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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Contact patterns in wild pigs ( Sus scrofa ) from GPS tracking reveal spatial and temporal dynamics of social behaviour

Wild pig ( Sus scrofa Linnaeus, 1758) social behaviour affects disease transmission and landscape-level population management. Recent research has incorporated analysis of social structure to better understand the risk of disease transmission in wild pigs, although the relationship between overall social structure of wild pigs remains unclear. Here, we seek to improve understanding of the spatial and temporal dynamics of wild pig social structure and contact rates to better inform management strategies. Using GPS tracking data, we measured home range overlap, and estimated contact rates of wild pigs at four study sites in the southern USA to identify pairwise social associations (i.e., contacts) based on synchronous movement. Contact rate was strongly associated with home range overlap, but exhibited substantial variation, especially at moderate levels of home range overlap. We found that female–female dyads had higher contact rates and longer duration phases of social association compared to female–male and male–male dyads. We found male–male dyads tended to experience social associations farther from their home range centers than female–female or female–male dyads. Social associations between wild pig dyads are highly dynamic in their spatial and temporal structure. Further, dyads with strong social associations still experience substantial time apart. Our findings highlight the challenges of predicting spatial and social associations in wild pig social pairs due to their dynamic social structure over space and time.

McIlraith, Jack R.↗
DOE OSTI2021

Digital Image Correlation as an Experimental Modal Analysis Capability

Digital image correlation (DIC) is an established test technique in several fields including quasi-static displacement measurements. Recently there has been growing interest in using DIC to measure structural dynamic response and even extract modal parameters from that information. Although high-speed cameras have become more ubiquitous, there are no commercial end-to-end packages for modal analysis based on image data, particularly when combined with traditional data acquisition systems. As such, the practitioner is left to develop several key data processing capabilities, hardware interface equipment, and testing practices themselves. This work highlights several practical aspects that have been encountered while establishing DIC as a viable modal testing capability in a laboratory environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Topological Analysis of Temporal Hypergraphs

In this work we study the topological properties of temporal hypergraphs. Hypergraphs provide a higher dimensional generalization of a graph that is capable of capturing multi-way connections. As such, they have become an integral part of network science. A common use of hypergraphs is to model events as hyperedges in which the event can involve many elements as nodes. This provides a more complete picture of the event in comparison to the standard dyadic connection limitation of a graph. However, a common attribution to events is temporal information as an interval for when the event occurred. Consequently, a temporal hypergraph is born which accurately captures both the temporal information of events as well as their multi-way connections. Common tools for studying these temporal hypergraphs typically use summary statistics of snapshots from a sliding window procedure to capture changes in the underlying dynamics. However, these do not provide insight into how the changing structure of the hypergraph evolves and which components of the temporal hypergraph persist and are influential to the underlying system. To alleviate this need we leverage zigzag persistence from the field of Topological Data Analysis (TDA) to study the change in topological structure of time-evolving hypergraphs. We apply our pipeline to both a cyber security and social network dataset and show how the topological structure of their temporal hypergraphs change and can be used to understand the underlying dynamics.

hypergraphs, topological data analysis, zigzag per↗
DOE OSTI2023

Aeroelastic Analysis Using Deforming Cartesian Grids

Ongoing work in air-vehicle design illustrates the potential of advanced concepts to provide significant improvements in efficiency; but with their incorporation of lightweight flexible structures, such configurations may require active control systems to ensure reliability and safety. However, many contemporary analysis methods are inefficient for aeroelastic analysis and design of such configurations. This paper describes the development of a new approach that automates the geometry setup, mesh generation, and assembly of fluid–structural coupling interfaces to enable efficient aeroelastic and aeroservoelastic analysis of advanced concepts. The core elements for this approach are a cut-cell Cartesian grid-based computational fluid dynamics solver, a nonlinear beam element structural model, a conservative fluid–structural interface treatment, and the formulation and implementation of a new deforming grid capability within the cut-cell Cartesian grid solver. In this paper, emphasis is on this latter component with detailed description given of the mesh motion strategy, evaluation of fluxes and structural loads at the surface, and computation of geometrical properties such as cell volume, directed face areas, centroids, and motion-induced fluxes for deforming Cartesian grids required to advance the flow states. Aeroelastic simulations exercising the capability show favorable agreement with data and predictions in the literature for subsonic and supersonic applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A new paradigm in electron microscopy: Automated microstructure analysis utilizing a dynamic segmentation convolutional neutral network

Over the past half century, the transmission electron microscope enabled insight into the fundamental arrangements and structures of materials. State-of-the-art electron microscopes can acquire large image datasets across multiple imaging modalities. However, the manual annotation process for feature or defect quantification may not be feasible with the modern microscope. Convolutional neural networks emerged to characterize individual microstructural features from an image in a cost-effective, consistent manner. However, many of these neural network approaches rely on thousands to hundreds of thousands of manual annotations of each feature type across hundreds of images to train the network for adequate performance. This work focused on the development and application of a pixel-wise defect detection machine-learning dynamic segmentation convolutional neural network with associated automated acquisition and postprocessing to identify microstructural features rapidly and quantitatively from a small initial dataset incorporating multiple imaging modes. The approach was demonstrated for characterization of superalloy 718 from both single image acquisition on multiple detectors to in-situ evolution captured with a single detector on a standard desktop computer to demonstrate the low barrier to entry required for widespread adoption. Pixel-by-pixel class identification was excellent with strong identification of chemically distinct phases, structurally distinct phases, and defect structures, thus demonstrating the new paradigm of machine learning-assisted characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lattice Structure and Dynamics of Sparse Molecular Crystals: OsO 4 and RuO 4

OsO 4 and RuO 4 are molecular oxides with unique tetrameric structures and rare +8 oxidation states. Accurately modeling their properties remains challenging for density functional theory (DFT) due to weak intertetramer interactions, which standard functionals fail to capture. Here, in this work, we show that the van der Waals (vdW)-corrected density functional (vdW-DF-optB86b) provides structural parameters that are much closer to experimental values than the standard generalized gradient approximation, with volume predictions that fall within the experimentally observed range. Phonon band structure analysis shows that the inclusion of vdW interactions stabilizes soft phonon modes, highlighting the importance of dispersion corrections for accurate predictions of lattice dynamics. Experimental measurements of the phonon density of states for OsO 4 , obtained via inelastic neutron scattering, demonstrate good agreement with our vdW-DF-optB86b calculations. These results validate OsO 4 and RuO 4 as valuable benchmarks for structural and vibrational calculations via vdW-corrected DFT methods and offer insights for studying the broader class of sparse molecular materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Molecular-Dynamics Analysis of the Mechanical Behavior of Plasma-Facing Tungsten

We report a systematic computational analysis of the mechanical behavior of plasma-facing component (PFC) tungsten focusing on the impact of void and helium (He) bubble defects on the mechanical response beyond the elastic regime. Specifically, we explore the effects of porosity and He atomic fraction on the mechanical properties and structural response of PFC tungsten, at varying temperature and bubble size. We find that the Young modulus of defective tungsten undergoes substantial softening that follows an exponential scaling relation as a function of matrix porosity and He atomic content. Beyond the elastic regime, our high strain rate simulations reveal that the presence of nanoscale spherical defects (empty voids and He bubbles) reduces the yield strength of tungsten in a monotonically decreasing fashion, obeying an exponential scaling relation as a function of tungsten matrix porosity and He concentration. Our detailed analysis of the structural response of PFC tungsten near the yield point reveals that yielding is initiated by emission of dislocation loops from bubble/matrix interfaces, mainly 1/2<111> shear loops, followed by gliding and growth of these loops and reactions to form <100> dislocations. Furthermore, dislocation gliding on the <111>{211} twin systems nucleates 1/6<111> twin regions in the tungsten matrix. These dynamical processes reduce the stress in the matrix substantially. Subsequent dislocation interactions and depletion of the twin phases via nucleation and propagation of detwinning partials lead the tungsten matrix to a next deformation stage characterized by stress increase during applied straining. Furthermore, our structural analysis reveals that the depletion of twin boundaries (areal defects) is strongly impacted by the density of He bubbles at higher porosities. After the initial stress relief upon yielding, increase in the dislocation density in conjunction with decrease in the areal defect density facilitates the initiation of dislocation-driven deformation mechanisms in the PFC crystal.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Molecular-based analysis of nanoparticle solvation: Classical density functional approach

Proper statistical mechanics understanding of nanoparticle solvation processes requires an accurate description of the molecular structure of the solvent. Achieving this goal with standard molecular dynamics (MD) simulation methods is challenging due to large length scales. An alternative approach to this problem can be formulated using classical density functional theory (cDFT), where a full configurational description of the positions of all the atoms is replaced by collective atomic site densities in the molecule. Using an example of the negatively charged silica-like system in an aqueous polar environment represented by a two-site water model, we demonstrate here that cDFT can reproduce MD data at a fraction of the computational cost. An important implication of this result is the ability to understand how the solvent molecular features may affect the system’s properties at the macroscopic scale. A concrete example highlighted in this work is the analysis of nanoparticle interactions with sizes of up to 100 nm in diameter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Temperature Evolution of the Activation Barriers Leads to Meyer−Neldel Rules for Structural Relaxation and Transport in Polymers

Understanding activation barriers controlling structural relaxation in glass-forming liquids, molecular transport, and ionic conductivity in amorphous polymers is a grand challenge of fundamental scientific and materials engineering interest across disciplines. Over decades, intriguing but puzzling empirical correlations between the elementary time scale of activated barrier crossing and the apparent Arrhenius activation energy, the so-called Meyer−Neldel (MN) rules, have been discovered in diverse liquids and glasses. Here, in this study, we formulate and successfully apply a new experimental analysis and an explicitly dynamical theoretical framework which provides an understanding of the origin, validity, and failure of such correlations, that bridge and unify the three fields of structural relaxation, molecular transport, and ionic conductivity in liquids and quenched glasses. Distinct quasi-universal laws are predicted in equilibrated liquids and nonequilibrium glasses, consistent with experiments. Our analysis reveals that even if the relaxation appears Arrhenius over a limited temperature range, the physical activation barrier is generally temperature-dependent in polymeric systems even below glass transition temperature. In addition, we show that the approximate validity of classical MN rules hinges on a linear temperature dependence of this barrier and the temperature range probed in experiments. Our findings are relevant for controlling the activation barrier in functional soft polymeric materials relevant to molecular separations, barrier coatings, and charge transport, and also provide new constraints on the theoretical understanding of the mechanism underlying slow activated dynamics in glass-forming condensed matter.

Meyer-Neldel rules↗
DOE OSTI2025

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – /c+ ∥ a 2 – /c – , stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + /c + ∥ a 2 – /c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. Here, this microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

automated scanning probe microscopy↗
DOE OSTI2020

Observations of grain-boundary phase transformations in an elemental metal

The theory of grain boundary (the interface between crystallites, GB) structure has a long history 1 and the concept of GBs undergoing phase transformations was proposed 50 years ago 2,3 . The underlying assumption was that multiple stable and metastable states exist for different GB orientations 4,5,6 . The terminology ‘complexion’ was recently proposed to distinguish between interfacial states that differ in any equilibrium thermodynamic property 7 . Different types of complexion and transitions between complexions have been characterized, mostly in binary or multicomponent systems 8,9,10,11,12,13,14,15,16,17,18,19 . Simulations have provided insight into the phase behaviour of interfaces and shown that GB transitions can occur in many material systems 20,21,22,23,24 . However, the direct experimental observation and transformation kinetics of GBs in an elemental metal have remained elusive. In this work we demonstrate atomic-scale GB phase coexistence and transformations at symmetric and asymmetric $[11\bar{1}]$ tilt GBs in elemental copper. Atomic-resolution imaging reveals the coexistence of two different structures at Σ19b GBs (where Σ19 is the density of coincident sites and b is a GB variant), in agreement with evolutionary GB structure search and clustering analysis 21,25,26 . We also use finite-temperature molecular dynamics simulations to explore the coexistence and transformation kinetics of these GB phases. Our results demonstrate how GB phases can be kinetically trapped, enabling atomic-scale room-temperature observations. Our work paves the way for atomic-scale in situ studies of metallic GB phase transformations, which were previously detected only indirectly 9,15,27,28,29 , through their influence on abnormal grain growth, non-Arrhenius-type diffusion or liquid metal embrittlement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring the Genetic Basis of Wild Boar ( Sus scrofa ) and Its Connection to Classical Swine Fever Spread

Classical swine fever (CSF) is the one of the most devastating contagious diseases in domestic swine and wild boar/pigs (Sus scrofa). Population genetics is often used to estimate animal dispersal and can also help evaluate host population connectivity, which is crucial for understanding pathogen dispersal. We surveyed genetic population structure of boars using MIG-seq analysis to clarify the geographic barriers that influence boar dispersal in north-central Japan and to demonstrate the relationship between the spread of CSF infection among boars and their population structure. We obtained 382 single-nucleotide polymorphisms from 348 wild boar samples, and the results of STRUCTURE analysis indicated that the highest ΔK value was at K = 2, followed by K = 4. Based on these results, it is evident that the Abukuma river, a major river within north-central Japan, does not act as a barrier to the gene flow of boars, but rather that human infrastructure hinders their dispersal. Further, according to the time series change in the capture site of CSF-infected wild boar and the sum of the probability of belonging to each of the four clades in individual CSF-infected wild boar, our results indicated that the genetic structure of boar populations was correlated with the outbreak pathway of CSF across our study region. Our study suggests that predictions of disease spread, especially for widely distributed host species, is challenging because of the risk of cryptic breaks and changes in wide range connectivity; however, understanding the genetic population structure of wild boar can be a useful tool for predicting the spread of CSF. We concluded that genetic analysis of host population structure may have the possibility to improve predictions of the future dynamics of disease spread.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Adaptive Recovery Model: Designing Systems for Testing Tracing and Vaccination to Support COVID-19 Recovery Planning.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Multi-Tiered Estimation for Correlation Spectroscopy in 3D (MTECS3D) v0.1

This innovative software estimates rotational diffusion coefficients of particles from X-ray photon correlation spectroscopy (XPCS) data of monodispersed particle systems. It is the first method capable of extracting rotational diffusion information from three-dimensional particle systems using XPCS. Using the angular-temporal cross-correlation of the XPCS images, this software is able to estimate the rotational diffusion coefficients with only a few percent relative errors while requiring minimal prior knowledge of particle structures. This software enhances XPCS analysis capabilities, allowing researchers to study translational and rotational Brownian dynamics of particles in suspension across various temporal and spatial scales.

Hu, Zixi↗
DOE OSTI2021

Recent Advances in Small Angle X-ray Scattering for Superlattice Study

Small-angle x-ray scattering is used for the structure determination of superlattice for its superior resolution, nondestructive nature, and high penetration power of x rays. With the advent of high brilliance x-ray sources and innovative computing algorithms, there have been notable advances in small angle x-ray scattering analysis of superlattices. High brilliance x-ray beams have made data analyses less model-dependent. Additionally, novel data acquisition systems are faster and more competitive than ever before, enabling a more accurate mapping of the superlattices' reciprocal space. Fast and high-throughput computing systems and algorithms also make possible advanced analysis methods, including iterative phasing algorithms, non-parameterized fitting of scattering data with molecular dynamics simulations, and the use of machine learning algorithms. As a result, solving nanoscale structures with high resolutions has become an attainable task. In this review, we highlight new developments in the field and introduce their applications for the analysis of nanoscale ordered structures, including nanoparticle supercrystals, nanoscale lithography patterns, and supramolecular self-assemblies. Particularly, we highlight the reciprocal space mapping techniques and the use of iterative phase retrieval algorithms. We also cover coherent-beam-based small angle x-ray scattering techniques such as ptychography and ptycho-tomography in view of the traditional small angle x-ray scattering perspective.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create

A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Emerging Electrochemical Techniques for Probing Site Behavior in Single-Atom Electrocatalysts

Single-atom catalysts (SACs) have aroused tremendous interest over the past decade, particularly in the community of energy and environment-related electrocatalysis. A rapidly growing number of recent publications have recognized it as a promising candidate with maximum atomic utilization, distinct activity, and selectivity in comparison to bulk catalysts and nanocatalysts. However, the complexity of localized coordination environments and the dispersion of isolated sites lead to significant difficulties when it comes to gaining insight into the intrinsic behavior of electrocatalytic reactions. Furthermore, the low metal loadings of most SACs make conventional ensemble measurements less likely to be accurate on the subnanoscale. Thus, it remains challenging to probe the activity and properties of individual atomic sites by available commercial instruments and analytical methods. In spite of this, continuing efforts have lately focused on the development of advanced measurement methodologies, which are very useful to the fundamental understanding of SACs. There have recently been a number of in situ/operando techniques applied to SACs, such as electron microscopy, spectroscopy, and other analysis methods, which support relevant functions to identify the active sites and reaction intermediates and to investigate the dynamic behavior of localized structures of the catalytic sites. This Account aims to present recent electrochemical probing techniques which can be used to identify single-atomic catalytic sites within solid supports. First, we describe the basic principles of molecular probe methods for the study and analysis of electrocatalytic site behavior. In particular, the in situ probing technique enabled by surface interrogation scanning electrochemical microscopy (SISECM) can measure the active site density and kinetic rate with high resolution. An alternative electrochemical probing technique is further demonstrated on the basis of single-entity electrochemistry, which allows the unique electrochemical imaging of the size and catalytic rate of single atoms, molecules, and clusters. Next, the merits and limitations of different electrochemical techniques are then discussed, along with perspectives for future prospects. Apart from this, we further showcase the powerful capability of emerging electrochemical probing techniques for determining significant effects and properties of SACs for various electrocatalytic reactions, including oxygen reduction and evolution, hydrogen evolution, and nitrate reduction. Overall, electrochemical techniques with atomic resolution have greatly increased opportunities for observing, measuring, and understanding the surface and interface chemistry during energy conversion. In the future, it is anticipated that the development of electrochemical probing techniques will be advanced with innovative perspectives on the behavior and features of SACs. We hope that this Account can contribute in several ways to promoting the fundamental knowledge and technical progress of emerging electrochemical measurements for studying SACs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗