Search NASA⌕ Search

SEARCH · Search NASA

Results for “decomposition”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Iterative image-domain decomposition for dual-energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Decomposition characteristics of C4F7N-based SF6-alternative gas mixtures

C4F7N [2,3,3,3-tetrafluoro-2-(trifluoromethyl)propanenitrile]/CO2 gas mixtures are being developed as an eco-friendly electrical insulator to replace SF6, the most potent greenhouse industrial gaseous dielectric. However, recent studies have reported complicated and often conflicting decomposition pathways for C4F7N/CO2 gas mixtures, which has raised concerns. In this work, the decomposition characteristics of C4F7N/CO2 gas mixtures were studied comprehensively by both designed computations and experiments. Computations were performed starting from fundamental propositions of C4F7N/CO2 decompositions, which were further experimentally verified by pyrolysis, long-term thermal aging with/without catalytic materials (industrial-grade molecular sieves 4A), and electrical decomposition by spark discharge. The results of both computations and experiments suggest that in an ideal thermal decomposition, C4F7N is likely to decompose into C2F6 and small fluoronitriles first at high temperatures. The generation of C3F6 and C2N2 from C4F7N thermal decomposition at lower temperatures appears because of the catalytic effect of incompatible materials, for example, the industrial-grade molecular sieves 4A that we tested. The electron impact dissociation of C4F7N plays an important role in C4F7N electrical decomposition, leading to additional formation of distinctive small molecules of CF4 and C2N2 of low concentrations. It was pointed out based on a real arcing test in a load disconnector that the decomposition of C4F7N gas mixtures in real applications will be at a much moderate and manageable rate than what was obtained from the highly accelerated laboratory tests presented in this work. The signatures of decomposition products extracted in this study provide invaluable guidance for developing decomposition-based diagnosis and fixation of decomposition byproducts toward SF6-free power grids.

Physics↗
DOE OSTI2015

A general framework of noise suppression in material decomposition for dual-energy CT

Purpose: As a general problem of dual-energy CT (DECT), noise amplification in material decomposition severely reduces the signal-to-noise ratio on the decomposed images compared to that on the original CT images. In this work, the authors propose a general framework of noise suppression in material decomposition for DECT. The method is based on an iterative algorithm recently developed in their group for image-domain decomposition of DECT, with an extension to include nonlinear decomposition models. The generalized framework of iterative DECT decomposition enables beam-hardening correction with simultaneous noise suppression, which improves the clinical benefits of DECT. Methods: The authors propose to suppress noise on the decomposed images of DECT using convex optimization, which is formulated in the form of least-squares estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance–covariance matrix of the decomposed images as the penalty weight in the least-squares term. Analytical formulas are derived to compute the variance–covariance matrix for decomposed images with general-form numerical or analytical decomposition. As a demonstration, the authors implement the proposed algorithm on phantom data using an empirical polynomial function of decomposition measured on a calibration scan. The polynomial coefficients are determined from the projection data acquired on a wedge phantom, and the signal decomposition is performed in the projection domain. Results: On the Catphan{sup ®}600 phantom, the proposed noise suppression method reduces the average noise standard deviation of basis material images by one to two orders of magnitude, with a superior performance on spatial resolution as shown in comparisons of line-pair images and modulation transfer function measurements. On the synthesized monoenergetic CT images, the noise standard deviation is reduced by a factor of 2–3. By using nonlinear decomposition on projections, the authors’ method effectively suppresses the streaking artifacts of beam hardening and obtains more uniform images than their previous approach based on a linear model. Similar performance of noise suppression is observed in the results of an anthropomorphic head phantom and a pediatric chest phantom generated by the proposed method. With beam-hardening correction enabled by their approach, the image spatial nonuniformity on the head phantom is reduced from around 10% on the original CT images to 4.9% on the synthesized monoenergetic CT image. On the pediatric chest phantom, their method suppresses image noise standard deviation by a factor of around 7.5, and compared with linear decomposition, it reduces the estimation error of electron densities from 33.3% to 8.6%. Conclusions: The authors propose a general framework of noise suppression in material decomposition for DECT. Phantom studies have shown the proposed method improves the image uniformity and the accuracy of electron density measurements by effective beam-hardening correction and reduces noise level without noticeable resolution loss.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration

Stream and river ecosystems play a central role in the movement and decomposition of particulate organic matter, serving as a conduit between terrestrial hillslopes and coastal environments. Microbial-catalyzed decomposition generates simpler organic molecules that fuel respiration, often in the sediments of these ecosystems. However, the degree of connection between sediment-associated respiration (ER??d) and organic-matter decomposition remains poorly understood. How that relationship compares to decomposition’s relationship with whole ecosystem (ERtot) and water column (ERwc) respiration is also not clear. We examined the link between particulate organic matter decomposition—using cellulose-based cotton strips as a standardized substrate—and all three components of respiration across 48 sites in the environmentally diverse Yakima River Basin (Washington State, USA). We hypothesized that decomposition within sediments would be most strongly related to ERsed, but decomposition rates were more closely associated with ERtot, with little connection to ERsed or ERwc. This suggests that particulate organic matter decomposition within stream/river sediments reflects integrated system respiration rather than processes confined to sediments or the water column alone. Further, across the basin, decomposition rates nearly spanned the previously reported global range for streams and rivers and were best explained by total dissolved nitrogen (TDN), sediment grain size, and aridity of the upstream drainage area. These results highlight the strong influence of land cover and basin-scale biophysical variation on sediment-associated decomposition processes and indicate that mechanistic models of organic matter decomposition in streams/rivers should account for coupled sediment–water–land interactions.

Stegen, James C. (ORCID:0000000191357424)↗
DOE OSTI2025

Thermal decomposition pathways of bulk electrolytes on vanadium oxide nanocrystals

The thermal stability of electrolytes at an elevated temperature induced by battery charge-discharge cycling is critical for the long cycling performance of a rechargeable battery. For many multivalent systems, such as rechargeable magnesium batteries, which offer great potential for high energy density and utilize earth-abundant resources, electrolyte instability and electrode surface passivation, arising from electrolyte decomposition, remain as major roadblocks. Understanding the electrolyte decomposition pathways at the electrode-electrolyte interface is essential to provide guidance in overcoming this challenge. In this work, in situ 13 C magic angle spinning nuclear magnetic resonance (MAS NMR) and first-principles calculations were used to investigate the thermal decomposition of the electrolyte in a system consisting of MgV 2 O 4 , a novel cathode for magnesium batteries, mixed with a bulk electrolyte consisting of magnesium bis(trifluoromethanesulfonyl)imide (Mg(TFSI) 2 ) in diglyme (G2). We show that significant electrolyte decomposition is observed in bulk 1.0 M Mg(TFSI) 2 in G2 mixed with nanometer sized MgV 2 O 4 powder at elevated temperatures. This observation is to mimic the possible thermal decomposition that might happen during battery cycling. We demonstrate that the MgV 2 O 4 surface is covered by a layer of decomposed G2 products. We conclude that the dominant reaction pathway for electrolyte decomposition is the thermal decomposition of the pure electrolytes at elevated temperatures, followed by adsorption of G2 decomposition products to the MgV 2 O 4 surface. The activation energy for the major decomposition pathway is obtained. In conclusion, this work highlights the importance of studying thermal decomposition of electrolytes for overall system stability and explores electrolyte stability at significantly elevated temperatures.

25 ENERGY STORAGE↗
DOE OSTI2023

Contrasting geochemical and fungal controls on decomposition of lignin and soil carbon at continental scale

Lignin is an abundant and complex plant polymer that may limit litter decomposition, yet lignin is sometimes a minor constituent of soil organic carbon (SOC). Accounting for diversity in soil characteristics might reconcile this apparent contradiction. Tracking decomposition of a lignin/litter mixture and SOC across different North American mineral soils using lab and field incubations, here we show that cumulative lignin decomposition varies 18-fold among soils and is strongly correlated with bulk litter decomposition, but not SOC decomposition. Climate legacy predicts decomposition in the lab, and impacts of nitrogen availability are minor compared with geochemical and microbial properties. Lignin decomposition increases with some metals and fungal taxa, whereas SOC decomposition decreases with metals and is weakly related with fungi. Decoupling of lignin and SOC decomposition and their contrasting biogeochemical drivers indicate that lignin is not necessarily a bottleneck for SOC decomposition and can explain variable contributions of lignin to SOC among ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Plant roots stimulate the decomposition of complex, but not simple, soil carbon

Roots release carbon into soil and can alleviate energy limitation of microbial organic matter decomposition. We know little about the effects of roots on microbial decomposition of different organic matter substrates, despite the importance for soil carbon stocks and turnover. Through implementing root-microbe interactions, the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model was previously shown to represent dynamics of total soil carbon in temperate forest field experiments. However, the model permits alternative hypotheses concerning microbial-substrate affinity. We investigated how root inputs affect decomposition of soil organic carbon (SOC) with variable decomposability. We simulated SOC stocks in CORPSE and compared microbial degradation of two substrates types with varying root-microbe interactions under two alternative hypotheses that varied in microbial-substrate affinity. We compared our modeled hypotheses to a forest field experiment where we quantified decomposition of isotopically-labeled starch and leaf tissues in soils with manipulated root access to microbes. Here, we tested the hypothesis that decomposition of leaves would be more sensitive to root inputs than decomposition of starch, corresponding to the alternative model hypothesis. In the field study, leaf decomposition increased with root density while starch decomposition was unchanged by root density. Microbial biomass and enzyme activity consistently increased with root inputs in CORPSE and the field study. Our field experiment supported the CORPSE simulations with high microbial-substrate affinity. Roots stimulated microbial growth and enzyme production, which increased degradation of more complex substrates such as leaf tissues. Substrates that were easily decomposed, such as starch, may already be degrading at a maximum rate in the absence of rhizosphere influence because their decomposition rate was unchanged by root inputs. We found that the degree to which roots stimulate microbial decomposition depends on the substrate being decomposed, and that root-microbe interactions influenced SOC stocks in both our model and field experiment. Environmental changes that alter root-microbe interactions could, therefore, alter soil C stocks and biogeochemical cycling, and models of these interactions should incorporate differential influence of rhizosphere inputs on different substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Long-Term Simulated Atmospheric Nitrogen Deposition Alters Leaf and Fine Root Decomposition

Atmospheric nitrogen deposition increases forest carbon sequestration across broad parts of the Northern Hemisphere. Slower organic matter decomposition and greater soil carbon accumulation could contribute to this increase in carbon sequestration. We investigated the effects of chronic simulated nitrogen deposition on leaf litter and fine root decomposition at four sugar maple (Acer saccharum)-dominated northern hardwood forests. At these sites, we previously observed that nitrogen additions increased soil organic carbon and altered litter chemistry. We conducted a 3-year decomposition study with litter bags. Litter production of leaves and fine roots were combined with decomposition dynamics to estimate how fine roots and leaf litter contribute to soil organic carbon. We found that nitrogen additions marginally stimulated early-stage decomposition of leaf litter, an effect associated with previously documented changes in litter chemistry. In contrast, nitrogen additions inhibited the later stages of fine root decomposition, which is consistent with observed decreases in lignin-degrading enzyme activities with nitrogen additions at these sites. At the ecosystem scale, slower fine root decomposition led to additional root mass retention (g m -2 ), and this greater retention of root residues was estimated to explain 5–51% of previously documented carbon accumulation in the surface soil due to nitrogen additions. Our results demonstrated that simulated nitrogen deposition created contrasting effects on the decomposition of leaf litter and fine roots. Although previous nitrogen deposition studies have focused on leaf litter, this work suggests that slower fine root decomposition is a major driver of soil organic carbon accumulation under elevated nitrogen deposition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Root litter decomposition rates and impacts of drought are regulated by ecosystem legacy

In grassland ecosystems, about two-thirds of productivity is in roots, and therefore roots constitute a major soil organic matter input. However, influences on the rate of root litter decomposition remain unresolved, especially in the context of land-use conversion and climate change. Ecosystem legacy can affect root decomposition rates via impacts on substrate chemistry and soil environments, and this may manifest in responses of decomposition to changing temperature and moisture. Here we investigate the impacts of anthropogenic legacy effects and moderate drought on root litter decomposition rates in five "Land Use History Types": crop fields, cow pastures, remnant tallgrass prairie, and prairie restored from crop fields and pastures. We measured root losses of mass, carbon, and nitrogen over 11 months. Further, soil bulk density was unimportant for decomposition, but soil moisture content and temperature were relevant for decomposition rates while time since disturbance predicted decomposition initiation times. Furthermore, soil moisture and temperature dynamics alone could not explain the responses of decomposition rates to drought, which were positively correlated to time since disturbance. Our findings suggest that anthropogenic legacy impacts decomposition rates in grasslands, especially when soil moisture and temperature dynamics are substantially altered, and mediates soil community responses to drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Land-use legacies regulate decomposition dynamics following bioenergy crop conversion

Land-use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land-use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land-use legacies with current management and litter quality. To evaluate how land-use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape-scale litterbag decomposition experiment. We proposed land-use legacies regulate decomposition, but their effects are weakened under higher quality litter and when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.

09 BIOMASS FUELS↗
DOE OSTI2014

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical properties of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Manganese effects on plant residue decomposition and carbon distribution in soil fractions depend on soil nitrogen availability

Recent studies have highlighted the critical role of manganese (Mn) in plant litter decomposition and soil organic carbon (C) cycling in forest ecosystems. Long term nitrogen (N) deposition and N fertilization can increase soil acidity and mobilize bioavailable Mn (Mn 2+ ) in soil. However, no studies have examined the interactive effect of N and Mn fertilization on litter decomposition and carbon distribution in agricultural soils, despite agroecosystems being subject to both N and Mn management. We hypothesized that increased soil N and Mn availability would accelerate plant residue decomposition and transfer of its C to mineral-associated organic matter (MAOM), and that the combined effect of Mn and N enrichment would be greater than the individual effect. Here, we conducted a laboratory incubation experiment by adding 13 C-labeled residue of perennial grass Glyceria striata (Lam.) to agricultural soils that had received 225 kg N ha –1 yr –1 for 27 years (N 1 ) and comparable soils that received no N (N 0 ). Before the experiment, these soils also received three levels of dissolved Mn 2+ , designated M 0 (no additional Mn), M 1 (50 mg kg –1 ), or M 2 (250 mg kg –1 ). We measured total CO 2 production as well as distribution of 13 C from the residue into CO 2 , particulate organic matter (POM), MAOM, and dissolved organic carbon (DOC) over a 1-year period. Manganese amendments significantly increased CO 2 production from residue decomposition in the N 1 soil, but no such effect was observed in the N 0 soil. Manganese also accelerated the loss of residue-derived C from POM and DOC, but increased its recovery in MAOM. However, the positive effect of added Mn in decomposition and recovery in MAOM in the presence of N fertilization occurred only during the initial 30-day decomposition period, where M 2 showed a 12% increase in cumulative CO 2 production from residue, 8% increase in POM loss, and 43% increase in recovery of residue C in MAOM compared to M 0 . For M 1 , only CO 2 emission from residue was significantly higher than Mo during this period. At 365 days M 2 showed 8% increase in CO 2 production, 1% increase in POM loss, and 16% increase in recovery of residue C in MAOM compared to M 0 , but none of these were statistically significant (p < 0.05). This study adds to the growing evidence that increasing Mn availability enhances plant litter decomposition. However, the occurrence and magnitude of Mn-induced stimulation of decomposition is context specific. Further investigation with greater temporal resolution, involving a multitude of litter and soil types and including microbial compositional and functional characterization, is recommended to fully elucidate the interactive role of Mn and N on C cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

High temperature phase decomposition in Ti{sub x}Zr{sub y}Al{sub z}N

Through a combination of theoretical and experimental observations we study the high temperature decomposition behavior of c-(Ti{sub x}Zr{sub y}Al{sub z}N) alloys. We show that for most concentrations the high formation energy of (ZrAl)N causes a strong tendency for spinodal decomposition between ZrN and AlN while other decompositions tendencies are suppressed. In addition we observe that entropic effects due to configurational disorder favor a formation of a stable Zr-rich (TiZr)N phase with increasing temperature. Our calculations also predict that at high temperatures a Zr rich (TiZrAl)N disordered phase should become more resistant against the spinodal decomposition despite its high and positive formation energy due to the specific topology of the free energy surface at the relevant concentrations. Our experimental observations confirm this prediction by showing strong tendency towards decomposition in a Zr-poor sample while a Zr-rich alloy shows a greatly reduced decomposition rate, which is mostly attributable to binodal decomposition processes. This result highlights the importance of considering the second derivative of the free energy, in addition to its absolute value in predicting decomposition trends of thermodynamically unstable alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microwave-induced selective decomposition of cellulose: Computational and experimental mechanistic study

Understanding microwave-material interactions will help facilitate the utilization of microwave technology in gasification and renewable energy production. In this study, cellulose was used as a model compound to simulate the organic matter in biomass, and its catalytic decomposition under a microwave (MW) field was studied to identify structural changes from the reaction. The study was conducted using a MW source coupled to a fixed-bed gas-flow reactor, mass spectroscopic, and Fourier transform infrared spectroscopy post-reaction analysis. Zeolite 13X was chosen as a microwave absorber to study the catalytic enhancement of the decomposition of cellulose. Density functional theory (DFT) was used to gain insights into the molecular transformations occurring in the presence of a static electric field, which was used to simulate the electric field component of the microwave electromagnetic radiation. Theoretical calculations demonstrated that both the positive and negative portion of the electric field interact with the permanent dipoles of the cellulose effecting the decomposition through the glycosidic bond breaking mechanism. The theoretical result was verified using infrared spectroscopic analysis of the pure cellulose during microwave heating. The theoretical calculations suggest only the positive electric field component may be active for the cellulose decomposition in the presence of Zeolite 13X. Physically mixing Zeolite 13X with the cellulose led to a significant enhancement in the decomposition rate of the glycosidic bond. Zeolite 13X enhanced the glycosidic O-C decomposition at lower MW power (lower temperatures), whereas the O-H functional group required higher MW power (higher temperature) for its decomposition. The DFT study coupled with the reaction studies revealed that the electric field polarizability is dependent upon both the direction and the orientation of the cellulose. Gas products revealed that applying 250 W of MW power led to the production of CO, H 2 , along with some CO 2 , CH 4 , and benzene at 305 °C. Finally, reaction under 500, 750, and 1000 W of power at constant temperature (305 °C) revealed that higher power led to the complete decomposition of cellulose to mostly CO, H 2 , and CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Modern insights into the mechanisms of neptunium oxalate decomposition

Neptunium oxalate (Np(C 2 O 4 ) 2 ·6H 2 O) is a historically relevant solid phase used in nuclear processing as a precursor for neptunium dioxide (NpO 2 ). Although Np oxalate has been synthesized and used for NpO 2 production for decades, the thermal decomposition mechanism of this phase remains poorly understood and has not been evaluated in over 30 years. Conflicting reports in historical literature suggest either a direct conversion from anhydrous oxalate to NpO 2 or a decomposition that includes the formation of Np carbonate or oxidized Np intermediate phases. In this work, we reexamine the decomposition pathway of Np(C 2 O 4 ) 2 ·6H 2 O using thermal analysis coupled with evolved gas analysis and temperature-dependent Raman spectroscopy to elucidate decomposition mechanisms and intermediate phases using modern analytical techniques. Thermal analysis revealed a three-stage decomposition process, including dehydration below 200 °C, oxalate breakdown between 170 and 370 °C, and NpO 2 formation by 500 °C. However, an unidentified plateau in the thermal data was observed during measurements. Raman spectroscopy confirmed the stages of decomposition, and in the analysis of potential intermediate phases, no carbonate phases or Np 2 O 5 were identified. Raman data suggest that residual oxalate or nonstoichiometric oxide are present during decomposition before pure NpO 2 is formed. These findings clarify aspects of the Np oxalate decomposition mechanism and address longstanding discrepancies in the literature, with a specific focus on Np-specific materials chemistry.

Lawson, Kathryn M. [Oak Ridge National Laboratory ↗
DOE OSTI2015

THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S{sup 4}G): MULTI-COMPONENT DECOMPOSITION STRATEGIES AND DATA RELEASE

The Spitzer Survey of Stellar Structure in Galaxies (S{sup 4}G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S{sup 4}G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G-PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK-EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Plants mediate soil organic matter decomposition in response to sea level rise

Abstract Tidal marshes have a large capacity for producing and storing organic matter, making their role in the global carbon budget disproportionate to land area. Most of the organic matter stored in these systems is in soils where it contributes 2–5 times more to surface accretion than an equal mass of minerals. Soil organic matter ( SOM ) sequestration is the primary process by which tidal marshes become perched high in the tidal frame, decreasing their vulnerability to accelerated relative sea level rise ( RSLR ). Plant growth responses to RSLR are well understood and represented in century‐scale forecast models of soil surface elevation change. We understand far less about the response of SOM decomposition to accelerated RSLR . Here we quantified the effects of flooding depth and duration on SOM decomposition by exposing planted and unplanted field‐based mesocosms to experimentally manipulated relative sea level over two consecutive growing seasons. SOM decomposition was quantified as CO 2 efflux, with plant‐ and SOM ‐derived CO 2 separated via δ 13 CO 2 . Despite the dominant paradigm that decomposition rates are inversely related to flooding, SOM decomposition in the absence of plants was not sensitive to flooding depth and duration. The presence of plants had a dramatic effect on SOM decomposition, increasing SOM ‐derived CO 2 flux by up to 267% and 125% (in 2012 and 2013, respectively) compared to unplanted controls in the two growing seasons. Furthermore, plant stimulation of SOM decomposition was strongly and positively related to plant biomass and in particular aboveground biomass. We conclude that SOM decomposition rates are not directly driven by relative sea level and its effect on oxygen diffusion through soil, but indirectly by plant responses to relative sea level. If this result applies more generally to tidal wetlands, it has important implications for models of SOM accumulation and surface elevation change in response to accelerated RSLR .

Mueller, Peter↗
DOE OSTI2014

TU-F-18A-02: Iterative Image-Domain Decomposition for Dual-Energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗