ORHis, a Natural Variant of OR, Specifically Interacts with Plastid Division Factor ARC3 to Regulate Chromoplast Number and Carotenoid Accumulation
Not provided.
Biochemistry & Molecular Biology↗
SEARCH · Search NASA
Results for “Nature”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Kinetics of propane cracking and position-specific isotope fractionation: Insights into the origins of natural gases
Not provided.
Geochemistry & Geophysics↗
Isotopic Constraints on the Nature of Primary Precipitates in Archean–Early Paleoproterozoic Iron Formations from Determinations of the Iron Phonon Density of States of Greenalite and 2L- and 6L-Ferrihydrite
Iron formations (IFs) are chemical sedimentary rocks that were widely deposited before the Great Oxidation Event (GOE) around 2.4- 2.2 Ga. It is generally thought that IFs precipitated as hydrated Fe 3+ oxides (HFOs) such as ferrihydrite following surface oxidation of Fe 2+ -rich, anoxic deep waters. This model often implicates biological oxidation and underpins reconstructions of marine nutrient concentrations. However, nanoscale petrography indicates that an Fe 2+ silicate, greenalite, is a common primary mineral in well-preserved IFs, motivating an alternative depositional model of anoxic ferrous silicate precipitation. It is unclear, however, if Fe 2+ -rich silicates can produce the Fe isotopic variations in IFs that are well explained by Fe 2+ oxidation. To address this question, we constrain the equilibrium Fe isotopic ( 56 Fe/ 54 Fe) fractionation of greenalite and ferrihydrite by determining the iron phonon densities of states for those minerals. Here, we use ab initio density functional theory (DFT + U) calculations and nuclear resonant inelastic X-ray scattering spectroscopy to show that ferrous greenalite should be isotopically lighter than ferrihydrite by similar to 1-1.2 parts per thousand at equilibrium, and fractionation should scale linearly with increasing Fe 3+ content in greenalite. By anchoring ferrihydrite-greenalite mineral pair fractionations to published experimental Fe isotopic fractionations between HFOs and aqueous Fe 2+ , we show that ferrous greenalite may produce all but the heaviest pre-GOE Fe isotopic compositions and mixed valence greenalites can produce the entire record. Our results suggest that heavy Fe isotope enrichments alone are not diagnostic of primary IF mineralogies, and ferrihydrite and partially oxidized or even purely ferrous greenalite are all viable primary IF mineralogies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The nature and origins of decametre-scale porosity in Ordovician carbonate rocks, Halahatang oilfield, Tarim Basin, China
At >7 km depths in the Tarim Basin, hydrocarbon reservoirs in Ordovician rocks of the Yijianfang Formation contain large cavities ( c . 10 m or more), vugs, fractures and porous fault rocks. Although some Yijianfang Formation outcrops contain shallow (formed near surface) palaeokarst features, cores from the Halahatang oilfield lack penetrative palaeokarst evidence. Outcrop palaeokarst cavities and opening-mode fractures are mostly mineral filled but some show evidence of secondary dissolution and fault rocks are locally highly ( c . 30%) porous. Cores contain textural evidence of repeated formation of dissolution cavities and subsequent filling by cement. Calcite isotopic analyses indicate depths between c . 220 and 2000 m. Correlation of core and image logs shows abundant cement-filled vugs associated with decametre-scale fractured zones with open cavities that host hydrocarbons. A Sm–Nd isochron age of 400 ± 37 Ma for fracture-filling fluorite indicates that cavities in core formed and were partially cemented prior to the Carboniferous, predating Permian oil emplacement. Repeated creation and filling of vugs, timing constraints and the association of vugs with large cavities suggest dissolution related to fractures and faults. In the current high-strain-rate regime, corroborated by velocity gradient tensor analysis of global positioning system (GPS) data, rapid horizontal extension could promote connection of porous and/or solution-enlarged fault rock, fractures and cavities. Supplementary material: Stable isotopic analyses and the velocity gradient tensor and principal direction and magnitude calculation are available at https://doi.org/10.6084/m9.figshare.c.4946046 Thematic collection: This article is part of the The Geology of Fractured Reservoirs collection available at: https://www.lyellcollection.org/cc/the-geology-of-fractured-reservoirs
Geology↗
Techno-Economic Analysis of Greenfield Geothermal Hybrid Power Plants using a Solar or Natural Gas Steam Topping Cycle
The relatively low generation costs associated with wind, solar photovoltaic (PV), and natural-gas power plants make it challenging for geothermal power plants to produce and sell the power that has the reliability and sustainability characteristics that are greatly needed in U.S. power markets. This is especially true for geothermal resources with low-to-medium temperatures, which results in relatively low-thermal efficiency and generation costs that are higher than those for wind, solar PV, and natural gas. This analysis evaluates solar thermal- and natural-gas combustion waste heat recovery-based topping cycle hybridization of geothermal binary power plants. This approach provides several benefits that may allow geothermal power plants to generate power at more competitive costs. First, the addition of solar thermal energy or natural-gas combustion waste heat input to a geothermal power plant provides additional heat input that can be converted to electrical power. Second, the temperature level of the heat obtained from concentrating solar collectors or natural-gas combustion exhaust is higher than that of geothermal heat, which provides opportunities for improving the efficiency of the conversion of thermal energy to electrical power. Third, the ease with which solar thermal systems integrate with energy storage and the flexibility of natural gas means power generation can occur during peak demand periods. The hybrid cycles are compared to equivalently sized, co-located, independent geothermal, concentrating solar, and/or natural-gas power plants. The hybrid cycle tends to produce slightly more power than the standalone plants combined. However, the hybrid plant Levelized Cost of Energy (LCOE) is slightly higher than the LCOE of the combined standalone power plants for each of the case study locations investigated. Using the steam-topping cycle, organic Rankine cycle (ORC)-bottoming cycle hybrid plant design to combine a solar thermal resource and low- temperature geothermal resource (<120 degrees C) leads to a hybrid plant with a lower LCOE than a standalone geothermal-only system. Thus, hybrid plants may enable the economic development of geothermal resources in locations with low geothermal resource temperatures. However, in areas with higher geothermal resource temperatures (>120 degrees C), the geothermal-only plant has a lower LCOE than the hybrid cycle and thus could be developed without the need for solar heat addition. iv A geothermal-natural-gas reciprocating engine hybrid plant was evaluated for an Elk Hills, California case study location. The Elk Hills case study analysis indicates that when the natural-gas engine operates for more than 12 hours per day the hybrid plant can produce power at an LCOE lower than a standalone geothermal plant, and comparable to that of the standalone natural-gas reciprocating engine, while also reducing the carbon intensity of the power generated relative to the standalone natural-gas engine. This may represent a scenario in which the hybrid plant provides an opportunity for the deployment of a low-temperature geothermal resource that otherwise may have an LCOE too high to develop and operate as a standalone resource, while also reducing the carbon intensity of natural-gas generation sources. A "triple-hybrid" plant that combines natural gas, solar thermal, thermal energy storage, and geothermal was also investigated. A natural-gas combustion turbine (NGCT) is added to the geothermal-solar hybrid such that the hot exhaust gas from the gas turbine provides an alternative source of heat to the steam turbine of the hybrid cycle. Analysis results suggest that the triple-hybrid plant has a significantly higher energy generation and revenue than a standalone NGCT or the original geothermal-solar hybrid. The triple-hybrid design benefits most from using a smaller solar field so that the solar energy can be dispatched at the most valuable times available. The triple-hybrid plant also has a lower LCOE than the standalone NGCT. The triple-hybrid plant was evaluated making simple assumptions about the dispatch profile of the gas cycle, and more nuanced and realistic dispatching schedules should be analyzed in future work.
15 GEOTHERMAL ENERGY↗
Editorial: Nanotechnology for natural products
Humans around the globe have lived through an unprecedented time. The emergence and rapid spread of coronavirus disease 2019 (COVID-19) have resulted in the loss of millions of lives, and this number is still climbing every day and hour. As a consequence, there have been drastic changes over the past two years in how we live, communicate, and work, some of which may have changed forever: remote conferencing has become a new norm for businesses, schools, and academia; work-from-home and hybrid working is now more than just acceptable in many industries; most importantly, COVID-19 has raised global awareness of infectious diseases and pandemic responses to an exceptional level. Certainly, COVID-19 is not the only disease that is causing human suffering at this moment. Other highly contagious and lethal viruses, such as the human immunodeficiency virus (HIV), Ebola, and the recent addition to the list, Monkeypox, pose extraordinary challenges to modern civilizations. On the other hand, non-communicable diseases, such as heart disease, stroke, and cancer, are still claiming the majority of deaths on a global level (World Health Organization, 2020). Before the availability of synthetic drugs, civilizations worldwide relied on natural products extracted from the environment and various organisms for healthcare. Natural products and their derivatives continue to be critical components in the drug library available today. Indeed, almost a quarter of the new drugs approved by the US Food and Drug Administration (FDA) since 1981 are natural products, botanical mixtures, or their derivatives (Newman and Cragg, 2020). Recent developments in analytical characterization, genome mining, and engineering have further increased interest in drug discovery from the pool of natural products (Atanasov et al., 2021). This Research Topic celebrates a collection of studies at the intersection of natural product research and nanotechnological advances. As a successor and extension of the Research Topic in “Nanotechnology in Traditional Medicines and Natural Products” published last year (Zhang et al., 2021), the present collection focused more on recent developments in employing the synthesis and characterization of nanostructures for the delivery of functional natural products. Specifically, the use of carrier nanostructures to conjugate or encapsulate therapeutically active natural products with carrier nanostructures could enable their robust, targeted delivery tailored to either tackle a specific disease or unlock a drug administration pathway. Over the last decade, nanostructures such as liposomes (Pattni et al., 2015) and lipid nanoparticles (Hou et al., 2021) have been developed as versatile platforms for the inclusion and delivery of a wide range of therapeutical compounds; a significant advance in this aspect is the stabilization of mRNA strands for COVID-19 vaccination recently produced by Pfizer/BioNTech and Moderna (Tenchov et al., 2021). Such engineered nanomaterials are now widely used in the development of new drugs, while regulatory forces, such as the US FDA, remain cautious with the evaluation of each product on a case-by-case basis (Wang and Grainger, 2022). In this collection, Zeng et al. provided a timely review of natural products conjugated to and contained within nanomaterials for the ongoing COVID-19 pandemic. Natural products that are potentially useful in the mitigation of this disease, such as chloroquine and curcumin, supported in nanocarrier systems, have been discussed in detail. More broadly, Cheng et al. comprehensively reviewed the use of liposomes as a nanocarrier for natural products. This article provides a summary of natural product compounds and extracts used to form liposomal structures. Readers can further enjoy the practical aspects of these engineered drugs for the treatment of specific diseases as well as insights into future directions in this field.
peptides↗
Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)
In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.
03 NATURAL GAS↗
Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook Salmon during spawning in the Klickitat River, Washington, USA
Abstract Objective A goal of many segregated salmonid hatchery programs is to minimize potential interbreeding between hatchery- and natural-origin fish. Our objective was to assess this on the Klickitat River, Washington, USA. Methods We used radiotelemetry to evaluate spatiotemporal spawning overlap between hatchery- and natural-origin steelhead Oncorhynchus mykiss and spring Chinook Salmon O. tshawytscha. We estimated percentages of tagged fish that spawned naturally in the Klickitat River subbasin, emigrated from the Klickitat River, or died before spawning. A kernel density analysis was used to estimate probability of spatiotemporal overlap between hatchery- and natural-origin spawners. Result For steelhead, 12% of hatchery-origin and 50% of natural-origin fish spawned naturally. For spring Chinook Salmon, 18% of hatchery-origin and 44% of natural-origin fish spawned naturally. Tag loss may result in underestimates in these percentages. Most hatchery-origin steelhead (90%) spawned downstream of river kilometer (rkm) 32, and 75% spawned from November to mid-March. The majority of natural-origin steelhead (64%) spawned upstream of rkm 32, and 75% spawned from mid-March to late May. Spawn timing of hatchery-origin Chinook Salmon (early August to mid-September) overlapped with that of natural-origin Chinook Salmon (late July to late September), and fish of both origins spawned in the same 30-km reach of the river. We estimated the percentage of hatchery-origin spawners (pHOS) on the natural spawning grounds to be 12% for steelhead and 40% for spring Chinook Salmon across all study years. For steelhead, we estimated the overlap probability to be 25% (95% CI = 22.5–28%). For spring Chinook Salmon, tight spatial clustering of hatchery-origin fish resulted in a lower overlap estimate of 21% (13–31%). Conclusion We suggest adjusting pHOS estimates using these overlap estimates or similar spatiotemporal data on actual spawner proximity and possible interactions, and that these types of analyses be used in conjunction with gene flow analysis to accurately evaluate effects of individual hatchery programs.
Zendt, Joseph S.↗
Evaluating U.S. Natural Gas Environmental Performance
This work summarizes the U.S. Department of Energy National Energy Technology Laboratory's (NETL) modeling and analysis of natural gas environmental performance. Over the past year, NETL updated its U.S. natural gas supply chain life cycle baseline model to incorporate 2020 data, regionalize the transmission and distribution network into six regions, incorporate improved gathering and boosting stage and distribution stage emissions factors, and assign environmental burdens among the various co-products (i.e., crude oil, natural gas liquids, natural gas) of the natural gas supply chain. The updated natural gas model helps generate more comprehensive and regionalized natural gas profiles, mapping production basins to the relevant transmission and distribution regions downstream. The work incorporates data from multiple peer reviewed measurement-based studies to achieve the objective of providing a comprehensive understanding of emissions from the U.S. natural gas supply chain. This presentation also explores future work by NETL to develop a platform that enables stakeholders to customize key parameters within the natural gas LCA model and observe the corresponding effects on the carbon intensity of the overall supply chain. The platform aims to offer a convenient method for stakeholders to obtain relevant insights from the updated model, without diving deep into the intricacies of the NETL natural gas model with hundreds of parameters and linkages.
Khutal, Harshvardhan↗
North American energy system responses to natural gas price shocks
As of 2020, North American natural gas extraction and use in the electricity sector have both reached all-time highs. The combination of North America's increased reliance on natural gas with a potential disruption to the natural gas market has several energy security implications. Additionally, policymakers interested in economic resiliency will find this study's results useful for informing the implications of the energy sectors' long-term planning and investment decisions. This paper evaluates how both the electricity and natural gas sectors could respond to hypothetical gas price shocks under different system configurations. We impose unforeseen natural gas price shocks under reference and alternative configurations resulting from a renewable generation mandate or variations to renewable capacity costs. Results from several different models are presented for the electricity and natural gas sectors separately for Canada, Mexico, and the United States. Generally, the US becomes more (less) reliant on electricity imports from Canada given a high (low) gas price shock but increases (decreases) exports to Mexico. The renewable mandate is shown to buffer electricity price increases under high price shocks but price reductions under the low price shocks are dampened given less flexibility to take advantage of the low-priced natural gas. The United States is demonstrated to reduce natural gas production and net exports with high natural gas price shocks given a reduction in demand.
03 NATURAL GAS↗
Ternary complexes of isopentenyl phosphate kinase from Thermococcus paralvinellae reveal molecular determinants of non‐natural substrate specificity
Abstract Isopentenyl phosphate kinases (IPKs) have recently garnered attention for their central role in biocatalytic “isoprenol pathways,” which seek to reduce the synthesis of the isoprenoid precursors to two enzymatic steps. Furthermore, the natural promiscuity of IPKs toward non‐natural alkyl‐monophosphates (alkyl‐Ps) as substrates has hinted at the isoprenol pathways' potential to access novel isoprenoids with potentially useful activities. However, only a handful of IPK crystal structures have been solved to date, and even fewer of these contain non‐natural substrates bound in the active site. The current study sought to elucidate additional ternary complexes bound to non‐natural substrates using the IPK homolog fromThermococcus paralvinellae(TcpIPK). Four such structures were solved, each bound to a different non‐natural alkyl‐P and the phosphoryl donor substrate/product adenosine triphosphate (ATP)/adenosine diphosphate (ADP). As expected, the quaternary, tertiary, and secondary structures ofTcpIPK closely resembled those of IPKs published previously, and kinetic analysis of a novel alkyl‐P substrate highlighted the potentially dramatic effects of altering the core scaffold of the natural substrate. Even more interesting, though, was the discovery of a trend correlating the position of two α helices in the active site with the magnitude of an IPK homolog's reaction rate for the natural reaction. Overall, the current structures ofTcpIPK highlight the importance of continued structural analysis of the IPKs to better understand and optimize their activity with both natural and non‐natural substrates.
Biochemistry & Molecular Biology↗
NP-MRD: the Natural Products Magnetic Resonance Database
The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation.
59 BASIC BIOLOGICAL SCIENCES↗
EVALUATION OF CONTROLLED END GAS AUTO IGNITION WITH EXHAUST GAS RECIRCULATION IN A STOICHIOMETRIC, SPARK IGNITED, NATURAL GAS ENGINE
Many stationary and heavy-duty on-road natural gas fueled engines today operate under stoichiometric conditions with a three-way catalyst. The disadvantage of stoichiometric natural gas engines compared to lean-burn natural gas and diesel engines is lower efficiency, resulting primarily from lower power density and compression ratio. Exhaust gas recirculation (EGR) coupled with advanced combustion controls can enable operation with higher compression ratio and power density, which yields higher efficiency. This also results in engine operation between the limits of knock and misfire. Operation between these limits has been named controlled end gas auto-ignition (C-EGAI) and can be used to improve the brake efficiency of the engine. Various methods of cylinder pressure-based knock quantification were explored to implement C-EGAI. The indicated quantification methods are used for the implementation of a control scheme for C-EGAI with a relation to the fractional heat release due to auto-ignition. A custom EGR system was built and the effect of EGR on the performance of a stochiometric, spark ignited, natural gas engine is evaluated. C-EGAI is implemented and the optimal parameters are determined for peak performance under EGR and C-EGAI conditions. In this study, knock detection is used for the recognition, magnitude, and location of the auto-ignition events. Cylinder pressure-based knock detection was the primary method for determining the occurrence and location of knock but was also used for implementing the ignition control scheme for controlled end gas auto-ignition. The combustion intensity metric (CIM) enabled parametric ignition timing control which allowed for the creation of a relationship between fractional heat release due to auto-ignition and CIM. Many stationary and heavy-duty on-road natural gas fueled engines today operate under stoichiometric conditions with a three-way catalyst. The disadvantage of stoichiometric natural gas engines compared to lean-burn natural gas and diesel engines is lower efficiency, resulting primarily from lower power density and compression ratio. Exhaust gas recirculation (EGR) coupled with advanced combustion controls can enable operation with higher compression ratio and power density, which yields higher efficiency. This also results in engine operation between the limits of knock and misfire. Operation between these limits has been named controlled end gas auto-ignition (C-EGAI) and can be used to improve the brake efficiency of the engine. Various methods of cylinder pressure-based knock quantification were explored to implement C-EGAI. The indicated quantification methods are used for the implementation of a control scheme for C-EGAI with a relation to the fractional heat release due to auto-ignition. A custom EGR system was built and the effect of EGR on the performance of a stochiometric, spark ignited, natural gas engine is evaluated. C-EGAI is implemented and the optimal parameters are determined for peak performance under EGR and C-EGAI conditions. In this study, knock detection is used for the recognition, magnitude, and location of the auto-ignition events. Cylinder pressure-based knock detection was the primary method for determining the occurrence and location of knock but was also used for implementing the ignition control scheme for controlled end gas auto-ignition. The combustion intensity metric (CIM) enabled parametric ignition timing control which allowed for the creation of a relationship between fractional heat release due to auto-ignition and CIM. Both exhaust gas recirculation and controlled end gas auto-ignition were analyzed with a cooperative fuel research (CFR) engine modified for boosted fuel/air intake. The data was interpreted to provide a proper evaluation of unique analytical methods to quantify the results of C_EGAI and characterize the live auto-ignition events. The control variables for this method of C-EGAI were optimized with EGR conditions to generate the point of peak performance on the CFR engine under stoichiometric, spark ignited, natural gas conditions.
Bayliff, Scott Michael↗
Techno-Economic Analysis of Repurposing Natural Gas Transmission Pipeline Networks to Accommodate Hydrogen Blends
Blending hydrogen into natural gas infrastructure could supplement natural gas supply and increase resilience for applications such as ammonia production, peaking and load-following power plants, and heating. The United States has an extensive network of natural gas pipelines, but the feasibility of employing this infrastructure to transport hydrogen is unclear. We analyze the costs associated with repurposing three distinct natural gas transmission pipelines in different locations within the United States to carry blends of hydrogen up to 100% via three different pipeline network modification methods and compare against the cost of building a new dedicated hydrogen pipeline. We conduct a sensitivity analysis on the hoop stress limit of the existing pipe, techno-economic parameters, emissions, and relative capacity. The results show that the capital costs required to upgrade a pipeline can vary from tens of millions to billions of dollars depending on the length and capacity of the existing pipeline section, whether the existing pipeline already operates at or below its maximum allowable operating pressure, whether future demand is expected to increase or decrease, the network modification method selected, and pipe material costs. The delivered cost of energy to end users is impacted less by the levelized cost of transporting hydrogen blends than by the cost of the natural gas and hydrogen fuels being transported. The emissions impact of blending hydrogen into natural gas transmission networks scales proportionally with the amount of energy displaced with low-emission hydrogen (such as from natural gas with carbon capture and sequestration or electrolysis powered by nuclear, renewable, or geothermal electricity), therefore low blend ratios (e.g., < 20% vol. hydrogen) will result in low emissions impacts. Factors such as permitting and right-of-way costs, the proximity of the pipeline to hydrogen demand and production, and the compatibility of and/or retrofitting costs of end-use gas-fueled technologies will likely be greater drivers in determining whether converting a particular natural gas pipeline to carry hydrogen makes economic sense.
08 HYDROGEN↗
Natural gas liquefaction employing independent refrigerant path
A method of liquefying natural gas. The method comprises cooling a gaseous natural gas process stream with a refrigerant flowing in a path isolated from the natural gas process stream. The refrigerant may differ in composition from a composition of the natural gas process stream, and the refrigerant composition may be selected to enhance efficiency of the refrigerant path with regard to a specific composition of the natural gas process stream. The refrigeration path may be operated at pressures, temperatures and flow rates differing from those of the natural gas process stream. Other methods of liquefying natural gas are described. A natural gas liquefaction plant is also described.
03 NATURAL GAS↗
Evaluating a Laboratory Flume Microbiome as a Window Into Natural Riverbed Biogeochemistry
Riverbeds are hotspots for microbially-mediated reactions that exhibit pronounced variability in space and time. It is challenging to resolve biogeochemical mechanisms in natural riverbeds, as uncontrolled settings complicate data collection and interpretation. To overcome these challenges, laboratory flumes are often used as proxies for natural riverbed systems. Flumes capture spatiotemporal variability and thus allow for controlled investigations of riverbed biogeochemistry. These investigations implicitly rely on the assumption that the flume microbiome is similar to the microbiome of natural riverbeds. However, this assumption has not been tested and it is unknown how the microbiome of a flume compares to natural aquatic settings, including riverbeds. To evaluate the fundamental assumption that a flume hosts a microbiome similar to natural riverbed systems, we used 16s rRNA gene sequencing and publicly available data to compare the sediment microbiome of a single large laboratory flume to a wide variety of natural ecosystems including lake and marine sediments, river, lake, hyporheic, soil, and marine water, and bank and wetland soils. Richness and Shannon diversity metrics, analyses of variance, Bray-Curtis dissimilarity, and analysis of the common microbiomes between flume and river sediment all indicated that the flume microbiome more closely resembled natural riverbed sediments than other ecosystems, supporting the use of flume experiments for investigating natural microbially-mediated biogeochemical processes in riverbeds.
54 ENVIRONMENTAL SCIENCES↗
Extending Power of Nature from Binary Problems to Real-Valued Graph Learning in Real World
Nature performs complex computations constantly at clearly lower cost and higher performance than digital computers. It is crucial to understand how to harness the unique computational power of nature in Machine Learning (ML). In the past decade, besides the development of Neural Networks (NNs), the community has also relentlessly explored nature-powered ML paradigms. Although most of them are still predominantly theoretical, a new practical paradigm enabled by the recent advent of CMOS-compatible room-temperature nature-based computers has emerged. By harnessing the nature's power of entropy increase, this paradigm can solve binary learning problems delivering immense speedup and energy savings compared with NNs, while maintaining comparable accuracy. Regrettably, its values to the real world are highly constrained by its binary nature. A clear pathway to its extension to real-valued problems remains elusive. This paper aims to unleash this pathway by proposing a novel end-to-end Nature-Powered Graph Learning (NP-GL) framework. Specifically, through a three-dimensional co-design, NP-GL can leverage the nature's power of entropy increase to efficiently solve real-valued graph learning problems. Experimental results across 4 real-world applications with 6 datasets demonstrate that NP-GL delivers, on average, 6970X speedup and 10^5x energy consumption reduction with comparable or even higher accuracy than Graph Neural Networks (GNNs).
artificial intelligence↗