Large-scale Molecular Dynamics Simulations Research Articles

Large-Scale Molecular Dynamics Simulation Based on Heterogeneous Many-Core Architecture.

As the application of molecular dynamics (MD) simulations continues to evolve, the demand for accelerating large-scale simulation systems and handling of enormous simulation tasks is steadily increasing. We propose a parallel acceleration method for large-scale MD simulations based on Sunway heterogeneous many-core processors. This method integrates task scheduling, simulation calculations, and data storage, effectively tackling issues related to large-scale simulations and numerous simulation tasks. The task scheduling strategy flexibly handles tasks on various scales and enables parallel execution of multiple tasks. During the simulation calculations, we ported GROMACS to the Sunway architecture and accelerated the calculation of short-range forces through a heterogeneous processor. Our method achieves approximately 10-fold acceleration and 90% scalability when executing a single simulation task. When handling numerous simulation tasks, our method achieves parallel execution of all of the tasks with 90% scalability. By employing our method, we carried out 50 ns simulations on over 3000 distinct conotoxin structures individually within just 5 h. Additionally, we evaluated more than 200 protein-ligand complexes, and the simulation efficiency significantly exceeded that of midsized to small GPU clusters.

Silicene growth mechanisms on Au(111) and Au(110) substrates

Despite the remarkable theoretical applications of silicene, its synthesis remains a complex task, with epitaxial growth being one of the main routes involving depositing evaporated Si atoms onto a suitable substrate. Additionally, the requirement for a substrate to maintain the silicene stability poses several difficulties in accurately determining the growth mechanisms and the resulting structures, leading to conflicting results in the literature. In this study, large-scale molecular dynamics simulations are performed to uncover the growth mechanisms and characteristics of epitaxially grown silicene sheets on Au(111) and Au(110) substrates, considering different temperatures and Si deposition rates. The growth process has been found to initiate with the nucleation of several independent islands homogeneously distributed on the substrate surface, which gradually merge to form a complete silicene sheet. The results consistently demonstrate the presence of a buckled silicene structure, although this characteristic is notably reduced when using an Au(111) substrate. Furthermore, the analysis also focuses on the quality and growth mode of the silicene sheets, considering the influence of temperature and deposition rate. The findings reveal a prevalence of the Frank–van der Merwe growth mode, along with diverse forms of defects throughout the sheets.

Development of machine learning force field for thermal conductivity analysis in MoAlB: Insights into anisotropic heat transfer mechanisms

The MAB phases have garnered significant attention as a new generation high-temperature structural materials due to their outstanding high-temperature mechanical properties, resistance to oxidation at elevated temperatures, low-temperature synthesis, and machining capabilities. The chemically anisotropic bonding within MAB phases leads to unique anisotropic elastic properties, oxidation behavior, and electrical characteristics, posing challenges in understanding the structure-property relationships.To address this challenge, we leveraged recent advances in machine learning force fields based on quantum mechanics methods. Using ab initio molecular dynamics simulations, we constructed a comprehensive dataset and developed an accurate machine learning force field for the Mo–Cr–Al–B system based on deep neural network. We then employed non-equilibrium molecular dynamics simulations to calculate the phonon thermal conductivity of MoAlB, investigating its temperature dependence and anisotropy. Our analysis includes phonon density of states, phonon participation ratio, and spectral heat flux analysis, shedding light on the temperature-dependent anisotropy of phonon thermal conductivity in MoAlB. This work not only provides a reliable force field for large-scale molecular dynamics simulations but also advances our understanding of the composition-structure-performance relationship in MAB phases.

Liquid-like thermal conductivity in solid materials: Dynamic behavior of silver ions in argyrodites

Argyrodite-type compounds are renowned for their exceptional thermoelectric performance and ultralow thermal conductivity. While the latter is commonly attributed to the superionic behavior of cations, there has been limited research into how cations' static or dynamic behavior affects the thermal transport properties of argyrodites. To address and bridge this research gap, we employ a wide range of measurements and develop ab-initio based machine-learning interatomic potentials to perform large-scale molecular dynamics simulations on Ag8SiTe6 under different temperatures. We highlight the symmetry breaking and lattice-distortion scattering caused by chilled ions at low temperatures and the enhanced ionic diffusion behavior at elevated temperatures endowing argyrodites with superior superionicity and liquid-like thermal conductivity. Our findings also provide valuable insights into the ionic diffusion kinetics and the exotic lattice dynamics of liquid-like thermoelectrics.

The shear softening and dislocation glide competition due to the shear-induced short-range order degeneration in CoCrNi medium-entropy alloy

The short-range order (SRO) in multi-principal element alloys (MPEAs) is an intriguing topic in advanced alloy research. The crucial question related to this topic lies in the effect of the local chemical fluctuations on the deformation behavior of MPEAs. In this study, the large-scale molecular dynamics (MD) simulation is used to investigate the dislocation glide behavior and mechanical performance of CoCrNi medium-entropy alloy (MEA) with respect to the SRO and lattice distortion (LD) effects. The slip plane softening and dislocation glide competition are found in the models with SRO. The change of energy barrier caused by SRO degeneration is the dominant reason for the slip plane softening, while the combination of dislocation pinning and slip plane softening leads to the dislocation glide competition, which is the primary mechanism for the shear localization in the CoCrNi MEA with SRO. Moreover, the dislocation glide competition compensates for the strength loss induced by slip plane softening. The results provide a new proposition for the conflicting simulation and experimental results on the topic of the SRO effect in MPEAs.

Revisiting Protein-Copolymer Binding Mechanisms: Insights beyond the "Lock-and-Key" Model.

The "lock-and-key" model that emphasizes the concept of chemical-structural complementary is the key mechanism for explaining the selectivity between small ligands and a larger adsorbent molecule. In this work, concerning the copolymer chain using only the combination of N-isopropylacrylamide (NIPAm) and hydrophobic N-tert-butylacrylamide (TBAm) monomers and by large-scale atomistic molecular dynamics simulations, our results show that the flexible copolymer chain may exhibit strong binding affinity for the biomarker protein epithelial cell adhesion molecule, in the absence of hydrophobic matching and strong structural complementarity. This surprising binding behavior, which cannot be anticipated by the "lock-and-key" model, can be attributed to the preferential interactions established by the copolymer with the protein's hydrophilic exterior. We observe that increasing the fraction of incorporated TBAm monomers leads to a prevalence of interactions with asparagine and glutamine amino acids due to the emerging hydrogen bonding with both NIPAm and TBAm monomers. Our findings suggest the appearance of highly specific and high-affinity binding sites on the protein created by engineering the copolymer composition, which motivates the applications of copolymers as protein affinity reagents.

Orientation-dependent atomic-scale mechanism and defect evolution in β-Ga2O3 thin film epitaxial growth

β-Ga2O3 has been subjected to intense research interest as an ultrawide bandgap semiconductor. The epitaxial growth technique of β-Ga2O3 thin films plays a fundamental and vital role in Ga2O3-based device fabrication. In this work, the epitaxial growth mechanisms of β-Ga2O3 on four low-Miller-index facets, (100), (010), (001), and (2¯01), are systematically explored using large-scale machine-learning molecular dynamics simulations at the atomic scale. The simulations reveal that the migration of the face-centered cubic stacking O sublattice plays a dominant role in the different growth mechanisms between the (100)/(010)/(001) and (2¯01) orientations. The resultant complex combinations of the stacking faults and twin boundaries are carefully identified and show good agreement with experimental observations and ab initio calculations. Our results provide useful insights into the gas-phase epitaxial growth of β-Ga2O3 thin films and suggest possible ways to tailor its properties for specific applications.

Enhanced bond switching at complexion layer facilitates high fracture energy of LATP solid-state electrolytes

Bond-switching events at the interface of glass-ceramic electrolyte play crucial role in impeding crack propagation.

Mechanism of long-range hydrophobic force based on cavitation of metastable liquid film

Hydrophobic force, a key driving force in colloid physicochemical system and biological macromolecular system, exhibits a distinct multi-scale effect. The prevailing scholarly consensus attributes long-range hydrophobic force to bubble bridging, facilitated by unstable liquid film cavitation, while short-range force is thought to arise from the reorganization of water molecules at the solid-liquid interface. However, a comprehensive theoretical study remains elusive. To further elucidate the mechanism of the long-range hydrophobic force based on unstable liquid film cavitation, we carry out systematic research on the long-range hydrophobic force between perfluorooctyl trichlorosilane hydrophobic particles and the surface, by utilizing atomic force microscopy (AFM) and molecular dynamics simulations. According to AFM force tests, the long-range hydrophobic force escalates incrementally with subsequent close contacts before reaching a plateau. On the tenth contact, the penetration curve exhibits a sudden jump to an adhesion distance of 502.01 nm. A distinct step in the retraction curve suggests the rupture of the cavitation bubble capillary bridge. Importantly, the classical capillary force mathematical model provides an effective fit for the penetration curve. Our calculations estimate the volume of the capillary bridge at 0.30 μm³, offering direct theoretical evidence of the unstable liquid film cavitation bubble capillary bridge. Further insights are gained from large-scale tensile molecular dynamics simulations by using GROningen MAchine for Chemical Simulations (GROMACS). The inherent correlation mechanism of the formation, evolution, and mechanical behavior of the cavitation bubble capillary bridge in the separation process of hydrophobic particles are further explored from a molecular perspective. The results demonstrate that the local pressure drop occurring at the moment of “jump-out” separation of the hydrophobic particles attracts nitrogen molecules to diffuse into the liquid film, thereby forming a cavitation bubble capillary bridge. Simultaneously, a jumping behavior is observed in the calculated spring potential curve at the moment of capillary bridge rupture. Finally, the influence of solution gas content on long-range hydrophobic force is investigated. There is a positive correlation between gas molecule content and both the growth rate of cavitation bubble capillary bridge volume and the length of capillary bridge stretch-rupture, further demonstrating the gas concentration dependence of long-range hydrophobic forces. In a word, revealing the long-range hydrophobic force mechanism based on the cavitation of unstable liquid film can enhance our understanding of the interaction between colloid physical chemistry and biological macromolecules. Meanwhile, hydrophobic force is the fundamental driving force of particle-bubble adhesion in mineral flotation system, and the revelation of its action mechanism has important guiding significance for regulating the actual mineral flotation process.

Influence of iron anisotropy on phase transition near grain boundary under shock

As is well known, iron plays an important role in the fields of national defense and industry, so it is of great significance to study its behavior under dynamic high pressure. As one of the most common defects in metals in nature, grain boundaries have an important influence on the mechanical properties and deformation of materials under shock. This work intends to use large-scale non-equilibrium molecular dynamics simulation to study the influence of iron anisotropy on the phase transition in bicrystal under shock loading. By tracking the local structure, shear stress distribution and morphology characteristics after shock on both sides of the grain boundaries, the factors affecting the response on both sides of the grain boundary are analyzed. Our research result shows that shocking along the non-centrosymmetric grain direction can cause significant differences in the phase transition threshold, path and mode on both sides of the symmetric grain boundary. Especially, the different phase transition dynamic processes on both sides of the sigma11 grain boundary are discussed in detail in this work, which have been rarely discussed in previous studies. Considering the symmetry of the microstructure on both sides of this type of grain boundary, the result of asymmetric shock response is different from people’s inertial cognition. Finally, it is found that the atoms in both models will shift along the direction perpendicular to the shocked direction under shock, indicating that the shock wave generated by the piston method should no longer be simply regarded as one-dimensional when shocked along the non centrosymmetric crystal direction, and the displacement of atoms along the direction perpendicular to the shocked direction is closely related to the symmetry of the crystal, which causes significant differences in shear stress on both sides of the grain boundary and ultimately affects the shock response. This study reveals that the anisotropy of lattice has an important effect on the phase transition on both sides of grain boundaries under shock loading, which can provide theoretical support for the experimental studies of polycrystalline metals and alloys under shock.

Visualizing the SEI formation between lithium metal and solid-state electrolyte

Large-scale molecular dynamics simulations reveal the formation mechanism and structure of the solid electrolyte interphase between lithium metal and β-Li3PS4 in all-solid-state batteries.

The Li2Ti6O13 and Li2Zr6O13 composite as a high-performance anode for alkali-ion batteries: a molecular dynamics study.

The current development of technology has highlighted the necessity of compounds that enhance the durability and performance of alkali-ion batteries. The anodes of these batteries need to overcome the challenges of low dc-conductivity at ambient temperatures and interfacial resistance between the solid-state electrolyte. By conducting large-scale molecular dynamics simulations, we investigated the transport properties of Li2Ti6O13 and Li2Zr6O13 mono- and bi-crystals, as well as Li2Ti6O13@Li2Zr6O13 composites. While the monocrystalline and bi-crystalline Li2Zr6O13 show similar transport properties, the composite materials, combining both compounds, exhibit the highest diffusion coefficients and dc-conductivity. The transport properties of the composite materials are found to be significantly higher than those mono- and bi-crystalline samples due to the Li interstitial mechanism and the presence of grain boundaries. Our study offers valuable insights for the development of high-performance energy storage materials.

Modeling of Ferroelectric Phase Transitions with Graph Convolutional Neural Networks

Ferroelectric materials are widely used in functional devices, however, achieving convenient and accurate theoretical modeling of them has been a long-standing issue. Here, we propose a noval approach for the modeling of ferroelectric materials using graph convolutional neural networks (GNN). This approach utilizes GNNs to approximate the potential energy surface of ferroelectric materials, which then serves as a calculator to enable large-scale molecular dynamics simulations. Given atomic positions, the well-trained GNN model can provide accurate predictions on the potential energy and atomic forces, reaching a level of accuracy of 1 meV, which is comparable to <i>ab inito</i> calculations but with much less time expense by orders of magnitude. Benefiting from the high accuracy and fast prediction of neural networks, we further combine it with molecular dynamics simulations to investigate two representative ferroelectric materials—bulk GeTe and CsSnI<sub>3</sub>, and successfully produce their temperature-dependent structural phase transitions, which are in good agreement with experimental observations.During the GNN-based MD simulation of GeTe, we obeserve an unusual negative thermal expansion around the region of its ferroelectric phase transition, which has been reported in previous experiments. For CsSnI<sub>3</sub>, we correctly obtain the octahedron tilting patterns associated with its phase transition sequence. These results demonstrate the accuracy and reliability of GNNs in the modeling of potential energy surfaces of ferroelectric materials, providing a universal approach for their theoretical investigations.

Relationship between Surface States of Carbon Support and Electrode Reaction Activity in Cathode Catalyst Layer Toward High Power Output of Polymer Electrolyte Fuel Cells by Large-Scale Reactive Molecular Dynamics Simulations

Higher output of polymer electrolyte fuel cells (PEFC) is required for use in many industrial fields such as the transport industry. PEFCs consist of a gas diffusion layer, a catalyst layer (CL), and a polymer electrolyte membrane. The output of PEFCs depends on the electrode reaction activity of the CL consisting of the carbon support, ionomer, water, and Pt nanoparticles (NPs). For high electrode reaction activity, the optimization of the CL structures such as Pt alloy, pore structures of the carbon support, and I/C (Ionomer carbon ratio), are key factors. To optimize the CL structures, computational simulation, which can propose theoretical design principles, is a promising method. Thus, many researchers have investigated the CL structures with high electrode reaction activity by computational simulation to propose design principles. For example, first-principles calculation can optimize highly active Pt catalysts by considering activation barriers, molecular adsorption structures and surface electronic states, which involves the behavior of atoms and molecules. However, this method cannot consider the effects of carbon support, ionomer, and water because of the limitation in computational costs. On the other hand, macro-scale approach using differential equations can discuss the highly active CL structures since this method can consider multiple structures such as carbon support, ionomer distribution, water content, and Pt loading. However, this approach cannot consider the behavior of atoms and molecules. Therefore, large-scale molecular simulations which, can simultaneously consider the behavior of atoms and molecules, and the CL structures are required. Here, reactive molecular dynamics (RMD) simulation is a practical approach to deal with the behavior of atoms and the chemical reactions in the CL. By using RMD method, we successfully constructed large-scale CL structures and established the CL design methodology both including atomic and molecular effects and clarifying the effect of the pore size of carbon support on the electrode reaction activity [1]. In order to design the higher-performance CL structures, we focused on the distribution of water which mediates proton transfer process. Improving the wettability of carbon support by termination of hydroxyl groups to the carbon support surface can alter the water distribution. Therefore, by large-scale RMD simulations, we investigated the effect of the ratio of the hydroxyl groups on the carbon support surface on water distribution to propose design principles for higher-performance cathode CL structures.A CL structures model consisting of 1 million atoms was constructed by modeling carbon support, Pt NPs, ionomer, and water. We selected the carbon support, where there were six meso pores on an amorphous carbon sphere. The ratios of hydroxyl groups to the carbon surface atoms were set to 10 and 32% to control the water distribution on the carbon surface. In addition, Pt NPs were put on the carbon support outer surface and interior of the pores. The water film whose thickness is 0.7 nm and ionomer are coated on Pt-supported carbon. Hereafter, we call this structure catalyst particle (CP) model (Fig. 1).To clarify the effect of the ratio of hydroxyl groups on the carbons support surface, the morphology of the water film was compared in the CP models with different hydroxyl ratios. At the exterior of the pores, the water film was peeled off from the carbon support surface regardless of the ratio of hydroxyl groups. At the interior of the pores, when the ratio of hydroxyl groups was 10%, the water film was peeling from the carbon support surface（Fig. 2(a), (b)). On the other hand, when the ratio of hydroxyl groups was 32%, the water film did not peel off from the carbon support surface, and the structure of the water film was maintained (Fig. 2(c), (d)). Next, to clarify the effect of the water film morphology on the proton conduction to the Pt NPs, the water clusters as proton conduction paths were analyzed. Water clusters were defined as a group of water molecules whose inter-molecular distance is less than 3.5Å. The amount of proton conduction paths to the Pt NPs at the exterior of the pores did not change regardless of the ratio of hydroxyl groups. On the other hand, the amount of proton conduction path to the Pt NPs at the interior of the pores was increased by increasing the ratio of hydroxyl groups (Fig. 3). These results indicate that the increasing the ratio of hydroxyl groups on the carbon support surface to improve the proton conduction path is an effective approach for the design of the higher-performance cathode CL.[1] T. NAKAMURA, M. KUBO et al. J. Comput. Chem. Jpn., 20,150-154, (2021). Figure 1

Effects of Nanoparticle Size on the Thermal Decomposition Mechanisms of 3,5-Diamino-6-hydroxy-2-oxide-4-nitropyrimidone through ReaxFF Large-Scale Molecular Dynamics Simulations.

ReaxFF-lg molecular dynamics method was employed to simulate the decomposition processes of IHEM-1 nanoparticles at high temperatures. The findings indicate that the initial decomposition paths of the nanoparticles with different sizes at varying temperatures are similar, where the bimolecular polymerization reaction occurred first. Particle size has little effect on the initial decomposition pathway, whereas there are differences in the numbers of the species during the decomposition and their evolution trends. The formation of the hydroxyl radicals is the dominant decomposition mechanism with the highest reaction frequency. The degradation rate of the IHEM-1 molecules gradually increases with the increasing temperature. The IHEM-1 nanoparticles with smaller sizes exhibit greater decomposition rate constants. The activation energies for the decomposition are lower than the reported experimental values of bulk explosives, which suggests a higher sensitivity.

Ultrahigh Oxygen Ion Mobility in Ferroelectric Hafnia.

Ferroelectrics and ionic conductors are important functional materials, each supporting a plethora of applications in information and energy technology. The underlying physics governing their functional properties is ionic motion, and yet studies of ferroelectrics and ionic conductors are often considered separate fields. Based on first-principles calculations and deep-learning-assisted large-scale molecular dynamics simulations, we report ferroelectric-switching-promoted oxygen ion transport in HfO_{2}, a wide-band-gap insulator with both ferroelectricity and ionic conductivity. Applying a unidirectional bias can activate multiple switching pathways in ferroelectric HfO_{2}, leading to polar-antipolar phase cycling that appears to contradict classical electrodynamics. This apparent conflict is resolved by the geometric-quantum-phase nature of electric polarization that carries no definite direction. Our molecular dynamics simulations demonstrate bias-driven successive ferroelectric transitions facilitate ultrahigh oxygen ion mobility at moderate temperatures, highlighting the potential of combining ferroelectricity and ionic conductivity for the development of advanced materials and technologies.

Large-scale molecular dynamics simulations of bubble collapse in water: Effects of system size, water model, and nitrogen

Molecular dynamics simulations in the microcanonical ensemble are performed to study the collapse of a bubble in liquid water using the single-site mW and the four-site TIP4P/2005 water models. To study system size effects, simulations for pure water systems are performed using periodically replicated simulation boxes with linear dimensions, L, ranging from 32 to 512 nm with the largest systems containing 8.7 × 106 and 4.5 × 109 molecules for the TIP4P/2005 and mW water models, respectively. The computationally more efficient mW water model allows us to reach converging behavior when the bubble dynamics results are plotted in reduced units, and the limiting behavior can be obtained through linear extrapolation in L−1. Qualitative differences are observed between simulations with the mW and TIP4P/2005 water models, but they can be explained by the models’ differences in predicted viscosity and surface tension. Although bubble collapse occurs on time scales of only hundreds of picoseconds, the system sizes used here are sufficiently large to obtain bubble dynamics consistent with the Rayleigh–Plesset equation when using the models’ thermophysical properties as input. For the conditions explored here, extreme heating of the interfacial water molecules near the time of collapse is observed for the larger mW water systems (but the model underpredicts the viscosity), whereas heating is less pronounced for the TIP4P/2005 water systems because its larger viscosity contribution slows the collapse dynamics. The presence of nitrogen within the bubble only starts to affect bubble dynamics near the very end of the initial collapse, leading to an incomplete collapse and strong rebound for the mW water model. Although nitrogen is non-condensable at 300 K, it becomes highly compressed and reaches a liquid-like density near the collapse point. We find that the dissolution of nitrogen is much slower than the movement of the collapsing water front, and the re-expansion of the dense nitrogen droplet gives rise to bubble rebound. The incompatibility of the collapse and dissolution time scales should be considered for continuum-scale modeling of bubble dynamics. We also confirm that the diffusion coefficient for dissolved nitrogen is insensitive to pressure as the liquid transitions from a compressed to a stretched state.

Origin of thermal deformation induced crystallization and microstructure formation in additive manufactured FCC, BCC, HCP metals and its alloys

The additive manufacturing (AM) technology has received the widespread attention in the industrial application because of its unique ability to achieve the complex shape and ideal performance. Unfortunately, the impact of the material natural characteristics, such as the crystal structure and alloying, on the microstructure formation at the nanoscale has never been revealed in AM metals. Here, we use large-scale molecular-dynamics simulations to study the rapid thermal deformation processes of additively-manufactured face-centered-cubic (FCC), body-centered-cubic (BCC), hexagonal close-packed (HCP) metals and their alloys (FCC Cu, CuAl0.1, BCC Fe, FeAl0.1, and HCP Mg, MgAl0.1) in the molten pool, in an attempt to elucidate the intrinsic physical mechanisms controlling the crystal nucleation and growth under the complex thermal stress. The results show that the arcuate solid-liquid interface migrates towards the liquid phase until the complete crystallization, in good agreement with the experimental observation. The solidification rate follows a unified slow-to-fast law in the three types of metals, due to the competition between the compressive thermal stress and fast atomic motion. It is noteworthy that the critical radius of the crystal nucleus in the FCC and BCC metals is smaller than that in the HCP metal. The FCC metal exhibits the weak nucleation ability and growth rate, and yet the HCP metal shows the fast growth rate and stable columnar crystal nucleation. Especially, due to the dual regulation of the steep thermal gradient and solute redistribution on the growth driving force, the alloying increases the constitutive supercooling of the solidification front and inhibits the growth of columnar crystals. This trend is particularly prominent in FCC alloys, which is manifested by the obvious amorphous phase and discrete nucleation point in the upper part of the melt pool. The nucleation barrier free energy descends in order of FCC, BCC, and HCP pure metals, but the alloying would increase this energy in the corresponding alloys. The current work gives an insight into the atomic mechanism of the nucleation and growth in AM FCC, BCC, and HCP metals.

Multiple structural phase transitions in single crystal silicon subjected to dynamic loading

Single crystal Silicon (SC Si), as one of the most extensively used elements, has a series of complex phase changes, however, it is not fully understood under dynamic loading conditions. In this letter, both the shock induced multiple solid-solid phase transformations and solid-liquid transition are systematically investigated using large-scale molecular dynamics (MD) simulations. With the increase of particle velocities up to 2.8 km/s, the SC Si is revealed to undergo a continuous structural phase transitions from cubic diamond (cd) to β-tin, bct5, near-simple cubic (sc), and body centered cubic (bcc) structure. Furthermore, the liquid Si is distinguished and shows solid-liquid coexistence under intensive shocks. Our work dissects the continues multiple phase transitions in shocked Si for the first time in MD simulations, which provides new understandings of phase transitions of Si under dynamic loadings, and strongly supports and complements the relevant reported experimental researches.

Simulation of two nanoparticle melting to understand the conductivity drop of 3D-printed silver nanowires

The future flexible sensor technology will require low-temperature, fast processing 3D printing techniques that will rely heavily on the quality of nanoparticle (NP) Ink. Electrical conductivity has been found to decrease in majority of the 3D printed electronic wires. Herein we report a fundamental understanding in drop of electrical conductivity in processed silver (Ag) line wire, generally found in Ag-nanoparticle Ink, using large-scale atomistic molecular dynamics (MD) simulations of sintering of five different sizes of Ag NPs. To preserve the high conductivity of pure silver wires, the integrity of the pristine face-centered cubic (FCC) crystalline structure must be retained in the processed line wires. Simulations show that the pristine Ag FCC structures of the nanoparticles are not recovered after melting and resolidification, instead, the resolidified material is paracrystaline. The breakdown of pristine FCC structures might be the cause of the drop in conductivity of processed Ag wires. Simulation results suggest that the intermediate size nanoparticles retain highest percentage of the pristine silver face-centered cubic (FCC) structure after pulse treatments. Our results show that the most promising Ag-Ink should contain smaller to medium size silver NPs that can retain FCC structure after 3D printing of the Ag-Ink.