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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Thermo-Mechanical Behavior of Genetically Modified Populus trichocarpa

Wood processing is often performed at elevated temperatures under moisture-saturated conditions; therefore, it is important to understand the impact of the lignin content and lignin chemical structure on the thermo-mechanical properties of wood. In this study, genetically modified Populus trichocarpa wood specimens with down-regulated cinnamyl alcohol dehydrogenase, cinnamate 3-hydroxylase, and cinnamate 4-hydroxylase with altered lignin contents and/or lignin structures were utilized to probe the relationship between the lignin content, lignin monomer composition, and thermo-mechanical properties of solid wood. The thermo-mechanical properties of these unique samples were measured using dynamic mechanical analysis and the nuclear magnetic resonance (NMR) spin-spin relaxation time. The results showed that the transgenic P. trichocarpa samples had decreased storage and loss moduli compared with the wildtype. The solid-state NMR revealed increased lignin molecular mobility in the reduced-lignin transgenic lines. Also, noticeably reduced glass transition temperatures (Tg) were observed in the transgenic lines with reduced lignin contents and altered lignin monomer compositions compared with the wildtype. The increased lignin molecular mobility and reduced Tg in these samples can probably contribute to wood utilization and processing, such as lignin removal for pulp and paper and biofuels production, as well as particle consolidation during wood composite manufacturing.

09 BIOMASS FUELS↗
DOE OSTI2022

Modern analogs for understanding pollen-vegetation dynamics in a Mediterranean mosaic landscape (Balearic Islands, Western Mediterranean)

This paper presents the study of modern pollen analogs from the Balearic Islands. While similar studies have been largely applied to mainland areas, research focused on modern vegetation dynamics on Mediterranean islands remains very rare. In this research, we combine vegetation surveys, pollen analysis and multivariate statistics to understand landscape composition. The main objectives of are: (1) to examine pollen-vegetation relationships in relation to environmental and land-use variables; (2) to understand modern pollen representation in a mosaic landscape structure; and (3) to propose pollen indicators that characterize the primary vegetation types from the Balearic Islands to better interpret past pollen records in Mediterranean island environments. Pollen results and Redundancy Analysis (RDA) distinguish three major groups: (a) Holm oak and box formations; (b) maquis and garrigues; and (c) anthropogenic and open habitats. Landscape form, mean decadal rainfall, mean decadal temperature, fire activity, trampling, slope percentage, wet/flooded soil, saline soil, distance to agropastoral cells, gHM index, domestic herbivory presence, agropastoral use, and soil type are the major variables explaining modern pollen assemblage variation in our research. Poaceae undiff., Plantago sp., Apiaceae undiff., Cerealia-t, and Cichorieae are highly correlated to human activities but should be interpreted cautiously when occurring in low values. Quercus ilex-t, Hypericum, and Buxus are correlated to humid locations while Pistacia, Pinus, Juniperus-t, and Olea to high mean decadal temperatures. Our study indicates how pollen analysis and multivariate analysis are powerful tools for characterizing the mosaic landscape, with special focus on the main vegetation types of the Balearic Islands.

Geology↗
DOE OSTI2017

Inverse load calculation procedure for offshore wind turbines and application to a 5‐MW wind turbine support structure

Abstract A significant number of wind turbines installed today have reached their designed service life of 20 years, and the number will rise continuously. Most of these turbines promise a more economical performance if they operate for more than 20 years. To assess a continued operation, we have to analyze the load‐bearing capacity of the support structure with respect to site‐specific conditions. Such an analysis requires the comparison of the loads used for the design of the support structure with the actual loads experienced. This publication presents the application of a so‐called inverse load calculation to a 5‐MW wind turbine support structure. The inverse load calculation determines external loads derived from a mechanical description of the support structure and from measured structural responses. Using numerical simulations with the software fast , we investigated the influence of wind‐turbine‐specific effects such as the wind turbine control or the dynamic interaction between the loads and the support structure to the presented inverse load calculation procedure. fast is used to study the inverse calculation of simultaneously acting wind and wave loads, which has not been carried out until now. Furthermore, the application of the inverse load calculation procedure to a real 5‐MW wind turbine support structure is demonstrated. In terms of this practical application, setting up the mechanical system for the support structure using measurement data is discussed. The paper presents results for defined load cases and assesses the accuracy of the inversely derived dynamic loads for both the simulations and the practical application. Copyright © 2017 John Wiley & Sons, Ltd.

Pahn, T.↗
DOE OSTI2018

Beam-Dynamics Analysis of Long-Range Wakefield Effects on the SCRF Cavities at the Fast Facility

Long-range wakefields in superconducting RF (SCRF) cavities create complicated effects on beam dynamics in SCRF-based FEL beamlines. The driving bunch excites effectively an infinite number of structure modes (including HOMs) which oscillate within the SCRF cavity. Couplers with loads are used to damp the HOMs. However, these HOMs can persist for long periods of time in superconducting structures, which leads to long-range wakefields. Clear understanding of the long-range wakefield effects is a critical element for risk mitigation of future SCRF accelerators such as XFEL at DESY, LCLS-II XFEL, and MaRIE XFEL. We are currently developing numerical tools for simulating long-range wakefields in SCRF accelerators and plan to experimentally verify the tools by measuring these wakefields at the Fermilab Accelerator Science and Technology (FAST) facility. This paper previews the experimental conditions at the FAST 50 MeV beamline based on the simulation results.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Particle Strain Analysis of Epoxy-Based Composites Following Quasi-Static and Dynamic Compression

We investigate localized strains in polymer-based composites subjected to varying strain-rates and strains. Research on composites is often focused on their bulk mechanical behavior. However, many material phenomena are influenced by their microstructure, such as the mixing and reaction mechanisms of constituents in structural energetic materials. Therefore, the response of composites at the mesoscale is of clear interest; especially as insight into the micro-deformation and damage, and interaction effects between the constituents at the local level will better inform our understanding of the bulk composite constitutive behavior. To more fully understand the composite mechanical behavior at the mesoscale, uniaxial compression experiments were conducted on epoxy reinforced with aluminum (20 or 40 vol%) and nickel (0 or 10 vol%) particles. Additionally, the particle size of aluminum was either 5 or 50 μm in diameter. Experiments were carried out at quasi-static and dynamic strain rates. Resulting microstructures were analyzed to measure the degree of particle strain and compared to the global material strains for different degrees of strain-rate, strain, and particle size and volume fraction. The aluminum particle strain increased with global strain and had a strong dependency on strain rate. Introducing stiffer nickel particles resulted in larger aluminum particle strains. The nickel particle strain was minimal (< 3%) and showed no dependency with strain rate. This research gives insight into the interactions of particle reinforced composite constituents and their deformation at the mesoscale which is important for understanding phenomena such as preignition mechanisms in structural energetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Stress Field Dynamics and Fault Slip Potential in the Paradox Basin

Abstract The Paradox Basin, straddling Utah, Colorado, Arizona, and New Mexico is characterized by an intricate amalgamation of evaporites and clastic layers and is dominated by prominent salt walls and related subsurface structures. Our research offers a new examination of the stress distribution across the basin, deriving from continuous and discrete stress measurements conducted in boreholes in the region and focal mechanism analysis, emphasizing variations over salt structures. Integrating Coulomb failure criteria with probabilistic methods, we assess potential fault movements resulting from fluid pressure alterations. Our approach provides a comprehensive understanding of the Paradox Basin's state of stress, showing a continuous change of the maximum horizontal stress orientation from N‐S at the Wasatch Fault Zone to WNW‐ESE in the northern part of the Paradox Basin and to WSW‐ENE in the southern part of the basin. Further East, into the Colorado Plateau and the Uncompahgre Uplift, the S H max orientation becomes E‐W. Decoding stress orientation dynamics has enabled critical insights into fault slip potential, especially in the basin's northern region. The salt wall faults are less likely to slip, and the Paradox Formation's evaporite and clastic rock sequence can serve as a potential low seismic risk target for carbon storage and hydrocarbon extraction.

Geochemistry & Geophysics↗
DOE OSTI2022

Conical intersection and coherent vibrational dynamics in alkyl iodides captured by attosecond transient absorption spectroscopy

The photodissociation dynamics of alkyl iodides along the C–I bond are captured by attosecond extreme-ultraviolet (XUV) transient absorption spectroscopy employing resonant ∼20 fs UV pump pulses. The methodology of previous experiments on CH3I [Chang et al., J. Chem. Phys. 154, 234301 (2021)] is extended to the investigation of a C–I bond-breaking reaction in the dissociative A-band of C2H5I, i-C3H7I, and t-C4H9I. Probing iodine 4d core-to-valence transitions in the XUV enables one to map wave packet bifurcation at a conical intersection in the A-band as well as coherent vibrations in the ground state of the parent molecules. Analysis of spectroscopic bifurcation signatures yields conical intersection crossing times of 15 ± 4 fs for CH3I, 14 ± 5 fs for C2H5I, and 24 ± 4 fs for i-C3H7I and t-C4H9I, respectively. Observations of coherent vibrations, resulting from a projection of A-band structural dynamics onto the ground state by resonant impulsive stimulated Raman scattering, indirectly reveal multimode C–I stretch and CCI bend vibrations in the A-bands of C2H5I, i-C3H7I, and t-C4H9I.

Chang, Kristina F. (ORCID:000000022315039X)↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends with Washed and Unwashed Legacy Coals and Other Waste Fuels to Generate White Hydrogen

The objective of this effort, primarily funded by the United States Department of Energy (DOE), and led by the Electric Power Research Institute, Inc. (EPRI), with support by Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), has been to qualify coal, biomass, and plastic waste blends based on performance testing of selected fuel pellet compositions in a pilot-scale updraft moving-bed (UDMB) gasifier. The testing provided relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are the focus. The gasifier used for testing is HMI’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips (biomass). However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The three feedstocks were densified and pelletized by California Pellet Mill (CPM) to meet the feedstock size required by Sotacarbo’s 30mm ID UDMB gasifier, under contract to HMI. The technical tasks and results from this two-year research project included: (1) Feed Procurement and Preparation: Nine different tri-fuel pellets were prepared from varying compositions of fresh mined PRB coal, corn stover biomass, and car fluff waste plastics. Tri-fuel pellets were produced by CPM and shipped to Sotacarbo’s test facility in Carbonia, Sardinia, Italy. (2) Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different UDMB gasification tests to be performed in Sotacarbo’s 12-inch ID pilot scale gasifier, the process monitoring instrumentation used, and the extractive samples recovered for analysis of the total gasification process mass and energy balance. (3) Gasifier Testing: Nine different gasification runs were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstock compositions generated from varying mixtures of PRB coal, biomass, and plastic wastes. The testing generated performance data on gasification reaction efficiency and performance, yielding relevant data for models used to scale up the gasifier design. This task also included work to refurbish and reassemble the pilot gasifier at Sotacarbo and perform a baseline 100% PRB coal run. (4) Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results are reported in the project’s final report, published in March 2024. The results show that all tri-fuel pellets gasified well and maintained structural integrity throughout the gasification process. The syngas generated can be shifted to hydrogen by using commercial syngas shifting technologies. (5) High Fidelity computational fluid dynamics (CFD) Simulation: The National Energy Technology Laboratory (NETL) team performed CFD simulations of the UDMB gasifier for two of the tri-fuel pellets gasified in Sotacarbo’s pilot scale gasifier. The kinetic mechanisms for the pyrolysis of each constituent, PRB coal, corn stover biomass, and waste plastics are based on thermogravimetric analysis performed by Sotacarbo. The gasification model was validated by comparing the predicted syngas composition at the exit of the gasifier with the measured syngas composition. In addition, the reactor’s measured internal temperature profile agreed well with the predicted internal reactor temperature profile. These results validate that the model can be used to predict the performance of the updraft moving bed gasifier for different feedstocks and operating conditions. This paper summarizes the results of the completed work in which the pelletizing procedure was validated to ensure the viability of the tri-fuel pellets for the gasification runs performed at Sotacarbo’s 30 mm UDMB gasifier. The gasification performance data from this series of nine runs will enable modeling of a full-scale HMI industrial scale gasifier supporting both combined heat and power, and Hydrogen production from coal (both fresh mined and legacy) combined with various biomass and waste plastics. Additionally, plans and progress on a follow-up project, being executed by the same project team, will be presented. In this project, a total of twenty (20) different feedstocks are being prepared from varying compositions of biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste, and refuse-derived fuel (RDF). The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design to 50 megawatt electric (MWe) (equivalent hydrogen production). Tests will also be performed on a bench-scale fluidized-bed gasifier for comparison purposes. The results of this testing will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends.

08 HYDROGEN↗
DOE OSTI2014

Effects of q-profile structure on turbulence spreading: A fluctuation intensity transport analysis

This paper studies effects of q-profile structure on turbulence spreading. It reports results of numerical experiments using global gyrokinetic simulations. We examine propagation of turbulence, triggered by an identical linear instability in a source region, into an adjacent, linearly stable region with variable q-profile. The numerical experiments are designed so as to separate the physics of turbulence spreading from that of linear stability. The strength of turbulence spreading is measured by the penetration depth of turbulence. Dynamics of spreading are elucidated by fluctuation intensity balance analysis, using a model intensity evolution equation which retains nonlinear diffusion and damping, and linear growth. It is found that turbulence spreading is strongly affected by magnetic shear s, but is hardly altered by the safety factor q itself. There is an optimal range of modest magnetic shear which maximizes turbulence spreading. For high to modest shear values, the spreading is enhanced by the increase of the mode correlation length with decreasing magnetic shear. However, the efficiency of spreading drops for sufficiently low magnetic shear even though the mode correlation length is comparable to that for the case of optimal magnetic shear. The reduction of spreading is attributed to the increase in time required for the requisite nonlinear mode-mode interactions. The effect of increased interaction time dominates that of increased mode correlation length. Our findings of the reduction of spreading and the increase in interaction time at weak magnetic shear are consistent with the well-known benefit of weak or reversed magnetic shear for core confinement enhancement. Weak shear is shown to promote locality, as well as stability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Identifying structural changes with unsupervised machine learning methods

In this work, unsupervised machine learning methods are used to identify structural changes using the melting point transition in classical molecular dynamics simulations as an example application of the approach. Dimensionality reduction and clustering methods are applied to instantaneous radial distributions of atomic configurations from classical molecular dynamics simulations of metallic systems over a large temperature range. Principal component analysis is used to dramatically reduce the dimensionality of the feature space across the samples using an orthogonal linear transformation that preserves the statistical variance of the data under the condition that the new feature space is linearly independent. From there, k-means clustering is used to partition the samples into solid and liquid phases through a criterion motivated by the geometry of the reduced feature space of the samples, allowing for an estimation of the melting point transition. This pattern criterion is conceptually similar to how humans interpret the data but with far greater throughput, as the shapes of the radial distributions are different for each phase and easily distinguishable by humans. The transition temperature estimates derived from this machine learning approach produce comparable results to other methods on similarly small system sizes. These results show that machine learning approaches can be applied to structural changes in physical systems.

42 ENGINEERING↗
DOE OSTI2013

Oblique shock structures formed during the ablation phase of aluminium wire array z-pinches

A series of experiments has been conducted in order to investigate the azimuthal structures formed by the interactions of cylindrically converging plasma flows during the ablation phase of aluminium wire array Z pinch implosions. These experiments were carried out using the 1.4 MA, 240 ns MAGPIE generator at Imperial College London. The main diagnostic used in this study was a two-colour, end-on, Mach-Zehnder imaging interferometer, sensitive to the axially integrated electron density of the plasma. The data collected in these experiments reveal the strongly collisional dynamics of the aluminium ablation streams. The structure of the flows is dominated by a dense network of oblique shock fronts, formed by supersonic collisions between adjacent ablation streams. An estimate for the range of the flow Mach number (M = 6.2-9.2) has been made based on an analysis of the observed shock geometry. Combining this measurement with previously published Thomson Scattering measurements of the plasma flow velocity by Harvey-Thompson et al.[Physics of Plasmas 19, 056303 (2012)] allowed us to place limits on the range of the ZT{sub e} of the plasma. The detailed and quantitative nature of the dataset lends itself well as a source for model validation and code verification exercises, as the exact shock geometry is sensitive to many of the plasma parameters. Comparison of electron density data produced through numerical modelling with the Gorgon 3D MHD code demonstrates that the code is able to reproduce the collisional dynamics observed in aluminium arrays reasonably well.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Implementation of a generalized coherent elastic scattering formulation for thermal neutron scattering analysis - 14487

The scattering interactions of thermal neutrons in matter are classified into inelastic and elastic components. In crystalline materials, coherent elastic scattering represents a dominant form of interaction. Traditionally, the treatment of this interaction in standard computer codes (e.g., the LEAPR module of the NJOY code system) was performed within the cubic approximation and restricted the analyst to a few materials that were hardwired into the code. In general, these restrictions can hinder the production of ENDF style thermal neutron scattering libraries for new materials outside the current portfolio of treated materials. In this work, a general formulation based on the exact theory of coherent elastic scattering was developed. This formulation is capable of processing the crystalline structure of any material. The cubic approximation is relaxed by accounting for the partial forces from asymmetric crystal structures in the calculation. The atom sites approximation is relaxed by utilizing a site-wise Debye-Waller factor. Specifically, the Debye-Waller factor is no longer regarded as a uniform constant across the crystal but treated as a matrix tensor that uses the integral of the partial phonon density of states. Therefore, the calculation of the coherent elastic scattering cross section is executed by applying the matrix-form of the Debye-Waller factor on each reciprocal space point and summing them up. Furthermore, the developed algorithm supports compounds with any number of elements and of any ratio to each other. This general formulation was successfully implemented and contributed to the production of ENDF style thermal neutron scattering libraries for silicon dioxide (α-SiO{sub 2}) and silicon carbide (3C-SiC). The needed input for the analysis was generated using density functional theory (DFT) atomistic simulations and dynamical matrix calculations for both materials. (authors)

42 ENGINEERING↗
DOE OSTI2019

Estimation of conductivity for nanoporous materials

Methods and systems for estimating conductivity of clay mineral systems, and for applying the estimates in larger-scale analysis. Conductivity of the clay may be estimated by constructing a molecular model of an anhydrous charge-neutral clay, and then assigning a charge density by substitution of ions in the model of the clay structure. Counterions are inserted for charge neutrality, and water molecules are added to the model to reflect a selected level of hydration. Following assignment of force-field coefficients, molecular dynamics simulation provides data from which diffusion coefficients can be estimated. Application of the Nernst-Einstein relationship to the diffusion coefficients of the counterions provides the ion conductivity of the clay system. This conductivity can be used to derive a formation factor, and can be applied in direct numerical simulation analysis.

58 GEOSCIENCES↗
DOE OSTI2016

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculations are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗
DOE OSTI2021

Revealing meso-structure dynamics in additive manufacturing of energy storage via operando coherent X-ray scattering

3D printing is an emerging technology for the fabrication of energy storage devices, offering advantages over traditional manufacturing methods. However, optimization and design of such devices requires an understanding of the meso-structure formation during the 3D printing process. This study utilizes operando coherent X-ray scattering, X-ray Photon Correlation Spectroscopy (XPCS), to study the spatiotemporally-resolved far-from-equilibrium dynamics during direct ink writing 3D printing. Here, Lithium Titanate (LTO) based ink is prepared and rheologically tested for its shear-thinning properties. Two-time intensity-intensity functions are calculated to be used in subsequent quantitative analysis, which allows for an overall characterization of the dynamics, description of an initial fast decorrelation and identification of sudden rearrangements of subdomains of the sample. The results show the dynamics to be anisotropic, spatiotemporally heterogenous and marked by distinct rearrangement events, all of which impact the electrochemical performance of energy storage devices. The studied 3D printing ink is used to fabricate electrodes which are then electrochemically tested, showing good performance in cycling and retaining structural integrity. This work furthers the understanding of the far-from-equilibrium material dynamics during 3D printing, giving quantitative characterization of this process, and highlights aspects of structure formation relevant to the electrochemical performance of the resultant energy storage device.

36 MATERIALS SCIENCE↗
DOE OSTI2024

INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Intermetallic phase formation in Al-Si-Zr alloys during hot isostatic pressing revealed by experiments and molecular dynamics

Understanding phase transformations at alloy interfaces is critical for the design of advanced structural materials. Here, in this study, we investigate the formation mechanisms of the Al 2 SiZr intermetallic phase in the Al-Si-Zr system under hot isostatic pressing (HIP) using molecular dynamics (MD) simulations and thermodynamic analysis. A unique aspect of our approach in MD involves the replacement of a disordered Al 2 SiZr stoichiometry with an ordered phase at the Al-Zr interface once HIP results in the desired Al 2 SiZr stoichiometry, allowing us to compute the total energetic cost of transformation by accounting for both formation energies and diffusion barriers. Diffusion coefficients and activation energies, extracted across a range of temperatures, reveal that HIP substantially enhances atomic mobility, creating favorable stoichiometry for phase evolution. Our results show that Al 2 SiZr phase formation is kinetically unfavorable at lower temperatures but becomes feasible when the thermodynamic driving energy surpass a critical energy threshold.

Roy, Ankit [Pacific Northwest National Laboratory ↗