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At least 721 records · Page 40

Wavefront distortion correction in scanning tunneling microscope image

Here, we report an algorithm to identify and correct distorted wavefronts in atomic resolution scanning tunneling microscope images. This algorithm can be used to correct nonlinear in-plane distortions without prior knowledge of the physical scanning parameters, the characteristics of the piezoelectric actuator, or individual atom positions. The 2D image is first defined as a sum of sinusoidal plane waves, where a nonlinear distortion renders a curve for an otherwise ideal linear wavefront. Using the Fourier transforms of local areas of the image, the algorithm generates a wavefront vector field. The identified wavefronts are subsequently linearized for each plane wave without changing lattice orders, giving rise to distortion corrections. Our algorithm is complementary to conventional post-processing algorithms that require prior detection of real space features, which can also be used to correct nonlinear distortions in 2D images acquired by other microscopy techniques.

47 OTHER INSTRUMENTATION↗

Efficient real space formalism for hybrid density functionals

We present an efficient real space formalism for hybrid exchange-correlation functionals in generalized Kohn–Sham density functional theory (DFT). In particular, we develop an efficient representation for any function of the real space finite-difference Laplacian matrix by leveraging its Kronecker product structure, thereby enabling the time to solution of associated linear systems to be highly competitive with the fast Fourier transform scheme while not imposing any restrictions on the boundary conditions. We implement this formalism for both the unscreened and range-separated variants of hybrid functionals. We verify its accuracy and efficiency through comparisons with established planewave codes for isolated as well as bulk systems. In particular, we demonstrate up to an order-of-magnitude speedup in time to solution for the real space method. We also apply the framework to study the structure of liquid water using ab initio molecular dynamics, where we find good agreement with the literature. Overall, the current formalism provides an avenue for efficient real-space DFT calculations with hybrid density functionals.

Chemistry↗

Combined molecular and spin dynamics simulation of BCC iron with vacancy defects

Utilizing an atomistic computational model, which handles both translational and spin degrees of freedom, combined molecular and spin dynamics simulations have been performed to investigate the effect of vacancy defects on spin wave excitations in ferromagnetic iron. Fourier transforms of space- and time-displaced correlation functions yield the dynamic structure factor, providing characteristic frequencies and lifetimes of the spin wave modes. A comparison of the system with a 5% vacancy concentration with pure lattice data shows a decrease in frequency and a decrease in lifetime for all transverse spin wave excitations observed. In addition, the clearly defined transverse spin wave excitations are distorted with the introduction of vacancy defects, and we observe reduced excitation lifetimes due to increased magnon–magnon scattering. We observe further evidence of increased magnon–magnon scattering, as the peaks in the longitudinal spin wave spectrum become less distinct. Finally, similar impacts are observed in the vibrational subsystem, with a decrease in characteristic phonon frequency and flattening of lattice excitation signals due to vacancy defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient analysis of magnetic field line behavior in toroidal plasmas

The confinement of plasmas in tokamaks and stellarators depends on magnetic field lines lying in nested toroidal surfaces. The transition near the plasma edge away from the lines lying in magnetic surfaces defines properties of divertors. The transition in time defines properties of disruptions. Divertor design and disruption analyses require a detailed understanding of these transitions. The use of a Fourier transform coupled with a Gaussian window function allows far more information to be extracted about these transitions using far shorter field line integrations than can be obtained using traditional methods based on Poincaré plots. The physics of divertors and disruptions is reviewed to clarify why the type of information that can be gained from more efficient methods of analysis is of central importance to the fusion program based on magnetic confinement.

Boozer, Allen H. [Columbia Univ., New York, NY (Un↗

Phase transitions of β-ZnTe(en) 0.5 under hydrostatic pressure

Organic–inorganic hybrid semiconductors have enhanced and distinctive material properties. β-ZnTe(en) 0.5 , which consists of alternating layers of two-monolayer-thick zinc telluride (ZnTe) and ethylenediamine (en), exhibits high crystallinity, stability, and tunable optical properties. Using x-ray diffraction (XRD) and Fourier transform infrared spectroscopy, this study investigated the structural response of β-ZnTe(en) 0.5 to applied hydrostatic pressure. Pressure-induced phase transitions were observed at 2.1 and 3.3 GPa. Shifts in the XRD peaks indicate substantial anisotropy in the pressure response, with the layer stacking direction ( b axis) exhibiting high compressibility. The a and b lattice parameters showed −0.55% strain/GPa and −2.26% strain/GPa, respectively, contradicting theoretical calculations that predicted a more isotropic response. IR spectroscopy revealed abrupt changes in NH 2 and CH 2 vibrational modes corresponding to the phase transitions.

Chemical compounds↗

A Bayesian approach to time-domain photonic Doppler velocimetry analysis

Photonic Doppler velocimetry (PDV) is an established technique for measuring the velocities of fast-moving surfaces in high-energy-density experiments. In the standard approach to PDV analysis, the short-time Fourier transform (STFT) is used to generate a spectrogram from which the velocity history of the target is inferred. The user chooses the form, duration, and separation of the window function. Here, in this study, we present a Bayesian approach to infer the velocity directly from the PDV oscilloscope trace, without using the spectrogram for analysis. This is clearly a difficult inference problem due to the highly periodic nature of the data, but we find that with carefully chosen prior distributions for the model parameters, we can accurately recover the injected velocity from synthetic data. We validate this method using PDV data collected at the STAR two-stage light gas gun at Sandia National Laboratories, recovering shock-front velocities in quartz that are consistent with those inferred using the STFT-based approach and are interpolated across regions of low signal-to-noise data. Although this method does not rely on the same user choices as the STFT, we caution that it can be prone to misspecification if the chosen model is not sufficient to capture the velocity behavior. Analysis using posterior predictive checks can be used to establish whether a better model is required, although more complex models come with additional computational cost, often taking more than several hours to converge when sampling the Bayesian posterior. We, therefore, recommend it be viewed as a complementary method to that of the STFT-based approach.

Allison, James R. [First Light Fusion Ltd., Yarnto↗

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallographic registry in epitaxial V3O5 thin films

Crystallographic orientation plays a central role in determining transport properties in correlated oxides with low-hysteresis metal–insulator transitions. Here, V3O5 thin films were grown on Al2O3 (0001) and their crystallographic registry was evaluated using x-ray diffraction and cross-sectional transmission electron microscopy. θ–2θ measurements show a single out-of-plane orientation defined by the (202) reflection. Azimuthal φ-scans of the V3O5 (310) reflection exhibit twelve discrete maxima over 360°, indicating a finite set of in-plane orientations imposed by the substrate symmetry. High-resolution TEM and fast Fourier transform analysis confirm crystallographic coherence at the film–substrate interface. The electrical conductivity exhibits a metal–insulator transition at TMIT ≈ 423 K with no measurable thermal hysteresis and a total change of ~1.6 orders of magnitude between 300 and 480 K. These results establish crystallographic registry in epitaxial V3O5 thin films and provide a structurally well-defined system for future studies of orientation-dependent transport.\r\nT

36 MATERIALS SCIENCE↗

Efficient computation of N -point correlation functions in D dimensions

We present efficient algorithms for computing the N-point correlation functions (NPCFs) of random fields in arbitrary D-dimensional homogeneous and isotropic spaces. Such statistics appear throughout the physical sciences and provide a natural tool to describe stochastic processes. Typically, algorithms for computing the NPCF components have $\mathscr O$(n N ) complexity (for a dataset containing n particles); their application is thus computationally infeasible unless N is small. By projecting the statistic onto a suitably defined angular basis, we show that the estimators can be written in a separable form, with complexity $\mathscr O$(n 2 ) or $\mathscr O$(n g log n g ) if evaluated using a Fast Fourier Transform on a grid of size n g . Our decomposition is built upon the D-dimensional hyperspherical harmonics; these form a complete basis on the (D – 1) sphere and are intrinsically related to angular momentum operators. Concatenation of (N – 1) such harmonics gives states of definite combined angular momentum, forming a natural separable basis for the NPCF. As N and D grow, the number of basis components quickly becomes large, providing a practical limitation to this (and all other) approaches: However, the dimensionality is greatly reduced in the presence of symmetries; for example, isotropic correlation functions require only states of zero combined angular momentum. We provide a Julia package implementing our estimators and show how they can be applied to a variety of scenarios within cosmology and fluid dynamics. The efficiency of such estimators will allow higher-order correlators to become a standard tool in the analysis of random fields.

97 MATHEMATICS AND COMPUTING↗

Disentangling the chemistry of Australian plant exudates from a unique historical collection

For thousands of years, the unique physicochemical properties of plant exudates have defined uses in material culture and practical applications. Native Australian plant exudates, including resins, kinos, and gums, have been used and continue to be used by Aboriginal Australians for numerous technical and cultural purposes. A historic collection of well-preserved native Australian plant exudates, assembled a century ago by plant naturalists, gives a rare window into the history and chemical composition of these materials. Here we report the full hierarchical characterization of four genera from this collection, Xanthorrhoea, Callitris, Eucalyptus, and Acacia, from the local elemental speciation, to functional groups and main molecular markers. We use high-resolution X-ray Raman spectroscopy (XRS) to achieve bulk-sensitive chemical speciation of these plant exudates, including insoluble, amorphous, and cross-linked fractions, without the limitation of invasive and/or surface specific methods. Combinatorial testing of the XRS data allows direct classification of these complex natural species as terpenoid, aromatic, phenolic, and polysaccharide materials. Differences in intragenera chemistry was evidenced by detailed interpretation of the XRS spectral features. We complement XRS with Fourier-transform infrared (FT-IR) spectroscopy, gas chromatography–mass spectrometry (GC-MS), and pyrolysis–GC-MS (Py-GC-MS). This multimodal approach provides a fundamental understanding of the chemistry of these natural materials long used by Aboriginal Australian peoples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Powers of magnetic graph matrix: Fourier spectrum, walk compression, and applications

Magnetic graphs, originally developed to model quantum systems under magnetic fields, have recently emerged as a powerful framework for analyzing complex directed networks. Existing research has primarily used the spectral properties of the magnetic graph matrix to study global and stationary network features. However, their capacity to model local, nonequilibrium behaviors, often described by matrix powers, remains largely unexplored. We present a combinatorial interpretation of the magnetic graph matrix powers through directed walk profiles—counts of graph walks indexed by the number of edge reversals. Crucially, we establish that walk profiles correspond to a Fourier transform of magnetic matrix powers. The connection allows exact reconstruction of walk profiles from magnetic matrix powers at multiple discrete potentials, and more importantly, an even smaller number of potentials often suffices for accurate approximate reconstruction in real networks. This shows the empirical compressibility of the information captured by the magnetic matrix. This fresh perspective suggests further applications; for example, we illustrate how powers of the magnetic matrix can identify frustrated directed cycles (e.g., feedforward loops) and can be effectively employed for link prediction by encoding local structural details in directed graphs.

complex networks↗

Data-driven Detection and Early Prediction of Thermoacoustic Instability in a Multi-nozzle Combustor

Thermoacoustic instability (TAI) is a critical issue in modern lean-burn gas-turbine combustors, which is induced by a strong coupling between the resonant combustor acoustics and fluctuations in the heat release rate. This instability may lead to high-amplitude pressure waves that generate undesirable noise levels as well as fatigue stresses in mechanical structures of the combustor. The intense pressure fluctuations due to TAI may also cause large flow perturbations and possibly flow reversal that may lead to flame oscillations, flame liftoff, and even flame blow-out. Hence, there is a strong need for exercising control actions in a timely fashion to mitigate the TAI phenomena. Anomaly detection is an essential prerequisite to the design of a good controller and such a detector must be able to reliably predict a forthcoming TAI. To detect and predict the onset of a TAI from an ensemble of pressure time series, this paper investigates three data-driven methods: Fast Fourier transform (FFT), symbolic time series analysis (STSA), and hidden Markov modeling (HMM). The main focus of the paper is to make a comparative evaluation of these three anomaly detection methods for classification of the current regime of operation into stable and unstable categories as well as for real-time identification of precursors to impending instabilities with short-length time series of measured variables (e.g., pressure oscillations). Finally, the results, generated on experimental data from a multi-nozzle combustor apparatus, have been compared to evaluate the performance of FFT, STSA, and HMM methods for TAI analysis.

42 ENGINEERING↗

Multiscale Modeling of the Mechanical Response of Silicon Carbide Composite Within the Accelerated Fuel Qualification Framework

The accelerated fuel qualification (AFQ) framework has been used for the initial development of multiscale modeling of silicon carbide (SiC) fiber reinforced composite (SiC-SiC). The AFQ framework provides a methodology to leverage physics-informed multiscale modeling along with a reduced set of empirical test data to reduce the time and cost of licensing and qualification of new nuclear fuel systems while maintaining the overall nuclear power plant safety case. SiC-SiC is being proposed for in-core applications, most notably fuel cladding, for current and next-generation nuclear reactors because of its high temperature stability, irradiation tolerance, and ability to withstand many accident conditions. As these composites exhibit multiscale architectures and complex microstructure-based fracture mechanics, it is an appealing use case for the AFQ methodology. While the end goal of this work is a single multiscale model that can be used for predictive in-core performance, current focus is on the individual various length scale models. Four individual models have been initially developed from microscale to engineering system level to capture key physics-based effects across different length scales. These models include a microscale homogenized tow model, a mesoscale fast Fourier transform–based weave model that integrates the homogenized tow model, a mesoscale finite element–based weave model, and a system-level BISON fuel performance model. Results of these models have undergone an initial comparison with separate-effects test data showing a good match to experimental results. By using the AFQ framework during model development, several near-term benefits have been secured including a reduction in development time for the SiC-SiC cladding, more targeted irradiation testing, and a better understanding of uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multi-Analytical Investigation of Arsenical Transfer and Remediation on Nineteenth-Century Green Books

Books containing heavy metals, specifically nineteenth-century green arsenical books, have been identified at Northwestern University Libraries, raising health and safety concerns related to handling. Copper acetoarsenite pigments, such as emerald green, were detected on book covers, decorative page edges, labels, and other components using noninvasive analytical techniques including X-ray fluorescence (XRF), Raman spectroscopy, and Fourier-transform infrared (FTIR) spectroscopy. Further examination of selected volumes using synchrotron radiation (SR) techniques revealed pigment migration, degradation, and arsenic transfer to adjacent books. This paper expands on initial findings through two related experiments. The first explored the transfer of arsenic using mechanical friction; Staedtler Mars® white vinyl erasers rubbed on arsenical books generated crumbs which were analyzed via scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM-EDX). Results confirmed the transfer of arsenic, copper, and lead, with decorative page edges being particularly prone to shedding arsenic onto other materials. The second experiment tested remediation methods on a book contaminated by prolonged exposure to an arsenical neighbor. Surface cleaning using erasers and a vacuum removed flecks of pigment but did not eliminate non-chromophoric arsenic as confirmed by SR analyses, which highlights its presence either as a degradation product embedded within the paper or present in the paper as part of its production process. Findings demonstrate the acute toxicity risk posed by arsenical books and support the need for safe handling protocols. However, materials with only trace levels of arsenic embedded during production may pose a lower risk of transfer. Cross contamination beyond prolonged direct contact appears limited. These results highlight critical considerations for library preservation practices and future research on arsenic in historical materials.

arsenic↗

NO 2 -mediated voloxidation for iodine separation from cesium iodide surrogates

Heterogeneous NO 2 -mediated oxidation of uranium, also known as advanced voloxidation, is a proposed head-end reprocessing method for used nuclear fuel. An advantage of advanced voloxidation is the removal of volatile fission products, which complicate downstream separation and containment challenges leading to increased processing economics. Iodine, one of the volatile species of interest, has exhibited varied results in this process. Using CsI as a surrogate material, this work mimics the effect of NO 2 -based voloxidation on iodine and sheds light on the factors that influence the solid–gas phase reaction. Solid-state analysis using Fourier transform infrared attenuated total reflectance spectroscopy and scanning electron microscopy with energy-dispersive X-ray spectroscopy confirmed the conversion of CsI to CsNO 3 . Iodine separation ranged from 46% to 100% across multiple tests. Iodine separation was most effective when multiple recharges of NO 2 were administered. In conclusion, at the bench scale, liberating iodine from CsI appears to occur within 1 h, but the presence of surface H 2 O and the composition of the NO x reagent mixtures greatly influence its success.

advanced voloxidation↗

Quantifying CTFE content in FK-800 using ATR-FTIR and time to peak crystallization

The chlorotrifluoroethylene (CTFE) content in vinylidene fluoride (VDF)-CTFE copolymers greatly influences the chemical and physical properties and ultimately determines the application. The copolymer known as FK-800 has a VDF:CTFE ratio of ~1:3 and is used almost exclusively as the binder in the insensitive high explosive (HE) formulation PBX 9502. Due to the dangerous nature of HE work and the effect CTFE content variations have, the ability to quickly and easily quantify CTFE content is of interest. Two techniques, attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and time to peak crystallization measured by heat flow calorimetry, were evaluated here as potential means for quantifying CTFE content. Based on the certificate of analyses (COAs), FK-800 lots with varied CTFE content encompassing the range historically used in HE applications were used as standards for both methodologies. For FTIR, a linear regression was performed on the peak area of the C-Cl IR stretch and the CTFE content; the methodology was then demonstrated on four samples, two lots of unadulterated material and material recovered from two HE samples. The calculated CTFE content and COAs were in good agreement for all four samples. Heat flow calorimetry revealed the relationship between time to peak crystallization and CTFE content was best fit by a power regression; the methodology was then tested on two different FK-800 lots. Only one sample showed good agreement between the calculated CTFE content and the COA. This discrepancy indicates the method developed is not suitable for quantifying CTFE, but provides valuable insight regarding the crystallization behavior of VDF-CTFE copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of end-of-shift respirable crystalline silica monitoring to construction

A pilot project was conducted to determine the effect of common construction dusts as interferences in a new portable end-of-shift (EoS), direct-on-filter (DoF) sampling and analysis method for respirable crystalline silica (RCS), in this case, quartz. Construction dusts were prepared from plaster, drywall, cement and brick by grinding, aerosolizing, and collecting respirable dust with high flow rate cyclones. Filters were loaded with different levels of commercial α-quartz powder Min-u-Sil 5, and different levels of interfering dusts, singly and in combination. Samples were analyzed by Fourier Transform Infrared Spectroscopy (FTIR). Good correlations were found between nominal quartz loading (0 µg, 25 µg, 50 µg, and 100 µg) adjusted for quartz in the interfering dust and FTIR absorbance alone and in the presence of all interfering dusts. The slopes of the correlations were similar whether the loading was quartz without interference, or with plaster, drywall, and cement dusts, regardless of quantity. The results show that (a) plaster and drywall dusts do not interfere substantially; (b) cement does not interfere, but a change in the intercept suggests an effect on the background absorbance of the filter; and (c) in addition to having a substantial quartz content, brick dust contains an additional material, probably a silicate mineral, which interferes with the quartz peak. Thus, the presence of cement leads to lower quartz values and brick leads to higher values, but overall, 83% of the quartz contents predicted from the calibration data agreed within 50% of the adjusted nominal loadings within the range 20–110 µg. This result is encouraging given the high levels of interfering dusts. Nine samples loaded with smaller amounts of all four dusts together gave results within 25% of the adjusted nominal loadings. A single mixture addition of the dusts to the filter gave tighter variance in results than sequential additions. Unexpectedly, the two Certified Reference Materials (CRMs) 1878a and 1878b, gave different results when used to calibrate XRD analysis of Min-u-Sil 5.

42 ENGINEERING↗

Spurious solar-wind effects on acceleration noise in LISA Pathfinder

Spurious solar-wind effects are a potential noise source in future Laser Interferometer Space Antenna (LISA) measurements. One noise coupling mechanism is constrained by estimating solar-wind effects on acceleration noise in LISA Pathfinder (LPF). While LISA is designed for drag-free differential measurement, predicting the realistic impact both bounds the operational environment and assesses whether LISA could provide serendipitous space-weather observations. Data from NASA's Advanced Composition Explorer (ACE), situated at the L1 Lagrange point, serves as a reliable source of solar-wind data. The data sets are compared over the 114 d time period from 1 March 2016 to 23 June 2016. This period gives the longest readily-available open data set, without interference from other commissioning activities. To evaluate space weather effects, the data from both satellites are formatted, gap-filled/interpolated, and fast-Fourier transformed for amplitude spectral density and coherence comparisons. Solar wind effects are not seen in a coherence plot between LPF and ACE; modest coherence in the planned LISA observational frequency band can be attributed to chance. This result indicates that measurable correlation due to solar-wind acceleration noise over 3 month timescales will be a negligible noise source. LISA is unlikely to inform solar wind measurements routinely. Another source of noise from the Sun, solar radiation pressure, is estimated to impart greater acceleration noise, but has yet to be analyzed.

79 ASTRONOMY AND ASTROPHYSICS↗