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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Arrhenius Analysis of the Degradation Modes in Emerging Photovoltaic Backsheets

With increasingly large-scale deployments of photovoltaic (PV) modules to meet global energy demands, interest in better establishing modules' lifespans is growing. We report on the performance of co-extruded polyolefin- (PO)-based backsheets as environmentally friendly alternatives to fluoropolymer-reinforced polyethylene-terephthalate (PET)-based backsheets using three hygrometric accelerated test conditions. After completing cumulative 4000 hours of aging, we analyzed data from electrical performance (I-V), surface roughness (gloss), and appearance (L, a*, b* color) characterizations to quantify degradation rates, quantify the corresponding activation energy, and cross-correlate between the characteristics examined, thereby providing insights into the relationship between physical characteristics and operating performance.

BackFLIP↗
DOE OSTI2024

Assessment of Training Performance, Degradation and Robustness of Paraffin-Wax Impregnated Nb 3 Sn Demonstrator Under High Magnetic Field

In the context of high-energy physics, the use of Nb 3 Sn superconducting magnets as a cost-effective and reliable technology depends on improvements in the following areas: long development and manufacturing cycles, conductor degradation after thermal cycling, long training, as well as a demonstration in accelerator magnets with a beam aperture of the full potential of modern Nb 3 Sn conductors. In short, performance, robustness, and cost are the three issues to be addressed. The Magnet Development project (MagDev) of the Swiss Accelerator Research and Technology initiative (CHART) at the Paul Scherrer Institute (PSI) aims to contribute to the solutions to each of these issues, re-thinking the manufacturing and design process. Here in our program, every innovation is to be validated by means of a panoply of fast-turnaround tools: from non-powered and powered samples and coils, tested under background field, to low-field subscale magnets and high field short prototypes. This work presents one element in this panoply of R&D vehicles: a stress-managed Nb 3 Sn coil called BigBOX, impregnated with paraffin wax, and tested, through a collaboration with the Magnet Development Program of the United States (US-MDP), in the background field of Brookhaven National Laboratory (BNL)’s common coils dipole DCC17.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Predominance of Methanomicrobiales and diverse hydrocarbon–degrading taxa in the Appalachian coalbed biosphere revealed through metagenomics and genome–resolved metabolisms

Coalbed deposits are a unique subsurface environment and represent an underutilized resource for methane generation. Microbial communities extant in coalbed deposits are responsible for key subsurface biogeochemical cycling and could be utilized to enhance methane production in areas where existing gas wells have depleted methane stores, or in coalbeds that are unmined, or conversely be utilized for mitigation of methane release. Here we utilize metagenomics and metagenome-assembled genomes to identify extant microbial lineages and genome-resolved microbial metabolisms of coalbed produced water, which has not yet been explored in the Appalachian Basin. Our analyses resulted in the recovery of over 40 metagenome-assembled genomes (MAGs) from eight coalbed methane wells. The most commonly identified taxa among samples were hydrogenotrophic methanogens from the order Methanomicrobiales and these dominant MAGs were highly similar to one another. Conversely, low-abundance coalbed bacterial populations were taxonomically and functionally diverse, mostly belonging to a variety of Proteobacteria classes, and encoding various hydrocarbon solubilization and degradation pathways. Further, the data presented herein provides novel insights into Appalachian Basin coalbed microbial ecology, and our findings provide new perspectives on underrepresented Methanocalculus species and low-relative abundance bacterial assemblages in coalbed environments, and their potential roles in stimulation or mitigation of methane release.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Unravelling the Glycan Code: Molecular Dynamics and Quantum Chemistry Reveal How O-Glycan Functional Groups Govern OgpA Selectivity in Mucin Degradation by Akkermansia muciniphila

Mucins, heavily O-glycosylated glycoproteins, are a key component of mucus, and certain gut microbiota, including Akkermansia muciniphila , can utilise mucin glycans as a carbon source. Akkermansia muciniphila produces the O-glycopeptidase enzyme OgpA, which cleaves peptide bonds at the N-terminus of serine (Ser) or threonine (Thr) residues carrying O-glycan substitutions, with selectivity influenced by the O-glycan functional groups. Using molecular dynamics (MD) simulations and quantum chemistry calculations, we explored how different O-glycan groups affect OgpA's selectivity. Our results show that peptides bind to the enzyme via hydrogen bonds, π–π interactions, van der Waals forces and electrostatic interactions, with key residues, including Tyr90, Val138, Gly176, Tyr210 and Glu91, playing important roles. The primary determinant of selectivity is the interaction between the peptide's functional group and the enzyme's binding cavity, while peptide–enzyme interface interactions are secondary. Quantum chemistry calculations reveal that OgpA prefers peptides with a lower electrophilic character. This study provides new insights into mucin degradation by gut microbiota enzymes, advancing our understanding of this critical biological process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Warming and elevated CO 2 promote rapid incorporation and degradation of plant‐derived organic matter in an ombrotrophic peatland

Abstract Rising temperatures have the potential to directly affect carbon cycling in peatlands by enhancing organic matter (OM) decomposition, contributing to the release of CO 2 and CH 4 to the atmosphere. In turn, increasing atmospheric CO 2 concentration may stimulate photosynthesis, potentially increasing plant litter inputs belowground and transferring carbon from the atmosphere into terrestrial ecosystems. Key questions remain about the magnitude and rate of these interacting and opposing environmental change drivers. Here, we assess the incorporation and degradation of plant‐ and microbe‐derived OM in an ombrotrophic peatland after 4 years of whole‐ecosystem warming (+0, +2.25, +4.5, +6.75 and +9°C) and two years of elevated CO 2 manipulation (500 ppm above ambient). We show that OM molecular composition was substantially altered in the aerobic acrotelm, highlighting the sensitivity of acrotelm carbon to rising temperatures and atmospheric CO 2 concentration. While warming accelerated OM decomposition under ambient CO 2 , new carbon incorporation into peat increased in warming × elevated CO 2 treatments for both plant‐ and microbe‐derived OM. Using the isotopic signature of the applied CO 2 enrichment as a label for recently photosynthesized OM, our data demonstrate that new plant inputs have been rapidly incorporated into peat carbon. Our results suggest that under current hydrological conditions, rising temperatures and atmospheric CO 2 levels will likely offset each other in boreal peatlands.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cell‐ and development‐specific degradation controls the levels of mixed‐linkage glucan in sorghum leaves

SUMMARY Mixed‐linkage glucan (MLG) is a component of the cell wall (CW) of grasses and is composed of glucose monomers linked by β‐1,3 and β‐1,4 bonds. MLG is believed to have several biological functions, such as the mobilizable storage of carbohydrates and structural support of the CW. The extracellular levels of MLG are largely controlled by rates of synthesis mediated by cellulose synthase‐like (CSL) enzymes, and turnover by lichenases. Economically important crops like sorghum accumulate MLG to variable levels during development. While in sorghum, like other grasses, there is one major MLG synthase (CSLF6), the identity of lichenases is yet unknown. To fill this gap, we identified three sorghum lichenases (SbLCH1‐3) and characterized them in leaves in relation to the expression of SbCSLF6 , and the abundance of MLG and starch. We established that SbLCH1‐3 are secreted to the apoplast, consistent with a role of degrading MLG extracellularly. Furthermore, while SbCSLF6 expression was associated with cell development, the SbLCH genes exhibited distinct development‐, cell‐type‐specific and diel‐regulated expression. Therefore, our study identifies three functional sorghum MLG lichenases and highlights that MLG accumulation in sorghum leaves is likely controlled by the activity of lichenases that tune MLG levels, possibly to suit distinct cell and developmental needs in planta . These findings have important implications for improving the growth, yield, and composition of sorghum as a feedstock.

Plant Sciences↗
DOE OSTI2024

Mechanical Properties of Irradiated U-10 wt. %Mo Alloy Degraded by Porosity Development

In this study, a plate-type nuclear fuel consisting of a solid monolithic foil of U-10 wt. %Mo is under development for use in the United States' high-performance research reactors. In support of developing this fuel, the fuel has been fabricated for the first time by a commercial fuel vendor and subsequently irradiated in a test reactor. This provides an opportunity to evaluate postirradiation mechanical properties of the commercially fabricated fuel. Four-point bend testing was conducted on the irradiated U-10Mo samples to generate the fuel material properties, including the modulus of elasticity and the bending strength. Although the material behaves in a brittle manner due to the accumulated porosity, a general trend of strength and modulus reduction was found as fission density increases. The data produced was evaluated using both Weibull statistics and a modulus degradation model with recommendations provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Data Driven Approach to Analyzing The Impact of Power Plant Cycling on Air Preheater Degradation and Remaining Useful Life

Due to the increased penetration of renewable energy generation sources, and fluctuations of the oil and gas prices, modern coal burning power plants deal with increased variability in the demand for power generation. These varying demands result in their intermittent under-capacity operation (cycling). Periodical ramping down and back up to follow the daily power demands causes damages to the plant components reducing its operational life. In this paper we analyze the impact of cycling on a rotary Ljungstrom air preheater (APH) unit installed at a coal fire power plant in the US. An inefficient air preheater can significantly impact boiler performance. Due to the repeated boiler’s hot-cold start, the APH experiences fluctuating operating conditions that result in accelerated degradation mechanisms, such as dew-point corrosion, fouling/deposition plugging, and air heater leakage. The analysis in this paper utilizes field data related to APH basket replacement, and the number of cycles experienced by the boiler to model the life expectancy of the baskets. The data-driven model enables preventive maintenance strategies for the APH by predicting how long the APH baskets will last in a probabilistic sense. Furthermore, the analysis showed that an increase in cycling for a fixed operation time can reduce the APH basket remaining useful life by about 30%.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Volcanic forcing degrades multiyear-to-decadal prediction skill in the tropical Pacific

Volcanic aerosol forcing can affect global climate, but its role in climate prediction remains poorly understood. We isolate the impact of volcanic eruptions on multiyear-to-decadal climate prediction skill by comparing two suites of initialized decadal hindcasts conducted with and without historical volcanic forcing. Unexpectedly, the inclusion of volcanic forcing in the prediction system significantly degrades the forecast skill of detrended multiyear-to-decadal sea surface temperature (SST) variability in the central-eastern tropical Pacific. The ensemble mean hindcasts produce multiyear-to-decadal tropical Pacific SST cooling in response to large tropical volcanic eruptions through thermodynamic and El Niño–Southern Oscillation (ENSO)–like dynamic processes. However, in observations, these eruptions coincided with tropical Pacific warming, which is well predicted by the no-volcano hindcasts and, hence, is likely related to internal climate variability. Improved model representation of volcanic response and its interaction with internal climate variability is required to advance prediction of tropical Pacific decadal variability and associated global impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Co-expression of a β-d-xylosidase from Thermotoga maritima and a Family 10 xylanase from A. cellulolyticus significantly improves the xylan degrading activity of the Caldicellulosiruptor bescii exoproteome

Caldicellulosiruptor species are hyperthermophilic, Gram-positive, anaerobes and the most thermophilic cellulolytic bacteria so far described. They have been engineered to convert switchgrass to ethanol without pretreatment and represent a promising platform for the production of fuels, chemicals and materials from plant biomass. Xylooligomers such as xylobiose and xylotriose that result from the breakdown of plant biomass more strongly inhibit cellulase activity than do glucose or cellobiose. High concentrations of xylobiose and xylotriose, are present in C. bescii fermentations after 90 h incubation and removal or breakdown of these types of xylooligomers is crucial to achieve high conversion of plant biomass to product. In previous studies the addition of exogenous β-d-xylosidase substantially improved the performance of glucanases and xylanases in vitro. β-d-Xylosidases are, in fact, essential enzymes in commercial preparations for efficient deconstruction of plant biomass. In addition, the combination of xylanase and β-d-xylosidase is known to exhibit synergistic action on xylan degradation. In spite of its ability to grow efficiently on xylan substrates, no extracellular β-d-xylosidase was identified in the C. bescii genome. Here we report that the co-expression of a thermal stable β-d-xylosidase from Thermotoga maritima and a xylanase from Acidothermus cellulolyticus in a C. bescii strain containing the A. cellulolyticus E1 endoglucanase significantly increased the activity of the exoproteome as well as growth on xylan substrates. The combination of these enzymes also resulted in increased growth on crystalline cellulose in the presence of exogeneous xylan.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Reduction of a Heme Cofactor Initiates N -Nitroglycine Degradation by NnlA

Linear nitramines are potentially carcinogenic environmental contaminants. The NnlA enzyme from Variovorax sp. strain JS1663 degrades the nitramine N-nitroglycine (NNG)—a natural product produced by some bacteria—to glyoxylate and nitrite (NO 2 –). Ammonium (NH 4 +) was predicted as the third product of this reaction. A source of nonheme Fe II was shown to be required for initiation of NnlA activity. However, the role of this Fe II for NnlA activity was unclear. This work reveals that NnlA contains a b-type heme cofactor. Reduction of this heme—either by a nonheme iron source or dithionite—is required to initiate NnlA activity. Therefore, Fe II is not an essential substrate for holoenzyme activity. Our data show that reduced NnlA (Fe II -NnlA) catalyzes at least 100 turnovers and does not require O 2 . Finally, NH 4 + was verified as the third product, accounting for the complete nitrogen mass balance. Size exclusion chromatography showed that NnlA is a dimer in solution. Additionally, Fe II -NnlA is oxidized by O 2 and NO 2 – and stably binds carbon monoxide (CO) and nitric oxide (NO). These are characteristics shared with heme-binding PAS domains. Furthermore, a structural homology model of NnlA was generated using the PAS domain from Pseudomonas aeruginosa Aer2 as a template. The structural homology model suggested His 73 is the axial ligand of the NnlA heme. Site-directed mutagenesis of His 73 to alanine decreased the heme occupancy of NnlA and eliminated NNG activity, validating the homology model. We conclude that NnlA forms a homodimeric heme-binding PAS domain protein that requires reduction for initiation of the activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cross-Feedings, Competition, and Positive and Negative Synergies in a Four-Species Synthetic Community for Anaerobic Degradation of Cellulose to Methane

A synthetic community was designed using four microbial species that together performed distinct key metabolic processes in the anaerobic degradation of cellulose to methane and CO 2 . The microorganisms exhibited expected interactions, such as cross-feeding of acetate from a cellulolytic bacterium to an acetoclastic methanogen and competition of H 2 between a sulfate reducing bacterium and a hydrogenotrophic methanogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metabolomics Highlights Different Life History Strategies of White and Brown Rot Wood-Degrading Fungi

Despite the ecological and economic importance of wood-degrading fungi, little is known about the array of metabolites that fungi produce during wood decomposition. This study provides an in-depth insight into the wood decomposition process by analyzing and comparing the changes of >100 compounds produced by fungi with metabolic distinct nutritional modes (white and brown rot fungi) at different decay stages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Parameter Estimation for Electrode Degradation: Learning in the Face of Model-Experiment Discrepancies

Use of physics-based models to interpret battery degradation data over the course of cycling can provide deeper physical insight into the internal states of the system and how they evolve. We present a neural network trained on simulations generated by a previously published physics-based model for a lithium trivanadate (LVO) cathode to estimate parameters that evolve over the course of cycling. We focus on the robustness of the neural network through two case studies that probe different kinds of discrepancies between model and experiment: nonideal data and imperfect model. In the former, the experimental protocols do not meet the assumption made in the training data generated by the physics-based model, while in the latter, the physics-based model fails to describe all of the measured cathode behavior even under ideal conditions. When there is total model-experiment agreement, a neural network estimates parameters with improved accuracy compared to a maximum likelihood analysis using the same set of simulations. However, in both types of model-experiment discrepancy, the neural network returned biased parameter estimates. We introduce a data augmentation procedure into the neural network training to mitigate these effects and improve robustness, and employ it to estimate parameters for a cycling LVO cathode.

Mayilvahanan, Karthik S. (ORCID:0000000316282332)↗
DOE OSTI2022

Investigating the Particle Growth in Bimodal Pt/C Catalysts by In-Situ Small-Angle X-ray Scattering: Challenges in the Evaluation of Stress Test Protocol-Dependent Degradation Mechanisms

The influence of different combinations of accelerated stress test (AST) protocols simulating load-cycle and start/stop conditions of a proton exchange membrane fuel cell (PEMFC) vehicle is investigated on a bimodal Pt/C catalyst. The bimodal Pt/C catalyst, prepared by mixing two commercial catalysts, serves as a model system and consists of two distinguishable size populations. The change in mean particle size was investigated by in situ small-angle X-ray scattering (SAXS). The comparison to the reference catalysts, i.e., the two single-size population catalysts, uncovers the presence of electrochemical Ostwald ripening as a degradation mechanism in the bimodal catalyst. Increasing the harshness of the applied AST protocol combinations by faster changing between load-cycle or start/stop conditions, the particle size of the larger population of the bimodal catalyst increases faster than expected. Surprisingly, the change in mean particle size of the smaller size population indicates a smaller increase for harsher AST protocols, which might be explained by a substantial electrochemical Ostwald ripening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗