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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH 4 ) emissions; however, no earth system model (ESM) has represented lake CH 4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH 4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH 4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH 4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH 4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH 4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH 4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH 4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH 4 outgassing events in non‐floodplain lakes and the seasonal variability of CH 4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH 4 emissions and climate‐CH 4 feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Electrolytic Methane Production from Reactive Carbon Solutions

Here, we report an electrochemical reactor that converts 3.0 M KHCO 3 into methane at the cathode, and oxidizes water at the anode. The molar ratio of methane product to unreacted CO 2 gas (defined herein as "methane yield") was measured to be 34% at a partial current density of 120 mA cm -2 . The highest previously reported CO 2 -to-methane yield is 3%. Our reactor achieved this improvement in methane yield because it is fed with 3.0 M KHCO 3 , a type of reactive carbon solution, rather than gaseous CO 2 . The reactor uses H + delivered by a bipolar membrane to form CO 2 at the cathode. This CO 2 is subsequently reduced into methane. A cationic surfactant added to the catholyte suppressed hydrogen evolution and increased methane formation. A 1D continuum model confirmed that H + from the membrane promotes the formation of methane over multicarbon products at the cathode. These findings present design principles for electrochemical methane synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Dynamic Tracking of NiFe Smart Catalysts using In Situ X-Ray Absorption Spectroscopy for the Dry Methane Reforming Reaction

The exsolution of nanoparticles from perovskite precursors has been explored as a route to synthesize catalysts with sinter or coke resistance. The characteristics of these exsolved nanoparticles are highly dynamic depending on the redox nature of the environment to which they are subjected. To develop their properties for thermo- and electrocatalytic applications, it is necessary to track the states and behavior of exsolved catalysts with in situ and ex situ characterization. In this study, we conduct in situ X-ray absorption spectroscopy (XAS) along with ex situ scanning transmission electron microscopy high-angle annular dark-field (STEM-HAADF) and energy-dispersive X-ray spectroscopy analysis of the parent perovskite oxide precursor, LaFe 0.8 Ni 0.2 O 3 , as its structure forms bimetallic NiFe nanoparticles and evolves in oxidative, reductive, and dry methane reforming environments. We develop a theory that NiFe exsolution is a function of the reduction potential where LaFe 0.8 Ni 0.2 O 3 transforms to NiFe alloy supported on LaO x -LaFeO x . The Ni starts to exsolve at 268 °C, while most Fe exsolves at 700 °C. During dry methane reforming conditions, most of the Fe is oxidized by CO 2 during the reaction and re-enters the perovskite as LaFeO 3 , while Ni remains on the surface as nanoparticles in the metallic state. During the oxidative regeneration phase, most of the Fe re-enters the bulk perovskite phase, while Ni is partially regenerated with a small percentage oxidized to large NiO nanoparticles. Finally, this study sheds light on the exsolution and regeneration of bimetallic alloy nanoparticles and the influence of the reaction conditions on their catalyst performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Microbial functional genes commonly respond to elevated carbon dioxide

Atmospheric CO 2 concentration is increasing, largely due to anthropogenic activities. Previous studies of individual free-air CO 2 enrichment (FACE) experimental sites have shown significant impacts of elevated CO 2 (eCO 2 ) on soil microbial communities; however, no common microbial response patterns have yet emerged, challenging our ability to predict ecosystem functioning and sustainability in the future eCO 2 environment. Here we analyzed 66 soil microbial communities from five FACE sites, and showed common microbial response patterns to eCO 2 , especially for key functional genes involved in carbon and nitrogen fixation (e.g., pcc/acc for carbon fixation, nifH for nitrogen fixation), carbon decomposition (e.g., amyA and pulA for labile carbon decomposition, mnp and lcc for recalcitrant carbon decomposition), and greenhouse gas emissions (e.g., mcrA for methane production, norB for nitrous oxide production) across five FACE sites. Also, the relative abundance of those key genes was generally increased and directionally associated with increased biomass, soil carbon decomposition, and soil moisture. In addition, a further literature survey of more disparate FACE experimental sites indicated increased biomass, soil carbon decay, nitrogen fixation, methane and nitrous oxide emissions, plant and soil carbon and nitrogen under eCO 2 . A conceptual framework was developed to link commonly responsive functional genes with ecosystem processes, such as pcc/acc vs. soil carbon storage, amyA/pulA/mnp/lcc vs. soil carbon decomposition, and nifH vs. nitrogen availability, suggesting that such common responses of microbial functional genes may have the potential to predict ecosystem functioning and sustainability in the future eCO 2 environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Soil gas probes for monitoring trace gas messengers of microbial activity

Abstract Soil microbes vigorously produce and consume gases that reflect active soil biogeochemical processes. Soil gas measurements are therefore a powerful tool to monitor microbial activity. Yet, the majority of soil gases lack non-disruptive subsurface measurement methods at spatiotemporal scales relevant to microbial processes and soil structure. To address this need, we developed a soil gas sampling system that uses novel diffusive soil probes and sample transfer approaches for high-resolution sampling from discrete subsurface regions. Probe sampling requires transferring soil gas samples to above-ground gas analyzers where concentrations and isotopologues are measured. Obtaining representative soil gas samples has historically required balancing disruption to soil gas composition with measurement frequency and analyzer volume demand. These considerations have limited attempts to quantify trace gas spatial concentration gradients and heterogeneity at scales relevant to the soil microbiome. Here, we describe our new flexible diffusive probe sampling system integrated with a modified, reduced volume trace gas analyzer and demonstrate its application for subsurface monitoring of biogeochemical cycling of nitrous oxide (N 2 O) and its site-specific isotopologues, methane, carbon dioxide, and nitric oxide in controlled soil columns. The sampling system observed reproducible responses of soil gas concentrations to manipulations of soil nutrients and redox state, providing a new window into the microbial response to these key environmental forcings. Using site-specific N 2 O isotopologues as indicators of microbial processes, we constrain the dynamics of in situ microbial activity. Unlocking trace gas messengers of microbial activity will complement -omics approaches, challenge subsurface models, and improve understanding of soil heterogeneity to disentangle interactive processes in the subsurface biome.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗
DOE OSTI2023

Inhibition of nitrous oxide reduction in forest soil microcosms by different forms of methanobactin

Copper plays a critical role in controlling greenhouse gas emissions as it is a key component of the particulate methane monooxygenase and nitrous oxide reductase. Some methanotrophs excrete methanobactin (MB) that has an extremely high copper affinity. As a result, MB may limit the ability of other microbes to gather copper, thereby decreasing their activity as well as impacting microbial community composition. Here, we show using forest soil microcosms that multiple forms of MB; MB from Methylosinus trichosporium OB3b (MB-OB3b) and MB from Methylocystis sp. strain SB2 (MB-SB2) increased nitrous oxide (N 2 O) production as well caused significant shifts in microbial community composition. Such effects, however, were mediated by the amount of copper in the soils, with low-copper soil microcosms showing the strongest response to MB. Furthermore, MB-SB2 had a stronger effect, likely due to its higher affinity for copper. The presence of either form of MB also inhibited nitrite reduction and generally increased the presence of genes encoding for the iron-containing nitrite reductase (nirS) over the copper-dependent nitrite reductase (nirK). Lastly, these data indicate the methanotrophic-mediated production of MB can significantly impact multiple steps of denitrification, as well as have broad effects on microbial community composition of forest soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explorations of the nonheme high-valent iron-oxo landscape: crystal structure of a synthetic complex with an [Fe IV 2 (μ-O) 2 ] diamond core relevant to the chemistry of sMMOH

Methanotrophic bacteria utilize methane monooxygenase (MMO) to carry out the first step in metabolizing methane. The soluble enzymes employ a hydroxylase component (sMMOH) with a nonheme diiron active site that activates O 2 and generates a powerful oxidant capable of converting methane to methanol. It is proposed that the diiron(II) center in the reduced enzyme reacts with O 2 to generate a diferric-peroxo intermediate called P that then undergoes O–O cleavage to convert into a diiron(IV) derivative called Q, which carries out methane hydroxylation. Most (but not all) of the spectroscopic data of Q accumulated by various groups to date favor the presence of an Fe IV 2 (μ-O) 2 unit with a diamond core. The Que lab has had a long-term interest in making synthetic analogs of iron enzyme intermediates. To this end, the first crystal structure of a complex with a Fe III Fe IV (μ-O) 2 diamond core was reported in 1999, which exhibited an Fe∙∙∙Fe distance of 2.683(1) Å. Now more than 20 years later, a complex with an Fe IV 2 (μ-O) 2 diamond core has been synthesized in sufficient purity to allow diffraction-quality crystals to be grown. Finally, its crystal structure has been solved, revealing an Fe∙∙∙Fe distance of 2.711(4) Å for comparison with structural data for related complexes with lower iron oxidation states.

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

Tethered oxygen turns methane into methanol

Precise control of the oxidant — that is, preventing overoxidation — is the missing link in low-temperature methane upgrading. Now, the electro-splitting of carbonate on rutile IrO 2 is shown to cover the surface with on-top oxygen adatoms that act as tethered, single-step hydrogen abstractors. One subset can pull the hydrogen from methane to form a methoxy intermediate, while the neighbouring site can protonate this intermediate to form methanol. Together, this mechanism delivers a room-temperature conversion of methane to methanol with >90% selectivity.

climate-change mitigation↗
DOE OSTI2024

In-Situ Species Concentration Measurements In Ammonia-Mix Flames Using Ftir Spectroscopy

Hydrogen and ammonia represent two carbon-free fuel sources that could be used in place of current fossil energy sources in combustion systems. To develop optimized ammonia combustion systems, validated modeling tools are needed. In the open literature, it has been shown that the complex chemistry associated with fuel-bound nitrogen contained in ammonia differs greatly from natural gas or hydrogen combustion. As a result, several new chemical kinetic mechanisms have been developed. Many of these mechanisms have been validated experimentally, however this has primarily focused on bulk parameters such as laminar flame speed and ignition delay time. Critically, high quality measurements of species concentrations are needed under controlled conditions which are easily represented by simple models. In this paper, direct, in-situ measurements of species concentrations and gas temperature are performed in a laminar flat-flame burner. This arrangement enables comparison with 1D model predictions, better isolating chemical kinetics from the fluid dynamics. Quantitative species concentrations are determined by absorption spectroscopy using an FTIR spectrometer. Fuel compositions representative of cracked ammonia (NH 3 /H 2 ) and ammonia-natural gas (NH 3 /CH 4 ) are considered for rich and lean equivalence ratios. A major focus of the paper is on the selection of spectral features for nitric oxide and ammonia and correcting for large amounts of baseline H 2 O absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying Drivers of Methane Hydrobiogeochemistry in a Tidal River Floodplain System

The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine learning (ML) framework to identify and rank the most influential processes, properties, and conditions controlling methane behavior in a freshwater floodplain responding to recently restored seawater inundation. Our unique multivariate, multiyear, and multi-site dataset comprises tidal creek and floodplain porewater observations encompassing water level, salinity, pH, temperature, dissolved oxygen (DO), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), partial pressure of carbon dioxide (pCO 2 ), nitrous oxide (pN 2 O), methane (pCH 4 ), and the stable isotopic composition of methane (δ 13 CH 4 ). Additionally, we incorporated topographical data, soil porosity, hydraulic conductivity, and water retention parameters for UQ analysis using a previously developed 3D variably saturated flow and transport floodplain model for a physical mechanistic understanding of factors influencing groundwater levels and salinity and, therefore, CH 4 . Principal component analysis revealed that groundwater level and salinity are the most significant predictors of overall biogeochemical variability. The ensemble ML models and UQ analyses identified DO, water level, salinity, and temperature as the most influential factors for porewater methane levels and indicated that approximately 80% of the total variability in hourly water levels and around 60% of the total variability in hourly salinity can be explained by permeability, creek water level, and two van Genuchten water retention function parameters: the air-entry suction parameter α and the pore size distribution parameter m. These findings provide insights on the physicochemical factors in methane behavior in coastal ecosystems and their representation in local- to global-scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Oxidation of alkanes to alcohols

The invention provides processes and materials for the efficient and cost-effective functionalization of alkanes, such as methane from natural gas, to provide esters, alcohols, and other compounds. The method can be used to produce liquid fuels such as methanol from a natural gas methane-containing feedstock. The soft oxidizing electrophile, a compound of a main group, post-transitional element such as Tl, Pb, Bi, and I, that reacts to activate the alkane C—H bond can be regenerated using inexpensive regenerants such as hydrogen peroxide, oxygen, halogens, nitric acid, etc. Main group compounds useful for carrying out this reaction includes haloacetate salts of metals having a pair of available oxidation states, such as Tl, Pb, Bi, and I. The inventors herein believe that a unifying feature of many of the MXn electrophiles useful in carrying out this reaction, such as Tl, Pb, and Bi species, is their isoelectronic configuration in the alkane-reactive oxidation state; the electrons having the configuration [Xe]4f145d10, with an empty 6s orbital. However, the iodine reagents have a different electronic configuration.

09 BIOMASS FUELS↗
DOE OSTI2023

Transport Mediating Core–Shell Photocatalyst Architecture for Selective Alkane Oxidation

The high activation barrier of the C-H bond in methane, combined with the high propensity of methanol and other liquid oxygenates toward overoxidation to CO 2 , have historically posed significant scientific and industrial challenges to the selective and direct conversion of methane to energy-dense fuels and chemical feedstocks. Here, we report a unique core-shell nanostructured photocatalyst, silica encapsulated TiO 2 decorated with AuPd nanoparticles (TiO 2 @SiO 2 -AuPd), that prevents methanol overoxidation on its surface and possesses high selectivity and yield of oxygenates even at high UV intensity. This room-temperature approach achieves high selectivity for oxygenates (94.5%) with a total oxygenate yield of 15.4 mmol/g cat ·h at 9.65 bar total pressure of CH 4 and O 2 . The working principles of this core-shell photocatalyst were also systematically investigated. Finally, this design concept was further demonstrated to be generalizable for the selective oxidation of other alkanes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Longwave infrared (6.6–11.4 µm) dual-comb spectroscopy with 240,000 comb-mode-resolved data points at video rate

Using sub-3-cycle pulses from mode-locked Cr:ZnS lasers at λ ≈ 2.4 µm as a driving source, we performed high-resolution dual-frequency-comb spectroscopy in the longwave infrared (LWIR) range. A duo of highly coherent broadband (6.6–11.4 µm) frequency combs were produced via intrapulse difference frequency generation in zinc germanium phosphide (ZGP) crystals. Fast (up to 0.1 s per spectrum) acquisition of 240,000 comb-mode-resolved data points, spaced by 80 MHz and referenced to a Rb clock, was demonstrated, resulting in metrology grade molecular spectra of N 2 O (nitrous oxide) and CH 3 OH (methane). The key to high-speed massive spectral data acquisition was low intensity and phase noise of the LWIR combs and high (7.5%) downconversion efficiency, resulting in a LWIR power of 300 mW for each comb.

Vasilyev, Sergey (ORCID:0000000225203547)↗
DOE OSTI2022

Investigation of the Mechanisms Underpinning Plasma-Catalyst Interaction for the Conversion of Methane to Oxygenates

Plasma catalysis is a promising approach to further enhance the conversion of methane into value-added products such as methanol. In this work, the mechanisms enabling the conversion of methane to CO, CO 2 and methanol enabled by plasma-enhanced catalysis were investigated. A catalyst reactor was incorporated downstream of the plasma jet to enable the separation between plasma generation and the catalyst bed. An enhancement in CH 3 OH and CO 2 production was observed for the shortest distance between the plasma and catalyst compared to the plasma-only case. Plasma-enabled gas heating was shown not to be responsible for the observed synergy while a gas temperature increase as low as 30-40 K significantly impacted desorption rates of CH 3 OH/C 2 H 5 OH on alumina particles. Correlations between molecular beam mass spectrometry (MBMS) measurements at the inlet and outlet of the catalytic reactor suggest that the observed synergistic effect was caused by radical species most likely the CH 3 O 2 radical. As a result, this study shows that surface reactions induced by radicals such as alkylperoxy radicals might play an important role in surface reactions in plasma-catalysis.

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

C3MechLite: An integrated component library of compact kinetic mechanisms for low-carbon, carbon neutral and zero-carbon fuels

Based on our latest detailed chemical reaction mechanism, C3MechV4.0, we have developed two reduced reaction mechanisms—C3MechLite and C3MechCore—targeting C 0 –C 3 chemical species including NH 3 . C3MechLite (61 species), contains a number of species comparable to GRI-Mech (53 species), that can accurately predict the combustion characteristics of hydrogen, carbon monoxide, ammonia, methane, natural gas, nitrogen oxides, and their mixtures for a wide range of conditions. C3MechCore (118 species) targets a more comprehensive range of C 0 –C 3 fuels, including ammonia, methanol, ethanol, and dimethyl ether. Both mechanisms demonstrate predictive accuracy comparable to C3MechV4.0 for the combustion characteristics of the target fuels. C3MechLite is designed with a component library structure, enabling further reduction in mechanism size depending on the fuel(s) of interest for 2D/3D numerical simulations. Various combinations of component libraries were validated, and the average prediction error remains within 1 % compared to C3MechLite. Furthermore, the mechanism was applied to 3D LES simulations of H 2 lifted flames and was confirmed to reproduce flame characteristics with high accuracy. C3MechLite and its component library structure enable high-fidelity and computationally efficient chemical kinetic mechanisms, paving the way for application in more complex combustion simulations.

Ammonia↗
DOE OSTI2023

A scalable framework for quantifying field-level agricultural carbon outcomes

Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in adopting certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N 2 O and CH 4 ) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”. Accurate quantification of agricultural carbon outcomes is the basis for achieving emission reductions for agriculture, but existing approaches for measuring carbon outcomes (including direct measurements, emission factors, and process-based modeling) fall short of achieving the required accuracy and scalability necessary to support credible, verifiable, and cost-effective measurement and improvement of these carbon outcomes. Here we propose a foundational and scalable framework to quantify field-level carbon outcomes for farmland, which is based on the holistic carbon balance of the agroecosystem: Agroecosystem Carbon Outcomes = Environment (E) × Management (M) × Crop (C). Following a comprehensive review of the scientific challenges associated with existing approaches, as well as their tradeoffs between cost and accuracy, we propose that the most viable path for the quantification of field-level carbon outcomes in agricultural land is through an effective integration of various approaches (e.g. diverse observations, sensor/in-situ data, and modeling), defined as the “System-of-Systems” solution. Such a “System-of-Systems” solution should simultaneously comprise the following components: (1) scalable collection of ground truth data and cross-scale sensing of environment variables (E), management practices (M), and crop conditions (C) at the local field level; (2) advanced modeling with necessary processes to support the quantification of carbon outcomes; (3) systematic Model-Data Fusion (MDF), i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; (4) high computation efficiency and artificial intelligence (AI) to scale to millions of individual fields with low cost; and (5) robust and multi-tier validation systems and infrastructures to ensure solution fidelity and true scalability, i.e. the ability of a solution to perform robustly with accepted accuracy on all targeted fields. In this regard, we provide here the detailed scientific rationale, current progress, and future research and development (R&D) priorities to achieve different components of the “System-of-Systems” solution, thus accomplishing the Environment×Management×Crop framework to quantify field-level agricultural carbon outcomes.

54 ENVIRONMENTAL SCIENCES↗