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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 OSTI2026

Decomposition of methane diluted with inert gas in an RF discharge cell

Decomposition of methane using non-thermal plasmas is an attractive route for producing hydrogen-rich gases and valuable carbon nanomaterials. Understanding how plasma discharge modes influence methane decomposition in optimizing plasma-assisted chemical conversion remains unexplored. This study explores the coupling between the discharge structure and product selectivity in RF capacitively coupled discharges operating in methane/inert gas mixtures in the pressure range of 2–3 torr. Under our experimental conditions the discharge exhibits mode transitions from uniform to striated in Ar and Kr and from diffuse to contracted in Ar and Kr with <5% CH 4 . The discharges in He and Ne remained uniform under our operating conditions, and their mixtures with CH 4 remained diffuse. A 0-d model for Ar/CH 4 discharge established a threshold for contraction while also asserting the importance of Ar$^{*}_{\textrm{m}}$ in the dissociation and ionization processes. The highest degree of methane decomposition, >99.7% with the main products of acetylene and graphitized solid carbon was achieved in the contracted discharge mode for both Kr or Ar with ⩽5% CH 4 . We demonstrate that contraction can play a crucial role in the effective decomposition of methane with value-added products and that both the electronic and thermal properties of plasma gas are responsible for this effect.

RF plasma↗
DOE OSTI2025

Multi-omics of a model bacterial consortium deciphers details of chitin decomposition in soil

Soil microorganisms interact to carry out decomposition of complex organic carbon and nitrogen compounds, such as chitin, but the high diversity and complexity of the soil microbiome and habitat have posed a challenge to elucidating such interactions. Here, we sought to address this challenge by analysis of a model soil consortium (MSC-2) consisting of eight soil bacterial species. Our aim was to elucidate the specific roles of the member species during chitin metabolism. Samples were collected from MSC-2 incubated in chitin-enriched soil over 3 months. Multi-omics was used to understand how the community composition, transcripts, proteins, and chitin decomposition shifted over time. The data clearly and consistently revealed a temporal shift during chitin decomposition with defined contributions by individual species. A Streptomyces genus member (sp001905665) was a key player in early steps of chitin decomposition, with other MSC-2 members being central in carrying out later steps. These results illustrate how multi-omics applied to a defined consortium untangles the interactions between soil microorganisms.

chitin↗
DOE OSTI2025

Water‐mediated Decomposition Pathways of ε‐Hexanitrohexaazaisowurtzitane

The dominant initial decomposition mechanism of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (HNIW) is understood from the literature to be the N─NO 2 bond scission unimolecular mechanism. Here we have found a water-mediated HONO release initial decomposition mechanism energetically competitive with the N─NO 2 bond scission mechanism modeled using ab initio nudged elastic band simulations. The activation energy of the water-mediated HONO mechanism was calculated to be 138.9 kJ/mol with the Perdew, Burke, and Ernzerhof (PBE) functional (177.8 with PBE0), while the double NO 2 release mechanism is 171.9 kJ/mol (203.3 with PBE0). Branching secondary, tertiary, and quaternary decomposition steps were also discovered including oxidation of HONO or H 2 O causing ring-opening that leads to C─N bond breaking and N 2 O or NO release. The reaction rate of HONO oxidation is much faster than HONO release, making the HONO concentration low. The Helmholtz free energy barrier of the double NO 2 release mechanism is lower than the water-mediated HONO release above 438 K (165°C) due to the vibrational contribution to the free energy. This helps explain why the literature reports more NO 2 release at higher temperatures. The present study reveals a physical mechanism for how water can catalyze the decomposition of HNIW at low enough temperatures, and reveals secondary, tertiary, and quaternary reaction mechanisms leading to NO x release. In conclusion, as water is realistically always present, the reported barriers are important for building kinetic models needed to ensure the safety and reliability of HNIW.

Steele, Brad A. [Lawrence Livermore National Labor↗
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 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 OSTI2026

NOx mediated formation of ε – UO 3 during thermal decomposition of uranyl nitrate hexahydrate under static air conditions

The thermal decomposition of uranyl nitrate hexahydrate in air at temperatures of 650 – 800 °C is expected to yield α – U 3 O 8 through intermediate UO 3 phases. Here, n this study, Raman spectroscopy complimented by powder X-ray diffraction revealed the unexpected formation of ε – UO 3 as an accompanying phase during thermal decomposition of UNH at 700 °C under static air conditions. Experiments demonstrated that ε – UO 3 does not form during the initial ramp up stage nor during the high temperature heating period; but instead forms during the cooling stage between 250 – 400 °C. Additional experiments revealed that UNH initially decomposes through an amorphous UO 3 intermediate prior to α – U 3 O 8 formation. Attempts to bypass the U 3 O 8 precursor in the formation of ε – UO 3 were unsuccessful, supporting the necessity of U 3 O 8 (α – U 3 O 8 in this study) in the formation of ε – UO 3 . The observed phase evolution is proposed to result from the NOx species generated during UNH thermal decomposition, which create localized oxidizing conditions within the furnace under static air conditions. Furthermore, a predominantly phase pure ε – UO 3 was synthesized under static air conditions through the addition of an extra plateau at 250 °C during the cooling step. These findings demonstrate the importance of gas-phase chemistry and cooling conditions in uranium oxide phase evolution and provide additional insight into ε – UO 3 formation pathways.

Epsilon uranium trioxide↗
DOE OSTI2025

First-Principles-Based Study of the Decomposition of Phenol and Hydroquinone on Pt(111) Combined with Quantitative Information from XPS Spectra to Address the Impact of Coverage and Number of Hydroxyl Functional Groups

A combined first-principles-based and experimental X-ray photoelectron spectroscopy approach was used to investigate the thermal decomposition of two model biofuel compounds, phenol and hydroquinone, on Pt(111) at both low and high coverages. The DFT-based approach yields adsorption geometries and energies, activation barriers and core-level binding energy shifts for C 1s and O 1s. Increasing the coverage in the theoretical model leads to slight shifts in core-level binding energies─toward higher values for C 1s and lower values for O 1s. It also alters the energy profiles of the decomposition reaction pathway, resulting in weaker adsorption energies and changes in both reaction and activation barriers. At low temperatures, we observe a multilayer for phenol and hydroquinone upon adsorption, with desorption occurring at 200 and 270 K, respectively. Following desorption of the multilayer, decomposition proceeds via initial O–H bond scission, followed by two parallel pathways involving either C–H or C–C bond scission, whereby in the case of phenol C–H bond scission occurs first. Here, we further provide characteristic core level binding energies by theoretical calculations that are subsequently used in experimental analyses, establishing a reference database for key spectra of phenolic functionalities applicable to a range of catalytic reactions.

09 BIOMASS FUELS↗
DOE OSTI2026

Continental-scale integration of soil metagenomes and organic matter chemistry reveals ubiquitous microbial capacity for chemically-recalcitrant carbon decomposition

Soil organic matter (SOM) decomposition by microorganisms is a major uncertainty in predicting terrestrial carbon–atmosphere feedbacks, partly because we lack understanding of the microbial diversity involved in depolymerizing different carbon pools across environmental gradients. We address this gap using a continental-scale dataset pairing shotgun metagenomes with high-resolution SOM chemistry, assembling 0.76 Tbp of prokaryotic MAGs (828 genomes) and identifying 66,727 SOM molecules from 47 standardized U.S. soil cores selected using respiration rates from 106 soils. Integrating these datasets reveals widespread microbial potential for depolymerizing chemically-recalcitrant SOM previously considered stable. We uncover complementary metabolic specialization between genera affiliated with two abundant bacterial orders, Rhizobiales and Chthoniobacterales, and an archaeal order, Nitrososphaerales. This metabolic partitioning is consistent across soil depths and activity levels, suggesting coordinated decomposition of complex SOM through distinct but complementary biochemical strategies. The metabolic potential for depolymerization of chemically-recalcitrant compounds is supported by the abundance of these molecules across the soils, as indicated by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS), and by flux balance analysis of metabolic models. Our results show that a substantial portion of ostensibly stable SOM remains vulnerable to microbial decomposition, a mechanism not captured in current Earth System Models.

Song, Young C. [Pacific Northwest National Laborat↗
DOE OSTI2025

Chemical decomposition in shock-compressed 1,1-diamino-2,2-dinitroethene (FOX-7) single crystals: Time-resolved Raman spectroscopy

Understanding the evolution of chemical decomposition—at the molecular level—in shock-compressed insensitive high explosive (IHE) single crystals is an important need. Toward this goal, time-resolved Raman spectra were measured in 1,1-diamino-2,2-dinitroethene (FOX-7) single crystals shock compressed to stresses above 20 GPa. At 22 GPa and higher stresses, the Raman peak intensities were significantly reduced, showing the onset and extent of chemical changes. At 33 GPa, no Raman peaks were observed, suggesting complete decomposition of FOX-7. The 22 GPa onset from Raman data is in marked contrast to the much higher (32 GPa) onset determined previously from wave profile measurements—showing the significantly greater sensitivity of Raman measurements for gaining insight into shock-induced molecular-level changes in IHE single crystals. The close match between the complete loss of Raman peaks at 33 GPa and the 32 GPa reaction threshold determined from continuum data makes a good case that the two results are related and they reflect significant energy release due to decomposition.

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

Simplifying the creation of thermal decomposition mechanisms for designing mixed fibre composites

Among the most challenging aspects of simulating thermal decomposition of fibre reinforced polymers is the determination of appropriate reaction parameters. Thermogravimetric analysis is typically used to generate decomposition data, to which the reaction parameters are then fit. When designing mixed fibre materials (e.g. combinations of glass and carbon fibres), the number of TGA experiments needed to explore the entire design space may be intractable. Here, we demonstrate the creation of two candidate proxy mixed fibre mechanisms and compare them to a mechanism created by fitting parameters from TGA on the mixed fibre composite. These mechanisms are then demonstrated in a 2D axisymmetric numerical decomposition, heat transfer, and porous flow model. We find a maximum 11% uncertainty in mass and 4% in temperature difference when using a proxy mechanism.

Scott, Sarah N. [Sandia National Lab. (SNL-CA), Li↗
DOE OSTI2025

Impact of moisture on microbial decomposition phenotypes and enzyme dynamics

Soil organic matter decomposition is a complex process reflecting microbial composition and environmental conditions. Moisture can modulate the connectivity and interactions of microbes. Due to heterogeneity, a deeper understanding of the influence of soil moisture on the dynamics of organic matter decomposition and resultant phenotypes remains a challenge. Soils from a long-term field experiment exposed to high and low moisture treatments were incubated in the laboratory to investigate organic matter decomposition using chitin as a model substrate. By combining enzymatic assays, biomass measurements, and microbial enrichment via activity-based probes, we determined the microbial functional response to chitin amendments and field moisture treatments at both the community and cell scales. Chitinolytic activities showed significant responses to the amendment of chitin, independent of differences in field moisture treatments. However, for other measurements of carbon metabolism and cellular functions, soils from high moisture field treatments had greater potential enzyme activity than soils from low moisture field treatments. A cell tagging approach was used to enrich and quantify bacterial taxa that are actively producing chitin-degrading enzymes. By integrating organism, community, and soil core measurements we show that (i) a small subset of taxa compose the majority (>50%) of chitinase production despite broad functional redundancy, (ii) the identity of key chitin degraders varies with moisture level, and (iii) extracellular enzymes that are not cell-associated account for most potential chitinase activity measured in field soil.

activity-based probes↗
DOE OSTI2026

EXCHANGE Campaign Degradation (ECD): Understanding Decomposition Dynamics Across Mid-Atlantic and Great Lakes Coastal Ecosystems

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Degradation Experiment (EXCHANGE-D) is an in situ experiment designed to assess organic matter decomposition rates across coastal terrestrial-aquatic interfaces (TAIs), from coastal uplands through transition zones to wetlands. Through a network of partner scientists and coastal sites, we are testing how environmental gradients shape decomposition and carbon dynamics across terrestrial-aquatic interfaces. Using standardized tea bag substrates deployed across a network of diverse coastal sites, we compare decomposition rates at different fresh- and salt-water TAIs to develop transferable knowledge that improves the representation of organic matter degradation in coastal ecosystem models. For more information, please see https://compass.pnnl.gov/FME/EXCHANGE. This is Version 1 of the data package, which includes: ecd_README.pdf flmd.csv dd.csv ecd_soil_weom_L2.csv ecd_soil_ph_conductivity_L2.csv ecd_soil_gwc_L2.csv ecd_soil_teabag_degradation_L2.csv ecd_readme.pdf

coastal soils↗
DOE OSTI2025

Comparison Study of Conventional and Adaptive Mesh Refinement in Organic Material Decomposition Models

This study compares conventional mesh refinement techniques, specifically Uniform Mesh Refinement (UMR), with a new Adaptive Mesh Refinement (AMR) method, applied to Organic Material Decomposition (OMD) models. The proposed benefit of AMR is that only areas that require refinement, based on minimizing a specific field gradient, are refined thus decreasing model wall time compared to conventional UMR methods. This work specifically focuses on comparing UMR and AMR methods on decomposing (both No-Flow and Porous-Flow material models) Polymeric Methylene Diisocyanate (PMDI) polyurethane foam. Throughout the work, the geometry increased in complexity to assess the refinement methods performance at varying levels geometric intricacy. While AMR has been shown to work well in a variety of applications, the UMR approach proved to be computationally faster, for many of the geometries and foam decomposition models, than AMR. However, it was observed that at higher levels of refinement, greater than 3 UMR, AMR begins to be computationally better. Additionally, the settings used to perform AMR greatly impact its performance, and lessons learned, in terms of OMD models, are shared. Due to physics involved in material decomposition, specifically the evolution of state variables, these problems don’t fully benefit from the advantages of AMR.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations

We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut problem. Our main focus is on compilation with trapped-ion simulators using Pauli-X operations and all-to-all Ising Hamiltonian HIsing evolution generated by Molmer-Sorensen or optical dipole force interactions, though some of our results also apply to standard gate-based compilations. Our results are based on principles of graph sparsification and decomposition; the former reduces the number of edges in a graph while maintaining its cut structure, while the latter breaks a weighted graph into a small number of unweighted graphs. Though these techniques have been used as heuristics in various hybrid quantum algorithms, there have been no guarantees on their performance, to the best of our knowledge. This work provides the first provable guarantees using sparsification and decomposition to improve quantum noise resilience and reduce quantum circuit complexity. For quantum hardware that uses edge-by-edge QAOA compilations, sparsification leads to a direct reduction in circuit complexity. For trapped-ion quantum simulators implementing all-to-all HIsing pulses, we show that for a (1−ϵ) factor loss in the Max-Cut approximation (ϵ>0), our compilations improve the (worst-case) number of HIsing pulses from O(n2) to O(nlog(n/ϵ)) and the (worst-case) number of Pauli-X bit flips from O(n2) to O(nlog(n/ϵ)ϵ2) for n-node graphs. This is an asymptotic improvement for any constant ϵ>0. We demonstrate that significant improvements to the approximation ratio are obtained using decomposition in simulated trapped-ion experiments with dephasing noise. We further present a generic argument showing that sparsification results in an exponentially improved circuit fidelity lower bound in digital computing schemes based on one- and two-qubit gates, which are relevant to a wide variety of hardwares such as superconducting qubits and certain neutral atom or trapped ion setups, and more sophisticated noise models. We anticipate these approximate compilation techniques will be useful tools in a variety of future quantum computing experiments.

Moondra, Jai [Georgia Institute of Technology]↗
DOE OSTI2025

SNoGloDe: A Structured Nonlinear Global Decomposition Solver

Large-scale optimization problems often require decomposition strategies and customized algorithms to achieve optimal solutions within a reasonable time. Building on the work of Cao and Zavala (2019) for solving nonlinear two-stage stochastic programs to global optimality, we implement and extend their approach. We generalize to optimization problems reformulated with a block-angular constraint structure (e.g., temporal decomposition). Our framework, written in Python using Pyomo, is highly customizable and enables parallel execution of the decomposition. SNoGloDe allows tailored branching strategies, lower bounding problems, and candidate generators to leverage problem-specific knowledge. To demonstrate effectiveness, we compare SNoGloDe’s performance with Gurobi on a temporally decomposed produced water case study.

algorithms↗
DOE OSTI2026

SPRUCE FT-ICR MS, Bulk Chemistry, and Mass Loss from Litter Decomposition Study in Experimental Plots, Marcell Experimental Forest, Minnesota, 2015-2017

This dataset contains molecular, bulk chemical, and mass loss measurements from a litter decomposition study at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. This site is in a Sphagnum spp. ombrotrophic bog forest. Litterbags were deployed into the peat in September 2015 across three warming levels (+0, +4.5, and +9°C) under ambient and elevated carbon dioxide (CO₂ - +500 ppm) and retrieved after roughly 0.5, 1, and 2 years of field incubation (2015-09-23 to 2017-08-02). Litterbags containing six peatland litter types: black spruce needles (Picea mariana - SPL), spruce fine roots (SPR), Sphagnum angustifolium (ANG), Sphagnum magellanicum (MAG), Labrador tea leaves (Rhododendron groenlandicum - LTL), and Labrador tea roots (LTR). Molecular composition of water-soluble organic matter extracts was characterized using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) at 9.4 Tesla, operated in negative ion mode with electrospray ionization, providing molecular formula assignments and compound-class distributions across the decomposition time series. Bulk chemical characterization included elemental analysis (percent carbon, nitrogen, and phosphorus) and Fourier Transform Infrared Spectroscopy (FTIR) to quantify functional group composition. Litter mass loss was tracked gravimetrically at each retrieval interval, expressed as percent mass remaining relative to initial dry mass for each litter type and treatment combination. These data are valuable for understanding how vegetation shifts driven by increased atmospheric CO2 and temperature in peatlands alter litter inputs and organic matter stabilization trajectories, with implications for projecting and modeling peatland carbon cycling. This dataset contains two data files in comma-separated value (.csv) format. Additional metadata are provided: two data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

decomposition↗
DOE OSTI2025

New Synthetic Route to 4,6‐Diamino‐5,7‐dinitro‐benzo‐furazan, Important Decomposition Product of 1,3,5‐Triamino‐2,4,6‐trinitrobenzene

The important 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) decomposition byproduct, 4,6-diamino-5,7-dinitro-benzo-furazan (F 1 ), was prepared in a four-step reaction sequence starting with commercially available materials through a key intermediate, 4,6-dichloro-5,7-dinitro-benzo-furazan. The introduction of azido to 4,6-dichloro-benzo-furazan, followed by nitration and amination gave F 1 in good yield. This new method showed a greatly improved yield and ease of purification than previous methods (the total yield was 30%–40% in seven steps). F 1 is a stable yellow solid with a melting point of 308.7°C and a thermal decomposing temperature of 310.3°C (differential scanning calorimetry at 10°C/min heating rate). The solid-state structure was solved by single-crystal X-ray analyses at low temperatures (100 K). The compound crystallizes in a P 2 1 c space group with the formula C 6 H 4 N 6 O 5 •H 2 O with 12 molecules of F 1 /H 2 O in the unit cell. This compound has eluded complete characterization for almost 50 years. With this information, more advanced decomposition models can be created to further improve critical safety margins in handling the energetic material, TATB.

decomposition↗
DOE OSTI2026

Graph-Based Modeling and Decomposition of Hierarchical Optimization Problems

We present a graph-theoretic modeling approach for hierarchical optimization that leverages the OptiGraph abstraction implemented in the Julia package Plasmo.jl. We show that the abstraction is flexible and can effectively capture complex hierarchical connectivity that arises from decision-making over multiple spatial and temporal scales (e.g., integration of planning, scheduling, and operations in manufacturing and infrastructures). We also show that the graph abstraction facilitates the conceptualization and implementation of decomposition and approximation schemes. Specifically, we propose a graph-based Benders decomposition (gBD) framework that enables the exploitation of hierarchical (nested) structures and that uses graph aggregation/partitioning procedures to discover such structures. In addition, we provide a Julia implementation of gBD, which we call PlasmoBenders.jl. We illustrate the capabilities using examples arising in the context of energy and power systems.

97 MATHEMATICS AND COMPUTING↗