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At least 1,099 records · Page 61

Atomistic modeling of LiF microstructure ionic conductivity and its influence on nucleation and plating

We report the formation and degradation of the solid electrolyte interphase (SEI) and its underlying transport properties play an essential role in the overall performance of lithium-ion batteries. This paper presents classical molecular dynamics studies on polycrystalline inorganic lithium fluoride (LiF) layers to model and predict the SEI transport properties. The ionic conductivity is obtained from the lithium-ion diffusivity in polycrystalline structures of LiF using the Nernst-Einstein relation. The predicted molecular dynamics data are used in a continuum scale phase-field model to evaluate the plating kinetics under fast charging conditions. The analysis emphasizes that the SEI ionic conductivity properties impact the plating dynamics, where SEI's low ion conductivity value is prone to large plating and subsequent capacity degradation. The combination of atomic and continuum scale studies shown herein lays a foundation to tune in SEI transport properties to decrease the amount of lithium plating and improve the performance of fast-charging batteries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The RAPTR furnace: a rapid heating and cooling sample furnace for in situ X-ray scattering studies of temperature-induced reactions

In situX-ray scattering provides valuable insights into the mechanisms and kinetics of reactions and structural transformations. For reactions and structural transformations primarily driven by temperature, and not coupled to chemical/electrochemical triggers, our ability to initiate and quench processes thermally is a practical limit for probing fast reactive phenomena. Meaningful quantitative analysis requires the dynamic phenomena to be triggered on fast time scales relative to the reaction/transformation kinetics. This article describes a new sample furnace, the Rapid-Actuating Pneumatic Thermal Reactor or RAPTR, for time-resolvedin situX-ray scattering studies initiated by temperature. The RAPTR quickly heats and cools samples by translating them into and out of a pre-heated hot zone. Using diffraction thermometry, it is shown that the samples can be heated/cooled in 10 s or less, with temperatures up to ∼1000°C being accessible. The application of the RAPTR furnace is demonstrated by exploring a fast solid-state reaction: the synthesis of scheelite-type lead tungstate, PbWO 4 , from PbO and WO 3 for which Pb 3 WO 6 is identified as a previously unrecognized reaction intermediate.

Chemistry↗

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations

Estrogen receptor alpha (ERα) is a ligand-dependent transcriptional factor in the nuclear receptor superfamily. Many structures of ERα bound with agonists and antagonists have been determined. However, the dynamic binding patterns of agonists and antagonists in the binding site of ERα remains unclear. Therefore, we performed molecular docking, molecular dynamics (MD) simulations, and quantum mechanical calculations to elucidate agonist and antagonist dynamic binding patterns in ERα. 17β-estradiol (E2) and 4-hydroxytamoxifen (OHT) were docked in the ligand binding pockets of the agonist and antagonist bound ERα. The best complex conformations from molecular docking were subjected to 100 nanosecond MD simulations. Hierarchical clustering was conducted to group the structures in the trajectory from MD simulations. The representative structure from each cluster was selected to calculate the binding interaction energy value for elucidation of the dynamic binding patterns of agonists and antagonists in the binding site of ERα. The binding interaction energy analysis revealed that OHT binds ERα more tightly in the antagonist conformer, while E2 prefers the agonist conformer. The results may help identify ERα antagonists as drug candidates and facilitate risk assessment of chemicals through ER-mediated responses.

59 BASIC BIOLOGICAL SCIENCES↗

Controlled Pyroshock Transients Can Be Used To Better Match Operational Shock Transients and Improve Shock Analysis and Testing

SRS analysis and testing to SRS is known to be conservative since SRS is generated from maxi-max shock transient data, maximum peaks are assumed to occur for each mode simultaneously, and the structural dynamics are not accounted for between the shock source and the test article. Knowing the structural dynamics of a shock test setup it is possible to subscribe a force shock transient applied at a particular strike location and direction to achieve a desired shock transient at a test reference accelerometer. The SRS at this test accelerometer reference location can be used to compare to the reference SRS, but the key reference is the shock transient not the SRS, which should lead to more realistic shock testing that better matches operational shock transient data and reduces artificial test failures that don’t occur in operational usage. The desired test shock transient should match operational shock transients. As such, the test shock transient should look similar to the operational shock transient and have similar positive and negative peaks, the same shape, and the same duration. Many shock transients can be created that satisfy an SRS, but better control of these shock transient parameters is needed to better match operational shock transients so that more realistic and less conservative shock testing can be performed. Three different shock transients are presented that satisfy a given SRS and the results are compared for an electronic board (test article) attached to a circular shock resonance test plate.

SRS, shock transient, frequency domain, FRF↗

Conservation laws and effective hadronization models

Hadronization models based on local string-breaking dynamics are typically Markovian by construction, yet the physical ensemble of final states is shaped by global constraints that couple the entire fragmentation trajectory. Recasting hadronization as a conditioned stochastic diffusion process provides a precise mathematical resolution to this tension. In particular, this language reveals explicitly that constraints stemming from conservation laws induce non-Markovian correlations between otherwise independent fragmentation steps, and that these correlations can be absorbed exactly into a renormalization of the local dynamics through a Doob $h$-transform. We develop this formalism for a $q\bar{q}$ string in the chiral limit, where the longitudinal-transverse factorization of the Lund kernel becomes exact, enabling systematic power counting and clean ultraviolet (UV)/infrared (IR) separation. The dynamics organize naturally into a tower of effective theories distinguished by the remaining string mass, spanning a UV fixed point with scale-invariant transport coefficients, an intermediate regime where transverse phase space induces controlled running, and an IR boundary layer where non-local effects enter at leading order. The tower exhibits genuine Wilsonian structure, including $β$-functions, anomalous dimensions, and systematic matching conditions. The resulting framework achieves a clean factorization of universal microscopic fragmentation dynamics from infrared constraint effects, and opens new directions for both the theoretical analysis and practical simulation of hadronization.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

Concentration dependence of hydrogen diffusion in α-iron from atomistic perspectives

Evaluation of hydrogen diffusion in structural materials is essential to predict the leakage and embrittlement of hydrogen storage applications. Here, we investigate the atomic-scale diffusion of interstitial hydrogen (H) in α-iron (Fe) over a temperature range from 350 to 900 K with different H concentrations (0.01–5%), employing classical molecular dynamics (MD) simulations. The self-diffusivity of H atoms increases with increasing temperature and decreasing concentration. With low concentrations, the calculated diffusion properties agree well with prior experiments. However, with a higher concentration (≥1%), the H diffusivity at low temperatures deviates from a high-temperature Arrhenius behavior. Through the energetic and structural analysis, we suggest that this deviation is attributed to a reduced mobility due to increased energy barrier by other H interstitials. This work contributes to the effective design of H storage applications by identifying temperature and concentration effects on permeability and addressing possible microstructural transformation.

08 HYDROGEN↗

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

Development and Verification of the Soil-Pile Interaction Extension for SubDyn

SubDyn is the substructure structural-dynamics module for the aero-hydro-servo-elastic tool FAST v8. SubDyn uses a finite-element model (FEM) to simulate complex multimember lattice structures connected to conventional turbines and towers, and it can make use of the Craig-Bampton model reduction. Here we describe the newly added capability to handle soil-pile stiffness and compare results for monopile and jacket-based offshore wind turbines as obtained with FAST v8, SACS, and EDP (the latter two are modeling software packages commonly used in the offshore oil and gas industry). The level of agreement in terms of modal properties and loads for the entire offshore wind turbine components is excellent, thus allowing SubDyn and FAST v8 to accurately simulate offshore wind turbines on fixed-bottom structures and accounting for the effect of soil dynamics, thus reducing risk to the project.

17 WIND ENERGY↗

Carbon dioxide in an ionic liquid: Structural and rotational dynamics

Ionic liquids (ILs), which have widely tunable structural motifs and intermolecular interactions with solutes, have been proposed as possible carbon capture media. In order to inform the choice of an optimal ionic liquid system, it can be useful to understand the details of dynamics and interactions on fundamental time scales (femtoseconds to picoseconds) of dissolved gases, particularly carbon dioxide (CO 2 ), within the complex solvation structures present in these uniquely organized materials. The rotational and local structural fluctuation dynamics of CO 2 in the room temperature ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EmimNTf2) were investigated by using ultrafast infrared spectroscopy to interrogate the CO 2 asymmetric stretch. Polarization-selective pump probe measurements yielded the orientational correlation function of the CO 2 vibrational transition dipole. It was found that reorientation of the carbon dioxide occurs on 3 time scales: 0.91 ± 0.03, 8.3 ± 0.1, 54 ± 1 ps. The initial two are attributed to restricted wobbling motions originating from a gating of CO 2 motions by the IL cations and anions. The final (slowest) decay corresponds to complete orientational randomization. Two-dimensional infrared vibrational echo (2D IR) spectroscopy provided information on structural rearrangements, which cause spectral diffusion, through the time dependence of the 2D line shape. Analysis of the time-dependent 2D IR spectra yields the frequency-frequency correlation function (FFCF). Polarization-selective 2D IR experiments conducted on the CO 2 asymmetric stretch in the parallel- and perpendicular-pumped geometries yield significantly different FFCFs due to a phenomenon known as reorientation-induced spectral diffusion (RISD), revealing strong vector interactions with the liquid structures that evolve slowly on the (independently measured) rotation time scales. To separate the RISD contribution to the FFCF from the structural spectral diffusion contribution, the previously developed first order Stark effect RISD model is reformulated to describe the second order (quadratic) Stark effect—the first order Stark effect vanishes because CO 2 does not have a permanent dipole moment. Through this analysis, we characterize the structural fluctuations of CO 2 in the ionic liquid solvation environment, which separate into magnitude-only and combined magnitude and directional correlations of the liquid’s time dependent electric field. This new methodology will enable highly incisive comparisons between CO 2 dynamics in a variety of ionic liquid systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic Structure of Ultrathin Gold Nanowires

Understanding of the atomic structure and stability of nanowires (NWs) is critical for their applications in nanotechnology, especially when the diameter of NWs reduces to ultrathin scale (1-2 nm). Here, using aberration-corrected high-resolution transmission electron microscopy (AC-HRTEM), we report a detailed atomic structure study of the ultrathin Au NWs, which are synthesized using a silane-mediated approach. The NWs contain large amounts of generalized stacking fault defects. These defects evolve upon sustained electron exposure, and simultaneously the NWs undergo necking and breaking. Quantitative strain analysis reveals the key role of strain in the breakdown process. Besides, ligand-like morphology is observed at the surface of the NWs, indicating the possibility of using AC-HRTEM for surface ligand imaging. Moreover, the coalescence dynamic of ultrathin Au NWs is demonstrated by in situ observations. This study provides a comprehensive understanding of the structure of ultrathin metal NWs at atomic-scale and could have important implications for their applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Dynamic Jahn–Teller Effect in the Metastable High-Spin State of Solvated [Fe(terpy) 2 ] 2+

Characterizing structural distortions in the metastable spin states of d4- 11 d7 transition metal ion complexes is crucial to understand the nature of their bistability 12 and eventually control their switching dynamics. In particular, the impact of the Jahn- 13 Teller effect needs to be assessed for any electronic configuration that could be 14 effectively degenerate, as in e.g. the high-spin (HS) manifold of highly symmetric 15 homoleptic FeII complexes. However, capturing its manifestations remains challenging 16 since crystallization generally alters the molecular conformations and their 17 interconversion. With the rapid progress of ultrafast X-ray absorption spectroscopy, it 18 is now possible to collect data with unprecedented signal-to-noise ratio, opening up for 19 detailed structural characterization of transient species in the homogeneous solution phase. By combining the analysis of 20 picosecond X-ray absorption spectra with DFT simulations, the structure of the photoinduced HS state is elucidated for solvated 21 [Fe(terpy)2]2+ (terpy = 2,2':6',2''-terpyridine). This species can be viewed as the average 5B structure in D2 symmetry that 22 originates from a dynamic Jahn-Teller effect in the HS manifold. These results evidence the active role played by this particular 23 instance of vibronic coupling in the formation of the HS state for this benchmark molecule. Ultimately, correlating the interplay 24 between intramolecular and intermolecular degrees of freedom to conformational strain and distortions in real time should 25 contribute to the development of advanced functionalities in transition metal ion complexes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Structure‐Aware Representation Learning for Effective Performance Prediction

ABSTRACT Application performance is a function of several unknowns stemming from the interactions between the application, runtime, OS, and underlying hardware, making it challenging to model performance using deep learning techniques, especially without a large labeled dataset. Collecting such labeled longitudinal datasets can take weeks. Intuitively, developers could save analysis time during code development by taking a comparative approach between multiple applications. However, the unknown dynamic interactions between applications and execution environments make it difficult for deep learning‐based models to predict the performance of new applications. In this paper, we address these problems by presenting a labeled dataset for the community and taking a comparative analysis approach to explore the source code differences between different correct implementations of the same problem. This paper assesses the feasibility of using purely static information, for example, Abstract Syntax Tree (AST), of applications to predict performance change based on code structure. We evaluate several deep learning‐based representation learning techniques for source code and propose an architecture for the tree‐based Long Short‐Term Memory (LSTM) models to discover latent representations for a source code's hierarchical structure. We demonstrate that our proposed architecture enables feed‐forward predictive models to predict change in performance using source code with up to 84% accuracy.

Ramadan, Tarek [Department of Computer Science Tex↗

Generation of the TSL for Zirconium Hydrides from Ab Initio Methods

Zirconium hydride (ZrHx) is a moderator material used in TRIGA and other reactors that may exist in multiple phases with varying stoichiometry, which include the δ phase and the ϵ phase. Current ENDF/B-VIII.0 ZrHx thermal scattering law (TSL) evaluations do not distinguish between phases. These sub-libraries were generated with the LEAPR module of NJOY using historic phonon spectra derived from a central force model and assume incoherent elastic scattering for both bound hydrogen and zirconium, which neglects the effects of crystal structures important for scattering from zirconium bound in ZrHx. In this work, the TSLs for hydrogen and zirconium bound in δ-ZrHx and ϵ-ZrH2 were generated from phonon spectra derived from modern ab initio lattice dynamics methods and ab initio molecular dynamics. Subsequently, TSLs for hydrogen and zirconium in ZrHx and ZrH2 were generated using the Full Law Analysis Scattering System Hub (FLASSH) code. The built-in generalized coherent elastic routine was used to generate the previously neglected elastic contribution from zirconium for this material. The present TSLs provide both a re-evaluation of the current ZrH sub-libraries and expansion of the set of TSLs available for the examination of neutrons in systems with zirconium hydride, permitting explicit treatment of δ and ϵ phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Effects of Inflow Spatiotemporal Discretization on Wake Meandering and Turbine Structural Response using FAST.Farm

FAST.Farm is a newly developed multiphysics, midfidelity engineering tool that can be used to predict turbine power and structural loads of wind turbines in a wind farm with minimal computational expense. Previous studies have shown similarities and differences in wind turbine performance between FAST.Farm and high-fidelity large-eddy simulations (LES) using both LES precursor-generated inflow and TurbSim-generated synthetic inflow. While conservative resolutions have been used to date, no formal spatial or temporal discretization study has been performed for the FAST.Farm model wind domains. This work aims to study the effects of varying the spatial and temporal discretization of the wind domains on wake meandering (low-resolution domain) and turbine structural response (high-resolution domains) and resulting wake and load calculations. The purpose of this study is to establish convergence criteria and recommendations for discretization values in terms of rotor diameter (D, expressed in meters) that will maximize computational efficiency. To ensure a percent error of ≤ 1% in standard deviation of wake center position relative to the finest included resolution, a low-resolution time step of 0.024D s, 0.016D s, and 0.0079D s and a low-resolution spatial discretization of 0.079D m, 0.16D m, and 0.24D m is recommended for 8 m/s, 12 m/s, and 18 m/s mean ambient wind speed at hub height, respectively. These guidelines are likely applicable to other implementations of the dynamic wake meandering model. To ensure a percent error of ≤ 1% in standard deviation of all considered structural response outputs, a high-resolution time step that captures the highest influential excitation and natural frequencies in the system and a high-resolution spatial discretization comparable to the maximum airfoil cord length is recommended. Lastly, these guidelines are likely applicable to any aeroelastic analysis.

17 WIND ENERGY↗

Equilibria, dynamics, and current sheet formation in magnetically confined coronae

The dynamics of magnetic fields in closed regions of solar and stellar coronae are investigated with a reduced magnetohydrodynamic (MHD) model in the framework of the Parker scenario for coronal heating. A novel analysis of reduced MHD equilibria shows that their magnetic fields have an asymmetric structure in the axial direction with variation length scale z{sub ℓ} ∼ ℓB{sub 0}/b, where B{sub 0} is the intensity of the strong axial guide field, b that of the orthogonal magnetic field component, and ℓ the scale of b. Equilibria are then quasi-invariant along the axial direction for variation scales larger than approximatively the loop length z{sub ℓ} ≳ L{sub z}, and increasingly more asymmetric for smaller variation scales z{sub ℓ} ≲ L{sub z}. The critical length z{sub ℓ} ∼ L{sub z} corresponds to the magnetic field intensity threshold b ∼ ℓB{sub 0}/L{sub z}. Magnetic fields stressed by photospheric motions cannot develop strong axial asymmetries. Therefore, fields with intensities below such a threshold evolve quasi-statically, readjusting to a nearby equilibrium, without developing nonlinear dynamics or dissipating energy. But stronger fields cannot access their corresponding asymmetric equilibria; hence, they are out of equilibrium and develop nonlinear dynamics. The subsequent formation of current sheets and energy dissipation is necessary for the magnetic field to relax to equilibrium, since dynamically accessible equilibria have variation scales larger than the loop length z{sub ℓ} ≳ L{sub z}, with intensities smaller than the threshold b ≲ ℓB{sub 0}/L{sub z}. The dynamical implications for magnetic fields of interest to solar and stellar coronae are investigated numerically and the impact on coronal physics discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Improvement of the Processes of Liquid-Phase Epitaxial Growth of Nanoheteroepitaxial Structures

We have revealed the shortcomings of equipment and technological approaches in growing nanoheteroepitaxial structures with quantum dots by liquid-phase epitaxy. We have developed and fabricated a new vertical barreltype cassette for growing quantum dots and epitaxial layers of various thicknesses in one technological process. A physico-mathematical simulation has been carried out of the processes of liquid-phase epitaxial growth of quantumdimensional structures with the use of the program product SolidWorks (FlowSimulation program). Analysis has revealed the presence of negative factors influencing the growth process of the above structures. The mathematical model has been optimized, and the equipment has been modernized without additional experiments and measurements. The flow dynamics of the process gas in the reactor at various flow rates has been investigated. A method for tuning the thermal equipment has been developed. The calculated and experimental temperature distributions in the process of growing structures with high reproducibility are in good agreement, which confirms the validity of the modernization made.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Molecular Dynamics Study of the Proposed Proton Transport Pathways in [FeFe]-Hydrogenase

Possible proton channels in Clostridium pasteurianum [FeFe]-hydrogenase were investigated with molecular dynamics simulations. This study was undertaken to discern proposed channels, compare their properties, evaluate the functional channel, and to provide insight into the features of an active proton channel. Our simulations suggest that protons are not transported through water wires. Instead, a five-residue motif (E282, S319, E279, HOH, C299) was found to be the likely channel, consistent with experimental observations. This channel connects the surface of the enzyme and the di-thiomethylamine bridge of the catalytic H-cluster, permitting the transport of protons. The channel was found to have a persistent hydrogen bonded core (residues E279 to S319), with less persistent hydrogen bonds at the ends of the channel. The hydrogen bond occupancy in this network was found to be sensitive to the protonation state of the residues in the channel, with different protonation states enhancing or stabilizing hydrogen bonding in different regions of the network. Single site mutations to non-hydrogen bonding residues break the hydrogen bonding network at that residue, consistent with experimental observations showing catalyst inactivation. In many cases, these mutations alter the hydrogen bonding in other regions of the channel which may be equally important in catalytic failure. A correlation between the protein dynamics near the proton channel and the redox partner binding regions was also found as a function of protonation state. The likely mechanism of proton movement in [FeFe]-hydrogenases is discussed based on the structural analysis presented here. This work was funded by the DOE Office of Science Early Career Research Program through the Office of Basic Energy Sciences. Computational resources were provided at W. R. Wiley Environmental Molecular Science Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research located at Pacific Northwest National Laboratory, and a portion of the research was performed using PNNL Institutional Computing at Pacific Northwest National Laboratory. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy.

biomimetics↗