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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Determining the Effects of Neutron Irradiation on the Structural Integrity of Additively Manufactured Heat Exchangers for Very Small Modular Reactor Applications, DOE Final Report (Project # 19-16980)

Auburn University (AU) teamed with the University of Missouri Research Reactor (MURR) and Kansas State University (KSU) to determine how to best use laser-powder bed fusion (L-PBF) additive manufacturing (AM) methods for generating radiation resistant nickel-based superalloys, Inconel alloy 625 and 718, for special purpose reactor (SPR) or very small modular reactor (vSMR) heat-exchangers (HeXs). Compact, conformal, and durable HeXs that are tolerant of extreme environments are needed for supporting the technical maturity of next-generation, portable compact reactors. AM is an enabler for realizing this new wave of HeXs – providing a means to make customizable hot and cold stream architectures with novel flow path geometries (e.g., tortuous channels with non-uniform, asymmetric cross-sections) and reduced layer-to-layer contact resistance (i.e., no separate bonding procedure required). AM further enables a more time/cost efficient means for fabricating SPRs by reducing the number of suppliers required for HeX assembly and allowing for on-site HeX fabrication. The project aim has been to better understand how neutron irradiation affects the microstructure and properties of additively manufactured nickel-based superalloys, to accelerate their safe, reliable use in the modular reactor industry. The major objective was to qualify/quantify the microstructure and microhardness of nickel-based superalloys (including Inconel 718 and 625) additively manufactured via the L-PBF process in the neutron-dosed (irradiated) and non-irradiated states over a course of 3 years. Effects of build orientation during L-PBF and post-AM heat treatments on neutron resistance, microstructure and mechanical properties were also investigated. Neutron damage mechanisms via hardening were characterized. This project combined subject-matter experts in AM, mechanical/microstructure metallic part characterization, and neutron irradiation, as well as unique assets and capabilities at AU and MURR at MU, to ensure project results translated to effectively addressing known gaps in nuclear science and engineering. Parts were fabricated using L-PBF systems readily available at AU. Specimens were then irradiated using MURR facilities; a manipulator equipped hot cell was also used to measure material hardness after dosing. MURR, a 10 MW, light-water nuclear reactor, is the largest, highest powered, highest-flux university owned research reactor in the U.S. The major findings in this project provide evidence that AM can serve as an alternative way to build structural components for future advanced small modular reactors using advanced materials like Inconel 625 (IN625) or Inconel 718 (IN718). After full spectrum neutron irradiation, vertically as-built AM IN625 samples were observed to display better resistance towards radiation-induced-hardening defects relative to traditionally machined metals. A Vickers microhardness tester, using settings of 1 kgf and dwell time of 15 seconds per indentation, was used to measure hardness in this study. The as-built, vertically printed samples experienced 1.2% of radiation hardening vs. 5.25% radiation hardening observed in wrought IN625. Another set of IN625 and IN718 samples were exposed to fast neutron irradiation. It was observed that IN718 showed more resistance towards radiation hardening compared to IN625 samples indicating IN718 had a better performance. Results showed that the IN718 samples experienced less change (-2.5 to 3.24 %) in microhardness. On the other hand, IN625 samples underwent more (0.9 to 7.21%) change in microhardness after fast neutron irradiation. AM IN625 samples were irradiated using an ion (proton) beam in cyclotron. The mechanical properties of AM samples post irradiation were compared with wrought samples. The irradiated region on the samples were tested using nano-hardness indention. It was observed that the beam current and time used in this study generated an annealing effect and thus reduced the hardness of the samples. The sum of the project results provide precious insight into how one may minimize radiation hardening in AM materials while maintaining material property constraints. Results should assist engineers in selecting an appropriate heat treatment for AM nickel-based superalloys for increased radiation resistance. Results should increase confidence levels for adopting AM for building nuclear reactor components which perform the same or better than conventionally manufactured components. Fast neutron irradiation testing provided an accelerated means of obtaining radiation effects without making materials radioactive and difficult to handle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2008

Effects of hand soldering MIL-PRF 55365 tantalum capacitors

Different values of MIL-PRF-55365 tantalum capacitors were subjected to three different types of soldering conditions— Convection Reflow, JPL Standard Hand Soldering, and Optimized Hand Soldering. The electrical parameters for a large number of capacitors of each value were measured before and after thermal soldering stress. The results indicate that tantalum capacitors subjected to convection reflow conditions experience detectable changes in electrical parameters; capacitors subjected to hand solder conditions show reduced changes in electrical parameters when compared to the reflow samples. Optimized hand solder conditions are shown to have a minimal effect on electrical parameters.

Sheldon, Douglas↗
DOE OSTI2014

Influence of La substitution on ferromagnetic properties of lead free Na{sub 0.5}Bi{sub 0.5}Ti{sub 0.988}Fe{sub 0.012}O{sub 3} multiferroic system

To study the effect of La doping and processing temperature, (Na{sub 0.5}Bi{sub 0.5}){sub 1−x}La{sub x}Ti{sub 0.988}Fe{sub 0.012}O{sub 3} (NBLTF) samples have been prepared by sol-gel method by employing two approaches namely with and without mol% excess of Na and Bi. X-ray diffraction analysis confirms the formation of rhombohedral perovskite structure in these samples with minor impurity phases. However, the impurity phases of stochiometric NBLTF samples disappear on increasing the sintering temperature from 650°C to 850°C. On other hand, NBLTF samples prepared with mol% excess of Na and Bi have shown pure perovskite structure only at lower sintering temperature 650°C and also at low concentration of La ∼ 1%. Transmission electron microscope investigation shows nano crystalline formation for all NBLTF samples sintered at 850°C. The enhancement in room temperature ferromagnetism is observed in La doped NBTF samples prepared at 850°C by taking stoichiometric amount of Na and Bi during synthesis.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1974

The application of large numbers of pleasure boats to collect synoptic sea-truth for ERTS-1 overpasses

The author has identified the following significant results. In order to interpret and annotate current circulation and suspended sediment concentration maps derived from ERTS-1 digital tapes, the University of Delaware has been collecting water samples and other data from boats and helicopters. In order to increase the number of samples at the exact time of the ERTS-1 pass over Delaware Bay, pleasure craft were organized to obtain samples of the entire test site. On the ERTS-1 pass of July second, scientists were stationed at three public boat launches along the Bay to hand out sampling packets to interested boaters. The packets contained two litre sampling bottles, a map, data card, and a pen. The boaters were asked to fill the two bottles between 11 and 11:15 a.m., mark their location on the map, and fill out the data card. Forty-nine packets were handed out of which 40 were returned (82%). Only four of the 40 were not in the alloted time range. This gave 36 real time data points covering approximately 30 nautical miles. The samples are being analyzed for sediment concentration, particle size, and salinity. Participating boaters will receive a copy of an ERTS image of the Delaware Bay and a summary report of the project. Because of the success of the project, future use of pleasure boaters is being planned.

Klemas, V.↗
DOE OSTI2023

Predicting SARS-CoV-2 Variant Using Non-Invasive Hand Odor Analysis: A Pilot Study

The adaptable nature of the SARS-CoV-2 virus has led to the emergence of multiple viral variants of concern. This research builds upon a previous demonstration of sampling human hand odor to distinguish SARS-CoV-2 infection status in order to incorporate considerations of the disease variants. This study demonstrates the ability of human odor expression to be implemented as a non-invasive medium for the differentiation of SARS-CoV-2 variants. Volatile organic compounds (VOCs) were extracted from SARS-CoV-2-positive samples using solid phase microextraction (SPME) coupled with gas chromatography–mass spectrometry (GC–MS). Sparse partial least squares discriminant analysis (sPLS-DA) modeling revealed that supervised machine learning could be used to predict the variant identity of a sample using VOC expression alone. The class discrimination of Delta and Omicron BA.5 variant samples was performed with 95.2% (±0.4) accuracy. Omicron BA.2 and Omicron BA.5 variants were correctly classified with 78.5% (±0.8) accuracy. Lastly, Delta and Omicron BA.2 samples were assigned with 71.2% (±1.0) accuracy. This work builds upon the framework of non-invasive techniques producing diagnostics through the analysis of human odor expression, all in support of public health monitoring.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Single Crystal Synthesis and STM Studies of High Temperature Superconductors

This is a final report for the work initiated in September of 1994 under the grant NAG8-1085 - NASA/OMU, on the fabrication of bulk and single crystal synthesis, specific heat measuring and STM studies of high temperature superconductors. Efforts were made to fabricate bulk and single crystals of mercury based superconducting material. A systematic thermal analysis on the precursors for the corresponding oxides and carbonates were carried out to synthesized bulk samples. Bulk material was used as seed in an attempt to grow single crystals by a two-step self flux process. On the other hand bulk samples were characterized by x-ray diffraction, electrical resistivity and magnetic susceptibility, We studied the specific heat behavior in the range from 80 to 300 K. Some preliminary attempts were made to study the atomic morphology of our samples. As part of our efforts we built an ac susceptibility apparatus for measuring the transition temperature of our sintered samples.

Barrientos, Alfonso↗
DOE OSTI2015

The effect of strontium non-stoichiometry on the physical properties of double perovskite Sr{sub 2}FeMoO{sub 6}

We present a detailed study on the effect of strontium non-stoichiometry on the properties of double perovskite Sr{sub 2}FeMoO{sub 6} (SFMO). A citrate route has been used to prepare high quality polycrystalline samples with (2−x)Sr:Fe:Mo (x=0, 0.02, 0.04) and (2+x)Sr:Fe:Mo (x=0.02, 0.04, 0.10) cationic ratios. The strontium deficient samples exhibit a significant decrease in their values of saturation magnetization (Ms), Curie temperature (Tc) and magnetoresistance (MR) compared to the stoichiometric SFMO. On the other hand, the samples prepared with an excess of strontium, respectively those with x=0.02 and 0.04, show remarkably superior magneto–transport characteristics, despite of their increased level of Fe/Mo disorder and somewhat diminished magnetic properties compared to the stoichiometric SFMO. We also show that these samples exhibit superior MR values under low magnetic field and persisting up to temperatures as high as 400 K. - Graphical abstract: Evolution of the magnetization versus temperature under an applied magnetic field of 1000 Oe (left panel) and magnetoresistance versus applied magnetic field at 300 K (right panel) for strontium off-stoichiometric Sr{sub 2}FeMoO{sub 6} samples. - Highlights: • Strontium nonstoichiometric samples of Sr{sub 2}FeMoO{sub 6} are prepared by a citrate route. • The nonstoichiometric samples exhibit an increased Fe/Mo disorder in the structure. • We observed important changes in their magnetic and magnetoresistive properties. • Improved magnetoresistive properties for samples prepared with strontium excess.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Infrared Database for Process Support Materials

Process support materials' compatibility with cleaning processes is critical to ensure final hardware cleanliness and that performance requirements are met. Previous discovery of potential contaminants in process materials shows the need for incoming materials testing and establishment of a process materials database. The Contamination Control Team of the Materials, Processes, and Manufacturing (MP&M) Department at Marshall Space Flight Center (MSFC) has initiated the development of such an infrared (IR) database, called the MSFC Process Materials IR database, of the common process support materials used at MSFC. These process support materials include solvents, wiper cloths, gloves, bagging materials, etc. Testing includes evaluation of the potential of gloves, wiper cloths, and other items to transfer contamination to handled articles in the absence of solvent exposure, and the potential for solvent exposure to induce material degradation. This Technical Memorandum (TM) summarizes the initial testing completed through December 2002. It is anticipated that additional testing will be conducted with updates provided in future TMs.Materials were analyzed using two different IR techniques: (1) Dry transference and (2) liquid extraction testing. The first of these techniques utilized the Nicolet Magna 750 IR spectrometer outfitted with a horizontal attenuated total reflectance (HATR) crystal accessory. The region from 650 to 4,000 wave numbers was analyzed, and 50 scans were performed per IR spectrum. A dry transference test was conducted by applying each sample with hand pressure to the HATR crystal to first obtain a spectrum of the parent material. The material was then removed from the HATR crystal and analyzed to determine the presence of any residues. If volatile, liquid samples were examined both prior to and following evaporation.The second technique was to perform an extraction test with each sample in five different solvents.Once the scans were complete for both the dry transference and the extraction tests, the residue from each scan was interpreted.

Bennett, K. E.↗
DOE OSTI2023

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects’ hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Fallon FORGE: Analogue Outcrop Samples

Compilation of results for mechanical and fluid flow properties of analogue outcrop samples - experimental data for compressional and shear wave velocities, tensile strengths, and compressive strengths. Outcrop location and sample orientation data are documented in a separate csv file.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

National Technology & Engineering Solutions of Sandia, LLC Technical Assistance With Dine College (Final CTAP Report)

Under the CTAP Statement of Work, Sandia was tasked with providing technical assistance to Dine College to create a testing program to determine hazardous contaminant levels in donated hand sanitizer. Sandia will loan instrumentation, provide a procedure, and act as technical advisor. The challenge for on-site testing lies in a balance of testing capability/speed, complexity, and cost of operations. Instruments that allow fastest and least expensive operation will be validated for performance for this sample problem (hand sanitizer w/ poisonous methanol or 1-propanol). The objective of this project is to enable Dine College personnel to perform on-site testing.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Self-Supervised Cloud Classification

Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive understanding of cloud morphology is critical for continued improvement of our atmospheric modeling and prediction capabilities moving forward. Deep learning has recently accelerated our ability to study clouds using satellite remote sensing, and machine learning classifiers have enabled detailed studies of cloud morphology. A major limitation of deep learning approaches to this problem, however, is the large number of hand-labeled samples that are required for training. This work applies a recently developed self-supervised learning scheme to train a deep convolutional neural network (CNN) to map marine cloud imagery to vector embeddings that capture information about mesoscale cloud morphology and can be used for satellite image classification. The model is evaluated against existing cloud classification datasets and several use cases are demonstrated, including training cloud classifiers with very few labeled samples, interrogation of the CNN’s learned internal feature representations, cross-instrument application, and resilience against sensor calibration drift and changing scene brightness. The self-supervised approach learns meaningful internal representations of cloud structures and achieves comparable classification accuracy to supervised deep learning methods without the expense of creating large hand-annotated training datasets. Significance Statement Marine clouds heavily influence Earth’s weather and climate, and improved understanding of marine clouds is required to improve our atmospheric modeling capabilities and physical understanding of the atmosphere. Recently, deep learning has emerged as a powerful research tool that can be used to identify and study specific marine cloud types in the vast number of images collected by Earth-observing satellites. While powerful, these approaches require hand-labeling of training data, which is prohibitively time intensive. This study evaluates a recently developed self-supervised deep learning method that does not require human-labeled training data for processing images of clouds. We show that the trained algorithm performs competitively with algorithms trained on hand-labeled data for image classification tasks. We also discuss potential downstream uses and demonstrate some exciting features of the approach including application to multiple satellite instruments, resilience against changing image brightness, and its learned internal representations of cloud types. The self-supervised technique removes one of the major hurdles for applying deep learning to very large atmospheric datasets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Mineralogy of SNC Meteorite EET79001 by Simultaneous Fitting of Moessbauer Backscatter Spectra

We have acquired M ssbauer spectra for SNC meteorite EET79001 with a MIMOS II backscatter M ssbauer spectrometer [1] similar to those now operating on Mars as part of the Mars Exploration Rover (MER) missions. We are working to compare the Fe mineralogical composition of martian meteorites with in-situ measurements on Mars. Our samples were hand picked from the >1 mm size fraction of saw fines on the basis of lithology, color, and grain size (Table 1). The chips were individually analyzed at approx.300K by placing them on a piece of plastic that was in turn supported by the contact ring of the instrument (oriented vertically). Tungsten foil was used to mask certain areas from analysis. As shown in Figure 1, a variety of spectra was obtained, each resulting from different relative contributions of the Fe-bearing minerals present in the sample. Because the nine samples are reasonably mixtures of the same Fe-bearing phases in variable proportions, the nine spectra were fit simultaneously (simfit) with a common model, adjusting parameters to a single minimum chi-squared convergence criterion [2]. The starting point for the fitting model and values of hyperfine parameters was the work of Solberg and Burns [3], who identified olivine, pyroxene, and ferrous glass as major, and ilmenite and a ferric phase as minor (<5%), Fe-bearing phases in EET79001.

Morris, Richard V.↗
DOE OSTI2020

Imaging systematics and clustering of DESI main targets

ABSTRACT We evaluate the impact of imaging systematics on the clustering of luminous red galaxies (LRG), emission-line galaxies (ELG), and quasars (QSO) targeted for the upcoming Dark Energy Spectroscopic Instrument (DESI) survey. Using Data Release 7 of the DECam Legacy Survey, we study the effects of astrophysical foregrounds, stellar contamination, differences between north galactic cap and south galactic cap measurements, and variations in imaging depth, stellar density, galactic extinction, seeing, airmass, sky brightness, and exposure time before presenting survey masks and weights to mitigate these effects. With our sanitized samples in hand, we conduct a preliminary analysis of the clustering amplitude and evolution of the DESI main targets. From measurements of the angular correlation functions, we determine power law fits $r_0 = 7.78 \pm 0.26\, h^{-1}$Mpc, γ = 1.98 ± 0.02 for LRGs and $r_0 = 5.45 \pm 0.1\, h^{-1}$Mpc, γ = 1.54 ± 0.01 for ELGs. Additionally, from the angular power spectra, we measure the linear biases and model the scale-dependent biases in the weakly non-linear regime. Both sets of clustering measurements show good agreement with survey requirements for LRGs and ELGs, attesting that these samples will enable DESI to achieve precise cosmological constraints. We also present clustering as a function of magnitude, use cross-correlations with external spectroscopy to infer dN/dz and measure clustering as a function of luminosity, and probe higher order clustering statistics through counts-in-cells moments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Structural anisotropic properties of a-plane GaN epilayers grown on r-plane sapphire by molecular beam epitaxy

Heteroepitaxial non-polar III-Nitride layers may exhibit extensive anisotropy in the surface morphology and the epilayer microstructure along distinct in-plane directions. The structural anisotropy, evidenced by the “M”-shape dependence of the (112{sup ¯}0) x-ray rocking curve widths on the beam azimuth angle, was studied by combining transmission electron microscopy observations, Raman spectroscopy, high resolution x-ray diffraction, and atomic force microscopy in a-plane GaN epilayers grown on r-plane sapphire substrates by plasma-assisted molecular beam epitaxy (PAMBE). The structural anisotropic behavior was attributed quantitatively to the high dislocation densities, particularly the Frank-Shockley partial dislocations that delimit the I{sub 1} intrinsic basal stacking faults, and to the concomitant plastic strain relaxation. On the other hand, isotropic samples exhibited lower dislocation densities and a biaxial residual stress state. For PAMBE growth, the anisotropy was correlated to N-rich (or Ga-poor) conditions on the surface during growth, that result in formation of asymmetric a-plane GaN grains elongated along the c-axis. Such conditions enhance the anisotropy of gallium diffusion on the surface and reduce the GaN nucleation rate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comprehensive Characterization of Multi-Phase Sulfurized Polyacrylonitrile Cathodes for Lithium-Sulfur Batteries

Sulfurized polyacrylonitrile (SPAN) is considered one of the most promising cathode materials to overcome the operational challenges that plague lithium-sulfur (Li-S) batteries. However, material properties and electrochemical performance implications of SPAN prepared under different synthesis conditions are not yet fully investigated. In this study, we show the impacts of different synthesis conditions on the formation of sulfur to PAN bonds and redox reaction mechanisms of multi-phase SPAN via comprehensive material and electrochemical characterizations. In-situ Raman analysis was first applied to study the multi-phase SPAN-based Li-S cells. We found that both elemental sulfur and chemically bonded sulfur are present under the synthesis condition of 300 degree C/3 h along with unreacted PAN. The incompletely sulfurized, multi-phase SPAN exhibited an unusually rapid capacity degradation in the resultant Li-S cells, which is attributed to polysulfide formation and continuously growing interfacial impedance in the Li-S cells. On the other hand, SPAN samples prepared under the synthesis condition of 350 degree C/3 h are found completely sulfurized with chemically bonded sulfur to the PAN backbone without the presence of free elemental sulfur. Complete sulfurization of SPAN led to exceptionally stable cycle performance due to excellent reversible redox processes of chemically bonded sulfur with Li+ in the Li-S cells.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗