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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
NASA NTRS1973

Central waste processing system

A new concept for processing spacecraft type wastes has been evaluated. The feasibility of reacting various waste materials with steam at temperatures of 538 - 760 C in both a continuous and batch reactor with residence times from 3 to 60 seconds has been established. Essentially complete gasification is achieved. Product gases are primarily hydrogen, carbon dioxide, methane, and carbon monoxide. Water soluble synthetic wastes are readily processed in a continuous tubular reactor at concentrations up to 20 weight percent. The batch reactor is able to process wet and dry wastes at steam to waste weight ratios from 2 to 20. Feces, urine, and synthetic wastes have been successfully processed in the batch reactor.

Kester, F. L.↗
NASA NTRS1981

Photoassisted carbon dioxide reduction and formation of twoand three-carbon compounds

The photoassisted reduction of aqueous carbon dioxide in the presence of naturally occurring minerals is investigated as a possible abiotic precursor of photosynthesis. Aqueous carbon dioxide saturated suspensions or surfaces of the minerals nontronite, bentonite, anatase, wolframite, molybdenite, minium, cinnabar and hematite were irradiated with high-pressure mercury lamps or sunlight. Chemical analyses reveal the production of formic acid, formaldehyde, methanol and methane, and the two and three-carbon compounds glyoxal (CHOCHO) and malonaldehyde (CH2(CHO)2). It is suggested that such photosynthetic reactions with visible light in the presence of semiconducting minerals may provide models for prebiological carbon and nitrogen fixation in both oxidized and reduced atmospheres.

Halmann, M.↗
NASA NTRS1988

Surface-catalyzed air oxidation reactions of hydrazines: Tubular reactor studies

The surface-catalyzed air oxidation reactions of hydrazine, monomethylhydrazine, unsymmetrical dimethylhydrazine, symmetrical dimethylhydrazine, trimethylhydrazine and tetramethylhydrazine were investigated in a metal-powder packed turbular flow reactor at 55 plus or minus 3 C. Hydrazine was completely reacted on all surfaces studied. The major products of monomethylhydrazine (MMH) oxidation were methanol, methane and methyldiazene. The di-, tri- and tetra-methyl hydrazines were essentially unreactive under these conditions. The relative catalytic reactivities toward MMH are: Fe greater than Al2O3 greater than Ti greater than Zn greater than 316 SS greater than Cr greater than Ni greater than Al greater than 304L SS. A kinetic scheme and mechanism involving adsorption, oxidative dehydrogenation and reductive elimination reactions on a metal oxide surface are proposed.

Kilduff, Jan E.↗
NASA NTRS1989

Upper limits on possible photochemical hazes on Pluto

The suggestion by Elliot et al., (1989) that a haze layer near the surface of Pluto may be photochemical in origin and similar to the aerosol hazes in the atmospheres of other outer solar system bodies is evaluated. The nature of hazes which may be produced in the Hubbard et al., (1989) atmosphere is explored as well. It is concluded that the very low pressure in Pluto's atmosphere requires an aerosol production rate equal to the total maximum methane photolysis rate expected at Pluto.

Stansberry, John A.↗
NASA NTRS1961

Atmospheric Photochemistry

The upper atmosphere offers a vast photochemical laboratory free from solid surfaces, so all reactions take place in the gaseous phase. At 30 km altitude the pressure has fallen to about one-hundredth of that at ground level, and we shall, rather arbitrarily, regard the upper atmosphere as beginning at that height. By a little less than 100 km the pressure has fallen to 10(exp -3) mm Hg and is decreasing by a power of ten for every 15 km increase in altitude. Essentially we are concerned then with the photochemistry of a nitrogen-oxygen mixture under low-pressure conditions in which photo-ionization, as well as photodissociation, plays an important part. Account must also be taken of the presence of rare constituents, such as water vapour and its decomposition products, including particularly hydroxyl, oxides of carbon, methane and, strangely enough, sodium, lithium and calcium. Many curious and unfamiliar reactions occur in the upper atmosphere. Some of them are luminescent, causing the atmosphere to emit a dim light called the airglow. Others, between gaseous ions and neutral molecules, are almost a complete mystery at this time. Similar interesting phenomena must occur in other planetary atmospheres, and they might be predicted if sufficient chemical information were available.

Massey, Harrie↗
DOE OSTI2023

Plasma assisted distributed chemical production

The present development is a process to produce commodity chemicals such as methanol and syngas using an integrated plasma catalysis technology. The method comprises providing a fixed or fluidized bed reactor having a microwave plasma flame and a catalyst bed with a catalyst, wherein the catalyst is an alloyed bimetallic nanowire. In the process, the plasma flame fluidizes the catalyst thereby producing a more effective catalyst than the non-fluidized catalyst. It is anticipated that the reactor can have a throughput capacity of up to 30 Lpm/kW and can be effective for the conversion of CO 2 , CH 4 , air, water, and combinations thereof, through reactions such as pure CO 2 splitting, reverse water gas shift (RWGS) for CO production, methanol synthesis, and plasma reforming of methane, thereby making a system that would be attractive for small GTL units.

Sunkara, Mahendra↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗
DOE OSTI2024

A synthetic co-culture for bioproduction of ammonia from methane and air

Abstract Fixed nitrogen fertilizers feed 50% of the global population, but most fixed nitrogen production occurs using energy-intensive Haber–Bosch-based chemistry combining nitrogen (N2) from air with gaseous hydrogen (H2) from methane (CH4) at high temperatures and pressures in large-scale facilities sensitive to supply chain disruptions. This work demonstrates the biological transformation of atmospheric N2 into ammonia (NH3) using CH4 as the sole carbon and energy source in a single vessel at ambient pressure and temperature, representing a biological “room-pressure and room-temperature” route to NH3 that could ultimately be developed to support compact, remote, NH3 production facilities amenable to distributed biomanufacturing. The synthetic microbial co-culture of engineered methanotroph Methylomicrobium buryatense (now Methylotuvimicrobium buryatense) and diazotroph Azotobacter vinelandii converted three CH4 molecules to l-lactate (C3H6O3) and powered gaseous N2 conversion to NH3. The design used division of labor and mutualistic metabolism strategies to address the oxygen sensitivity of nitrogenase and maximize CH4 oxidation efficiency. Media pH and salinity were central variables supporting co-cultivation. Carbon concentration heavily influenced NH3 production. Smaller-scale NH3 production near dispersed, abundant, and renewable CH4 sources could reduce disruption risks and capitalize on untapped energy resources. One-Sentence Summary Co-culture of engineered microorganisms Methylomicrobium buryatense and Azotobacter vinelandii facilitated the use of methane gas as a sole carbon feedstock to produce ammonia in an ambient temperature, atmospheric pressure, single-vessel system.

Biotechnology & Applied Microbiology↗
DOE OSTI2020

In Situ Identification of Reaction Intermediates and Mechanistic Understandings of Methane Oxidation over Hematite: A Combined Experimental and Theoretical Study

Effective methane utilization for either clean power generation or value-added chemical production has been a subject of growing attention worldwide for decades, yet challenges persist mostly in relation to methane activation under mild conditions. Here, we report hematite, an earth-abundant material, to be highly effective and thermally stable to catalyze methane combustion at low temperatures (<500 °C) with a low light-off temperature of 230 °C and 100% selectivity to CO 2 . The reported performance is impressive and comparable to those of precious-metal-based catalysts, with a low apparent activation energy of 17.60 kcal·mol –1 . Our theoretical analysis shows that the excellent performance stems from a tetra-iron center with an antiferromagnetically coupled iron dimer on the hematite (110) surface, analogous to that of the methanotroph enzyme methane monooxygenase that activates methane at ambient conditions in nature. Isotopic oxygen tracer experiments support a Mars van Krevelen redox mechanism where CH 4 is activated by reaction with a hematite surface oxygen first, followed by a catalytic cycle through a molecular-dioxygen-assisted pathway. Surface studies with in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and density functional theory (DFT) calculations reveal the evolution of reaction intermediates from a methoxy CH 3 –O–Fe, to a bridging bidentate formate b-HCOO–Fe, to a monodentate formate m-HCOO–Fe, before CO 2 is eventually formed via a combination of thermal hydrogen-atom transfer (HAT) and proton-coupled electron transfer (PCET) processes. Finally, the elucidation of the reaction mechanism and the intermediate evolutionary profile may allow future development of catalytic syntheses of oxygenated products from CH 4 in gas-phase heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Interaction of Methane with Calcium Ferrite in the Chemical Looping Partial Oxidation Application: Experimental and DFT Study

In this study, experimental studies using mass spectroscopy, thermogravimetric analysis, in situ X-ray diffraction (XRD), and theoretical density functional theory calculations were carried out to investigate the mechanism of methane partial oxidation over a CaFe 2 O 4 oxygen carrier. The XRD analysis revealed the formation of the calcium ferrite phases during methane reduction occurred in the sequence CaFe 2 O 4 →CaFe 3 O 5 + Ca 2 Fe 2 O 5 →FeO + Fe + CaO→Fe + CaO. Each of these phases was modeled using periodic density functional theory to study the activity of these phases for the reactivity with CH 4 , CO, and H 2 along with the adsorbed surface species to help elucidate the effect that phase changes during reduction have on the chemical looping products CO and H 2 . Mass spectroscopic analysis revealed the formation of H 2 O and CO 2 occurred prior to the formation of CO and H 2 , and these products may be due to the removal of lattice oxygen bound in the discrete primary phase, which contributes to a small portion (~16%) of the total transferable oxygen in the solid. The density functional theory (DFT) results suggest that the gaseous CO and H 2 are not thermodynamically favorable to react with the Ca 2 Fe 2 O 5 where the release of CO and H 2 led to an increase in selectivity for these products. The DFT results suggest that some of the adsorbed atomic hydrogen combined to form adsorbed H 2 and then gaseous H 2 on the CaFe 2 O 4 surface, while the carbon deposition and some adsorbed atomic hydrogen react to form the CaFe 3 O 5 and Ca 2 Fe 2 O 5 phases simultaneously. DFT simulations suggest that both the gaseous H 2 and adsorbed atomic H are less thermodynamically favorable to drive the deep reduction of Ca 2 Fe 2 O 5 to CaO and Fe0. The deep reduction of the calcium ferrite therefore favors the generation of syngas products (CO and H 2 ) through mechanisms of methane dehydrogenation and selective oxidation of carbon to CO. The significant difference in mechanisms for partial oxidation of methane to syngas with the CaFe 2 O 4 carrier can be correlated to the differences in the oxide phases present during the reduction process, concentration of oxygen species, and bonding in the lattice structure.

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

Bioinspired Cu(II) Defect Sites in ZIF-8 for Selective Methane Oxidation

Activating the C–H bonds of alkanes without further oxidation to more thermodynamically stable products, CO and CO 2 , is a long-sought goal of catalytic chemistry. Here, inspired by the monocopper active site of methane monooxygenase, we synthesized a Cu-doped ZIF-8 metal–organic framework with 25% Cu and 75% Zn in the nodes and activated it by heating to 200 °C and dosing in a stepwise fashion with O 2 , methane, and steam. We found that it does oxidize methane to methanol and formaldehyde. The catalysis persists through at least five cycles, and beyond the third cycle, the selectivity improves to the extent that no CO 2 can be detected. Experimental characterization and analysis were carried out by PXRD, DRUV–vis, SEM, and XAS (XANES and EXAFS). The reaction is postulated to proceed at open-coordination copper sites generated by defects, and the mechanism of methanol production was explicated by density functional calculations with the revMO6-L exchange–correlation functional. The calculations reveal a catalytic cycle of oxygen-activated Cu I involving the conversion of two molecules of CH 4 to two molecules of CH 3 OH by a sequence of hydrogen atom transfer reactions and rebound steps. For most steps in the cycle, the reaction is more favored by singlet species than by triplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Investigation of degradation mechanisms in composite matrices

Degradation mechanisms were investigated for graphite/polysulfone and graphite/epoxy laminates exposed to ultraviolet and high-energy electron radiations in vacuum up to 960 equivalent sun hours and 10 to the ninth power rads respectively. Based on GC and combined GC/MS analysis of volatile by-products evolved during irradiation, several free radical mechanisms of composite degradation were identified. The radiation resistance of different matrices was compared in terms of G values and quantum yields for gas formation. All the composite materials evaluated show high electron radiation stability and relatively low ultraviolet stability as indicated by low G values and high quantum for gas formation. Mechanical property measurements of irradiated samples did not reveal significant changes, with the possible exception of UV exposed polysulfone laminates. Hydrogen and methane were identified as the main by-products of irradiation, along with unexpectedly high levels of CO and CO2.

Giori, C.↗
DOE OSTI2024

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗
DOE OSTI2025

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗