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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Versatile Graphitized Carbon Nanofibers in Energy Applications

Graphitized carbon nanofibers (CNFs) are the allotropic forms of carbon that offer exceptional electrical conductivity, high aspect ratio, large surface-to-volume ratio, flexibility, mechanical robustness, and structural stability. These properties render CNFs as useful materials in energy applications, including water electrocatalysis and electrochemical energy storage devices (EESDs). Graphitized CNFs manifest huge versatility in EESDs and have been employed as electrode materials, as supports for other electrode materials, and conductive additives. This perspective summarizes the production methods, structural aspects, and energy applications of graphitized CNFs. Different design strategies have been employed to produce CNFs with diverse and distinct morphologies and structures. Their fabrication methods, along with precursors and dopants or cocatalysts, impact the overall structural, functional, and topographical properties. Recent developments on the state-of-the-art interests of graphitic CNFs in lithium-ion batteries (LIBs), lithium–sulfur (Li–S) batteries, vanadium redox flow batteries (VRFBs), supercapacitors, and water splitting have explored the many possibilities in energy sectors. Finally, the assembly and functioning of CNFs in water splitting and EESDs as well as primary challenges are discussed in this perspective.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An Analytical Solution for the Initiation and Early Progression of Fretting Wear in Spherical Contacts

Abstract This article derives analytical solutions to calculate the wear volume at the initiation of fretting motion and its early progression over the first few oscillation cycles. The Archard-based model considers a deformable hemisphere that is contact with a deformable flat block. The material pairs investigated are special alloys, the Inconel 617/Incoloy 800H, and Inconel 617/Inconel 617. The analytical study begins with a unidirectional frictional sliding contact, where the local interfacial sliding distance and the nominal sliding distance at the initiation of gross slip are derived. The obtained analytical expressions for unidirectional sliding are then used to derive the corresponding wear volume for the initiation and early progression of gross slip and the wear volume for a general fretting cycle under elastic conditions. These analytical derivations are all verified by the finite element analysis (FEA). The FEA method and the analytical solutions render virtually identical results for both similar and dissimilar material pairs. The effects of plasticity on the wear volume under elastic–plastic conditions are also investigated. It is found that the fretting wear volumes obtained from the FEA simulations, which include plasticity, are close to those obtained from the analytical expressions for purely elastic regimes. All the results are presented in normalized forms, which can be easily generalized and applied to three-dimensional fretting wear of other material pairs.

Engineering↗
DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗
DOE OSTI2023

Design Principles for Using Amphiphilic Polymers To Create Microporous Water

Aqueous dispersions of microporous nanocrystals with dry, gas-accessible pores—referred to as “microporous water”—enable high densities of gas molecules to be transported through water. For many applications of microporous water, generalizable strategies are required to functionalize the external surface of microporous particles to control their dispersibility, stability, and interactions with other solution-phase components—including catalysts, proteins, and cells—while retaining as much of their internal pore volume as possible. Here, in this work, we establish design principles for the noncovalent surface functionalization of hydrophobic metal–organic frameworks with amphiphilic polymers that render the particles dispersible in water and enhance their hydrolytic stability. Specifically, we show that block co-polymers with persistence lengths that exceed the micropore aperture size of zeolitic imidazolate frameworks (ZIFs) can dramatically enhance ZIF particle dispersibility and stability while preserving porosity and >80% of the theoretical O 2 carrying capacity. Moreover, enhancements in hydrolytic stability are greatest when the polymer can form strong bonds to exposed metal sites on the external particle surface. More broadly, our insights provide guidelines for controlling the interface between polymers and metal–organic framework particles in aqueous environments to augment the properties of microporous water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Stealthy Cyber Anomaly Detection On Large Noisy Multi-material 3D Printer Datasets Using Probabilistic Models

As Additive Layer Manufacturing (ALM) becomes pervasive in industry, its applications in safety critical component manufacturing are being explored and adopted. However, ALM's reliance on embedded computing renders it vulnerable to tampering through cyber-attacks. Sensor instrumentation of ALM devices allows for rigorous process and security monitoring, but also results in a massive volume of noisy data for each run. As such, in-situ, near-real-time anomaly detection is very challenging. The ideal algorithm for this context is simple, computationally efficient, minimizes false positives, and is accurate enough to resolve small deviations. In this paper, we present a probabilistic-model-based approach to address this challenge. To test our approach, we analyze current measurements from a polymer composite 3D printer during emulated tampering attacks. Our results show that our approach can consistently and efficiently locate small changes in the presence of substantial operational noise.

Yoginath, Srikanth↗
DOE OSTI2023

Scalable Volume Visualization for Big Scientific Data Modeled by Functional Approximation

Considering the challenges posed by the space and time complexities in handling extensive scientific volumetric data, various data representations have been developed for the analysis of large-scale scientific data. Multivariate functional approximation (MFA) is an innovative data model designed to tackle substantial challenges in scientific data analysis. It computes values and derivatives with high-order accuracy throughout the spatial domain, mitigating artifacts associated with zero- or first-order interpolation. However, the slow query time through MFA makes it less suitable for interactively visualizing a large MFA model. In this work, we develop the first scalable interactive volume visualization pipeline, MFA-DVV, for the MFA model encoded from large-scale datasets. Our method achieves low input latency through distributed architecture, and its performance can be further enhanced by utilizing a compressed MFA model while still maintaining a high-quality rendering result for scientific datasets. We conduct comprehensive experiments to show that MFA-DVV can decrease the input latency and achieve superior visualization results for big scientific data compared with existing approaches.

big scientific dataset↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Galaxy mock catalogs for BAO analysis

The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of baryon acoustic oscillation (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey Year 3 BAO sample over its full photometric redshift range 0.6 < zphoto < 1.1. The mocks are based upon 488 ICE-COLA fast N-body simulations of full-sky light cones and were created by populating halos with galaxies, using a hybrid halo occupation distribution – halo abundance matching model. This model has ten free parameters, which were determined, for the first time, using an automatic likelihood minimization procedure. We also introduced a novel technique to assign photometric redshift for simulated galaxies, following a two-dimensional probability distribution with VIMOS Public Extragalactic Redshift Survey data. The calibration was designed to match the observed abundance of galaxies as a function of photometric redshift, the distribution of photometric redshift errors, and the clustering amplitude on scales smaller than those used for BAO measurements. An exhaustive analysis was done to ensure that the mocks reproduce the input properties. Finally, mocks were tested by comparing the angular correlation function w(θ), angular power spectrum Cℓ, and projected clustering ξp(r⊥) to theoretical predictions and data. The impact of volume replication in the estimate of the covariance is also investigated. The success in accurately reproducing the photometric redshift uncertainties and the galaxy clustering as a function of redshift render this mock creation pipeline as a benchmark for future analyses of photometric galaxy surveys.Key words: catalogs / large-scale structure of Universe / galaxies: distances and redshifts / Galaxy: halo / methods: numerical

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Interpreting T-History Data on Supercooling and Phase Change Enthalpy of a Salt-Hydrogel Complex for Building Thermal Management

Phase change materials (PCMs) are promising materials for storing and discharging latent heat in buildings to regulate the thermal environment. Measurement of salt hydrate PCM thermal performance is often challenging because of supercooling and phase segregation. Though differential scanning calorimetry (DSC) has been widely used to measure thermal properties of various phase change materials, DSC uses milligrams of sample and is unrealistic for predicting large-scale materials performance. The T-history method [1], in contrast, handles higher volumes but the analysis typically requires a lumped capacitance assumption. Here, we report and analyze T-History data on a novel salt-hydrogel complex with high viscosity, that renders low Biot number sample preparation extremely challenging. We re-examine the standard T-history method and compared against DSC data in this complex material. We report details of an experimental setup, built with necessary additions to a controlled environmental chamber. We carefully examine the validity of the lumped capacitance assumption and suggest a modified analysis using a computational approach for reliable data. Experimental parameters such as ramp rate and temperature range of the environmental chamber are considered via computational modeling to understand the effect of ramp rate on supercooling [2]. Finally, we report thermal cycling experiments on the salt-hydrogel complex. Our modified approach to measuring supercooling and enthalpy of fusion at large scales is important in better understanding the performance of phase-change materials at scale for building thermal storage. References: [1] Marin, Jose M, Belen Zalba, Luisa F Cabeza, and Harald Mehling. “Determination of Enthalpy Temperature Curves of Phase Change Materials with the Temperature-History Method: Improvement to Temperature Dependent Properties.” Measurement Science and Technology 14, no. 2 (February 1, 2003): 184–89. https://doi.org/10.1088/0957-0233/14/2/305. [2] Safari, A., R. Saidur, F.A. Sulaiman, Yan Xu, and Joe Dong. “A Review on Supercooling of Phase Change Materials in Thermal Energy Storage Systems.” Renewable and Sustainable Energy Reviews 70 (April 2017): 905–19. https://doi.org/10.1016/j.rser.2016.11.272

thermodynamics↗
DOE OSTI2024

A Highly Effective Polysulfide-Trapping Approach for the Development of High Energy Density, Scalable Lithium-Sulfur Batteries

Lithium-sulfur (Li-S) batteries are identified as one of the most promising next-generation battery technologies owing to their high theoretical specific energy, sustainability, and affordability. However, the commercialization of Li-S batteries has been hindered by severe technical challenges, including the lithium polysulfide (PS) dissolution/shuttling effect, a major cause of fast capacity degradation over cycling. We demonstrated that, for the first time, nanolayer polymer coated high surface area porous carbons (NPCs) were coated directly on sulfur electrodes (NPC-S), which led to a high specific capacity of ∼1,600 mAh g −1 approaching the theoretical specific capacity limit in the NPC-S based Li-S batteries. The NPC-S based Li-S batteries maintained their large initial specific capacity gain compared with the Baseline-S based Li-S batteries (control) over extended cycles. A follow-on study indicated that the NPC-S approach is a necessary and critical step to boost the near-theoretical specific capacity while being stabilized over long cycles with a synergistic strategy. Our experimental and computational results suggest that NPC coated on sulfur electrodes provides not only an effective and strong PS-trapping power but also an increased redox reaction kinetics for sulfur ↔ PS’s conversions during battery charge and discharge, rendering the realization of near-theoretical discharge specific capacity in the NPC-S based Li-S batteries. The findings presented in this study may inspire a new, simple, low-cost, and commercially scalable approach, without adding any appreciable dead weight or volume to the batteries, in the effort to tackle the technical challenges facing SOA Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Engineering Self-Assembled Domain Asymmetry in Solvent Vapor Annealed Block Copolymer–Homopolymer Blend Films

Thin-film block copolymer (BCP) self-assembly is a powerful approach to generate highly uniform nanopatterns across large areas, yet the symmetries of these nanopatterns are constrained by the relative volume occupied by each polymer block. Here, we present a conceptually new approach to circumvent this limitation by combining homopolymer (HP) blending with solvent vapor annealing (SVA), demonstrated here for ternary blends of a near-symmetric BCP with athermal, low molar mass HPs. Screening of BCP–HP interactions by a weakly selective solvent promotes entropically driven delocalization of HP throughout both blocks and enables assembly of metastable lamellae for volume fractions as high as 0.78. Subsequent brief thermal annealing induces HPs to withdraw to their enthalpically favored domains, sharpening domain interfaces on a time scale much shorter than pattern coarsening. This renders lamellar nanopatterns with tunable widths that can be transferred to other materials with high fidelity. Furthermore, the persistence of the metastable asymmetric lamellae upon thermal annealing is sensitive to film confinement, as they are preserved in submonolayer films but transition to horizontal cylinders in films more than one monolayer thick. SVA using a strongly selective solvent results in assembled morphologies aligned closely with expectations based on the total polymer blend composition, underscoring the key role of BCP–HP interactions in dictating domain asymmetry. Overall, this work details important principles for using SVA to mediate BCP–HP interactions in thin films, thereby presenting opportunities to engineer pathways for the assembly of well-ordered nanopatterns with designer feature asymmetry for lithographic or nanotexturing applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Chain conformations and phase separation in polymer solutions with varying solvent quality

Molecular dynamics simulations are used to investigate the conformations of a single polymer chain, represented by the Kremer-Grest bead-spring model, in a solution with a Lennard-Jones liquid as the solvent when the interaction strength between the polymer and solvent is varied. Results show that when the polymer-solvent interaction is unfavorable, the chain collapses as one would expect in a poor solvent. For more attractive polymer-solvent interactions, the solvent quality improves and the chain is increasingly solvated and exhibits ideal and then swollen conformations. However, as the polymer-solvent interaction strength is increased further to be more than about twice the strength of the polymer-polymer and solvent-solvent interactions, the chain exhibits an unexpected collapsing behavior. Correspondingly, for strong polymer-solvent attractions, phase separation is observed in the solutions of multiple chains. These results indicate that the solvent becomes effectively poor again at very attractive polymer-solvent interactions. Nonetheless, the mechanism of chain collapsing and phase separation in this limit differs from the case with a poor solvent rendered by unfavorable polymer-solvent interactions. In the latter, the solvent is excluded from the domain of the collapsed chains while in the former, the solvent is still present in the pervaded volume of a collapsed chain or in the polymer-rich domain that phase separates from the pure solvent. Finally, in the limit of strong polymer-solvent attractions, the solvent behaves as a glue to stick monomers together, causing a single chain to collapse and multiple chains to aggregate and phase separate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

YOLO2U-Net: Detection-guided 3D instance segmentation for microscopy

Microscopy imaging techniques are instrumental for characterization and analysis of biological structures. As these techniques typically render 3D visualization of cells by stacking 2D projections, issues such as out-of-plane excitation and low resolution in the z-axis may pose challenges (even for human experts) to detect individual cells in 3D volumes as these non-overlapping cells may appear as overlapping. In this paper a comprehensive method for accurate 3D instance segmentation of cells in the brain tissue is introduced. The proposed method combines the 2D YOLO detection method with a multi-view fusion algorithm to construct a 3D localization of the cells. Next, the 3D bounding boxes along with the data volume are input to a 3D U-Net network that is designed to segment the primary cell in each 3D bounding box, and in turn, to carry out instance segmentation of cells in the entire volume. The promising performance of the proposed method is shown in comparison with current deep learning-based 3D instance segmentation methods.

3D instance segmentation↗
DOE OSTI2026

The Squeezed Bispectrum from CHIME H I Emission and Planck Cosmic Microwave Background Lensing: Current Sensitivity and Forecasts

Line intensity mapping using atomic hydrogen (H I) has the potential to efficiently map large volumes of the Universe if the signal can be successfully separated from overwhelmingly bright radio foreground emission. This motivates cross correlations, to ascertain the cosmological nature of measured H I fluctuations, and to study their connections with galaxies and the underlying matter density field. However, these same foregrounds render the cross correlation with projected fields such as the lensing of the cosmic microwave background (CMB) difficult. Indeed, the correlated Fourier modes vary slowly along the line of sight and are thus most contaminated by the smooth-spectrum radio continuum foregrounds. In this paper, we implement a method that avoids this issue by attempting to measure the nonlinear gravitational coupling of the small-scale 21 cm power from the Canadian Hydrogen Intensity Mapping Experiment (CHIME) with large-scale Planck CMB lensing. This measurement is a position-dependent power spectrum, i.e., a squeezed integrated bispectrum. Using 94 nights of CHIME data between 1.0 < z < 1.3 and aggressive foreground filtering, we find that the expected signal is 5 times smaller than the current noise. We forecast that incorporating the additional nights of CHIME data already collected would enable a signal-to-noise ratio of 3, without any further improvements in filtering for foreground cleaning.

21cm↗
DOE OSTI2024

Tusqh

SAND2025-00675O Tusqh is a software tool that generates cubical meshes in 2D and 3D and computes the homology of these meshes using persistent homology. It includes a grid cell in the output if its volume-fraction is above a selectable threshold, estimated by sampling points within the cell. Tusqh incorporates anti-aliasing algorithms to mitigate grid orientation and scale effects. It is designed for creating finite element meshes for simulations and can be used in various applications such as heat diffusion, mechanical simulations, and computer graphics rendering. The software outputs meshes in an open format compatible with downstream software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗
DOE OSTI2022

Composition-dependent ordering transformations in Pt–Fe nanoalloys

Significance Dynamically understanding the microscopic processes governing ordering transformations has rarely been attained. The situation becomes even more challenging for nanoscale alloys, where the significantly increased surface-area-to-volume ratio not only opens up a variety of additional freedoms to initiate an ordering transformation but also allows for kinetic interplay between the surface and bulk due to their close proximity. We provide direct evidence of the microscopic processes controlling the ordering transformation through the surface–bulk interplay in Pt–Fe nanoalloys and new features rendered by variations in alloy composition and chemical stimuli. These results provide a mechanistic detail of ordering transformation phenomena which are widely relevant to nanoalloys as chemical ordering occurs in most multicomponent materials under suitable environmental bias.

25 ENERGY STORAGE↗
DOE OSTI2025

Design of a High-Pressure Fuel System for Use with Dimethyl Ether

The paper documents the modeling and experimental work on a common rail fuel injection system for Dimethyl Ether, a potential diesel substitute with a low carbon intensity signature. The DME fuel system is deployed on a light duty 2.2L compression ignition engine. The paper describes the injector optimization to shift to higher flows to account for the lower heating value and density of the DME when compared to diesel. The type of the injection system used for the DME application is an advanced rendering of the Common rail noted for a one-piece piston-needle injector construction and a solenoid driven spill valve featuring a pressure balanced poppet. A dedicated high-pressure fuel pump designed to pressurize DME is used. The design results in a fast acting open and close injection event, reduced leakage, with reduced cavitation in the fuel injector volume. Design parameters for system optimization included fill and spill orifices, needle lift, bias spring, and injector hole size. The design model provides good correlation of the instantaneous rates of injection with experiments across a wide range of pressure and injection timings. Proposed performance milestones for the design included similar DME injection duration to the diesel counterpart for same fuel energy injected into the cylinder to retain high engine cycle efficiency. Here, the dedicated DME design provided reduced hydraulic delays of 50%. Tests demonstrated sustained operation at pressures of 1000 bar, with capability to reach 1500bar. Durability tests showed no cavitation-deterioration over a 200-hour test cycle by means of spray imaging and hardware inspection.

De Ojeda, William [WM International Engineering, L↗
DOE OSTI2025

Robotic Assembly of SRF Cavity Pair

Superconducting Radio Frequency (SRF) cavities for particle accelerators require tight tolerances, ultrahigh vacuum, and strict cleanliness during assembly. As in the semiconductor industry, defects such as particles and residues are deleterious to performance, possibly rendering a cavity unfit for use. This problem is addressed primarily through cleanroom assembly during sensitive steps and rigorous chemical processing to prevent and remove such defects. Human workers are often the largest source of contamination, even with proper gowning and practices. The semiconductor industry has long integrated robots in cleanroom operation, but this has not occurred for SRF cavity production; SRF cavities, unlike wafers, are complex shapes, require more hands-on mechanical assembly, and are low-volume production items. At Jefferson Laboratory, a co-operative robot (cobot) has been setup to overcome these problems. Cobots are safe for use alongside human workers and can integrate new tools such as a 3D camera part detection and gripper for item manipulation. Therefore, cobots represent a promising avenue for reducing particulate generated during a variety of assembly tasks. A mockup of a cavity pair and coupler was setup and the cobot programmed to automatically pick up the coupler and place on the mating cavity flange. Particle counting methods were setup to measure human vs cobot assembly particulate generation inside a cavity mockup. Other potential uses will be discussed for further improving SRF cavity assembly steps, where a cobot can replace or assist a human operator, and what potential gains are expected.

Duzik, Adam [Thomas Jefferson National Accelerator↗
DOE OSTI2023

Pressure Transient Analyses and Poroelastic Modeling of Hydraulic Fracture Dilation for Multiple Injections at the Devine Fracture Pilot Site

Our team has conducted electromagnetic (EM) surveys for the past six years to monitor hydraulic-fracture behavior at the Devine Fracture Pilot Site (DFPS). The sub-horizontal orientation of a shallow hydraulic fracture at the DFPS provides uniform access to the fracture area for interrogation and data collection. Ahmadian et al. (2023) suggested a possible correlation between spatiotemporal changes in the flow rate, bottomhole pressure (BHP), and the observed surface recorded electric field at the DFPS. In this paper, we present the development of poroelastic forward models and pressure transient analyses (PTAs) to support the development of a multiphysics inverse model for these EM surveys. First, we conducted PTAs of the shut-in periods after six injections out of 10 to determine the fracture closure pressure (FCP) or the overburden pressure used in a poroelastic fracture reopening model. Second, we developed a finite-element poroelastic model throughout five injection cycles to include the effect of the cumulative injected volumes due to the previous injections on current fracture dilation in the presence of highly permeable unpropped and propped zones adjacent to the cohesive layer that models fracture reopening. Fracture reopening in this poroelastic model is based on a calibrated traction-separation response using the bottomhole pressure collected in two injection campaigns in 2020 and 2022. We used the outcomes of a previous simulation study of the primary hydraulic-fracturing stimulation to define the dimension of an unpropped fracture zone ahead of the propped fracture area. The PTAs led to FCPs consistent with those obtained using the injection data collected at the DFPS in 2020. Further, these analyses showed that at later injections, the fracture closure occurred at a later time with respect to the shut-in time, inferring the effect of cumulative injected volumes in previous injections. The simulation results show that considering the propped and unpropped fracture zones improves our poroelastic model in predicting the injection-well BHP. The numerical simulation results demonstrate a significant excess pore pressure near the fracture because of the preceding formation loadings by the previous injections. The obtained fracture dilation area and fluid pressure distribution provide a basis to improve the development of a multiphysics inverse model. Furthermore, in an iteratively coupled scheme, this pressure distribution can be introduced into EM models to render a holistic view of the causative mechanisms for the surface signal anomalies.

02 PETROLEUM↗