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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Stellar decomposition: A compact representation for simplicial complexes and beyond

Here, we introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex’s vertices and cells such that each region has sufficient information to locally reconstruct the star of its vertices, i.e., the cells incident in the region’s vertices. Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain. They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by a corresponding global topological data structure on the complex. As a concrete realization of this model for spatially embedded complexes, we introduce the Stellar tree, which combines a nested spatial tree with a simple tuning parameter to control the number of vertices in a region. Stellar trees exploit the complex’s spatial locality by reordering vertex and cell indices according to the spatial decomposition and by compressing sequential ranges of indices. Stellar trees are competitive with state-of-the-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes. We conclude with a high-level description of several mesh processing and analysis applications that utilize Stellar trees to process large datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Unconventional Pathways to Carbide Phase Synthesis via Thermal Decomposition of UI 4 (1,4-dioxane) 2

UI4(1,4-dioxane) 2 was subjected to laser-based heating-a method that enables localized, fast heating (T > 2000 °C) and rapid cooling under controlled conditions (scan rate, power, atmosphere, etc.)-to understand its thermal decomposition. A predictive computational thermodynamic technique estimated the decomposition temperature of UI 4 (1,4-dioxane) 2 to uranium (U) metal to be 2236 °C, a temperature achievable under laser irradiation. Dictated by the presence of reactive, gaseous byproducts, the thermal decomposition of UI 4 (1,4-dioxane) 2 under furnace conditions up to 600 °C revealed the formation of UO 2 , UI x , and U(C 1–x O x ) y , while under laser irradiation, UI 4 (1,4-dioxane) 2 decomposed to UO 2 , U(C 1–x O x ) y , UC 2–z O z , and UC. Despite the fast dynamics associated with laser irradiation, the central uranium atom reacted with the thermal decomposition products of the ligand (1,4-dioxane = C 4 H 8 O 2 ) instead of producing pure U metal. In conclusion, the results highlight the potential to co-develop uranium precursors with specific irradiation procedures to advance nuclear materials research by finding new pathways to produce uranium carbide.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗
DOE OSTI2021

Dynamic Mode Decomposition of Random Pressure Fields over Bluff Bodies

Fluctuating surface pressures on a bluff body exposed to a boundary layer flow generally are characterized as a spatiotemporally varying random field. In this paper, a dynamic mode decomposition (DMD) was applied to extract dominant features embedded in these random pressure fields. Utilizing an unsupervised machine learning algorithm, spatial modes and their temporal variations were grouped into different clusters at scales, e.g., macro, meso, and micro. A proper orthogonal decomposition (POD) of the experimental data was carried out to observe commonalities and distinctive perspectives each decomposition offers. Here, a comprehensive examination of the DMD/POD for their convergence criteria, data sufficiency, and modal components analysis was conducted. The physical interpretation of the spatiotemporal pressure field based on these decomposition schemes was discussed. At different scales, the DMD modes can capture the evolution of aerodynamic features, e.g., convection of vortices (or vortex tubes) and other structures. The distribution of energy among these three broad scales also reflects an energy cascade in pressure fluctuations akin to turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Shock-induced chemical decomposition and overdriven detonation in hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) single crystals

Understanding the differences in the shock compression and detonation response of insensitive high explosives (IHEs) and conventional HEs (CHEs) is a long-standing need in HE science and technology. Having previously examined 1,1-diamino-2,2-dinitroethene (FOX-7) IHE single crystals, the shock and detonation response of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX)—a widely used CHE—was determined using wave profile measurements in ~250 μm thick single crystals shock compressed to 63 GPa. In marked contrast to FOX-7, RDX single crystals shocked along the [100] and [111] orientations showed wave profile features consistent with chemical decomposition onset at 15 GPa. These features were more pronounced for [100] RDX, suggesting a higher decomposition rate compared to [111] RDX. At 51 GPa and above, flat-topped single waves were observed for both orientations, showing the classic Chapman–Jouget (C–J) detonation response in which the decomposition is completed within the detonation front. The Hugoniot states and sound speeds determined for the detonation products were similar for both [100] and [111] orientations, showing that the overdriven detonation response for RDX does not depend on crystal orientation. The C–J pressure for RDX single crystals (35 GPa)—determined experimentally—is comparable to that of FOX-7. However, compared to FOX-7, chemical decomposition onset for RDX occurs at much lower pressures and the overdriven C–J detonation response occurs at higher pressures. Lastly, the present findings constitute the first experimental comparison of the shock and detonation response of conventional and insensitive HE single crystals over a broad pressure range below and above the C–J pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Initial decomposition mechanisms of 2,4,6-triamino-1,3,5-trinitrobenzene (TATB) and their kinetic isotope effect

2,4,6-triamino-1,3,5-trinitrobenzene (TATB) is an insensitive High Explosive (HE) that is widely studied to better understand the physical properties of safety and sensitivity of HE. A dominant initial decomposition mechanism of TATB is believed to be a dehydration reaction that forms mono- and di-furazans, although other mechanisms have been reported. In this work, seven initial decomposition mechanisms were modeled with ab initio simulations to calculate its free energy barriers, decomposition rates, and kinetic isotope effects. The energy barrier for mono-benzofurazan mechanisms was found to be high, >61 kcal/mol in the gas phase; however, the reaction energy can decrease significantly in a disordered condensed state. The predicted kinetic isotope effect ratio of the furazan mechanism was found to be k h /k d ≈ 1.41 at 60K, in agreement with the experiment. The NO 2 scission mechanism was found to be an entropy-driven mechanism because the free energy barrier decreased significantly with temperature, making it the most energetically favorable mechanism at high temperatures in the gas phase. So the results provide a better understanding of the atomistic decomposition mechanisms of TATB and may be useful for improving models of safety and sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Porewater constituents inhibit microbially mediated greenhouse gas production (GHG) and regulate the response of soil organic matter decomposition to warming in anoxic peat from a Sphagnum -dominated bog

Abstract Northern peatlands store approximately one-third of terrestrial soil carbon. Climate warming is expected to stimulate the microbially mediated degradation of peat soil organic matter (SOM), leading to increasing greenhouse gas (GHG; carbon dioxide, CO2; methane, CH4) production and emission. Porewater dissolved organic matter (DOM) plays a key role in SOM decomposition; however, the mechanisms controlling SOM decomposition and its response to warming remain unclear. The temperature dependence of GHG production and microbial community dynamics were investigated in anoxic peat from a Sphagnum-dominated peatland. In this study, peat decomposition, which was quantified by GHG production and carbon substrate utilization is limited by terminal electron acceptors (TEA) and DOM, and these controls of microbially mediated SOM degradation are temperature-dependent. Elevated temperature led to a slight decrease in microbial diversity, and stimulated the growth of specific methanotrophic and syntrophic taxa. These results confirm that DOM is a major driver of decomposition in peatland soils contains inhibitory compounds, but the inhibitory effect is alleviated by warming.

Song, Tianze (ORCID:0000000282060247)↗
DOE OSTI2024

Simulated nitrogen deposition and precipitation events alter microbial carbon cycling during early stages of litter decomposition

Plant litter decomposition is a major nutrient input to terrestrial ecosystems that is primarily driven by microorganisms. Litter quality is considered a key drive of decomposition; however, human-induced global disturbance like nitrogen deposition and increasing extreme precipitation events will shift nutrient availability during litter decomposition. Little is known about how shifting nutrient availability will impact dissolved organic matter concentrations and microbially driven carbon cycling that are critical to soil organic matter formation. This study investigated the effect of simulated nitrogen deposition and repeated precipitation events on microbially driven carbon flow during short-term litter decomposition using a ‘common garden’ experiment with microcosms containing sand and blue grama grass litter inoculated with different microbial communities. Overall, nitrogen deposition decoupled respiration and dissolved organic carbon (DOC) by increasing respiration and not affecting DOC concentrations. Moreover, nitrogen deposition had no effect on microbial carbon use efficiency (CUE). Repeated simulated precipitation events significantly increased DOC concentrations, decreased microbial CUE, increased the microbial metabolic quotient (qCO2), and altered microbial composition and diversity. These findings highlight the complex interactions and responses of surface litter decomposers to shifting nutrient availability and contradicts previous findings that nitrogen deposition will increase soil carbon sequestration from a larger supply of DOC and reduced respiration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

SymProp: Scaling Sparse Symmetric Tucker Decomposition via Symmetry Propagation

Sparse symmetric tensors are an important class of tensors, and their decompositions serve as powerful tools for revealing low-rank structures. This paper introduces SymProp, a novel approach for scaling sparse symmetric Tucker decomposition by propagating symmetry through intermediate computations. SymProp optimizes two key computational kernels: Sparse Symmetric Tensor Times Same Matrix chain (S3 TTMc) for Higher-Order Orthogonal Iteration (HOOI) and Sparse Symmetric Tensor Times Same Matrix chain Times Core (S3 TTMcTC) for Higher-Order QR Iteration (HOQRI). Our method employs a metaprogramming-based index iteration approach to efficiently handle the upper triangular parts of intermediate dense symmetric tensors. SymProp achieves up to 50.9× speedup over SPLATT and up to 360.8× over Compressed Sparse Symmetric (CSS) format on the S3 TTMc operation. Moreover, our S3 TTMc and S3 TTMcTC implementations support tensor orders four levels higher than state-of-the-art methods. Our HOQRI demonstrates superior scalability and up to a 33.6× speedup over optimized HOOI. By enabling more scalable Tucker decompositions for higher orders, decomposition ranks, and dimension sizes, SymProp opens new possibilities for analyzing complex hypergraph structures in fields such as network science, data mining, and machine learning.

Li, Zecheng [North Carolina State University]↗
DOE OSTI2020

DECT-MULTRA: Dual-Energy CT Image Decomposition With Learned Mixed Material Models and Efficient Clustering

Dual-energy computed tomography (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Image-domain decomposition operates directly on CT images using linear matrix inversion, but the decomposed material images can be severely degraded by noise and artifacts. This paper proposes a new method dubbed DECT-MULTRA for image-domain DECT material decomposition that combines conventional penalized weighted-least squares (PWLS) estimation with regularization based on a mixed union of learned transforms (MULTRA) model. Our proposed approach pre-learns a union of common-material sparsifying transforms from patches extracted from all the basis materials, and a union of cross-material sparsifying transforms from multi-material patches. The common-material transforms capture the common properties among different material images, while the cross-material transforms capture the cross-dependencies. The proposed PWLS formulation is optimized efficiently by alternating between an image update step and a sparse coding and clustering step, with both of these steps having closed-form solutions. The effectiveness of our method is validated with both XCAT phantom and clinical head data. The results demonstrate that our proposed method provides superior material image quality and decomposition accuracy compared to other competing methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Engineering Solid Electrolyte Interphase Composition by Assessing Decomposition Pathways of Fluorinated Organic Solvents in Lithium Metal Batteries

Studies have shown fluorinated electrolyte solvents can form desirable solid electrolyte interphase (SEI) in lithium metal batteries. In this study, we develop a detailed mechanistic understanding of two high performing electrolytes, Fluoroethylene Carbonate (FEC) and Difluoroethylene Carbonate (DFEC) to demonstrate minimal structural variations can lead to different decomposition products, and thereby the nature of the SEI. Using density functional theory (DFT) calculations, we find different initial bond-breaking mechanisms between FEC and DFEC. We develop free energy diagrams for the decomposition pathways including both electrochemical and chemical steps. Using the computational Li electrode, we identify the largest limiting potential of 1.77 V for FEC decomposition, associated with the formation of lithium fluoride, lithium oxide and FEC oligomers, and 1.53 V for DFEC, which correspond to the formation of polymerized vinylene carbonate and lithium fluoride. We suggest the formation of oligomers in the case of FEC instead of long polymers may lead to better SEI compactness. We also demonstrate the SEI components of FEC and DFEC are not stable on typical cathode voltage (3.87 V). This study presents a unified electrocatalytic perspective on SEI formation and decomposition.

25 ENERGY STORAGE↗
DOE OSTI2020

Warming-induced permafrost thaw exacerbates tundra soil carbon decomposition mediated by microbial community

BACKGROUND:It is well-known that global warming has effects on high-latitude tundra underlain with permafrost. This leads to a severe concern that decomposition of soil organic carbon (SOC) previously stored in this region, which accounts for about 50% of the world's SOC storage, will cause positive feedback that accelerates climate warming. We have previously shown that short-term warming (1.5 years) stimulates rapid, microbe-mediated decomposition of tundra soil carbon without affecting the composition of the soil microbial community (based on the depth of 42684 sequence reads of 16S rRNA gene amplicons per 3 g of soil sample). RESULTS:We show that longer-term (5 years) experimental winter warming at the same site altered microbial communities (p < 0.040). Thaw depth correlated the strongest with community assembly and interaction networks, implying that warming-accelerated tundra thaw fundamentally restructured the microbial communities. Both carbon decomposition and methanogenesis genes increased in relative abundance under warming, and their functional structures strongly correlated (R 2 > 0.725, p < 0.001) with ecosystem respiration or CH4 flux. CONCLUSIONS:Our results demonstrate that microbial responses associated with carbon cycling could lead to positive feedbacks that accelerate SOC decomposition in tundra regions, which is alarming because SOC loss is unlikely to subside owing to changes in microbial community composition. Video Abstract.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Winter warming in Alaska accelerates lignin decomposition contributed by Proteobacteria

Background: In a warmer world, microbial decomposition of previously frozen organic carbon (C) is one of the most likely positive climate feedbacks of permafrost regions to the atmosphere. However, mechanistic understanding of microbial mediation on chemically recalcitrant C instability is limited; thus, it is crucial to identify and evaluate active decomposers of chemically recalcitrant C, which is essential for predicting C-cycle feedbacks and their relative strength of influence on climate change. Using stable isotope probing of the active layer of Arctic tundra soils after depleting soil labile C through a 975-day laboratory incubation, the identity of microbial decomposers of lignin and, their responses to warming were revealed. Results: The β - Proteobacteria genus Burkholderia accounted for 95.1% of total abundance of potential lignin decomposers. Consistently, Burkholderia isolated from our tundra soils could grow with lignin as the sole C source. A 2.2 °C increase of warming considerably increased total abundance and functional capacities of all potential lignin decomposers. In addition to Burkholderia , α - Proteobacteria capable of lignin decomposition (e.g. Bradyrhizobium and Methylobacterium genera) were stimulated by warming by 82-fold. Those community changes collectively doubled the priming effect, i.e., decomposition of existing C after fresh C input to soil. Consequently, warming aggravates soil C instability, as verified by microbially enabled climate-C modeling. Conclusions: Our findings are alarming, which demonstrate that accelerated C decomposition under warming conditions will make tundra soils a larger biospheric C source than anticipated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Theoretically and practically efficient parallel nucleus decomposition

This paper studies the nucleus decomposition problem, which has been shown to be useful in finding dense substructures in graphs. We present a novel parallel algorithm that is efficient both in theory and in practice. Our algorithm achieves a work complexity matching the best sequential algorithm while also having low depth (parallel running time), which significantly improves upon the only existing parallel nucleus decomposition algorithm (Sariyüce et al. , PVLDB 2018). The key to the theoretical efficiency of our algorithm is a new lemma that bounds the amount of work done when peeling cliques from the graph, combined with the use of a theoretically-efficient parallel algorithms for clique listing and bucketing. We introduce several new practical optimizations, including a new multi-level hash table structure to store information on cliques space-efficiently and a technique for traversing this structure cache-efficiently. On a 30-core machine with two-way hyper-threading on real-world graphs, we achieve up to a 55x speedup over the state-of-the-art parallel nucleus decomposition algorithm by Sariyüce et al. , and up to a 40x self-relative parallel speedup. We are able to efficiently compute larger nucleus decompositions than prior work on several million-scale graphs for the first time.

Computer Science↗
DOE OSTI2022

Plant and shrub tissue decompositions in changing environments after six-years in a Peatland ecosystem

SPRUCE, Spruce and Peatland Responses Under Changing Environments, is a ten-year long ecosystem manipulation that tests the responses of a high-carbon peatland ecosystem to warming and elevated CO2. This experiment is located a Northern Minnesota peatland. Here we studied how plant tissue decomposition is affected by the climate treatments at SPRUCE. Six different litter types were placed into mesh bags and deployed into the peatland. The samples were then removed after six years, and we analyzed those samples in the laboratory. Analysis of these samples consisted of removing foreign growth, drying each sample, weighing each litter bag, grinding into a fine powder, and finally sending each sample off for phosphorus, carbon, and nitrogen analysis. Although we expected to observe effects of warming on decomposition rates, with faster decomposition in the warmer treatments, we only observed faster decomposition in the warmer plots in a few litter types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data from "What regulates decomposition in agroecosystems? Insights from reading the tea leaves"

Litter decomposition is a critical Earth process, recycling nutrients and setting a portion of plant tissue on a path toward soil organic matter. Despite this importance, we still lack a good understanding of local factors that regulate decomposition, especially in agroecosystems where management plays an outsized role. To help understand these factors, 1308 tea bags containing green and rooibos tea leaves were buried in 109 plots being exposed to a variety of management practices. This dataset contains the decomposition measurements (mass) of those tea bags that were collected 6 times during the 2018 growing season at 9 long-term experimental farms in Iowa, USA. Additionally, the dataset contains a variety of soil and crop measurements to support the understanding of the soils and the decomposition measurements. Files are presented in .csv format.

Agricultural land management↗
DOE OSTI2020

Material Discovery and High Throughput Exploration of Ru Based Catalysts for Low Temperature Ammonia Decomposition

High throughput experimentation has the capability to generate massive, multidimensional datasets, allowing for the discovery of novel catalytic materials. Here, we show the synthesis and catalytic screening of over 100 unique Ru-Metal-K based bimetallic catalysts for low temperature ammonia decomposition, with a Ru loading between 1–3 wt% Ru and a fixed K loading of 12 wt% K, supported on γ-Al2O3. Bimetallic catalysts containing Sc, Sr, Hf, Y, Mg, Zr, Ta, or Ca in addition to Ru were found to have excellent ammonia decomposition activity when compared to state-of-the-art catalysts in literature. Furthermore, the Ru content could be reduced to 1 wt% Ru, a factor of four decrease, with the addition of Sr, Y, Zr, or Hf, where these secondary metals have not been previously explored for ammonia decomposition. The bimetallic interactions between Ru and the secondary metal, specifically RuSrK and RuFeK, were investigated in detail to elucidate the reaction kinetics and surface properties of both high and low performing catalysts. The RuSrK catalyst had a turnover frequency of 1.78 s−1, while RuFeK had a turnover frequency of only 0.28 s−1 under identical operating conditions. Based on their apparent activation energies and number of surface sites, the RuSrK had a factor of two lower activation energy than the RuFeK, while also possessing an equivalent number of surface sites, which suggests that the Sr promotes ammonia decomposition in the presence of Ru by modifying the active sites of Ru.

McCullough, Katherine (ORCID:0000000197525740)↗
NASA NTRS1972

Microscopic observations of X-ray and gamma-ray induced decomposition of ammonium perchlorate crystals

The X-ray and gamma-ray induced decomposition of ammonium perchlorate was studied by optical, transmission, and scanning electron microscopy. This material is a commonly used oxidizer in solid propellents which could be employed in deep-space probes, and where they will be subjected to a variety of radiations for as long as ten years. In some respects the radiation-induced damage closely resembles the effects produced by thermal decomposition, but in other respects the results differ markedly. Similar radiation and thermal effects include the following: (1) irregular or ill-defined circular etch pits are formed in both cases; (2) approximately the same size pits are produced; (3) the pit density is similar; (4) the c face is considerably more reactive than the m face; and (5) most importantly, many of the etch pits are aligned in crystallographic directions which are the same for thermal or radiolytic decomposition. Thus, dislocations play an important role in the radiolytic decomposition process.

Herley, P. J.↗