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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sticking Coefficients of Fusion Reactor Impurities from Molecular Dynamics Simulations for the Design of Cryopumps

A cryopump can be utilized as an impurity removal component of a direct internal recirculation (DIR) system for the fusion fuel cycle. The DIR facilitates a low fuel inventory by continuously pumping unburnt fuel while removing impurities from the fusion exhaust stream. A cryopump can target multiple impurity species by maintaining a temperature lower than the gas triple-point temperature that promotes desublimation. The desublimation/condensation of gases in cryopumps can be characterized by the sticking coefficient, which is defined as the probability for a gas particle to stick to a (cryo-)surface upon collision. The sticking coefficient is one of the important design/operation parameters for cryopumps, and it depends on a variety of surface and gas properties. Here, in this study, molecular dynamics simulations were utilized to estimate the sticking coefficients of typical fusion gas impurity species N 2 , CO 2 , and CH 4 over a Cu surface for a range of gas temperatures and surface coverages. The molecular dynamics study showed that the sticking coefficients for gases decrease with an increase in gas temperature. The presence of a single full monolayer of condensate on the metallic surface showed an adverse effect on the sticking of gases; however the sticking improved with two full monolayers of condensate on the surface. The sticking of gases over the mixed condensate on a surface was more favorable than the condensate of the same species for N 2 and CH 4 , with an exception for CO 2 , which showed a decrease in sticking over the mixed condensate.

cryopump↗
DOE OSTI2024

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.'s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U parameter for the 5f electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl3) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

All-atom molecular dynamics simulations of weak polyionic brushes: influence of charge density on the properties of polyelectrolyte chains, brush-supported counterions, and water molecules

All atom molecular dynamics (MD) simulations of planar Na+-counterion-neutralized polyacrylic acid (PAA) brushes are performed for varying degrees of ionization (and thereby varying charge density) and varying grafting density. Variation in the PE charge density (or degree of ionization) and grafting density leads to massive changes of the properties of the PE molecules (quantified by the changes in the height and the mobility of the PE brushes) as well as the local arrangement and distribution of the brush-supported counterions and water molecules within the brushes. The effect on the counterions is manifested by the corresponding variation of the counterion mobility, counterion concentration, extent of counterion binding to the charged site of the PE brushes, water-in-salt-like structure formation, and counterion-water–oxygen radial distribution function within the PE brushes. On the other hand, the effect on water molecules is manifested by the corresponding variation of water–oxygen–water–oxygen RDF, local water density, water–water and water–PE functional group hydrogen bond networks, static dielectric constant of water molecules, orientational tetrahedral order parameter, and water mobility. Enforcing such varying degree of ionization of weak polyelectrolytes is possible by changing the pH of the surrounding medium. Thus, our results provide insights into the changes in microstructure (at the atomistic level) of weak polyionic brushes at varying pH. Finally, we anticipate that this knowledge will prove to be vital for the efficient design of several nano-scale systems employing PE brushes such as nanomechanical gates, current rectifiers, etc.

42 ENGINEERING↗
DOE OSTI2022

Towards computational polar-topotronics: Multiscale neural-network quantum molecular dynamics simulations of polar vortex states in SrTiO3/PbTiO3 nanowires

Recent discoveries of polar topological structures ( e.g ., skyrmions and merons) in ferroelectric/paraelectric heterostructures have opened a new field of polar topotronics. However, how complex interplay of photoexcitation, electric field and mechanical strain controls these topological structures remains elusive. To address this challenge, we have developed a computational approach at the nexus of machine learning and first-principles simulations. Our multiscale neural-network quantum molecular dynamics molecular mechanics approach achieves orders-of-magnitude faster computation, while maintaining quantum-mechanical accuracy for atoms within the region of interest. This approach has enabled us to investigate the dynamics of vortex states formed in PbTiO 3 nanowires embedded in SrTiO 3 . We find topological switching of these vortex states to topologically trivial, uniformly polarized states using electric field and trivial domain-wall states using shear strain. These results, along with our earlier results on optical control of polar topology, suggest an exciting new avenue toward opto-electro-mechanical control of ultrafast, ultralow-power polar topotronic devices.

Linker, Thomas↗
DOE OSTI2020

Statistically averaged molecular dynamics simulations of hydrogen diffusion in magnesium and magnesium hydrides

Magnesium has a different crystal structure from its dihydride with hydrogenation leading to a phase transition from the hexagonal closely packed Mg into a tetragonal α-MgH 2 rutile type structure. Such materials exhibit complex hydrogen uptake and release kinetics because hydrogen diffusivities significantly change when the crystal structure changes. To provide a foundational understanding of (de)hydrogenation kinetics that is applicable to all stages of the reaction, we performed statistically averaged molecular dynamics simulations to derive hydrogen diffusivities as a function of temperature and hydrogen content for both magnesium and magnesium hydride. Furthermore, our studies confirm that hydrogen diffusivities in magnesium hydride are much lower than in magnesium, in agreement with experimental data. Additionally, we observe that in either magnesium or magnesium hydride, higher hydrogen compositions result in reduced diffusivities. The latter was not revealed by prior experiments, which were conducted at fixed hydrogen composition. Finally, we discover a non-Arrhenius behavior in magnesium hydride. The physical origin of this behavior is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning‐Augmented Molecular Dynamics Simulations (MD) Reveal Insights Into the Disconnect Between Affinity and Activation of ZTP Riboswitch Ligands

Abstract The challenge of targeting RNA with small molecules necessitates a better understanding of RNA–ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand‐induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure‐informed design, crystallography, and machine learning‐augmented all‐atom molecular dynamics simulations (MD), we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the 5‐aminoimidazole–4–carboxamide ribonucleotide triphosphate (ZTP) riboswitch, a ligand‐binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on‐rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Chemistry↗
DOE OSTI2025

Understanding Viscoelasticity of an Entangled Silicone Copolymer via Coarse-Grained Molecular Dynamics Simulations

Entangled dynamics is important for understanding rheological properties of long-chain polymers. For entangled homopolymers, the classic tube-reptation model and its refinements have been successfully applied to quantify properties like diffusion coefficient and zero-rate viscosity. However, the application of such models to copolymers has been limited despite scientific and industrial importance. Here, we study the entangled melt dynamics of poly(dimethyl-co-diphenyl)siloxane random copolymer for a range of mean-composition-ratio ϕ of the diphenyl component via long-term molecular dynamics simulation with a recently developed coarse-grained model. We found that the segmental relaxation is heterogeneous at the monomeric level because of compositional fluctuations. However, at the chain-entanglement level and higher length scales, the viscoelastic response is homogeneous with compositional dependence only through the overall diphenyl fraction ϕ. The relaxation modulus of the entangled copolymer melt conforms to the Likhtman–McLeish model, and the viscosity predicted using our current coarse-grained parameters is in good quantitative agreement with experimental data.

Copolymers↗
DOE OSTI2022

On the equivalence of nonequilibrium and equilibrium measurements of slip in molecular dynamics simulations

Here, we show that nonequilibrium and equilibrium measurements of slip are consistent, provided the hydrodynamic wall location associated with the equilibrium measurement is properly taken into account. The latter is a strong function of the fluid state and wall-fluid interaction and cannot be neglected as it typically has been. Our results are based on an alternative approach for calculating the hydrodynamic wall location which alleviates most of the difficulties associated with its calculation via a Green-Kubo integral that appear to have contributed to its neglect. Extensive molecular dynamics simulations are used to validate our approach including a model for calculating the slip length that does not involve a Green-Kubo integral.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Effect of Zwitterionic Additives on Solvation and Transport of Sodium and Potassium Cations in (Ethylene Oxide)10: A Molecular Dynamics Simulation Study

Sodium- (Na + ) and potassium- (K + ) ion batteries are cost-effective alternatives to lithium-ion (Li + ) batteries due to the abundant sodium and potassium resources. Solid polymer electrolytes (SPEs) are essential for safer and more efficient Na + and K + batteries because they often exhibit low ionic conductivity at room temperature. While zwitterionic (ZW) materials enhance Li+ battery conductivity, their potential for Na + and K + transport in batteries remains unexplored. In this study, we investigated the effect of three ZW molecules (ChoPO4, i.e., 2-methacryloyloxyethyl phosphorylcholine, ImSO3, i.e., sulfobetaine ethylimidazole, and ImCO2, i.e., carboxybetaine ethylimidazole) on the dissociation of Na + and K + coordination with ethylene oxide (EO) chains in EO-based electrolytes through molecular dynamics simulations. Our results showed that ChoPO4 possessed the highest cation–EO10 dissociation ability, while ImSO3 exhibited the lowest. Such dissociation ability correlated with the cation–ZW molecule coordination strength: ChoPO4 and ImSO3 showed the strongest and the weakest coordination with cations. However, the cation–ZW molecule coordination could slow the cationic diffusion. The competition of these effects resulted in accelerating or decelerating cationic diffusion. Our simulated results showed that ImCO2 enhanced Na + diffusion by 20%, while ChoPO4 and ImSO3 led to a 10% reduction. For K + , ChoPO4 reduced its diffusion by 40%, while ImCO2 and ImSO3 caused a similar decrease of 15%. These findings suggest that the ZW structure and the cationic size play an important role in the ionic dissociation effect of ZW materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Advanced analysis of laser-driven pulsed magnetic diffusion based on quantum molecular dynamics simulation

Magnetic diffusion plays an important role in inertial confinement fusion with strong magnetic fields. In this paper, we improve a previous analysis of the generation and diffusion of the magnetic field [Morita et al., Phys. Plasmas 25, 094505 (2018)]. For the generation process, we calculate the temporal evolution of the coil current using a self-consistent circuit model. The results show that the peak of the calculated magnetic field is delayed by 1.2 ns compared with that of the incident laser pulse. For the diffusion process, we evaluate the electrical conductivity of warm dense gold over a wide temperature range (300 K–100 eV) by combining the Kubo–Greenwood formula based on a quantum molecular dynamics simulation with the modified Spitzer model. Our simulation shows that the maximum magnetic field (530 T) that penetrates the cone is delayed by 2.5 ns compared with the laser peak. This result is consistent with experiments [Sakata et al., Nat. Commun. 9, 3937 (2018)] that showed that applying a strong magnetic field improved the heating efficiency of fusion fuel.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Investigating structure and dynamics of unentangled poly(dimethyl- co -diphenyl)siloxane via molecular dynamics simulation

Polysiloxane is one of the most important polymeric materials in technological use. Polydimethylsiloxane displays glass-like mechanical properties at low temperatures. Incorporation of phenyl siloxane, via copolymerization for example, improves not only the low-temperature elasticity but also enhances its performance over a wide range of temperatures. Copolymerization with the phenyl component can significantly change the microscopic properties of polysiloxanes, such as chain dynamics and relaxation. However, despite much work in the literature, the influence of such changes is still not clearly understood. In this work, we systematically study the structure and dynamics of random poly(dimethyl- co -diphenyl)siloxane via atomistic molecular dynamics simulations. As the molar ratio Φ of the diphenyl component increases, we find that the size of the linear copolymer chain expands. At the same time, the chain-diffusivity slows down by over an order of magnitudes. In conclusion, the reduced diffusivity appears to be a result of a complex interplay between the structural and dynamic changes induced by phenyl substitution.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Comparing theoretical predictions of radiation-free velocities of edge dislocations to molecular dynamics simulations

Transonic defect motion is of interest for high strain-rate plastic deformation as well as for crack propagation. Ever since Eshelby's 1949 prediction [J. D. Eshelby, Proc. Phys. Soc. A 62, 307 (1949)] in the isotropic limit of a “radiation-free” transonic velocity $v$ RF = $\sqrt{2}$c T , where shock waves are absent, there has been speculation about the significance of radiation-free velocities (if they truly exist) for defect mobility. Here, in this work, we argue that they do not play any significant role in dislocation dynamics in metals, based on comparing theoretical predictions of radiation-free velocities for transonic edge dislocations with molecular dynamics simulations for two face-centered cubic metals: Ag, where theory predicts radiation-free states, and Cu, where it does not.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Prediction of Bi 2 Te 3 -Sb 2 Te 3 Interfacial Conductance and Superlattice Thermal Conductivity Using Molecular Dynamics Simulations

Bismuth telluride (Bi 2 Te 3 ) and its alloys with antimony telluride (Sb 2 Te 3 ) have long been considered to be the best room-temperature bulk thermoelectric (TE) materials. In recent decades, proof-of-concept demonstrations on Bi 2 Te 3 -Sb 2 Te 3 nanostructures have shown high TE performance due to reduction in lattice thermal conductivities. Particularly, ultra-low thermal conductivities have been observed in Bi 2 Te 3 -Sb 2 Te 3 1D superlattices, leading to thermoelectric figures of merit (ZT) as high as 2.4. In contrast, very few computational studies have been performed to provide insight into the phonon transport across these nanostructures. In this work, we use non-equilibrium molecular dynamics simulations with previously developed force fields to simulate thermal transport across Bi 2 Te 3 -Sb 2 Te 3 interfaces and superlattices. We first calculate the thermal conductance associated with a Bi 2 Te 3 -Sb 2 Te 3 interface across a temperature range of 200–400 K. Furthermore, the values are also compared with thermal conductances calculated by a modified Landauer transport formalism using phonon transmission coefficients obtained from the diffuse mismatch model. Our results show that inelastic scattering processes contribute to an increase in interfacial thermal conductance at higher temperatures. Finally, we calculate the thermal conductivities of Bi 2 Te 3 -Sb 2 Te 3 superlattices with varying period lengths from 2 to 18 nm. A minimum thermal conductivity of 0.27 W/mK is observed at a period length of 4 nm, which is attributed to the competition between incoherent and coherent phonon transport regimes. In comparison with previous experimental measurements in the literature, our results show good agreement with respect to the range of thermal conductivity values and the period length corresponding to the minimum superlattice thermal conductivity.

42 ENGINEERING↗
DOE OSTI2023

Fluid-phase helium: Shock-compression experiments, quantum molecular dynamics simulations, and development of an equation of state

Helium (He) plays a critical role in numerous areas ranging from the study of celestial objects like brown dwarfs and gas giants to modern-day technologies like nuclear energy and rocket propulsion. For many of these applications, it is essential to have a reliable equation of state (EOS) for He that yields an accurate representation of its thermodynamic behavior. To help constrain and develop such EOS models, we have performed a series of shock-compression experiments on cryogenic liquid He to pressures exceeding 100 GPa using a magnetically accelerated flyer plate on Sandia National Laboratories' Z-machine. We have also performed quantum molecular dynamics simulations that are consistent with our shock measurements. None of the previously available EOSs agree with our experimental and simulation results, motivating the development of a fluid-phase He EOS that we present in this study. Here, we show that our EOS yields good agreement with published data that span temperatures and pressures encountered across a diverse array of applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗
DOE OSTI2024

Microscale mechanical property variations of Al-substituted LLZO: insights from compression testing and molecular dynamics simulations

Ceramic solid electrolytes based on LLZO (Li 7 La 3 Zr 2 O 12 ) are promising candidates for all-solid-state batteries due to their high ionic conductivity and good apparent stability vs. lithium metal, however they are prone to mechanical failure. Lithium metal intrusions, alongside cell stack pressure, transition polycrystalline solid electrolyte grains into a compressed state that promotes crack propagation and fracture. Here this work examines the mechanical response of Al-substituted LLZO to compressive forces by measuring ultimate strength under pillar compression with a flat punch tip. Failure modes characterized by in situ scanning electron microscopy show diverse splitting patterns arising from internal porosity, grain boundaries, and slip planes. Large correlated variations in compressive strength (0.93–2.63 GPa) and Young's modulus (72.1–150.97 GPa) are observed across microscale regions of the solid electrolyte. Molecular dynamics simulations of LLZO with different porosities describe the variation of compressive strength and Young's modulus, and enable a microscale porosity model to be fit accounting for Young's modulus reduction across the solid electrolyte. Overall, the results indicate the importance of microscale mechanical testing of ceramic solid electrolytes to identify preferential sites for mechanical degradation and Li intrusion, and ensure the robust design of all-solid-state lithium metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

36 MATERIALS SCIENCE↗