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Results for “Molecular dynamics simulation”

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At least 1,117 records · Page 62

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DOE OSTI2022

How arsenic makes amorphous GeSe a robust chalcogenide glass for advanced memory integration

The 3D integration technology in semiconductor fabrication requires a key component, the ovonic threshold switching (OTS) selector, to suppress the current leakage. The As doped amorphous (a-) GeSe glass is a commercialized OTS material in 3D phase-change memory, but the understanding of such a doping mechanism is still inadequate. Here we systematically explore the effect of As doping on the structural, bonding, and dynamics properties of a-GeAsSe using ab initio molecular dynamics simulations. The results reveal that As atoms form strong bonds with both Ge and Se atoms. The distorted octahedral structures and the 5-fold rings linked by atoms are increased. All of these structural features lead to a more disordered configuration. Moreover, as atoms have notably slowed down the atomic mobility, rendering a-GeAsSe a high stability. Overall, our studies offer insightful understanding of As-doping in OTS materials, paving the way for the design and application of advanced selector devices.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Equilibrium Separation of Siloxanes in Metal–Organic Frameworks

We present an in silico assessment of metal–organic frameworks (MOFs) for the equilibrium separation of linear and cyclic siloxanes. Using a combination of configurational bias/continuous fractional component Monte Carlo (CB/CFCMC) simulations and Ideal Adsorbed Solution Theory (IAST), we investigated the adsorption of both equimolar and nonequimolar mixtures of linear and cyclic siloxanes in a selection of synthesizable MOFs with medium to large pore volumes. We showed that configurational entropy effects drive the preferential adsorption of linear siloxanes over cyclic siloxanes. Based on synthesizability metrics we identified ZIF-70 as a promising adsorbent for the separation of linear and cyclic siloxanes. Self-diffusivities of linear and cyclic siloxanes in ZIF-70 calculated from molecular dynamics simulations show that equilibrium can be reached on reasonable time scales. We explored vacuum-temperature swing adsorption (VTSA) as a potential method for the recovery of adsorbed linear siloxanes from ZIF-70, achieving a 75% reduction in adsorbed phase concentration. Additionally, we demonstrated that supercritical CO 2 offers an alternative desorption strategy by displacing adsorbed linear siloxanes in ZIF-70 at pressures above 200 bar driven by entropy effects.

Adsorption↗

DOE OSTI2026

Surface Hydroxyls of Imogolite Nanotubes Drive Distinct Structures and Mobility Differentiation of Nanoconfined Water

Abstract Nanoconfined fluids, particularly water, govern subsurface geochemistry, yet the molecular-level mechanisms by which mineral surfaces dictate confined water structure and mobility remain poorly resolved. Here, we combine solution- and solid-state proton (1H) NMR spectroscopy, NMR relaxometry, modulated-gradient spin–echo (MGSE) NMR diffusometry, infrared spectroscopy, and molecular dynamics simulations to demonstrate that surface hydroxyls drive the structural and dynamic differentiation of water in imogolite nanotubes. In saturated suspensions, we observe the coexistence of distinct water 1H environments, each exhibiting significantly reduced mobility, which we attribute to strong interactions with the imogolite surfaces. As more mobile water is removed, long-range water diffusivity in the fibrous solid samples slows to 1.6 × 10–10 m2·s–1 while local fluctuations increase to 3.4 × 10–8 m2·s–1, indicating a significant increase in molecular restriction through surface interactions. Together, our experiments reveal three coexisting populations with varied structures and mobilities, all distinct from liquid bulk water. We resolve a persistent solid-like interfacial layer strongly bound to surface hydroxyls, characterized by an unusually short T2 (<1 ms), and a very close effective 1H–1H distance of ∼1.55 Å between water and the inner-surface silanol group. An inner-core population occupying the inner cavity exhibits an intermediate dynamic regime with restricted axial diffusion, while outer-surface water associated with aluminum hydroxyls retains relatively higher mobility. These results experimentally substantiate a hierarchy of water populations in imogolite and show how surface chemistry dictates the structures and dynamics of confined water.

Fleming, Xander B. [Earth and Environmental Scienc↗

DOE OSTI2023

Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery

Passive permeation of cellular membranes is a key feature of many therapeutics. The relevance of passive permeability spans all biological systems as they all employ biomembranes for compartmentalization. A variety of computational techniques are currently utilized and under active development to facilitate the characterization of passive permeability. These methods include lipophilicity relations, molecular dynamics simulations, and machine learning, which vary in accuracy, complexity, and computational cost. This review briefly introduces the underlying theories, such as the prominent inhomogeneous solubility diffusion model, and covers a number of recent applications. Various machine-learning applications, which have demonstrated good potential for high-volume, data-driven permeability predictions, are also discussed. Due to the confluence of novel computational methods and next-generation exascale computers, we anticipate an exciting future for computationally driven permeability predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Unexpected Observation of Disorder and Multiple Phase-Transition Pathways in Shock-Compressed Zr

The response of materials under dynamic compression involves a complex interplay of various deformation mechanisms aimed at relieving shear stresses, yielding a remarkable diversity in material behavior. Here, in this Letter, we utilize femtosecond x-ray diffraction coupled with nanosecond laser compression to reveal an intricate competition between multiple shear-relieving mechanisms within an elemental metal. Our observations in shocked-compressed single-crystal Zr indicate a disorder-mediated shear relaxation at lower pressures. Above the phase-transition pressure, we observe the increasing contribution of structural phase transition in relieving shear stress. We detect not one but three concurrent pathways during the transition from the hcp to a hex-3 structure. These complex dynamics are partially corroborated through multimillion-atom molecular dynamics simulations employing a machine-learned interatomic potential. Our observation of multiple concurrent pathways and disorder during shock compression underscore the far greater intricacies in the dynamic response of metals than previously assumed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Modeling the Solvation and Acidity of Carboxylic Acids Using an Ab Initio Deep Neural Network Potential

Formic and acetic acid constitute the simplest of carboxylic acids, yet they exhibit fascinating chemistry in the condensed phase such as proton transfer and dimerization. The go-to method of choice for modeling these rare events have been accurate but expensive ab-initio molecular dynamics simulations. Here, we present a deep neural network potential trained using accurate ab-initio data that can be used in tandem with enhanced-sampling methods to perform an efficient exploration of the free-energy surface of aqueous solutions of weak carboxylic acids. In particular, we show that our model captures proton dissociation and provides a good estimate of the pK a , as well as the dimerization of formic and acetic acid. This provides a suitable starting point for applications in different research areas where computational efficiency coupled with the accuracy of ab-initio methods is required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Stoichiometry dependent properties of cerium hydride: An active learning developed interatomic potential study

Cerium hydride has a variety of interesting properties, including a known lattice contraction and densification with increasing hydrogen content. However, precise stoichiometric control is not experimentally straightforward and ab initio approaches are not computationally feasible for many properties such as melting and low temperature diffusion. Therefore, we develop a machine-learned interatomic potential for cerium hydride that is valid for H to Ce ratios from 2.0 to 3.0. A query-by-committee active learning approach is used to develop the training set. Leveraging classical molecular dynamics simulations, we assess a range of properties and provide fundamental mechanisms for the trends with stoichiometry. Finally, a majority of the properties follow the trend of lattice contraction, being governed by the stronger lattice binding induced by adding octahedral atoms.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Computational study of the electrostatic potential and charges of multivalent ionic liquid molecules

The electrostatic interactions in ionic liquids (ILs) can be difficult to quantify, but this information is very valuable for improving intermolecular potentials for performing molecular-level simulations. Although polarizable forcefields can provide improved accuracy, the computational efficiency of fixed charge molecular models is often preferred for larger systems. Here, we propose a multi-scale screening approach for analyzing the charge scaling behavior and other electrostatic properties of ILs, which is more attainable than previous analysis methods that rely on the IL crystalline structures. Based on isolated molecules and small clusters, we study the electrostatic potential properties and charges of multivalent IL molecules using density-functional theory calculations and ab initio molecular dynamics simulations. The charges of the IL molecules are calculated and compared using several different charge estimation techniques. Although there are some differences among the estimated partial charges on the atoms, the total anion and cation charges are very similar. In conclusion, the charge scaling factors are substantial, and they are only slightly affected by the IL cluster size model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Substrate binding-induced conformational transitions in the omega-3 fatty acid transporter MFSD2A

Major Facilitator Superfamily Domain containing 2 A (MFSD2A) is a transporter that is highly enriched at the blood-brain and blood-retinal barriers, where it mediates Na + -dependent uptake of ω-3 fatty acids in the form of lysolipids into the brain and eyes, respectively. Despite recent structural insights, it remains unclear how this process is initiated, and driven by Na + . Here, we perform Molecular Dynamics simulations which demonstrate that substrates enter outward facing MFSD2A from the outer leaflet of the membrane via lateral openings between transmembrane helices 5/8 and 2/11. The substrate headgroup enters first and engages in Na + -bridged interactions with a conserved glutamic acid, while the tail is surrounded by hydrophobic residues. This binding mode is consistent with a “trap-and-flip” mechanism and triggers transition to an occluded conformation. Furthermore, using machine learning analysis, we identify key elements that enable these transitions. These results advance our molecular understanding of the MFSD2A transport cycle.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Thermal exchange-correlation functionals: Capturing quantum electron behavior in warm, dense plasmas

We summarize and give perspective upon recent progress in developing non-empirical constraint-based thermal (i.e., free energy) exchange-correlation (XC) density functionals essential for accurate description of the quantum behavior of electrons in warm, dense plasmas. After delineating the critical role of ground-state functionals for zero-temperature, time-dependent DFT, we outline the underpinnings of local density approximation, generalized gradient approximation (GGA), and meta-GGA XC free-energy functionals. Two basic thermalization principles for upgrading ground-state XC functionals to successful thermal ones are emphasized. Then, we turn to a long-standing challenge, assessment of the accuracy of well-founded functionals. Unlike the ground state, there are a few exact results for large T and P. An exception is path integral Monte Carlo (PIMC) data for dense H/D and He plasmas. For those, we did ab initio molecular dynamics simulations under selected thermodynamic conditions employing five thermal XC functionals: two approximate thermal GGAs, fully thermal GGA, an approximate meta-GGA, and fully thermal meta-GGA. Comparisons with the PIMC data show that functionals thermalized by augmenting a non-thermal functional with a lower-level thermal contribution are inferior to functionals with thermal XC and spatial inhomogeneity effects taken into account at the same level of refinement. We believe this and similar evidence should be convincing to the high-energy density physics community of the necessity of use of proper thermal XC functionals in simulation studies of finite-temperature quantum effects in warm, dense plasmas.

Ab-initio molecular dynamics↗

DOE OSTI2024

Familial Alzheimer mutations stabilize synaptotoxic γ-secretase-substrate complexes

Mutations that cause familial Alzheimer’s disease (FAD) are found in amyloid precursor protein (APP) and presenilin, the catalytic component of γ-secretase, that together produce amyloid β-peptide (Aβ). Nevertheless, whether Aβ is the primary disease driver remains controversial. We report here that FAD mutations disrupt initial proteolytic events in the multistep processing of APP substrate C99 by γ-secretase. Cryoelectron microscopy reveals that a substrate mimetic traps γ-secretase during the transition state, and this structure aligns with activated enzyme-substrate complex captured by molecular dynamics simulations. In silico simulations and in cellulo fluorescence microscopy support stabilization of enzyme-substrate complexes by FAD mutations. Neuronal expression of C99 and/or presenilin-1 in Caenorhabditis elegans leads to synaptic loss only with FAD-mutant transgenes. Designed mutations that stabilize the enzyme-substrate complex and block Aβ production likewise led to synaptic loss. Collectively, these findings implicate the stalled process—not the products—of γ-secretase cleavage of substrates in FAD pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Structure of maize BZR1-type β-amylase BAM8 provides new insights into its noncatalytic adaptation

Plant β-amylase (BAM) proteins play an essential role in growth, development, stress response, and hormone regulation. Despite their typical (β/α) 8 barrel structure as active catalysts in starch breakdown, catalytically inactive BAMs are implicated in diverse yet elusive functions in plants. Further, the noncatalytic BAM7/8 contain N-terminal BZR1 domains and were shown to be involved in the regulation of brassinosteroid signaling and possibly serve as sensors of yet an uncharacterized metabolic signal. While the structures of several catalytically active BAMs have been reported, structural characterization of the catalytically inactive BZR1-type BAMs remain unknown. Here, we determine the crystal structure of β-amylase domain of Zea mays BAM8/BES1/BZR1-5 and provide comprehensive insights into its noncatalytic adaptation. Using structural-guided comparison combined with biochemical analysis and molecular dynamics simulations, we revealed conformational changes in multiple distinct highly conserved regions resulting in rearrangement of the binding pocket. Altogether, this study adds a new layer of understanding to starch breakdown mechanism and elucidates the acquired adjustments of noncatalytic BZR1-type BAMs as putative regulatory domains and/or metabolic sensors in plants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Structure and dynamics of $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquids close to Earth's liquid core conditions

Using an artificial neural-network machine learning interatomic potential, we have performed molecular dynamics simulations to study the structure and dynamics of $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquid close to the Earth's liquid core conditions. Here, the simulation results reveal that the short-range structural order (SRO) in the $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquid is very strong. About 80% of the atoms are arranged in crystallinelike SRO motifs. In particular, ~ $70$% of Fe-centered clusters can be classified as either hexagonal-close-packed-like or icosahedrallike SRO motifs. The SRO clusters centered on Fe, Si, or O atoms are strongly intermixed and homogenously distributed throughout the liquid. The atomic structure of the liquid and the fractions of dominant SRO clusters are not sensitive to pressure/temperature used in the simulations except that the SRO of the O-centered clusters is enhanced close to inner core pressures. The O-diffusion coefficient is about two to three times larger than the Fe and Si ions and increases more rapidly in the deeper core regions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Ferroelectric materials such as BaTiO 3 show tremendous potential for emerging advances in memory devices, particular neuromorphic type devices. High density of memory can be obtained by stabilising polar domain walls at the nanoscale, regions of discontinuity between the well-defined polarization order parameter, but little is known about what controls their structure and dynamics in real nanoscale materials. Indeed, chiral polar domain walls have been observed in heterogeneous ferroelectrics, such as oxygen-deficient BaTiO 3 , but very little is known about how such polar-domains walls interact with defects. Indeed, a critical understanding of how dynamics of domain-walls depend on point-defects is crucial to create engineered ferroelectric memory devices. For this work, we perform large-scale simulations of nansocale domain-wall dynamics in pristine and defective BaTiO 3 using reactive force-field developed by us earlier (Phys. Chem. Chem. Phys., 2019, 21, 18240–18249), and capture their dynamical dependence on point defects using a graph dynamical neural-network approach, which we adapted to interrogate solids with well-defined order-parameters, and implemented using Pytorch based libraries. Our machine learning (ML) approach goes beyond the traditional post-processing methods to capture both spatial and temporal heterogeneities of large-scale molecular dynamics simulations of complex defective ferroelectric oxide materials. We crucially find that isolated oxygen vacancies introduce very localized spatial regions (~1–2 unit-cell in length) that show slow dipole relaxation due to formation of defect-dipoles, and that these defect-dipoles in turn slow the intrinsic dynamics of domain walls. Further, the roughness of domain walls, also influenced by vacancies, introduce dynamic heterogeneity along the domain-wall. As such we find a novel mechanism by which quenched disorder due to defects introduce dynamic heterogeneity thereby influencing response to external fields (particularly time varying fields) in a ferroelectric. Our study also emphasizes the need for creating digital twins of dynamical quantities to achieve autonomous in operando control of nanoscale switching.

42 ENGINEERING↗

DOE OSTI2022

Molecular-level solvation and selectivity behavior of Na + , K + , and Li + within glycerol-derived solvents

Ether-based acyclic solvents have a tendency to confine positively charged atoms, forming structures called podands. Due to the stability of these structures, podands have been identified as promising candidates for several different electrochemical applications. In this work, we use molecular dynamics simulations to investigate the solvation and selectivity of Na + , K + , and Li + by different glycerol-derived solvents. The structural properties suggest that the solvent-cation association is stable over a very wide temperature range. Further, a strong correlation is observed between the more electronegative oxygen sites and preferential interaction with the cations, which suggests that the electrostatic oxygen-ion interactions dominate the coordination between these species. Significantly more intense interactions are observed between the solvents and Li + , versus Na + or K + . These molecular-level thermodynamic insights provide fundamental support for further exploring the performance of glycerol-derived podand complexes in Li + capture applications and/or electrolyte formulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Solvation Energy of Ions in a Stockmayer Fluid

We calculate the solvation energy of monovalent and divalent ions in various liquids with coarse-grained molecular dynamics simulations. Our theory treats the solvent as a Stockmayer fluid, which accounts for the intrinsic dipole moment of molecules and the rotational dynamics of the dipoles. Despite the simplicity of the model, we obtain qualitative agreement between the simulations and experimental data for the free energy and enthalpy of ion solvation, which indicates that the primary contribution to the solvation energy arises mainly from the first and possibly second solvation shells near the ions. Our results suggest that a Stockmayer fluid can serve as a reference model that enables direct comparison between theory and experiment and may be invoked to scale up electrostatic interactions from the atomic to the molecular length scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Energy-efficient pathway for selectively exciting solute molecules to high vibrational states via solvent vibration-polariton pumping

Abstract Selectively exciting target molecules to high vibrational states is inefficient in the liquid phase, which restricts the use of IR pumping to catalyze ground-state chemical reactions. Here, we demonstrate that this inefficiency can sometimes be solved by confining the liquid to an optical cavity under vibrational strong coupling conditions. For a liquid solution of 13 CO 2 solute in a 12 CO 2 solvent, cavity molecular dynamics simulations show that exciting a polariton (hybrid light-matter state) of the solvent with an intense laser pulse, under suitable resonant conditions, may lead to a very strong (>3 quanta) and ultrafast (<1 ps) excitation of the solute, even though the solvent ends up being barely excited. By contrast, outside a cavity the same input pulse fluence can excite the solute by only half a vibrational quantum and the selectivity of excitation is low. Our finding is robust under different cavity volumes, which may lead to observable cavity enhancement on IR photochemical reactions in Fabry–Pérot cavities.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Barkas effect in strongly magnetized plasmas

Strongly magnetized plasmas, which are characterized by the particle gyrofrequency exceeding the plasma frequency, exhibit novel transport properties. For example, recent work showed that the friction force on a test charge moving through a strongly magnetized plasma not only consists of the typical stopping power component but also includes components perpendicular to the test charge's velocity. However, these studies only considered test charges that have the same sign as the charge of the plasma particles. Here, we extend these calculations to the case of charges with opposite signs (such as an ion interacting with strongly magnetized electrons). This is done with both a novel generalized Boltzmann kinetic theory and molecular dynamics simulations. It is found that the friction force changes dramatically depending on the sign of the interacting charges. Likewise, the stopping power component for oppositely charged particles decreases in magnitude compared with like-charged particles, and the perpendicular components increase in magnitude. Moreover, the difference between the two cases increases as the gyrofrequency becomes larger compared with the plasma frequency. Finally, the electrical resistivity is calculated from the friction force, where it is found that strong magnetization in conjunction with oppositely charged interactions significantly decreases the parallel resistivity and increases the perpendicular resistivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗