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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structures of methane and ammonia monooxygenases in native membranes

Methane- and ammonia-oxidizing bacteria play key roles in the global carbon and nitrogen cycles, respectively. These bacteria use homologous copper membrane monooxygenases to accomplish the defining chemical transformations of their metabolisms: the oxidations of methane to methanol by particulate methane monooxygenase (pMMO) and ammonia to hydroxylamine by ammonia monooxygenase (AMO), enzymes of prime interest for applications in mitigating climate change. However, investigations of these enzymes have been hindered by the need for disruptive detergent solubilization prior to structure determination, confounding studies of pMMO and precluding studies of AMO. Here, we overcome these challenges by using cryoEM to visualize pMMO and AMO directly in their native membrane arrays at 2.4 to 2.8 Å resolution. These structures reveal details of the copper centers, numerous bound lipids, and previously unobserved components, including identifiable and distinct supernumerary helices interacting with pMMO and AMO, suggesting a widespread role for these helices in copper membrane monooxygenases. Comparisons between these structures, their metallocofactors, and their unexpected protein–protein interactions highlight features that may govern activity or the formation of higher-order arrays in native membranes. The ability to obtain molecular insights within the native membrane will enable further understanding of these environmentally important enzymes.

Science & Technology - Other Topics↗
DOE OSTI2024

Simulation of metal nanoparticles growth in methane atmosphere of arc discharge: comparison to experiment

A direct current arc discharge in a methane atmosphere is a scalable and sustainable method to produce metal-carbon core–shell nanoparticles and single-walled carbon nanotubes, where a metal catalyst can be continuously supplied through evaporation of an anode made from the catalyst material. The size of catalyst particles is of critical importance as it can affect the synthesis yield and properties of nanotubes and core–shell nanoparticles. This study presents a numerical model describing the formation and growth of metal particles for the conditions representative of the arc discharge with an evaporating iron anode at near-atmospheric pressure of a methane-rich atmosphere. The model incorporates carbon adsorption to the metal surface and explains the limiting effect of carbon coverage on the size of metal nanoparticles. The predicted particle sizes are compared with experimental observations. The model also predicts higher concentrations of metal particles with the increasing partial pressure of methane.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Decoupling plasma, catalyst, and gaseous mechanisms for non-oxidative methane conversion

Direct non-oxidative methane (CH 4 ) conversion to value-added hydrogen (H 2 ) and C 2 products remains hindered by fundamental catalytic scaling constraints and rapid surface deactivation at elevated temperatures. Plasma-enabled catalysis offers a promising route to overcome the thermodynamic and kinetic barriers of direct non-oxidative methane upgrading at mild conditions, yet control over C–C product selectivity and catalyst stability remains elusive. Here, we establish a unified mechanistic framework including Langmuir–Hinshelwood (L–H) and Langmuir–Rideal (L–R) mechanisms that disentangles the roles of plasma excitation (including vibrationally activated species and radicals), surface temperature (T sur ), and catalyst binding energy in steering CH 4 conversion to H 2 and C 2 hydrocarbons. Through a combination of density functional theory (DFT) informed microkinetic modeling, in situ and ex situ surface characterization, and product quantification under dielectric barrier discharge conditions, we show that vibrationally excited CH 4 lowers activation barriers selectively for dissociative chemisorption, enabling surface activation across a wide range of transition metal catalysts at low thermal energy input. We find that once CH 4 is dissociatively chemisorbed, the branching between C 2 H 2 , C 2 H 4 , and C 2 H 6 is governed by surface properties (carbon binding energy, T sur , etc), regardless of plasma excitation. The DFT informed microkinetic model decouples the effects of molecular activation from surface properties and indentifies operating windows that maximize target yields while suppressing carbon accumulation and subsequent catalytic inactivation. Experiments on polycrystalline Cu/Al 2 O 3 , Ni/Al 2 O 3 , and Pt/Al 2 O 3 validate these predictions, revealing catalyst-dependent branching toward ethane or ethylene and distinct deactivation profiles. We unify these trends into a generalized three-dimensional plasma-thermal-catalytic design space, from which reduced descriptors such as T vib /T sur in the limit of vibrationally excited L–H pathways emerge as predictive metrics. These results enable rational tuning of methane conversion pathways and unlock selective C 2 formation using earth-abundant metals under mild plasma conditions.

catalyst inactivation↗
DOE OSTI2025

Structure of active methyl-CoM reductase, Earth’s main methane producer

Summary Our work reveals the structure of the active state of Methyl-Coenzyme M Reductase (MCR), the key and rate-limiting enzyme in biological methane formation. We find large differences between the active Ni(I) and inactive Ni(II) proteins and provide insight into how nature makes and breaks the C-H bond of methane. The Ni(II)-F430 center in inactive MCR contains four planar nitrogen ligands, a lower axial glutamine oxo, and an upper axial thiolate. The Ni(I)-enzyme replaces the axial ligands with a single water. The one-electron redox change results in movement of the Ni ion and upward swing of the β-lactam ring in the tetrapyrrole coupled to a domino-like protein quake through second sphere residues, inter-subunit interactions, a substrate tunnel, affecting even the dimensions of the unit cell. These structural changes lead Ni(I)-MCR to release a charge clamp that, in the Ni(II) state, locks down substrate Coenzyme B. Determining the Ni(I)-MCR structure required development of rigorous anaerobic crystallographic techniques. Validation of the MCR redox state was accomplished by in-line and parallel spectroscopic and unit cell analyses. This structure has large implications for developing technologies to limit methane emissions and efficiently produce biofuels. Methodology described here will enhance structural biology for other oxygen-sensitive enzymes.

09 BIOMASS FUELS↗
DOE OSTI2024

Evidence for dissociation in shock-compressed methane

Theory and experiments show that with increasing pressure, the chemical bonds of methane rearrange, leading to the formation of complex polymers and then to dissociation. However, there is disagreement on the exact conditions where these changes take place. In this study, methane samples were precompressed in diamond-anvil cells and then shock compressed to pressures reaching 400 GPa, the highest pressures yet explored in methane. Furthermore, the results reveal a qualitative change in the Hugoniot curve at 80-150 GPa, which is interpreted as a signature of dissociation based on thermodynamic calculations and theoretical predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A hybrid machine-learning approach for analysis of methane hydrate formation dynamics in porous media with synchrotron CT imaging

Fast multi-phase processes in methane hydrate bearing samples pose a challenge for quantitative micro-computed tomography study and experiment steering due to complex tomographic data analysis involving time-consuming segmentation procedures. This is because of the sample's multi-scale structure, which changes over time, low contrast between solid and fluid materials, and the large amount of data acquired during dynamic processes. Here, a hybrid approach is proposed for the automatic segmentation of tomographic data from time-resolved imaging of methane gas-hydrate formation in sandy granular media, which includes a deep-learning 3D U-Net model. To prepare a training dataset for the 3D U-Net, a technique to automate data labeling based on sample-specific information about the mineral matrix immobility and occasional fluid movement in pores is proposed. Automatic segmentation allowed for studying properties of the hydrate growth in pores, as well as dynamic processes such as incremental flow and redistribution of pore brine. Results of the quantitative analysis showed that for typical gas-hydrate stability parameters (100 bar methane pressure, 7°C temperature) the rate of formation is slow (less than 1% per hour), after which the surface area of contact between brine and gas increases, resulting in faster formation (2.5% per hour). Hydrate growth reaches the saturation point after 11 h of the experiment. Finally, the efficacy of the proposed segmentation scheme in on-the-fly automatic data analysis and experiment steering with zooming to regions of interest is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Water-promoted interfacial pathways in methane oxidation to methanol on a CeO 2 -Cu 2 O catalyst

Highly selective oxidation of methane to methanol has long been challenging in catalysis. Here, we reveal key steps for the pro­motion of this reaction by water when tuning the selectivity of a well-defined CeO 2 /Cu 2 O/Cu(111) catalyst from carbon monoxide and carbon dioxide to methanol under a reaction environment with methane, oxygen, and water. Ambient-pressure x-ray photoelectron spectroscopy showed that water added to methane and oxygen led to surface methoxy groups and accelerated methanol production. These results were consistent with density functional theory calculations and kinetic Monte Carlo simulations, which showed that water preferentially dissociates over the active cerium ions at the CeO 2 –Cu 2 O/Cu(111) interface. The adsorbed hydroxyl species blocked O-O bond cleavage that would dehydrogenate methoxy groups to carbon monoxide and carbon dioxide, and it directly converted this species to methanol, while oxygen reoxidized the reduced surface. Water adsorption also displaced the produced methanol into the gas phase.

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

Data from: “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”

This dataset is associated with the manuscript “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”. Bald cypress “knees” (aboveground woody roots) have been shown to contribute to wetland methane (CH4) efflux, with large variation within and between studies. To explain this variation, we investigated spatial (i.e., across knee surface, within sites, between sites) and temporal dynamics of CH4 fluxes from knees. Methane fluxes were collected from September 2022 to August 2024 at three locations in western Kentucky, USA, within the Mississippi Alluvial Valley: a main channel (semi-permanently flooded), side channel (seasonally flooded), and reservoir edge (artificially flooded). Knee CH4 fluxes (“Ross_et_al_Knee_Flux_Data.csv”) were measured from multiple heights on knees (20, 40, and 60 cm) of various sizes (knee straight height ranged from 24 to 93 cm) using a LiCOR LI-7810 CH4/CO2/H2O Trace Gas Analyzer. The dataset also includes environmental variables collected with each knee measurement, including water level adjusted for knee-to-knee elevational differences, subsurface and air temperature, and humidity. Soil CH4 fluxes (“Ross_et_al_Soil_Flux_Data.csv”) were also collected adjacent to knees (starting in April 2023) when water levels didn’t overtop soil collars, using a LiCOR Smart Chamber and calculated in SoilFluxPro software. The soil flux dataset includes associated variables collected by the Smart Chamber. Three separate files (“*_Water_Level.csv”) are included for water level and subsurface temperature data collected at each site using HOBO U20L barometric pressure loggers. Each file type (knee flux, soil flux, water level) has an associated data dictionary (“*_dd.csv”). For specifics on methodology used and calculations, see the associated manuscript. The R script includes code used for figures and analyses reported in the manuscript.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Designing Catalysts for Dehydrogenation of Methane for Reducing Greenhouse Gas during Natural Gas Extraction

Catalytic conversion of methane (CH 4 ) into useful products is critical for maximizing the utility of natural gas output and for reducing green house gas release associated with flaring (burning off CH 4 at natural gas extraction sites). One particular useful technique is methane dry reforming (DRM), which involves the chemical reaction of CH 4 with carbon dioxide (CO 2 ) to generate carbon monoxide (CO), hydrogen gas (H 2 ), and subsequently other useful products. New and improved catalysts are required to facilitate efficient dry methane reforming. In this report, we apply the Density Functional Theory (DFT) computational technique to investigate a catalyst consisting of small nickel clusters (Ni n , n < 10) on ceria (Ce0 2 (111) surfaces) support. One main thrust of this project is to study the initial CH 4 and CO 2 reactions with the catalyst. We find that CH 4 exhibits barrierless reactive adsorption on to the catalyst. In order words, this step is likely not the rate-determining step. A second thrust is to perform detailed studies of the catalyst itself and examine the role of oxygen vacancies. Using a specific DFT method and a hypothesis about the absence of the Ce(III) redox state, we obtain predictions about oxygen vacancies in good agreement with experimental observations.

03 NATURAL GAS↗
DOE OSTI2024

Functional-type modeling approach and data-driven parameterization of methane emissions in wetlands (Final Technical Science Report)

Our goals are to improve understanding and quantitative representation of the multiple processes that affect methane emissions at a high (patch level, vertically detailed) spatial resolution, and translate this understanding to improved modeling capability of coastal wetland fluxes using the E3SM Land Model (ELM v1) wetland CH4 biogeochemistry module. We propose an experimental approach to identify and parameterize uncertainties in ELM. Understanding of methane emissions can be improved along three conceptual axes: (i) horizontal (ecohydrological patch resolution), (ii) vertical (through the depth of the soil column), and (iii) process level (e.g., resolving microbial pathways, vegetation specific transport pathways). Along each of the three axes, we will characterize, quantify, and model, the key ecological, hydrological, and meteorological controls of methane (CH4) flux heterogeneity in four model coastal wetlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Leverage Microbial Innovations to Address Methane Emission Challenges: Input for FY24 Annual LDRD Report

Sandia researchers are addressing the urgent challenge of minimizing dilute and distributed methane emissions. The team is focused on generating stable methane-consuming microbial consortia for deployment in engineered environmental systems. This innovative work aims to produce stable inocula of these consortia and implement viral controls for microbes that generate methane, significantly reducing emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Potential Challenges of HyBlend Storage in a Methane Reservoir Located in Southwestern United States

Hydrogen has been identified as a flexible energy carrier with zero or negative emissions across multiple energy systems. It is possible to utilize hydrogen by storing Hyblend, or hydrogen gas blended with methane, in existing natural gas infrastructure. However, the compatibility of adapting the current CH4 storage strategies to include H2 injection has not been fully demonstrated. It is essential that we understand the impact of H2 gas on the naturally occurring microbial community of subsurface storage reservoirs before deploying large-scale H2-CH4 storage. We designed a series of experiments that allowed us to identify potential geochemical and microbial challenges of HyBlend Storage in existing methane reservoirs. First, we collected and characterized field fluid samples from a methane reservoir located in southwestern United States. Next, we used these field fluid samples to complete a series of short-term reactor experiments at reservoir conditions (80 °C and ~1,000 psi) for a natural gas (100% CH4) and HyBlend(80% CH4/20% H2) storage environment to measure the transformation of gas content. We conducted both biotic and abiotic (sterilized) measurements to accurately understand and decouple abiotic and microbially driven processes. Overall, we found that our field sample was characterized by a diverse microbial community with the metabolic capacity for sulfur reduction, iron reduction, and acetogenesis. Across our reactors, there was minimal change in geochemistry.

hydrogen storage↗
DOE OSTI2022

Discovering hydrothermalism from Afar: In Situ methane instrumentation and change-point detection for decision-making

Seafloor hydrothermalism plays a critical role in fundamental interactions between geochemical and biological processes in the deep ocean. A significant number of hydrothermal vents are hypothesized to exist, but many of these remain undiscovered due in part to the difficulty of detecting hydrothermalism using standard sensors on rosettes towed in the water column or robotic platforms performing surveys. Here, we use in situ methane sensors to complement standard sensing technology for hydrothermalism discovery and compare sensors on a towed rosette and an autonomous underwater vehicle (AUV) during a 17 km long transect in the Northern Guaymas Basin in the Gulf of California. This transect spatially intersected with a known hydrothermally active venting site. These data show that methane signalled possible hydrothermal-activity 1.5–3 km laterally (100–150 m vertically) from a known vent. Methane as a signal for hydrothermalism performed similarly to standard turbidity sensors (plume detection 2.2–3.3 km from reference source), and more sensitively and clearly than temperature, salinity, and oxygen instruments which readily respond to physical mixing in background seawater. We additionally introduce change-point detection algorithms—streaming cross-correlation and regime identification—as a means of real-time hydrothermalism discovery and discuss related data supervision technologies that could be used in planning, executing, and monitoring explorative surveys for hydrothermalism.

58 GEOSCIENCES↗
DOE OSTI2022

Understanding the Accuracy Limitations of Quantifying Methane Emissions Using Other Test Method 33A

Researchers have utilized Other Test Method (OTM) 33A to quantify methane emissions from natural gas infrastructure. Historically, errors have been reported based on a population of measurements compared to known controlled releases of methane. These errors have been reported as 2σ errors of ±70%. However, little research has been performed on the minimum attainable uncertainty of any one measurement. We present two methods of uncertainty estimation. The first was the measurement uncertainty of the state-of-the-art equipment, which was determined to be ±3.8% of the estimate. This was determined from bootstrapped measurements compared to controlled releases. The second approach of uncertainty estimation was a modified Hollinger and Richardson (H&R) method which was developed for quantifying the uncertainty of eddy covariance measurements. Using a modified version of this method applied to OTM 33A measurements, it was determined that uncertainty of any given measurement was ±17%. Combining measurement uncertainty with that of stochasticity produced a total minimum uncertainty of 17.4%. Due to the current nature of stationary single-sensor measurements and the stochasticity of atmospheric data, such uncertainties will always be present. This is critical in understanding the transport of methane emissions and indirect measurements obtained from the natural gas industry.

Heltzel, Robert↗
DOE OSTI2020

Metagenomic Insight into Environmentally Challenged Methane-Fed Microbial Communities

In this study, we aimed to investigate, through high-resolution metagenomics and metatranscriptomics, the composition and the trajectories of microbial communities originating from a natural sample, fed exclusively with methane, over 14 weeks of laboratory incubation. This study builds on our prior data, suggesting that multiple functional guilds feed on methane, likely through guild-to-guild carbon transfer, and potentially through intraguild and intraspecies interactions. We observed that, under two simulated dioxygen partial pressures—low versus high—community trajectories were different, with considerable variability among the replicates. In all microcosms, four major functional guilds were prominently present, representing Methylococcaceae (the true methanotrophs), Methylophilaceae (the nonmethanotrophic methylotrophs), Burkholderiales, and Bacteroidetes. Additional functional guilds were detected in multiple samples, such as members of Opitutae, as well as the predatory species, suggesting additional complexity for methane-oxidizing communities. Metatranscriptomic analysis suggested simultaneous expression of the two alternative types of methanol dehydrogenases in both Methylococcaceae and Methylophilaceae, while high expression of the oxidative/nitrosative stress response genes suggested competition for dioxygen among the community members. The transcriptomic analysis further suggested that Burkholderiales likely feed on acetate that is produced by Methylococcaceae under hypoxic conditions, while Bacteroidetes likely feed on biopolymers produced by both Methylococcaceae and Methylophilaceae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Impact of Hydrogen on Methane and Pollutant Emissions over Three-Way Catalysts with Natural Gas–Hydrogen Blends

Blending natural gas (NG) with hydrogen (H₂) can improve combustion and engine performance while potentially facilitating the catalytic conversion of methane and other pollutants, resulting in cleaner tailpipe emissions. This study evaluates the impact of H2 on the conversion of methane, CO, and NOx emissions on a commercial three-way catalyst (TWC) in a flow reactor using synthetic gas mixtures that simulate stoichiometric engine exhausts with NG or NG+H₂ combustion. The work examines whether, and how, the additional amount of H₂ in the exhaust stream affects the conversion efficiency of methane and other pollutants. Experiments were conducted with both degreened and aged catalysts under controlled conditions, systematically varying temperature, the air-to-fuel equivalence ratio (λ), and λ modulation. Test conditions covered λ values from 0.996 to 1.000 to represent nominally stoichiometric engine operation with different λ modulation amplitudes, as well as a range of temperatures to inform control strategies for effective CH₄, CO, and NOₓ reduction. Overall, the results show that hydrogen addition significantly improves the conversion efficiency of CH₄ and NOₓ, particularly at temperatures below 500 °C. More significantly, this study highlights that exhaust gas composition, operating temperature, λ management, and the oxygen storage capacity of the TWC all play major roles in affecting the tailpipe emissions from NG and NG+H₂ combustion.

Prikhodko, Vitaly [ORNL] (ORCID:0000000244685836)↗
DOE OSTI2021

Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions

Abstract. We apply airborne measurements across three seasons (summer, winter and spring 2017–2018) in a multi-inversion framework to quantify methane emissions from the US Corn Belt and Upper Midwest, a key agricultural and wetland source region. Combing our seasonal results with prior fall values we find that wetlands are the largest regional methane source (32 %, 20 [16–23] Gg/d), while livestock (enteric/manure; 25 %, 15 [14–17] Gg/d) are the largest anthropogenic source. Natural gas/petroleum, waste/landfills, and coal mines collectively make up the remainder. Optimized fluxes improve model agreement with independent datasets within and beyond the study timeframe. Inversions reveal coherent and seasonally dependent spatial errors in the WetCHARTs ensemble mean wetland emissions, with an underestimate for the Prairie Pothole region but an overestimate for Great Lakes coastal wetlands. Wetland extent and emission temperature dependence have the largest influence on prediction accuracy; better representation of coupled soil temperature–hydrology effects is therefore needed. Our optimized regional livestock emissions agree well with the Gridded EPA estimates during spring (to within 7 %) but are ∼ 25 % higher during summer and winter. Spatial analysis further shows good top-down and bottom-up agreement for beef facilities (with mainly enteric emissions) but larger (∼ 30 %) seasonal discrepancies for dairies and hog farms (with > 40 % manure emissions). Findings thus support bottom-up enteric emission estimates but suggest errors for manure; we propose that the latter reflects inadequate treatment of management factors including field application. Overall, our results confirm the importance of intensive animal agriculture for regional methane emissions, implying substantial mitigation opportunities through improved management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A new aerial approach for quantifying and attributing methane emissions: implementation and validation

Methane (CH 4 ) is a powerful greenhouse gas that is produced by a diverse set of natural and anthropogenic emission sources. Biogenic methane sources generally involve anaerobic decay processes such as those occurring in wetlands, melting permafrost, or the digestion of organic matter in the guts of ruminant animals. Thermogenic CH 4 sources originate from the breakdown of organic material at high temperatures and pressure within the Earth's crust, a process which also produces more complex trace hydrocarbons such as ethane (C 2 H 6 ). Here, we present the development and deployment of an uncrewed aerial system (UAS) that employs a fast (1 Hz) and sensitive (1–0.5 ppb s -1 ) CH 4 and C 2 H 6 sensor and ultrasonic anemometer. The UAS platform is a vertical-takeoff, hexarotor drone (DJI Matrice 600 Pro, M600P) capable of vertical profiling to 120 m altitude and plume sampling across scales up to 1 km. Simultaneous measurements of CH 4 and C 2 H 6 concentrations, vector winds, and positional data allow for source classification (biogenic versus thermogenic), differentiation, and emission rates without the need for modeling or a priori assumptions about winds, vertical mixing, or other environmental conditions. The system has been used for direct quantification of methane point sources, such as orphan wells, and distributed emitters, such as landfills and wastewater treatment facilities. With detectable source rates as low as 0.04 and up to ~1500 kg h -1 , this UAS offers a direct and repeatable method of horizontal and vertical profiling of emission plumes at scales that are complementary to regional aerial surveys and localized ground-based monitoring.

54 ENVIRONMENTAL SCIENCES↗