Nonequilibrium Molecular Dynamics Research Articles

The identification of the generalised Maxwell fluid for n-hexadecane liquids via non-equilibrium molecular dynamics simulations

ABSTRACT Linear viscoelasticity is very important for chain-molecular fluids. The generalised Maxwell constitutive equation is classical in which the linear viscoelastic fluids consist of a series of spring and dashpot. It is significant to identify the generalised Maxwell fluid of linear viscoelasticity for n-hexadecane liquids through non-equilibrium molecular dynamics simulations of small-strain amplitude oscillatory shear flows. For describing a characteristic of material viscoelasticity, the predicted relaxation modulus curves at different temperatures exhibit three regions: transition, rubbery, and flow. Additionally, the Cox-Merz rule is verified in which the complex oscillation-shear viscosity almost equals the steady-state shear viscosity with respect to shear rates.

Phonon transport across GaAs/Ge heterojunctions by nonequilibrium molecular dynamics

Interfaces are ubiquitous in modern electronics and assessing their properties is crucial when it comes to device reliability. Here, we present nonequilibrium molecular dynamics calculations of heat transport across GaAs/Ge heterojunctions. We compute the thermal boundary resistance, considering different interface morphologies, ranging from atomically flat to gradual or rough interfaces. We also discuss the implications for thermal rectification and predict a rectification coefficient as large as 30%.

Porosity and specific surface area dependence of shock-induced plasticity and melting in open-cell nanoporous Cu

We systematically study the plasticity and melting behavior in shock loading, as well as their dependence on porosity (ϕ) and specific surface area (γ) for nanoporous copper (NPC), by conducting large-scale non-equilibrium molecular dynamics simulations. During shock compression, the plasticity (i.e., dislocation slips) is dominant at lower impact velocities, while melting is governing at higher impact velocities. With increasing ϕ, both the plasticity and melting undergo the transitions from “heterogeneity” to “homogeneity” along the transverse directions. The increase in γ prompts an apparent heat release and gives rise to the transition from local plasticity to uniform solid disordering at lower impact velocities, while accelerates the melting at higher impact velocities, by converting more surface energy into internal energy. Upon impact, shock-induced pores collapse accelerates the consolidation of NPCs and is controlled by two mechanisms, i.e., the shearing ligament, prompted by plasticity, under low-velocity impact, and the internal micro-jetting facilitated by melting under high-velocity impact.

Explosions of nanodroplets studied with molecular dynamics simulations

Explosions of droplets that are caused by superheating of the liquid phase occur in many combustion processes but are difficult to investigate experimentally. We have studied this process for nanodroplets using non-equilibrium molecular dynamics simulations. Starting from an equilibrium state in which a spherical droplet is surrounded by a vapor phase, a local thermostat is used to impose a high temperature in a small control volume in the droplet center and the following process is studied for varying set temperatures. The fluid is modeled using the Lennard–Jones truncated and shifted potential. Depending on the set temperature, three different system responses were observed: (i) Low set temperatures lead to a shrinking of the droplet due to evaporation that follows the well-known d2 law. (ii) At intermediate set temperatures, a vapor bubble emerges in the droplet center and the liquid phase is formed into spherical shell that expands as the bubble inside of it grows. However, that spherical shell is only temporarily stable and eventually breaks apart. (iii) For high set temperatures, the abrupt and violent formation of the vapor bubble leads to an immediate breakup of the droplet. For case (ii), unexpected phenomena were observed. Oscillations in the diameter of the vapor bubble surrounded by the liquid film occurred. In some simulations, small holes formed temporarily in the liquid shell during its expansion, which closed again over the course of the simulation. Moreover, for one specific set temperature, a transition of the spherical droplet shell into a torus-like object was observed.

Comparative Study of the Orientation and Order Effects on the Thermoelectric Performance of 2D and 3D Perovskites.

Calcium titanium oxide has emerged as a highly promising material for optoelectronic devices, with recent studies suggesting its potential for favorable thermoelectric properties. However, current experimental observations indicate a low thermoelectric performance, with a significant gap between these observations and theoretical predictions. Therefore, this study employs a combined approach of experiments and simulations to thoroughly investigate the impact of structural and directional differences on the thermoelectric properties of two-dimensional (2D) and three-dimensional (3D) metal halide perovskites. Two-dimensional (2D) and three-dimensional (3D) metal halide perovskites constitute the focus of examination in this study, where an in-depth exploration of their thermoelectric properties is conducted via a comprehensive methodology incorporating simulations and experimental analyses. The non-equilibrium molecular dynamics simulation (NEMD) was utilized to calculate the thermal conductivity of the perovskite material. Thermal conductivities along both in-plane and out-plane directions of 2D perovskite were computed. The NEMD simulation results show that the thermal conductivity of the 3D perovskite is approximately 0.443 W/mK, while the thermal conductivities of the parallel and vertical oriented 2D perovskites increase with n and range from 0.158 W/mK to 0.215 W/mK and 0.289 W/mK to 0.309 W/mK, respectively. Hence, the thermal conductivity of the 2D perovskites is noticeably lower than the 3D ones. Furthermore, the parallel oriented 2D perovskites exhibit more effective blocking of heat transfer behavior than the perpendicular oriented ones. The experimental results reveal that the Seebeck coefficient of the 2D perovskites reaches 3.79 × 102 µV/K. However, the electrical conductivity of the 2D perovskites is only 4.55 × 10-5 S/cm, which is one order of magnitude lower than that of the 3D perovskites. Consequently, the calculated thermoelectric figure of merit for the 2D perovskites is approximately 1.41 × 10-7, slightly lower than that of the 3D perovskites.

Understanding the mechanism of permanganate ion rejection in TpPa-1/Ti3C2T2 composite membranes via molecular dynamic simulation

The purification and separation of small molecules can be improved by fabricating different composite membranes, in this work, the TpPa-1/Ti3C2T2 composite membranes with different structural parameters and terminating functional groups were designed for better permanganate (PP) ions separation with non-equilibrium molecular dynamics simulations. The rejection mechanism was explored from molecular level. It is found that water flux is mainly influenced by the offset and interlayer spacing of Ti3C2T2, while the rejection rate of PP ion is affected more by the slit width of MXene. The combination of TpPa-1 and Ti3C2(OH)2 membrane provides a comfortable zone in for PP ion rejection from the viewpoint of thermodynamic. While the other two composite membranes constructed with terminating functional groups (-F, –O) in Ti3C2T2 show different rejection mechanism from that in TpPa-1/Ti3C2(OH)2 composite membrane. The rejection of PP ions mainly caused by the dynamic hindrance caused by water wall formed in the entrance of Ti3C2T2 (T = –F, –O) slits.

Thermal transports of 2D phosphorous carbides by machine learning molecular dynamics simulations

Carbon phosphide is a newly discovered two-dimensional semiconductor material which wrinkles and has a significant carrier mobility. Due to lack an accurate force field, the use of molecular dynamics to study its phonon-dominated thermal conductivity which lead to inaccurate results. At present, the use of machine learning to construct a high-precision force field has become the mainstream research method to solve this problem. The main work of this study is to construct a comprehensive training sets for Phosphorus-Doped Graphene (PCn) (n = 3, 5, 6) and to use the fitted potential to calculate the related thermal properties. The research found that (PC5) exhibited anisotropic behavior, with a thermal conductivity of 106.6 Wm−1K−1 in the y-direction and 63.6 Wm−1K−1 in the x-direction. In comparison, (PC6) and (PC3) showed isotropic behavior, with thermal conductivity of approximately 104 Wm−1K−1 and 76.83 Wm−1K−1, respectively. Compared to monolayer graphene, the lower thermal conductivity of PCn is mainly attributed to phonon-phonon scattering effects, which are limited by the regular wrinkled structure. Additionally, low-frequency phonon have been found to have a significant impact on the thermal performance of PCn. Furthermore, we investigated the influence of uniaxial strain on the PC6 and observed an increase in the thermal conductivity with increasing strain. This study used key computational and analytical techniques, including phonon dispersion relations, homogeneous nonequilibrium molecular dynamics method, spectral thermal conductivity analysis. These findings provide a theoretical basis for understanding the thermal transport properties of PCn and will guide its potential applications value.

Effect of Tautomerization on Water Desalination by Covalent Organic Frameworks

Covalent organic frameworks (COFs) have gained increasing interest as promising building blocks for desalination membranes due to their inherent porosity. Efforts have been made to prepare COF membranes and explore their transport mechanisms, however the effect of tautomerization has not been reported. Using non-equilibrium molecular dynamics, we discover here that a mere 0.5-Å atomic displacement between two tautomers of an imine-based COF (TpHZ) can surprisingly lead to dramatic changes in the desalination behavior of their multilayers. The tautomeric transformation (from TpHZ-NH to TpHZ-OH) improves the water permeability by about 1.6–3 times. The interior resistance rather than the entrance resistance is found to dominate the water transport. The weaker adhesion and the smoother channel path of TpHZ-OH result in a much lower interior resistance. Furthermore, NaCl rejection increases from ∼ 89 % to 100 % due to the stronger sieving effect resulting from the reduced compensatory effect of TpHZ-OH for ion hydrations.

A molecular dynamics study on the solid–liquid polymer interface: insight into the effect of surface roughness scale and polymer chain length on interfacial thermal resistance

Understanding the role of surface morphology and molecular structure interface thermal transport is essential for designing thermal management materials. In the present work, models of solid–liquid interfaces were created by placing liquid n-alkane between two platinum crystals. The effect of different levels of crystal surface roughness–flat, small, and large-scale grooves–and polymer chain lengths, under varying solid–liquid affinity, on the interface thermal resistance (ITR) were assessed using non-equilibrium molecular dynamics simulations. The overall trend confirmed that grooved surfaces have higher ITR than flat surfaces at low affinity, and lower ITR values were observed at high affinity. Large grooves enabled more favourable polymer orientations than those of small grooves, resulting in a smaller ITR. However, long chains did not facilitate heat transfer normal to the interface because they preferentially aligned parallel to it. For efficient heat transfer, a balance between the roughness scale and polymer length must be considered.

Challenges in molecular dynamics simulations of heat exchange statistics.

We study heat exchange in temperature-biased metal-molecule-metal molecular junctions by employing the molecular dynamics simulator LAMMPS. Generating the nonequilibrium steady state with Langevin thermostats at the boundaries of the junction, we show that the average heat current across a gold-alkanedithiol-gold nanojunction behaves physically, with the thermal conductance value matching the literature. In contrast, the full probability distribution function for heat exchange, as generated by the simulator, violates the fundamental fluctuation symmetry for entropy production. We trace this failure back to the implementation of the thermostats and the expression used to calculate the heat exchange. To rectify this issue and produce the correct statistics, we introduce single-atom thermostats as an alternative to conventional many-atom thermostats. Once averaging heat exchange over the hot and cold thermostats, this approach successfully generates the correct probability distribution function, which we use to study the behavior of both the average heat current and its noise. We further examine the thermodynamic uncertainty relation in the molecular junction and show that it holds, albeit demonstrating nontrivial trends. Our study points to the need to carefully implement nonequilibrium molecular dynamics solvers in atomistic simulation software tools for future investigations of noise phenomena in thermal transport.

Understanding Water Diffusion Behaviors in Epoxy Resin through Molecular Simulations and Experiments.

The unclear understanding of the water diffusion behavior posts a big challenge to the manipulation of water absorption properties in epoxy resins. Herein, we investigated the water diffusion behavior and its relationship with molecule structures inside an epoxy resin mainly by the nonequilibrium molecular dynamics and experiments. It is found that at the initial rapid water absorption stage, bound water and free water both contribute, while at the later slow water absorption stage, free water plays a dominant role. The observed evolution of free water and bound water cannot be explained by the traditional Langmuir model. In addition, molecule polarity, free volume, and segment mobility can all influence the water diffusion process. Hence, the epoxy resin with low polarity and high molecular segment mobility is endowed with higher diffusion coefficients. The saturated water absorption content is almost dependent on the polarity. The understanding of how water diffuses and what decides the diffusion process is critical to the rational design of molecule structures for improving the water resistance in epoxy resin.

Dissimilar thermal transport properties in κ-Ga2O3 and β-Ga2O3 revealed by homogeneous nonequilibrium molecular dynamics simulations using machine-learned potentials

The lattice thermal conductivity (LTC) of Ga2O3 is an important property due to the challenge in the thermal management of high-power devices. In this work, we develop machine-learned neuroevolution potentials (NEPs) for single-crystalline β−Ga2O3 and κ−Ga2O3 and demonstrate their accuracy in modeling thermal transport properties. Combining NEP-driven homogeneous non-equilibrium molecular dynamics simulations with tensor analysis, we determine the spatial distributions of LTCs for two Ga2O3 crystals, showing dissimilar thermal behaviors. Specifically, β−Ga2O3 shows isotropic thermal transport properties, with the LTCs along [100], [010], and [001] directions being predicted to be 10.3±0.2, 19.9±0.2, and 12.6±0.2 W/(m K), respectively, consistent with previous experimental measurements. For κ−Ga2O3, our predictions suggest nearly isotropic thermal transport properties, with the LTCs along [100], [010], and [001] being estimated to be 4.5±0.1, 3.9±0.1, and 4.0±0.1 W/(m K). The reduced LTC of κ−Ga2O3 vs β−Ga2O3 stems from its restricted low-frequency phonons up to 5 THz. Furthermore, we find that the β phase exhibits a typical temperature dependence slightly stronger than ∼T−1, whereas the κ phase shows a weaker temperature dependence, ranging from ∼T−0.5 to ∼T−0.7.

Investigating thermal conductivity and mechanical properties of a hybrid material based on cellulose nanofibers and boron nitride nanotubes using molecular dynamics simulations

Cellulose nanofibers (NFCs) have emerged as a preferred choice for fabricating nanomaterials with exceptional mechanical properties. At the same time, boron nitride nanotubes (BNNTs) have long been favored in thermal management devices due to their superior thermal conductivity (k). This study uses reverse non-equilibrium molecular dynamics (MD) simulations to investigate k for a hybrid material based on NFCs and BNNTs. The result is then compared with pure NFC and BNNT-based structures with equivalent total weight content to elucidate how incorporating BNNT fillers enhances k for the hybrid system. Furthermore, the fundamental phonon vibration modes responsible for driving thermal transport in NFC-based materials upon incorporating BNNTS are identified by computing the vibrational density of states from the Fourier transform analysis of the averaged mass-weighted velocity autocorrelation function. Additionally, MD simulations demonstrate how both NFCs and BNNTs synergistically improve the constituting hybrid structure’s mechanical properties (e.g. tensile strength and stiffness). The overarching aim is to contribute towards the engineered design of novel functional materials based on nanocellulose that simultaneously improve crucial physical properties pertaining to thermal transport and mechanics.

Thermal Rectification across an Asymmetric Layer Carbon Nanotube van der Waals Heterostructure.

The exceptional thermal conductivity and strength of carbon nanotubes (CNTs) position them as outstanding materials for thermal conduction. The intriguing properties introduced by van der Waals (vdW) heterojunctions have also captured the interest of researchers. However, further refinement of the research concerning the integration of these two elements is required. In our study, a vdW heterostructure with asymmetric layer nesting of multiwalled CNTs (ALCNTs) is devised, with a specific focus on the model's heat flux and thermal rectification (TR) properties, which are analyzed using nonequilibrium molecular dynamics (NEMD). Notably, the greatest TR ratio is observed in the connection of three-layer and single-layer ALCNTs. Moreover, multilayer variable-length nested models exhibit a sluggish TR ratio. An examination of the interface thermal resistance (ITR) reveals that the maximum ITR in the multilayer nested model resides at the rightmost interface. However, it is essential to highlight that the determinant of the TR ratio and heat flux in the multilayer nested model is not the maximum ITR of the rightmost interface but rather the ITR of the outermost layer on the left. Additionally, the impacts of the defect density, length, temperature difference, and hydrogenation on the model's heat flux and TR are explored, yielding noteworthy conclusions. For instance, defects in the outer CNT have a minimal influence on the heat flux and TR compared with those in the inner CNT. As the length increases, the heat flux initially decreases and then increases. Hydrogenation significantly enhances the model's heat flux but does not favor the TR. Our study contributes to advancing the understanding of CNT vdW heterojunctions and offers valuable insights for their practical applications.

Investigation of nanocomposite PNIPAm‐g‐graphene with pre‐lower critical solution temperature rapid thermal response function for chip adaptive cooling: A molecular dynamics and computational fluid dynamics simulations

AbstractTemperature‐sensitive hydrogels have been widely used for rapid adaptive cooling in electronic device thermal management with promising applications. However, existing temperature‐sensitive hydrogels can only regulate the flow in the chip cooling system after the ambient temperature reaches their lower critical solution temperature (LCST). Before reaching LCST, effective rapid heat dissipation for electronic chips is not achievable. This study aims to develop a temperature‐sensitive hydrogel that can provide assisted adaptive cooling for electronic chips before reaching its LCST. This requires the hydrogel to have a thermal conductivity far surpassing existing hydrogel materials. Using the temperature‐sensitive hydrogel PNIPAm and graphene molecules as base materials, this research utilized molecular dynamics simulations to graft graphene molecules onto PNIPAm molecules in different ways, resulting in the temperature‐sensitive hydrogel material PNIPAm‐g‐graphene. Non‐equilibrium molecular dynamics (NEMD) was employed to calculate the thermal conductivity of this material under different temperature conditions. The results indicate that the thermal conductivity of PNIPAm‐g‐graphene can reach up to 1.95474 W/m K (graphene grafted at CH3 functional group, temperature at 280 K). Compared to the thermal conductivity of PNIPAm under the same conditions (0.45 W/m K), the increase in thermal conductivity is significant, demonstrating excellent thermal conductivity compared to PNIPAm. Subsequently, this study analyzed the underlying mechanisms of different thermal conductivities in materials obtained by grafting graphene molecules at different points using the method of overlap in Phonon Density of States Curves (PDOS) from the perspective of interfacial thermal conduction. Finally, through computational fluid dynamics (CFD) simulations, this study investigates the chip's adaptive cooling performance with PNIPAm‐g‐graphene material. The results show that, compared to traditional temperature‐sensitive hydrogels, PNIPAm‐g‐graphene can achieve efficient adaptive cooling of chip hotspots before the cooling fluid temperature reaches its LCST value. This finding is significant for the field of chip cooling. The study proposes a new method for rapid, adaptive cooling of chip hotspots and explores its feasibility from the perspectives of molecular dynamics and CFD simulation. It holds importance in the thermal management of electronic devices and the rapid adaptive cooling of electronic chips.

Salt Effects on the Mechanical Properties of Ionic Conductive Polymer: A Molecular Dynamics Study.

Functional polymers can be used as electrolyte and binder materials in solid-state batteries. This often requires performance targets in terms of both the transport and mechanical properties. In this work, a model ionic conductive polymer system, i.e., poly(ethylene oxide)-LiTFSI, was used to study the impact of salt concentrations on mechanical properties, including different types of elastic moduli and the viscoelasticity with both nonequilibrium and equilibrium molecular dynamics simulations. We found an encouragingly good agreement between experiments and simulations regarding Young's modulus, bulk modulus, and viscosity. In addition, we identified an intermediate salt concentration at which the system shows high ionic conductivity, high Young's modulus, and short elastic restoration time. Therefore, this study laid the groundwork for investigating ionic conductive polymer binders with self-healing functionality from molecular dynamics simulations.

Understanding neural network tuned Langevin thermostat effect on predicting thermal conductivity of graphene-coated copper using nonequilibrium molecular dynamics simulations

Copper has always been used in thermoelectric applications due to its extensive properties among metals. However, it requires further improving its heat transport performance at the nanosized applications by supporting another high thermal conductivity material. Herein, copper was coated with graphene, and the neural network fitting was employed for the nonequilibrium molecular dynamics simulations of graphene-coated copper nanomaterials to predict thermal conductivity. The Langevin thermostat that was tuned with a neural network fitting (NNF), which makes up the backbone of deep learning, generated the temperature difference between the two ends of the models. The NNF calibrated the Langevin thermostat damping constants that helped to control the temperatures precisely. The buffer and thermostat lengths were also analyzed, and they have considerable effects on the thermostat temperatures and a significant impact on the thermal conductivity of the graphene-coated copper. Regarding thermal conductivity, the four different shapes of vacancy defect concentrations and their locations in the graphene sheets were further investigated. The vacancy between the thermostats significantly decreases the thermal conductivity; however, the vacancy defect in thermostats does not have a similar effect. When the graphene is placed between two copper blocks, the thermal conductivity decreases drastically, and it continues to drop when the sine wave amplitude on the graphene sheet increases.

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.

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.

Boosting phonon transport across AlN/SiC interface by fast annealing amorphous layers

The high increase in interface density has become the main bottleneck for heat dissipation in gallium nitride/aluminum nitride (AlN)/silicon carbide (SiC) based nanodevices. In this paper, the interfacial thermal conductance (ITC) of AlN/SiC interface is investigated by non-equilibrium molecular dynamics simulation. It is found that introducing amorphous layers at AlN/SiC interface will result in an enhancement of its ITC by 2.32 times. Three different amorphous layers are investigated and can be achieved by fast thermal annealing. Among them, the amorphous SiC layers work best, and the amorphous AlN layers work worst. Further spectral analysis reveals that the enhancement of ITC comes from the strengthening of interfacial inelastic phonon processes, which boosts the transport of modes at a wide frequency range. What is more, as the thickness of amorphous layers increases, the enhancement of ITC weakens. This research provides a highly operational strategy to enhance ITC and enriches our understanding of inelastic phonon process at interface.