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DOE OSTI2022

Driven superconducting vortex dynamics in systems with twofold anisotropy in the presence of pinning

Abstract We examine the dynamics of superconducting vortices with twofold anisotropic interaction potentials driven over random pinning, and compare the behavior under drives applied along the hard and the soft anisotropy directions. As the driving force increases, the number of topological defects reaches a maximum near the depinning threshold, and then decreases as the vortices form one-dimensional (1D) chains. This coincides with a transition from a pinned nematic to a moving smectic aligned with the soft anisotropy direction. The system is generally more ordered when the drive is applied along the soft direction of the anisotropy. For driving along the hard direction, there is a critical value of the twofold anisotropy above which the system remains aligned with the soft direction. Hysteretic behavior appears upon cycling the driving force, with 1D vortex chains persisting during the decreasing leg below the threshold for chain formation for increasing drive. More anisotropic systems have a greater amount of structural disorder in the moving state. For lower anisotropy, the system forms a moving smectic-A state, while at higher anisotropy, a moving nematic state appears instead.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Impact of Noncovalent Interactions on the Structural Chemistry of Thorium(IV)-Aquo-Chloro Complexes

Five novel tetravalent thorium (Th) compounds that consist of Th(H 2 O) x Cl y structural units were isolated from acidic aqueous solutions using a series of nitrogen-containing heterocyclic hydrogen (H) bond donors. Taken together with three previously reported phases, the compounds provide a series of monomeric Th IV complexes wherein the effects of noncovalent interactions (and H-bond donor identity) on Th structural chemistry can be examined. Seven distinct structural units of the general formulas [Th(H 2 O) x Cl 8–x ] x-4 (x = 2, 4) and [Th(H 2 O) x Cl 9–x] x-5 (x = 5–7) are described. The complexes range from chloride-deficient [Th(H 2 O) 7 Cl 2 ] 2+ to chloride-rich [Th(H 2 O) 2 Cl 6 ] 2– species, and theory was used to understand the relative energies that separate complexes within this series via the stepwise chloride addition to an aquated Th cation. Electronic structure theory predicted the reaction energies of chloride addition and release of water through a series of transformations, generally highlighting an energetic driving force for chloride complexation. To probe the role of the counterion in the stabilization of these complexes, electrostatic potential (ESP) surfaces were calculated. Finally, the ESP surfaces indicated a dependence of the chloride distribution about the Th metal center on the pK a of the countercation, highlighting the directing effects of noncovalent interactions (e.g., Hbonding) on Th speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Molecular Optoelectronics (Final Technical Report)

The project developed new theoretical tools for analysis of nanodevices subjected to external optical and bias driving. Traditional theoretical techniques for molecular optoelectronics are either based on kinetic schemes or utilize quasiparticle description. The former fails to account for quantum mechanics of the system-bath interface and may fail qualitatively when used in open interacting systems. The latter is inconvenient in (usual for molecular optical spectroscopy) many body states description of the system. We developed a new technique - the Hubbard nonequilibrium Green's functions method - which allows to avoid shortcomings of standard theoretical approaches. The Hubbard NEGF was applied to analysis of experimental measurements of photoinduced current and bias-induced electroluminescence in STM molecular junctions. We also demonstrated practical usefulness of the Hubbard NEGF within newly proposed universal theory of current-induced forces for nonadiabatic molecular dynamics which generalizes celebrated Head-Gordon and Tully expression for electronic friction. Finally, following latest trends in laser techniques we studied local responses (local fluxes and local noise spectroscopy) of biased junctions as a source of information not accessible by total responses (total fluxes and noises) of the system.

30 DIRECT ENERGY CONVERSION↗

NASA NTRS2004

[Using Molecular Simulations to Understand Complex Nanoscale Dynamic Phenomena in Polymer Solutions]

The first half of the project concentrated on molecular simulation studies of the translocation of model molecules for single-stranded DNA through a nanosized pore. This has resulted in the publication, Translocation of a polymer chain across a nanopore: A Brownian dynamics simulation study, by Pu Tian and Grant D. Smith, JOURNAL OF CHEMICAL PHYSICS VOLUME 119, NUMBER 21 1 DECEMBER 2003, which is attached to this report. In this work we carried out Brownian dynamics simulation studies of the translocation of single polymer chains across a nanosized pore under the driving of an applied field (chemical potential gradient) designed to mimic an electrostatic field. The translocation process can be either dominated by the entropic barrier resulted from restricted motion of flexible polymer chains or by applied forces (or chemical gradient). We focused on the latter case in our studies. Calculation of radius of gyration of the translocating chain at the two opposite sides of the wall shows that the polymer chains are not in equilibrium during the translocation process. Despite this fact, our results show that the one-dimensional diffusion and the nucleation model provide an excellent description of the dependence of average translocation time on the chemical potential gradients, the polymer chain length and the solvent viscosity. In good agreement with experimental results and theoretical predictions, the translocation time distribution of our simple model shows strong non-Gaussian characteristics. It is observed that even for this simple tube-like pore geometry, more than one peak of translocation time distribution can be generated for proper pore diameter and applied field strengths. Both repulsive Weeks-Chandler-Anderson and attractive Lennard-Jones polymer-nanopore interaction were studied. Attraction facilitates the translocation process by shortening the total translocation time and dramatically improve the capturing of polymer chain. The width of the translocation time distribution was found to decrease with increasing temperature, increasing field strength, and decreasing pore diameter.

Smith, Grant↗

NASA NTRS1995

Large Enhancements in the O/N2 Ratio in the Evening Sector of the Winter Hemisphere During Geomagnetic Storms

In this paper, we have looked for enhancements of the O/N2 ratio in data measured by the Dynamics Explorer 2 (DE 2) satellite in the middle latitudes of the winter hemisphere, based on a prediction that was made by the National Center for Atmospheric Research thermosphere/tonosphere general circulation model (NCAR-TIGCM) that such increases occur. The NCAR-TIGCM predicts that these enhancements should be seen throughout the low latitude region and in many middle latitude locations, but that the enhancements in O/N2 are particularly strong in the middle-latitude, evening-to-midnight sector of the winter hemisphere. When this prediction was used to look for these effects in DE 2 NACS (neutral atmosphere composition spectrometer) data, large enhancements in the O/N2 ratio (approx. 50 to 90%) were seen. These enhancements were observed during the main phase of a storm that occurred on November 24, 1982, and were seen in the same region of the winter hemisphere predicted by the NCAR-TIGCM. They are partially the result of the depletion of N2 and, as electron loss is dependent on dissociative recombination at F(sub 2) altitudes, they have implications for electron densities in this area. Parcel trajectories, which have been followed through the NCAR-TIGCM history file for this event, show that large O/N2 enhancements occur in this limited region in the winter hemisphere for two reasons. First, these parcels of air are decelerated by the antisunward edge of the ion convection pattern; individual parcels converge and subsidence occurs. Thus molecular-nitrogen-poor air is brought from higher to lower heights. Because neutral parcels that are found a little poleward of the equatorial edge of the eveningside convection pattern are swept inward toward the center of the auroral oval, the enhancements occur only in a very limited range of latitudes. Second, nitrogen-poor air is transported from regions close to the magnetic pole in the winter hemisphere. During geomagnetic storms, enhanced meridional winds are driven by the increased pressure-gradient force that is associated with intensified Joule heating in the auroral oval. These pressure-driven winds decrease rapidly on the dayside beyond the auroral oval where the parcels originate, limiting the region into which the parcels can be transported. Thus these two processes drive values of O/N2 in a limited region of the winter hemisphere, and reinforce only in the evening sector, causing large changes in this region.

Burns, A. G.↗

DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

NASA NTRS1995

Molecular Sieve Bench Testing and Computer Modeling

The design of an efficient four-bed molecular sieve (4BMS) CO2 removal system for the International Space Station depends on many mission parameters, such as duration, crew size, cost of power, volume, fluid interface properties, etc. A need for space vehicle CO2 removal system models capable of accurately performing extrapolated hardware predictions is inevitable due to the change of the parameters which influences the CO2 removal system capacity. The purpose is to investigate the mathematical techniques required for a model capable of accurate extrapolated performance predictions and to obtain test data required to estimate mass transfer coefficients and verify the computer model. Models have been developed to demonstrate that the finite difference technique can be successfully applied to sorbents and conditions used in spacecraft CO2 removal systems. The nonisothermal, axially dispersed, plug flow model with linear driving force for 5X sorbent and pore diffusion for silica gel are then applied to test data. A more complex model, a non-darcian model (two dimensional), has also been developed for simulation of the test data. This model takes into account the channeling effect on column breakthrough. Four FORTRAN computer programs are presented: a two-dimensional model of flow adsorption/desorption in a packed bed; a one-dimensional model of flow adsorption/desorption in a packed bed; a model of thermal vacuum desorption; and a model of a tri-sectional packed bed with two different sorbent materials. The programs are capable of simulating up to four gas constituents for each process, which can be increased with a few minor changes.

Mohamadinejad, Habib↗

DOE OSTI2026

A tunable autonomous RNA-fueled micro-engine

Autonomous molecular machines capable of converting chemical energy into mechanical motion are foundational components for synthetic nanoscale systems. Inspired by biological motors, we report the construction of a tunable, RNA-fueled DNA origami engine that drives the cyclic movement of a 500 nm-diameter particle at the microscale. The engine operates via sequential RNA–DNA hybridization and enzymatic cleavage by RNase H, enabling reversible switching between folded and unfolded conformations without external intervention. By modulating RNA and enzyme concentrations and controlling temperature, we achieve tunable switching kinetics, with transition periods as short as ~10 s. Kinetic modeling reveals that the folding pathway is governed by both productive RNA binding and the enzymatic clearance of misfolded intermediates, while unfolding is primarily controlled by RNase H activity. Since the RNA fuel binds specifically to the DNA strands, each engine is addressable simply by changing the sequences. This work demonstrates a programmable, self-resetting molecular actuator and offers a blueprint for building more complex nanomechanical systems with forces and energies comparable to molecular motors.

DNA nanomachines↗

DOE OSTI2025

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Microbiology↗

NASA NTRS2005

Growth from Solutions: Kink dynamics, Stoichiometry, Face Kinetics and stability in turbulent flow

1. Kink dynamics. The first segment of a polygomized dislocation spiral step measured by AFM demonstrates up to 60% scattering in the critical length l*- the length when the segment starts to propagate. On orthorhombic lysozyme, this length is shorter than that the observed interkink distance. Step energy from the critical segment length based on the Gibbs-Thomson law (GTL), l* = 20(omega)alpha/(Delta)mu is several times larger than the energy from 2D nucleation rate. Here o is tine building block specific voiume, a is the step riser specific free energy, Delta(mu) is the crystallization driving force. These new data support our earlier assumption that the classical Frenkel, Burton -Cabrera-Frank concept of the abundant kink supply by fluctuations is not applicable for strongly polygonized steps. Step rate measurements on brushite confirms that statement. This is the1D nucleation of kinks that control step propagation. The GTL is valid only if l* <Dk/vk, the diffusion path of a kink that has diffusivity Dk and average growth velocity vk. This is equivalent to supersaturations sigma less than approx. alpha/2l*, where alpha is the building block size. For lysozyme, sigma much less than (1%). Conventionally used interstep distance generated by screw dislocation, 19(omega)alpha/Delta(mu) should be replaced by the very different real one, approx.4l*. 2. Stoichiometry. Kink, and thus step and face rates of a non-Kossel complex molecular monocomponent or any binary, AB, lattice was found theoretically to be proportional to 1/(zeta(sup 1/2) + zeta(sup - 1/2)), where zeta = [B]/[A] is the stoichiometry ratio in solution. The velocities reach maxima at zeta = 1. AFM studies of step rates on CaOxalate monohydrate (kidney stones) from aqueous solution was found to obey the law mentioned above. Generalization for more complex lattice will be discussed. 3. Turbulence. In agreement with theory, high precision in-situ laser interferometry of the (101) KDP crystal face shows step bunching if solution flows parallel to the step flow. The bunch height increases with the distance the bunch travels, i.e. with the face size. However, when the flow rate, u, increases, at u greater than approx. 1 m / s , the average step bunch height decreases as 1/u. The pheonomenon is attributed to the turbulent rather than laminar viscous boundary layer where diffusivity Dt = 0.5u(sub tau),y, i.e. increases linearly with the distance y from the solid face. Friction velocity, u(sub tau) approx. u(sup 7/8). Dramatically larger rate of the mass/heat transport within the turbulent, as compared to the laminar, viscous layer will be discussed.

Chernov, A. A.↗

DOE OSTI2023

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains

Peptoids are a class of highly customizable biomimetic foldamers that retain properties from both proteins and polymers. It has been shown that peptoids can adopt peptide-like secondary structures through the careful selection of sidechain chemistries, but the underlying conformational landscapes that drive these assemblies at the molecular level remain poorly understood. Given the high flexibility of the peptoid backbone, it is essential that methods applied to study peptoid secondary structure formation possess the requisite sensitivity to discriminate between structurally similar yet energetically distinct microstates. In this work, a generalizable simulation scheme is used to robustly sample the complex folding landscape of various 12mer polypeptoids, resulting in a predictive model that links sidechain chemistry with preferential assembly into one of 12 accessible backbone motifs. Using a variant of the metadynamics sampling method, four peptoid dodecamers are simulated in water: sarcosine, N-(1-phenylmethyl)glycine (Npm), (S)-N-(1-phenylethyl)glycine (Nspe), and (R)-N-(1-phenylethyl)glycine (Nrpe)–to determine the underlying entropic and energetic impacts of hydrophobic and chiral peptoid sidechains on secondary structure formation. Our results indicate that the driving forces to assemble Nrpe and Nspe sequences into polyproline type-I helices in water are found to be enthalpically driven, with small benefits from an entropic gain for isomerization and steric strain due to the presence of the chiral center. The minor entropic gains from bulky chiral sidechains in Nrpe- and Nspe-containing peptoids can be explained through increased configurational entropy in the cis state. However, overall assembly into a helix is found to be overall entropically unfavorable. Furthermore, these results highlight the importance of considering the many various competing interactions in the rational design of peptoid secondary structure building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Bespoke Liquid/Liquid Interfaces (Final Technical Report)

The goal of DE-SC0001815 was to advance the basic science of liquid:liquid interface formation, to develop a deeper understanding of the mechanisms of phase separation and the essential relationships between solution composition, organization and dynamics that underlie the kinetic regime of solvent extraction. This included learning how interfacial organization and dynamics alters the properties of the primary coordination sphere of ions and the free energy of transport of ions complexes across a phase boundary. We relied primarily upon classical molecular dynamics studies to determine the equilibrium ensembles of these complex systems, but also utilized ab-initio MD and cluster-based density functional theory (DFT) calculations when more detailed investigation of the electronic structure was needed. We continued development of graph-theory based analyses to elucidate hierarchical correlations and expanded into geometric topology methods to quantify the collectively organized structures that can organize at a liquid/liquid interface during solute transport. One of the main conclusions was from the observation of two distinct mechanisms for solute transport - those that derive from amplifications of interfacial heterogeneity and surface roughness, and those wherein surface roughness has been dampened and instead collectively organized macrostructures work to bring solutes into the organic phase. It was our aim to create a concrete chemical model of the underlying driving forces behind interfacial primary and secondary structure formation and to map out the energetic features of solute transport so that tailored liquid/liquid can be developed that have characteristic kinetic features associated with mass transport.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Infrared Spectroscopic Observation of Oxo- and Superoxo-Intermediates in the Water Oxidation Cycle of a Molecular Ir Catalyst

Molecular Ir catalysts have emerged as an important class of model catalysts for understanding structure–activity relationships in water oxidation, a reaction that is central to renewable fuel synthesis. Prior efforts have mostly focused on controlling and elucidating the emergence of active species from prepared precursors. However, the development of efficient and stable molecular Ir catalysts also necessitates probing of reaction intermediates. To date, relatively little is known about the key intermediates in the cycles of the molecular Ir catalysts. Herein, we probed the catalytic cycle of a homogeneous Ir catalyst (“blue dimer”) at a Au electrode/aqueous electrolyte interface by combining surface-enhanced infrared absorption spectroscopy (SEIRAS) with phase-sensitive detection (PSD). Cyclic voltammograms (CVs) from 1.4 to 1.7 VRHE (RHE = reversible hydrogen electrode) give rise to a band at ~818 cm –1 , whereas CVs from 1.4 to ≥1.85 VRHE generate an additional band at ~1146 cm –1 . Isotope labeling experiments indicate that the bands at ~818 and ~1146 cm –1 are attributable to oxo (Ir V =O) and superoxo (Ir IV –OO • ) moieties, respectively. Furthermore, this study establishes PSD-SEIRAS as a sensitive tool for probing water oxidation cycles at electrode/electrolyte interfaces and demonstrates that the relative abundance of two key intermediates can be tuned by the thermodynamic driving force of the reaction.

25 ENERGY STORAGE↗

DOE OSTI2021

WISP3 suppresses ESCC progression by inhibiting the IGF-2-IGF1R-AKT signaling cascade

Esophageal squamous cell carcinoma (ESCC) is a major health problem worldwide, especially in the Chinese population. However, the intrinsic molecular mechanisms of ESCC progression are largely unclear, thus there is an unmet need to identify essential genes governing this disease. Here, we discovered WISP3, an important member of the CCN family, is markedly downregulated in ESCC tissues compared to the normal esophageal epithelium. Downregulation of WISP3 in cancer tissue correlates with worse overall survival of ESCC patients. Using ESCC cell lines as models, we found that forced expression of WISP3 not only suppressed proliferation and migration of cancer cells in vitro, but also inhibited ESCC tumor growth and metastasis in vivo. On the contrary, WISP3 depletion strongly promoted the tumorigenicity of ESCC cells. Mechanistically, we found that WISP3 negates the activity of AKT via inhibiting the IGF-2-IGF1R signaling cascade, which mediates the tumor-suppressive function of WISP3 in esophageal cancers. Together, we identified a novel factor driving the development of ESCC, and revealed a potential therapeutic target for ESCC treatment.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields

Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-‘Herringbone,’ Au(110)-(1 × 2)-‘Missing-Row,’ and Au(100)-‘Quasi-Hexagonal’ reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Energy coupling and stoichiometry of Zn 2+ /H + antiport by the prokaryotic cation diffusion facilitator YiiP

YiiP from Shewanella oneidensis is a prokaryotic Zn 2+ /H + antiporter that serves as a model for the Cation Diffusion Facilitator (CDF) superfamily, members of which are generally responsible for homeostasis of transition metal ions. Previous studies of YiiP as well as related CDF transporters have established a homodimeric architecture and the presence of three distinct Zn 2+ binding sites named A, B, and C. In this study, we use cryo-EM, microscale thermophoresis and molecular dynamics simulations to address the structural and functional roles of individual sites as well as the interplay between Zn 2+ binding and protonation. Structural studies indicate that site C in the cytoplasmic domain is primarily responsible for stabilizing the dimer and that site B at the cytoplasmic membrane surface controls the structural transition from an inward facing conformation to an occluded conformation. Binding data show that intramembrane site A, which is directly responsible for transport, has a dramatic pH dependence consistent with coupling to the proton motive force. A comprehensive thermodynamic model encompassing Zn 2+ binding and protonation states of individual residues indicates a transport stoichiometry of 1 Zn 2+ to 2–3 H + depending on the external pH. This stoichiometry would be favorable in a physiological context, allowing the cell to use the proton gradient as well as the membrane potential to drive the export of Zn 2+ .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Extended Lagrangian Born–Oppenheimer molecular dynamics using a Krylov subspace approximation

It is shown how the electronic equations of motion in extended Lagrangian Born–Oppenheimer molecular dynamics simulations can be integrated using low-rank approximations of the inverse Jacobian kernel. This kernel determines the metric tensor in the harmonic oscillator extension of the Lagrangian that drives the evolution of the electronic degrees of freedom. The proposed kernel approximation is derived from a pseudoinverse of a low-rank estimate of the Jacobian, which is expressed in terms of a generalized set of directional derivatives with directions that are given from a Krylov subspace approximation. The approach allows a tunable and adaptive approximation that can take advantage of efficient preconditioning techniques. The proposed kernel approximation for the integration of the electronic equations of motion makes it possible to apply extended Lagrangian first-principles molecular dynamics simulations to a broader range of problems, including reactive chemical systems with numerically sensitive and unsteady charge solutions. This can be achieved without requiring exact full calculations of the inverse Jacobian kernel in each time step or relying on iterative non-linear self-consistent field optimization of the electronic ground state prior to the force evaluations as in regular direct Born–Oppenheimer molecular dynamics. We note the low-rank approximation of the Jacobian is directly related to Broyden’s class of quasi-Newton algorithms and Jacobian-free Newton–Krylov methods and provides a complementary formulation for the solution of nonlinear systems of equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗