Large-scale Molecular Dynamics Simulations Research Articles

Mapping microstructure to shock-induced temperature fields using deep learning

The response of materials to shock loading is important to planetary science, aerospace engineering, and energetic materials. Thermally activated processes, including chemical reactions and phase transitions, are significantly accelerated by energy localization into hotspots. These result from the interaction of the shockwave with the materials’ microstructure and are governed by complex, coupled processes, including the collapse of porosity, interfacial friction, and localized plastic deformation. These mechanisms are not fully understood and the lack of models limits our ability to predict shock to detonation transition from chemistry and microstructure alone. We demonstrate that deep learning can be used to predict the resulting shock-induced temperature fields in composite materials obtained from large-scale molecular dynamics simulations with the initial microstructure as the only input. The accuracy of the Microstructure-Informed Shock-induced Temperature net (MISTnet) model is higher than the current state of the art and its evaluation requires a fraction of the computation cost.

Nanoscale Prediction of the Thermal, Mechanical, and Transport Properties of Hydrated Clay on 106- and 1015-Fold Larger Length and Time Scales.

Coupled thermal, hydraulic, mechanical, and chemical (THMC) processes, such as desiccation-driven cracking or chemically driven fluid flow, significantly impact the performance of composite materials formed by fluid-mediated nanoparticle assembly, including energy storage materials, ordinary Portland cement, bioinorganic nanocomposites, liquid crystals, and engineered clay barriers used in the isolation of hazardous wastes. These couplings are particularly important in the isolation of high-level radioactive waste (HLRW), where heat generated by radioactive decay can drive the temperature up to at least 373 K in the engineered barrier. Here, we use large-scale all-atom molecular dynamics simulations of hydrated smectite clay nanoparticle assemblages to predict the fundamental THMC properties of hydrated compacted clay over a wide range of temperatures (up to 373 K) and dry densities relevant to HLRW management. Equilibrium simulations of clay-water mixtures at different hydration levels are analyzed to quantify material properties, including thermal conductivity, heat capacity, thermal expansion, suction, water and ion self-diffusivity, and hydraulic conductivity. Predictions are validated against experimental results for the properties of compacted bentonite clay. Our results demonstrate the feasibility of using atomistic-level simulations of assemblages of clay nanoparticles on scales of tens of nanometers and nanoseconds to infer the properties of compacted bentonite on scales of centimeters and days, a direct upscaling over 6 orders of magnitude in space and 15 orders of magnitude in time.

Viscosity Prediction of High-Concentration Antibody Solutions with Atomistic Simulations.

The computational prediction of the viscosity of dense protein solutions is highly desirable, for example, in the early development phase of high-concentration biopharmaceutical formulations where the material needed for experimental determination is typically limited. Here, we use large-scale atomistic molecular dynamics (MD) simulations with explicit solvation to de novo predict the dynamic viscosities of solutions of a monoclonal IgG1 antibody (mAb) from the pressure fluctuations using a Green-Kubo approach. The viscosities at simulated mAb concentrations of 200 and 250 mg/mL are compared to the experimental values, which we measured with rotational rheometry. The computational viscosity of 24 mPa·s at the mAb concentration of 250 mg/mL matches the experimental value of 23 mPa·s obtained at a concentration of 213 mg/mL, indicating slightly different effective concentrations (or activities) in the MD simulations and in the experiments. This difference is assigned to a slight underestimation of the effective mAb-mAb interactions in the simulations, leading to a too loose dynamic mAb network that governs the viscosity. Taken together, this study demonstrates the feasibility of all-atom MD simulations for predicting the properties of dense mAb solutions and provides detailed microscopic insights into the underlying molecular interactions. At the same time, it also shows that there is room for further improvements and highlights challenges, such as the massive sampling required for computing collective properties of dense biomolecular solutions in the high-viscosity regime with reasonable statistical precision.

Predicting the Fracture Propensity of Amorphous Silica Using Molecular Dynamics Simulations and Machine Learning

Amorphous silica (a-SiO2) is a widely used inorganic material. Interestingly, the relationship between the local atomic structures of a-SiO2 and their effects on ductility and fracture is seldom explored. Here, we combine large-scale molecular dynamics simulations and machine learning methods to examine the molecular deformations and fracture mechanisms of a-SiO2. By quenching at high pressures, we demonstrate that densifying a-SiO2 increases the ductility and toughness. Through theoretical analysis and simulation results, we find that changes in local bonding topologies greatly facilitate energy dissipation during plastic deformation, particularly if the coordination numbers decrease. The appearance of fracture can then be accurately located based on the spatial distribution of the atoms. We further observe that the static unstrained structure encodes the propensity for local atomic coordination to change during applied strain, hence a distinct connection can be made between the initial atomic configurations before loading and the final far-from-equilibrium atomic configurations upon fracture. These results are essential for understanding how atomic arrangements strongly influence the mechanical properties and structural features in amorphous solids and will be useful in atomistic design of functional materials.

Dynamic deformation behaviors and mechanisms of CoCrFeNi high-entropy alloys

Due to their unique microstructures and chemical compositions, high-entropy alloys (HEAs) exhibit remarkable mechanical properties, such as high strength, excellent ductility and good thermal stability. However, to date, there have been limited studies on the dynamic behaviors of HEAs. Here, we systemically investigated the mechanical behaviors and deformation mechanisms of CoCrFeNi HEAs and their connections under dynamic loading by combining mechanical tests and molecular dynamics simulations. Compressive testing on polycrystalline CoCrFeNi HEA samples at different strain rates showed that both yield and flow stresses increase with strain rate and exhibit a significant strain rate sensitivity due to solid solution strengthening and lattice distortion of the HEA. The strain rate sensitivity of the CoCrFeNi HEA transitions from 0.010 at low strain rates (5.0×10−5–2.5×103 s−1) to 0.333 at high strain rates (2.5×103–6.5×103 s−1). Large-scale molecular dynamics simulations further revealed that this transition is related to the plastic deformation mechanism transition from dislocation nucleation and slip at low strain rates to massive dislocation nucleation and drag at high strain rates. Furthermore, the CoCrFeNi HEA exhibited a remarkable strain-hardening capability at high strain rates, which originated from the formation of primary and secondary nanoscale twins and twin-twin and twin-dislocation interactions. Our current study sheds light on the plastic deformation mechanisms of HEAs under dynamic loading, providing guidance for the design and fabrication of HEAs with excellent dynamic mechanical properties.

An empirical potential for simulating hydrogen isotope retention in highly irradiated tungsten

We describe the parameterization of a tungsten-hydrogen empirical potential designed for use with large-scale molecular dynamics simulations of highly irradiated tungsten containing hydrogen isotope atoms, and report test results. Particular attention has been paid to getting good elastic properties, including the relaxation volumes of small defect clusters, and to the interaction energy between hydrogen isotopes and typical irradiation-induced defects in tungsten. We conclude that the energy ordering of defects changes with the ratio of H atoms to point defects, indicating that this potential is suitable for exploring mechanisms of trap mutation, including vacancy loop to plate-like void transformations.

Unraveling Anisotropy in Crystalline Orientation under Shock-Induced Dynamic Responses in High-Entropy Alloy Co25Ni25Fe25Al7.5Cu17.5.

Shock-induced plastic deformation and spall damage in the single-crystalline FCC Co25Ni25Fe25Al7.5Cu17.5 high-entropy alloy (HEA) under varying shock intensities were systematically investigated using large-scale molecular dynamics simulations. The study reveals the significant influence of crystalline orientation on the deformation mechanism and spall damage. Specifically, the shock wave velocities in the [110] and [111] directions are significantly higher than that in the [001] direction, resulting in a two-zone elastic-plastic shock wave structure observed in the [110] and [111] samples, while only a single-wave structure is found in the [001] sample. The plastic deformation is dominated by the FCC to BCC transformation following the Bain path and a small amount of stacking faults during the compression stage in the [001] sample, whereas it depends on the stacking faults induced by Shockley dislocation motion in the [110] and [111] samples. The stacking faults and phase transformation in the [001] sample exhibit high reversibility under release effects, while extensive dislocations are present in the [110] and [111] samples after release. Interestingly, tension-strain-induced FCC to BCC phase transformation is observed in the [001] sample during the release stage, resulting in increased spall strength compared to the [110] and [111] samples. The spall strength estimated from both bulk and free surface velocity history shows reasonable consistency. Additionally, the spall strength remains stable with increasing shock intensities. The study discusses in detail the shock wave propagation, microstructure change, and spall damage evolution. Overall, our comprehensive studies provide deep insights into the deformation and fracture mechanisms of Co25Ni25Fe25Al7.5Cu17.5 HEA under shock loading, contributing to a better understanding of dynamic deformation under extreme environments.

Large-scale machine-learning molecular dynamics simulation of primary radiation damage in tungsten

Large-scale machine-learning molecular dynamics simulation of primary radiation damage in tungsten

Phase Separation and Ion Diffusion in Ionic Liquid, Organic Solvent, and Lithium Salt Electrolyte Mixtures.

The highly desirable characteristics of ternary mixtures of ionic liquids, organic solvents, and metal salts make them a promising candidate for use in various electrothermal energy storage and conversion systems. In this study, using large-scale classical molecular dynamics simulations, we looked into 10 different ternary electrolyte mixtures using combinations of [EMIM]+, [BMIM]+, and [OMIM]+ cations with [NO3]-, [BF4]-, [PF6]-, [ClO4]-, [TFO]-, and [NTf2]- anions, tetraglyme, and Li salt to study the effect of ionic liquid composition on the phase behavior of ternary electrolyte mixtures. We uncovered that in these electrolytes, phase separation is mainly a function of pairwise binding energy of the constituents of the mixture. To corroborate this theory, several simulations are performed at various temperatures ranging from 260 to 500 K for each mixture, followed by calculating the binding energy of ionic liquid pairs using density functional theory. Our results verify that the transition temperature for the phase separation of each system is indeed a function of the pairwise binding energy of its ionic liquid pairs. It is also found that in some cases, the diffusion coefficient of the Li+ ions decreased even with the increase in the temperature, an effect that is attributed to the presence of condensed ionic domains in the electrolyte. This study provides a new insight for the design of multicomponent electrolyte mixtures for a wide range of energy applications.

High-temperature active oxidation of nanocrystalline silicon-carbide: A reactive force-field molecular dynamics study

Flexible woven SiC ceramics are prone to accelerated fiber embrittlement under high temperature oxidation in dynamic oxygen environments. The nanocrystalline structure of the constituent fibers impacts the reaction kinetics and phase transformations during active oxidation. However, fundamental understanding and quantification of grain boundary effects on oxidation behavior in nanocrystalline SiC remain elusive when temperatures exceed 1500 K. This study deploys large-scale molecular dynamics simulations with a reactive force-field to elucidate the complex roles of atomic oxygen reservoir conditions and grain size on oxidation kinetics and the nature of oxides produced in both monocrystalline and nanocrystalline 3C-SiC between 1100 K and 2000 K. The simulations with dynamically replenished oxygen provide good agreement with oxidation kinetics and activation energies for the monocrystalline Si(100) and C(100) orientations published in the available literature. This study reveals that, by contrast, nanocrystalline SiC samples exhibit two distinct oxidation kinetics with a transition point at 1500 K due to surface melting, which is supported by experimental evidence. The introduction of a grain-boundary network produces a two-fold decrease in oxidation activation energies compared to monocrystalline SiC below 1500 K. Above 1500 K, however, the activation energies rise substantially due to the formation of a liquid Si phase at the SiC/Si oxide interface. It is shown that the stability of the interfacial liquid phase is promoted by incoherent grain boundaries in the crystalline SiC. These findings are important for the deployment of nanocrystalline SiC fibers in advanced thermal protection systems for high-temperature applications.

Quinone Catalysis Modulates Proton Transfer Reactions in the Membrane Domain of Respiratory Complex I.

Complex I is a redox-driven proton pump that drives electron transport chains and powers oxidative phosphorylation across all domains of life. Yet, despite recently resolved structures from multiple organisms, it still remains unclear how the redox reactions in Complex I trigger proton pumping up to 200 Å away from the active site. Here, we show that the proton-coupled electron transfer reactions during quinone reduction drive long-range conformational changes of conserved loops and trans-membrane (TM) helices in the membrane domain of Complex I from Yarrowia lipolytica. We find that the conformational switching triggers a π → α transition in a TM helix (TM3ND6) and establishes a proton pathway between the quinone chamber and the antiporter-like subunits, responsible for proton pumping. Our large-scale (>20 μs) atomistic molecular dynamics (MD) simulations in combination with quantum/classical (QM/MM) free energy calculations show that the helix transition controls the barrier for proton transfer reactions by wetting transitions and electrostatic effects. The conformational switching is enabled by re-arrangements of ion pairs that propagate from the quinone binding site to the membrane domain via an extended network of conserved residues. We find that these redox-driven changes create a conserved coupling network within the Complex I superfamily, with point mutations leading to drastic activity changes and mitochondrial disorders. On a general level, our findings illustrate how catalysis controls large-scale protein conformational changes and enables ion transport across biological membranes.

Diameter-Optimum Spreading for the Impinging of Water Nanodroplets on Solid Surfaces.

The impinging of water nanodroplets on solid surfaces is crucial to many nanotechnologies. Through large-scale molecular dynamics simulations, the size effect on the spreading of water nanodroplets after impinging on hydrophilic, graphite, and hydrophobic surfaces under low impinging velocities has been systematically studied. The spreading rates of nanodroplets first increase and then decrease and gradually become constant with the increase of nanodroplet diameter. The nanodroplets with the diameters of 17-19 nm possess the highest spreading rates because of the combined effect of the strongest interfacial interaction and the strongest surface interaction within water molecules. The highest water molecule densities, hydrogen bond numbers, and dielectric constants of interface and surface layers mainly contribute to the lowest interface work of adhesion and surface tension values at optimal diameters. These results unveil the nonmonotonic characteristics of spreading velocity, interface work of adhesion and surface tension with nanodroplet diameter for nanodroplets on solid surfaces.

Effects of solvents on Li+ distribution and dynamics in PVDF/LiFSI solid polymer electrolytes: An all-atom molecular dynamics simulation study

Large-scale all-atom molecular dynamics simulations are used to investigate the structure and dynamics of a solid polymer electrolytes (SPE) model made up of polyvinylidene fluoride (PVDF) as the polymer matrix, lithium bis(fluorosulfonyl)imide salt (LiFSI), and six distinct solvent types in varying quantities. The influence of solvents on the physicochemical parameters of SPEs relevant to the Li-Battery sector is analysed. We prove that the presence of solvents containing oxygens atoms has different abilities to dissociate the LiFSI ions, form confined channels in the SPEs, and decrease the PVDF crystallinity. Besides, some solvents having a high affinity to the cations reduce the Li+ transport assembling in nano-domains, separated from the PVDF chains, when they present with a high amount, dramatically decreasing the Li+ transference number (tLi+). On the contrary, the ionic conductivity boosts preserving a good tLi+ for high dynamics solvents that form small Li+-solvent clusters. Our nanoscale investigations edify approaches for improving the ionic conductivity and controlling the arrangement of the ions in the SPE needed for proper battery operation by choosing a suitable solvent with a regulated amount.

Shock-induced deformation and spallation in CoCrFeMnNi high-entropy alloys at high strain-rates

Shock-induced deformation and fracture in single-crystalline and nanocrystalline CoCrFeMnNi high-entropy alloys (HEAs) under different shock intensities are investigated systematically using large-scale molecular dynamics simulations. The strong anisotropy in the single-crystalline HEA and how the reversibility of HCP-structured atoms influences the void nucleation and growth are revealed. Specifically, shock-induced FCC to HCP structural transformations are largely reversible in the case of the [001] loading direction, leading to homogeneous void nucleation; while they are largely irreversible in the cases of the [110] and [111] loading directions, resulting in void nucleation in the intersection of HCP layers. In nanocrystalline HEA, the deformations in the grain interior are similar to those in the single crystals, while the grain boundaries serve as void nucleation sites and thus weaken the spall strength. The SRO effects on the shock response in single-crystalline and nanocrystalline CoCrFeMnNi HEA are revealed, and the chemical heterogeneity is analyzed. Our results show that SRO can only slightly increase the shear stress and the spall strength, but it can cause a reduction of ductility during the spallation. The differences in SRO effects between single-crystalline and nanocrystalline models are attributed to the grain boundaries, where Cr and Mn are favorable, while Ni is favored inside the grains in the SRO model. Moreover, the comparison between CoCrFeMnNi HEA and its subsystem as well as single-element metal indicates Mn seems to be the most influential elements in CoCrFeMnNi HEA, resulting in significant changes in strength. A relation between the spall strength and strain rate is proposed to describe the simulation results and reported experimental data. Our comprehensive and systematical studies provide deep insights into the deformation and fracture in CoCrFeMnNi HEA subjected to shock loading, which deepens the understanding on the dynamic deformations of CoCrFeMnNi HEA and benefits the rational design of new HEAs/MEAs with enhanced performance.

The thermodynamic-pathway-determined microstructure evolution of copper under shock compression.

Shock-induced structural transformations in copper exhibit notable directional dependence and anisotropy, but the mechanisms that govern the responses of materials with different orientations are not yet well understood. In this study, we employ large-scale non-equilibrium molecular dynamics simulations to investigate the propagation of a shock wave through monocrystal copper and analyse the structural transformation dynamics in detail. Our results indicate that anisotropic structural evolution is determined by the thermodynamic pathway. A shock along the [Formula: see text] orientation causes a rapid and instantaneous temperature spike, resulting in a solid-solid phase transition. Conversely, a liquid metastable state is observed along the [Formula: see text] orientation due to thermodynamic supercooling. Notably, melting still occurs during the [Formula: see text]-oriented shock, even if it falls below the supercooling line in the thermodynamic pathway. These results highlight the importance of considering anisotropy, the thermodynamic pathway and solid-state disordering when interpreting phase transitions induced by shock. This article is part of the theme issue 'Dynamic and transient processes in warm dense matter'.

Surface properties of alkali silicate glasses: Influence of the modifiers.

Using large-scale molecular dynamics simulations, we investigate the surface properties of lithium, sodium, and potassium silicate glasses containing 25 mol % of alkali oxide. The comparison of two types of surfaces, a melt-formed surface (MS) and a fracture surface (FS), demonstrates that the influence of the alkali modifier on the surface properties depends strongly on the nature of the surface. The FS exhibits a monotonic increase of modifier concentration with increasing alkali size while the MS shows a saturation of alkali concentration when going from Na to K glasses, indicating the presence of competing mechanisms that influence the properties of a MS. For the FS, we find that larger alkali ions reduce the concentration of under-coordinated Si atoms and increase the fraction of two-membered rings, implying an enhanced chemical reactivity of the surface. For both types of surfaces, the roughness is found to increase with alkali size, with the effect being more pronounced for the FS than for the MS. The height-height correlation functions of the surfaces show a scaling behavior that is independent of the alkali species considered: The ones for the MS are compatible with the prediction of the frozen capillary wave theory while the ones for the FS show a logarithmic growth, i.e., on the nanoscale these surfaces are not self-affine fractals. The influence of the modifier on the surface properties are rationalized in terms of the interplay between multiple factors involving the size of the ions, bond strength, and charge balance on the surface.

A Comparison of Experimental and Ab Initio Structural Data on Fe under Extreme Conditions

Iron is the major element of the Earth’s core and the cores of Earth-like exoplanets. The crystal structure of iron, the major component of the Earth’s solid inner core (IC), is unknown under the high pressures (P) (3.3–3.6 Mbar) and temperatures (T) (5000–7000 K) and conditions of the IC and exoplanetary cores. Experimental and theoretical data on the phase diagram of iron at these extreme PT conditions are contradictory. Though some of the large-scale ab initio molecular dynamics (AIMD) simulations point to the stability of the body-centered cubic (bcc) phase, the latest experimental data are often interpreted as evidence for the stability of the hexagonal close-packed (hcp) phase. Applying large-scale AIMD, we computed the properties of iron phases at the experimental pressures and temperatures reported in the experimental papers. The use of large-scale AIMD is critical since the use of small bcc computational cells (less than approximately 1000 atoms) leads to the collapse of the bcc structure. Large-scale AIMD allowed us to compare the measured and computed coordination numbers as well as the measured and computed structural factors. This comparison, in turn, allowed us to suggest that the computed density, coordination number, and structural factors of the bcc phase are in agreement with those observed in experiments, which were previously assigned either to the liquid or hcp phase.

Probing Confinement Effects on the Infrared Spectra of Water with Deep Potential Molecular Dynamics Simulations.

The hydrogen-bond network of confined water is expected to deviate from that of the bulk liquid, yet probing these deviations remains a significant challenge. In this work, we combine large-scale molecular dynamics simulations with machine learning potential derived from first-principles calculations to examine the hydrogen bonding of water confined in carbon nanotubes (CNTs). We computed and compared the infrared spectrum (IR) of confined water to existing experiments to elucidate confinement effects. For CNTs with diameters >1.2 nm, we find that confinement imposes a monotonic effect on the hydrogen-bond network and on the IR spectrum of water. In contrast, confinement below 1.2 nm CNT diameter affects the water structure in a complex fashion, leading to a strong directional dependence of hydrogen bonding that varies nonlinearly with the CNT diameter. When integrated with existing IR measurements, our simulations provide a new interpretation for the IR spectrum of water confined in CNTs, pointing to previously unreported aspects of hydrogen bonding in this system. This work also offers a general platform for simulating water in CNTs with quantum accuracy on time and length scales beyond the reach of conventional first-principles approaches.

Coarse-grained molecular dynamic model for metallic materials

It is not yet straightforward to expand the time scale of molecular dynamics simulations in spite of recent progress in high-performance computing since time series of atomic motion cannot be parallelized easily. In this study, a novel coarse-grained molecular dynamic model is employed to scale up the time range of atomistic simulations for metallic materials. Basic mechanical and thermal properties of nickel including elastic constants, bulk modulus, shear modulus, Young modulus and melting point are well reproduced with the definition of the coarse-grained model. Moreover, it was found that single crystal plasticity occurring in the coarse-grained model compares very well with all-atom molecular dynamics simulations. This can be explained by the equality of the ratio in the generalized stacking fault energy curve between coarse-grained and all-atom models. Furthermore, a large-scale coarse-grained molecular dynamics simulation of the crystal growth was performed on the supercomputer as a practical example of the acceleration of simulation, in which a submicron-order crystal appears from the seed crystal in the undercooled melt. It is expected that the coarse-grained molecular dynamics method has a variety of applications in the future since it can handle calculations on such a large scale with relative ease.

Deep-learning-assisted theoretical insights into the compatibility of environment friendly insulation medium with metal surface of power equipment

Exploring a new generation of eco-friendly gas insulation medium to replace greenhouse gas sulphur hexafluoride (SF6) in power industry is significant for reducing the greenhouse effect and building a low-carbon environment. The gas–solid compatibility of insulation gas with various electrical equipment is also of significance before practical applications. Herein, take a promising SF6 replacing gas trifluoromethyl sulfonyl fluoride (CF3SO2F) for example, one strategy to theoretically evaluate the gas–solid compatibility between insulation gas and the typical solid surfaces of common equipment was raised. Firstly, the active site where the CF3SO2F molecule is prone to interact with other compounds was identified. Secondly, the interaction strength and charge transfer between CF3SO2F and four typical solid surfaces of equipment were studied by first-principles calculations and further analysis was conducted, with SF6 as the control group. Then, the dynamic compatibility of CF3SO2F with solid surfaces was investigated by large-scale molecular dynamics simulations with the aid of deep learning. The results indicate that CF3SO2F has excellent compatibility similar to SF6, especially in the equipment whose contact surface is Cu, CuO, and Al2O3 due to their similar outermost orbital electronic structures. Besides, the dynamic compatibility with pure Al surfaces is poor. Finally, preliminary experimental verifications indicate the validity of the strategy.