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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 OSTI2020

Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment About Older Adults and COVID-19 Using Machine Learning

Objectives This study examined public discourse and sentiment regarding older adults and COVID-19 on social media and assessed the extent of ageism in public discourse. Methods Twitter data (N = 82,893) related to both older adults and COVID-19 and dated from January 23 to May 20, 2020, were analyzed. We used a combination of data science methods (including supervised machine learning, topic modeling, and sentiment analysis), qualitative thematic analysis, and conventional statistics. Results The most common category in the coded tweets was “personal opinions” (66.2%), followed by “informative” (24.7%), “jokes/ridicule” (4.8%), and “personal experiences” (4.3%). The daily average of ageist content was 18%, with the highest of 52.8% on March 11, 2020. Specifically, more than 1 in 10 (11.5%) tweets implied that the life of older adults is less valuable or downplayed the pandemic because it mostly harms older adults. A small proportion (4.6%) explicitly supported the idea of just isolating older adults. Almost three-quarters (72.9%) within “jokes/ridicule” targeted older adults, half of which were “death jokes.” Also, 14 themes were extracted, such as perceptions of lockdown and risk. A bivariate Granger causality test suggested that informative tweets regarding at-risk populations increased the prevalence of tweets that downplayed the pandemic. Discussion Ageist content in the context of COVID-19 was prevalent on Twitter. Information about COVID-19 on Twitter influenced public perceptions of risk and acceptable ways of controlling the pandemic. Finaly, public education on the risk of severe illness is needed to correct misperceptions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Manipulation and statistical analysis of the fluid flow of polymer semiconductor solutions during meniscus-guided coating

Recent work in structure–processing relationships of polymer semiconductors have demonstrated the versatility and control of thin-film microstructure offered by meniscusguided coating (MGC) techniques. Here, we analyze the qualitative and quantitative aspects of solution shearing, a model MGC method, using coating blades augmented with arrays of pillars. The pillars induce local regions of high strain rates—both shear and extensional—not otherwise possible with unmodified blades, and we use fluid mechanical simulations to model and study a variety of pillar spacings and densities. We then perform a statistical analysis of 130 simulation variables to find correlations with three dependent variables of interest: thin-film degree of crystallinity and transistor field-effect mobilities for charge-transport parallel (Μ para ) and perpendicular (Μ perp ) to the coating direction. Our study suggests that simple fluid mechanical models can reproduce substantive correlations between the induced fluid flow and important performance metrics, providing a methodology for optimizing blade design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Customizable wave tailoring nonlinear materials enabled by bilevel inverse design

Abstract Passive wave transformation via nonlinearity is ubiquitous in settings from acoustics to optics and electromagnetics. It is well known that different nonlinearities yield different effects on propagating signals, which raises the question of “what precise nonlinearity is the best for a given wave tailoring application?” In this work, considering a one-dimensional spring-mass chain connected by polynomial springs (a variant of the Fermi-Pasta-Ulam-Tsingou system), we introduce a bilevel inverse design method which couples the shape optimization of structures for tailored constitutive responses with reduced-order nonlinear dynamical inverse design. We apply it to two qualitatively distinct problems—minimization of peak transmitted kinetic energy from impact, and pulse shape transformation—demonstrating our method’s breadth of applicability. For the impact problem, we obtain two fundamental insights. First, small differences in nonlinearity can drastically change the dynamic response of the system, from severely under- to outperforming a comparative linear system. Second, the oft-used strategy of impact mitigation via “energy locking” bistability can be significantly outperformed by our optimal nonlinearity. We validate this case with impact experiments and find excellent agreement. This study establishes a framework for broader passive nonlinear mechanical wave tailoring material design, with applications to computing, signal processing, shock mitigation, and autonomous materials.

Science & Technology - Other Topics↗
DOE OSTI2026

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗
DOE OSTI2023

$μ$ $\mathrm{SR}$ study of the dipole-octupole quantum spin ice candidate $\mathrm{Ce_2Zr_2O_7}$

The Ce 3+ pseudospin-1/2 degrees of freedom in Ce 2 Zr 2 O 7 possess both dipolar and octupolar character which enables the possibility of novel quantum spin liquid ground states in this material. In this study, we report muon spin relaxation and rotation (μSR) measurements on single-crystal samples of Ce 2 Zr 2 O 7 in zero magnetic field and in magnetic fields directed along the [1, $\overline{1}$, 0] and [1, 1, 1] crystallographic directions, and for magnetic fields directed both longitudinal and transverse to the direction of muon polarization. Our zero-field results show no signs of magnetic ordering or spin freezing, consistent with earlier zero-field μSR measurements on a powder sample of Ce 2 Zr 2 O 7 , and also with the expectations for a quantum spin ice. However, we measure a more gentle relaxation rate for Ce 2 Zr 2 O 7 in zero field at low temperatures than was previously reported. This difference in relaxation rate is likely due to the low oxidation and, correspondingly, the high stoichiometry of our singlecrystal samples. Longitudinal field measurements confirm that the magnetic dipole moments in Ce 2 Zr 2 O 7 remain dynamic at T = 0.1 K on the microsecond timescale. For both [1, $\overline{1}$, 0] and [1, 1, 1] magnetic fields, our μSR Knight shift measurements show a field-induced leveling off of the magnetic susceptibility at low temperature which is qualitatively consistent with corresponding calculations using the numerical-linked-cluster method in combination with recent estimates for the nearest-neighbor exchange parameters of Ce 2 Zr 2 O 7 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

On the Fidelity of Computational Models for the Flow of Milled Loblolly Pine: A Benchmark Study on Continuum-Mechanics Models and Discrete-Particle Models

The upstream of bioenergy industry has suffered from unreliable operations of granular biomass feedstocks in handling equipment. Computational modeling, including continuum-mechanics models and discrete-particle models, offers insightful understandings and predictive capabilities on the flow of milled biomass and can assist equipment design and optimization. This paper presents a benchmark study on the fidelity of the continuum and discrete modeling approaches for predicting granular biomass flow. We first introduce the constitutive law of the continuum-mechanics model and the contact law of the coarse-grained discrete-particle model, with model parameters calibrated against laboratory characterization tests of the milled loblolly pine. Three classical granular material flow systems (i.e., a lab-scale rotating drum, a pilot-scale hopper, and a full-scale inclined plane) are then simulated using the two models with the same initial and boundary conditions as the physical experiments. The close agreement of the numerical predictions with the experimental measurements on the hopper mass flow rate, the hopper critical outlet width, the material stopping thickness on the inclined plane, and the dynamic angle of repose, clearly indicates that the two methods can capture the critical flow behavior of granular biomass. The qualitative comparison shows that the continuum-mechanics model outperforms in parameterization of materials and wall friction, and large-scale systems, while the discrete-particle model is more preferred for discontinuous flow systems at smaller scales. Industry stakeholders can use these findings as guidance for choosing appropriate numerical tools to model biomass material flow in part of the optimization of material handling equipment in biorefineries.

Jin, Wencheng↗
DOE OSTI2023

Water narratives in local newspapers within the United States

Sustainable use of water resources continues to be a challenge across the globe. This is in part due to the complex set of physical and social behaviors that interact to influence water management from local to global scales. Analyses of water resources have been conducted using a variety of techniques, including qualitative evaluations of media narratives. This study aims to augment these methods by leveraging computational and quantitative techniques from the social sciences focused on text analyses. Specifically, we use natural language processing methods to investigate a large corpus (approx. 1.8M) of newspaper articles spanning approximately 35 years (1982–2017) for insights into human-nature interactions with water. Focusing on local and regional United States publications, our analysis demonstrates important dynamics in water-related dialogue about drinking water and pollution to other critical infrastructures, such as energy, across different parts of the country. Our assessment, which looks at water as a system, also highlights key actors and sentiments surrounding water. Extending these analytical methods could help us further improve our understanding of the complex roles of water in current society that should be considered in emerging activities to mitigate and respond to resource conflicts and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fourier-informed knot placement schemes for B-spline approximation

Fitting B-splines to scientific data is especially challenging when the given data contain noise, jumps, or corners. Here, we describe how periodic data sets with these features can be efficiently approximated with B-splines by analyzing the Fourier spectrum of the data. Our method uses a collection of spectral filters to compute high-order derivatives, smoothed versions of noisy data, and the locations of jump discontinuities. Further, these quantities are then combined to choose knots that capture the qualitative features of the data, leading to accurate B-spline approximations with few knots. The method we introduce is direct and does not require any intermediate B-spline fitting before choosing the final knot distribution. Aside from fast Fourier transforms to transfer to and from Fourier space, the method runs in linear time with very little communication. We assess performance on several test cases in one and two dimensions, including data sets with jump discontinuities and noise. These tests show the method fits discontinuous data without spurious oscillations and remains effective in the presence of noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Multiamorphous Phases in Diketopyrrolopyrrole-Based Conjugated Polymers: From Bulk to Ultrathin Films

The glass transition temperature (T g ) of conjugated polymers is a crucial physical parameter that governs their mechanical and electrical properties for applications from sensor technology to skin-like electronics. Despite some well-developed methods that exist for detecting T g of conjugated polymers, there is still a need for the combination of advanced calorimetric methodologies to characterize T g in a broad range of temperatures and scales from bulk to nanometer-thin films. In this work, alternating current (ac) chip calorimetry and flash differential scanning calorimetry (flash DSC) are applied to successfully identify the Tgs and segmental relaxations of conjugated polymers. The detected relaxations were interpreted, in agreement with existing observations in similar systems, as a side-chain relaxation (low temperature), mobile amorphous fractions (MAF), and rigid amorphous fractions (RAF). T g s of MAF and RAF increase and decrease with increasing size of fused thiophene units in the backbone, respectively. The T g s of diketopyrrolopyrrole-based conjugated polymer thin films are also identified by the same method, with both T g s showing a decreased value compared to those of bulk samples. Furthermore, the weight fractions of MAF and RAF with various film thicknesses are qualitatively analyzed based on the heat capacity step of each amorphous fraction during the glass transition. This facile method gives insights into the physical nature of amorphous phases in conjugated polymers for better revealing their structure-property relationships, which will guide the designs of new materials with optimized electrical and mechanical properties in the future.

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

Development and testing of coarse-grained models for ultrasonic simulations of cast austenitic stainless steel

Ultrasonic inspection of cast austenitic stainless steel (CASS) in the nuclear industry is particularly challenging because of sound field scatter and attenuation caused by the coarse-grained microstructure. Modeling and simulation are important tools in ultrasonic testing, as they can be used to help address key aspects of inspections, such as developing new probe designs, predicting inspection reliability, and testing phased-array focal laws. However, developing a useful and reliable CASS model is challenging due to the many grain interfaces and crystalline orientations that must be captured. We demonstrate a method of creating a realistic CASS model that is usable in CIVA, a commercially available modeling and simulation software platform. Using polished and chemically etched sections, we generate models of a coarse-grained equiaxed specimen and a columnar specimen. We also test an alternative method of generating a coarse-grained model using Voronoi regions. We qualitatively compare sound field scatter and quantitatively compare sound field attenuation and beam partitioning in simulated sound fields to those of laboratory-measured sound fields. Results show that the Voronoi models perform as well as or better than the models based on actual grain morphology. Here we also show that model-to-model randomness in Voronoi grain structure can impact the magnitude of a simulated echo response by a factor of two or more. Although CASS models are potentially a good depiction of reality for a given scenario, they should not be considered representative since CASS morphology can change significantly from specimen to specimen or within the same specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The many-body expansion for metals. I. The alkaline earth metals Be, Mg, and Ca

We examine the many-body expansion (MBE) for alkaline earth metal clusters, Be n , Mg n , Ca n ( n = 4, 5, 6), at the Møller–Plesset second order perturbation theory, coupled-cluster singles and doubles with perturbative triples, multi-reference perturbation theory, and multi-reference configuration interaction levels of theory. The magnitude of each term in the MBE is evaluated for several geometrical configurations. We find that the behavior of the MBE for these clusters depends strongly on the geometrical arrangement and, to a lesser extent, on the level of theory used. Another factor that affects the MBE is the in situ (ground or excited) electronic state of the individual atoms in the cluster. For most geometries, the three-body term is the largest, followed by a steady decrease in absolute energy for subsequent terms. Though these systems exhibit non-negligible multi-reference effects, there was little qualitative difference in the MBE when employing single vs multi-reference methods. Useful insights into the connectivity and stability of these clusters have been drawn from the respective potential energy surfaces and quasi-atomic orbitals for the various dimers, trimers, and tetramers. Through these analyses, we investigate the similarities and differences in the binding energies of different-sized clusters for these metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

SnowPac : a multiscale cubic B-spline wavelet compressor for astronomical images

ABSTRACT As more advanced and complex survey telescopes are developed, the size and scale of data being captured grows at increasing rates. Across various domains, data compression through wavelets has enabled the reduction of data size and increase in computation efficiency. In this paper, we provide qualitative and quantitative tests of a new wavelet-based image compression method compared against the current standard for astronomical images. The analysis is improved by making use of state-of-the-art object detection systems to accurately measure the impact of the compression. We find that a combination of lossy wavelet-based methods, efficient quantization, and lossless dictionary compressors can preserve up to 98 per cent of astronomical objects at a 10:1 compression ratio. This significant reduction in file size also preserves astronomical object properties better than existing methods. These methods help further reduce future workloads for image-heavy processing pipelines.

Pulido, Jesus↗
DOE OSTI2021

Computed Tomography Scanning and Geophysical Measurements of the Wabash No.1 Core

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize Mt. Simon core from the Wabash CarbonSAFE project, Wabash No. 1 well. The primary impetus of the work in this report is a collaboration between NETL Research and Innovation Center and the Illinois State Geological Survey at the Prairie Research Institute, University of Illinois Urbana-Champaign in Champaign, Illinois. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/wabash-no-1-well. The Wabash No. 1 well was drilled as part of a U.S. Department of Energy (DOE) funded Carbon Storage Assurance Facility Enterprise field project to assess the feasibility of developing a commercial-scale geological storage complex at the Wabash Valley Resources Integrated Gasification Combined Cycle plant near Terre Haute, Indiana. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. None of the equipment used was suitable for direct visualization of the pore space in fine-grained structures; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy-related examinations traditionally performed at NETL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Field evaluation of semi‐automated moisture estimation from geophysics using machine learning

Geophysical methods can provide three-dimensional (3D), spatially continuous estimates of soil moisture. However, point-to-point comparisons of geophysical properties to measure soil moisture data are frequently unsatisfactory, resulting in geophysics being used for qualitative purposes only. This is because (1) geophysics requires models that relate geophysical signals to soil moisture, (2) geophysical methods have potential uncertainties resulting from smoothing and artifacts introduced from processing and inversion, and (3) results from multiple geophysical methods are not easily combined within a single soil moisture estimation framework. To investigate these potential limitations, an irrigation experiment was performed wherein soil moisture was monitored through time, and several surface geophysical datasets indirectly sensitive to soil moisture were collected before and after irrigation: ground penetrating radar, electrical resistivity tomography (ERT), and frequency domain electromagnetics (FDEM). Data were exported in both raw and processed form, and then snapped to a common 3D grid to facilitate moisture prediction by standard calibration techniques, multivariate regression, and machine learning. A combination of inverted ERT data, raw FDEM, and inverted FDEM data was most informative for predicting soil moisture using a random regression forest model (one-thousand 60/40 training/test cross-validation folds produced root mean squared errors ranging from 0.025–0.046 cm 3 /cm 3 ). This cross-validated model was further supported by a separate evaluation using a test set from a physically separate portion of the study area. Machine learning was conducive to a semi-automated model-selection process that could be used for other sites and datasets to locally improve accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Numerical simulations of liquid jetting with solid inclusions

The dynamics of finite-sized particles in fluids, and their influence on the overall flow, are of great interest across several industrial, environmental, and medical fields. In the context of inkjet printing, the presence of solid inclusions can be either intentional, as in additive manufacturing, or unintentional, as in standard printing processes. These inclusions can strongly impact the jetting process, causing effects such as jet asymmetry, bubble entrapment, and the formation of satellite droplets. Understanding and controlling particle behavior is therefore essential, particularly to predict how and when particles are ejected over multiple jetting cycles. It is therefore critical to develop reliable models that allow for a deeper understanding of the complex interplay between particle and fluid during the whole printing process. To address this, we present a tailored implementation of the Color-Gradient multicomponent Lattice Boltzmann Method for fully resolved three-dimensional (3D) simulations of multicycle liquid jetting with particles. Our method supports realistic parameter settings aligned with industrial inkjet systems, and we provide both qualitative and quantitative validation against experimental data. Additionally, we introduce a simplified model based on the Stokes drag law, in which solid particles are represented as point particles and do not influence the fluid flow. Despite this limitation, the model offers a computationally efficient means to explore the vast parameter space typically encountered in industrial applications, allowing, e.g., identifying critical ejection regions and estimating the number of cycles required for particle release. These qualitative insights are valuable for guiding and complement fully two-way coupled simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Investigating the impact of cloud-radiative feedbacks on tropical precipitation extremes

Abstract Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Anion diffusion in two-dimensional halide perovskites

Commercialization of halide perovskites in the semiconductor industry is hindered by their short-term stability. The instability of perovskites is closely interlinked with ionic diffusion. Historically, attempts to study diffusion in 2D perovskites mostly utilized electrical characterizations, but these characterizations pose a challenge in deconvoluting the impact of device architecture, interlayers, and ionic species. In this Perspective, we focus our attention on simple optical characterizations employed in the literature to investigate halide diffusion in 2D perovskites using lateral and vertical heterostructure platforms. We review the various synthesis techniques used for fabrication of halide perovskite heterostructures and discuss the qualitative and quantitative diffusion studies performed using these platforms. We discuss the numerical methods used to validate and supplement the experimental halide diffusion kinetics. Finally, we highlight the need to conduct further research on the impact of device operating conditions, lattice structure, and vacancy concentration on halide diffusion. Through this Perspective, we aim to emphasize the need of developing a comprehensive understanding of halide diffusion in perovskites for their successful deployment in optoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Photon Doppler velocimetry surface return study for common surface preparations

Photon Doppler velocimetry (PDV) is a ubiquitous diagnostic method in dynamic compression experiments. It typically requires the roughening of the test surface to ensure scattering of the probe light back into the PDV probe at non-normal angles of incidence. Although surface scattering plays an essential role in the quality of PDV data, surface scattering properties for common materials and preparations have not previously been studied with specific relevance to PDV. Here, we present detailed measurements of the bidirectional reflectance distribution function for four different surface preparations (Scotch-Brite hand and drill roughened, ball-rolled, and grit blasted) and four different materials (copper, aluminum, stainless steel, and tantalum). These measurements employ a conventional PDV probe and obtain a diffraction limited angular resolution with 10 pW accuracy and 2.6% repeatability. In addition to scattering data, we employ scattering theory and simulations to accurately emulate the measured data. We also present a straightforward method to derive the average scattering distribution from surface profilometry and observe several qualitative aspects of the scattering data that may help to optimize PDV signals.

42 ENGINEERING↗