in which the atoms are arranged in a bcc crystal structure. Two different sizes with diameters of 2.5 nm and 4.5 nm for nanowires (NWs) are created and their lengths are set as four times their diameters. Their structural and thermodynamic properties are investigated through the molecular dynamics (MD) simulation technique in the canonical (NVT) statistical ensemble implemented in the open-source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) software package. Atomic interactions between the atoms are described by using the many-body potentials based on the Embedded Atom Model (EAM). The melting temperatures of the NWs have been determined by investigating the behavior of the potential energy, specific heat capacity, radial distribution function, Lindemann melting criterion, the mean square displacement, and diffusion coefficients as a variation of temperature. The same melting temperatures are acquired from all these temperature-dependent physical properties for all NWs considered in this study. To the best of our knowledge, our simulation results are presented for the first time in this work and have the potential to guide experimental studies.

Investigation of dislocation and twinning behavior in HMX under high-velocity impact employing molecular dynamics simulations.

Under the ReaxFF/lg force field, the multiscale shock technique (MSST) was employed to investigate the decomposition behavior of perfect, dislocated, and twinned octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) at a velocity of 11 km/s. This study aimed to analyze the changes in system temperature, bond formation and breaking, variations in the number of small molecules, and the number of clusters. The results indicated that the sensitivity of dislocated HMX was the lowest, while the sensitivity of twinned and perfect HMX was comparable. Comparing the formation and breaking of bonds in HMX during the shock process, it was found that the change in the number of bonds in dislocated HMX was similar to that in perfect HMX, whereas twinning accelerated the breaking of bonds. By analyzing the changes in small molecular fragments (CO, CO2, H, H2, H2O, N2, N2H, NH2, NO, NO2, and O) during the shock process of HMX, it was found that dislocation had a relatively minor effect on the small molecular fragments, while twinning promoted the generation of CO, H, NO, and O and accelerated the decomposition of NO. A comparison of the number, weight, and atomic ratio of clusters under perfect, dislocated, and twinned conditions revealed that under the influence of shock, the number of clusters initially increased sharply and then decreased slowly. Meanwhile, compared to the perfect and dislocated explosives, the number of clusters under the twinned structure was significantly fewer, indicating that the twinned structure could reduce cluster formation. The proportion of oxygen to carbon in the twinned HMX was lower than that in the perfect and dislocated explosives, possibly due to the higher content of small molecular fragment O in twinned HMX. Different structures of HMX crystals were constructed, including twinned defect structure (with a supercell containing 6458 atoms), dislocation defect structure (with a supercell containing 2352 atoms), and perfect structure (also with a supercell containing 2352 atoms). The modeling of defect crystal structures was carried out using the Atomsk software. For the twinned defect structure, we first constructed a mirror symmetric structure of the original configuration and then merged these two structures together. For the dislocation defect structure, we shifted a segment of the originally ordered perfect crystal structure by a certain distance using Atomsk. Before conducting the simulations, we performed geometric optimization of the models using the conjugate gradient (CG) algorithm and carried out 10 ps of NVT and NPT simulations to equilibrate the energy, temperature, and other parameters within the system. Finally, a 50-ps MSST impact simulation was performed using Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS).

Effects of Topological Parameters on Thermal Properties of Carbon Nanotubes via Molecular Dynamics Simulation

Due to their unique properties, carbon nanotubes (CNTs) are finding a growing number of applications across multiple industrial sectors. These properties of CNTs are subject to influence by numerous factors, including the specific chiral structure, length, type of CNTs used, diameter, and temperature. In this topic, the effects of chirality, diameter, and length of single-walled carbon nanotubes (SWNTs) on the thermal properties were studied using the reverse non-equilibrium molecular dynamics (RNEMD) method and the Tersoff interatomic potential of carbon–carbon based on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). For the shorter SWNTs, the effect of chirality on the thermal conductivity is more obvious than for longer SWNTs. Thermal conductivity increases with increasing chiral angle, and armchair SWNTs have higher thermal conductivity than that of zigzag SWNTs. As the tube length becomes longer, the thermal conductivity increases while the effect of chirality on the thermal conductivity decreases. Furthermore, for SWNTs with longer lengths, the thermal conductivity of zigzag SWNTs is higher than that of the armchair SWNTs. Thermal resistance at the nanotube–nanotube interfaces, particularly the effect of CNT overlap length on thermal resistance, was studied. The simulation results were compared with and in agreement with the experimental and simulation results from the literature. The presented approach could be applied to investigate the properties of other advanced materials.

Effects of sp3 bond ratio and modulation ratios on nanotribology behaviors of diamond-like carbon coatings investigated using atomistic nanoscratching simulations.

Diamond-like carbon (DLC) films are amorphous solids in which carbon atoms are linked by hybridized sp3, sp2, and sp bonds. The mechanical and tribological properties of DLC films can be adjusted by tuning the sp2/sp3 bond ratio. These films are typically used as protective coatings for components such as dies, automotive engines, mechanical seals, hard disk drives, biological engineering devices, and micro/nano-electromechanical systems. Further exploration of the mechanical and tribological behavior of DLC films is important for enhancing functional design for the above applications. The simulation results show that single-layer DLC with a higher sp3 ratio has better resistance to indentation. Single-layer DLC with a lower initial sp3 ratio has lower friction and a shorter repeated cycle in the friction force curve due to an increase in the graphitization of the friction interface. Single-layer DLC with a higher sp3 ratio has a higher coefficient of friction because compared with the normal force, the friction force is much more sensitive to an increase in the sp3 ratio. Molecular dynamics simulations based on the Tersoff potential were performed using the open-source code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator).