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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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Proposed apparatus for welding large arrays of solar cells to flexible circuit substrates would sense infrared emission from welding spot. Emission would provide feedback for control of welding heat. Welding platform containing optical fibers moves upward through slots in movable holding fixture to contact solar cells. Fibers pick up infrared radiation from weld area.
Methane is an important atmospheric gas with potentially critical roles in both photochemical and radiation transfer processes. A major natural source of atmospheric methane involves anaerobic fermentation of organic materials in wetland soils and sediments. A data base of field measurements of atmospheric methane was used in the development of a global methane emissions inventory. Calculations support the following hypotheses: (1) Human activities currently produce methane at a rate approximately equal to natural resources (these rapidly increasing anthropogenic sources can explain most of the recent increase observed in tropospheric methane); and (2) Prior to 200 B.P. (before the present), the influence of climate on wetland extent and distribution was probably a dominant factor controlling global biogenic methane emissions to the atmosphere.
A series of controlled experiments were conducted to determine the significance of crop residues or stubble in estimating the emission of the underlying soil. Observations using truck-mounted L and C band passive microwave radiometers showed that for dry wheat and soybeans the dry residue caused negligible attenuation of the background emission. Green residues, with water contents typical of standing crops, did have a significant effect on the background emission. Results for these green residues also indicated that extremes in plant structure, as created using parallel and perpendicular stalk orientations, can cause very large differences in the degree of attenuation.
Modern tokamaks have achieved significant fusion production, but further progress towards steady-state operation has been stymied by a host of kinetic and MHD instabilities. Control and identification of these instabilities is often complicated, warranting the application of data-driven methods to complement and improve physical understanding. In particular, Alfvén eigenmodes are a class of ubiquitous mixed kinetic and MHD instabilities that are important to identify and control because they can lead to loss of confinement and potential damage to the walls of a plasma device. In the present work, we use reservoir computing networks to classify Alfvén eigenmodes in a large labeled database of DIII-D discharges, covering a broad range of operational parameter space. However, despite the large parameter space, we show excellent classification and prediction performance, with an average hit rate of 91% and false alarm ratio of 7%, indicating promise for future implementation with additional diagnostic data and consolidation into a real-time control strategy.
A universal modulation and frequency control system for use with data collection platform (DCP) transmitters is examined. The final design discussed can, under software/firmwave control, generate all of the specific digital data modulation formats currently used in the NASA satellite data collection service and can simultaneously synthesize the proper RF carrier frequencies employed. A novel technique for DCP time and frequency control is presented. The emissions of NBS radio station WWV/WWVH are received, detected, and finally decoded in microcomputer software to generate a highly accurate time base for the platform; with the assistance of external hardware, the microcomputer also directs the recalibration of all DCP oscillators to achieve very high frequency accuracies and low drift rates versus temperature, supply voltage, and time. The final programmable DCP design also employs direct microcomputer control of data reduction, formatting, transmitter switching, and system power management.
Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.
A readily parallelized Maximum Likelihood Estimation (MLE) algorithm with linear computational complexity is demonstrated in real time using only measurements from an extreme ultraviolet (EUV) diagnostic to control the horizontal position of a tokamak plasma. A set of trial emissivity profiles are parameterized by the control quantity of interest (R m ), and the MLE is identified from the profile which minimizes the signal reconstruction residual. The algorithm depends on an empirically determined likelihood function with exponential form. EUV emission (λ ≈ 15eV-1keV) is captured in a poloidal plane by four 16-channel AXUV diodes mounted at different poloidal angles with radial and angular resolution sufficient to discern plasma equilibrium evolution in HBT-EP. Calculations of the plasma major radius by the system are consistent within diagnostic uncertainty for the majority of the discharge with those of: a weighted average of vertical soft X-ray or EUV chords, magnetic sensors, and an equilibrium reconstruction. The feedback system corrects for a horizontal displacement of the major radius equal to 20% of the plasma minor radius by adjusting the vertical field produced from 40 in-vessel control coils in real time. The MLE calculation is performed on a GPU in a 15 μs cycle, with similar performance in this application to a simple weighted average of vertical chords. Finally, results demonstrate horizontal position control using magnetic actuators and an optical observer.
This project explored advanced ignition technologies to significantly enhance efficiency and reduce operating costs for heavy-duty natural gas engines operating at stoichiometric conditions, while meeting ultra-low NOx emission standards. The main goal was to develop and validate a plasma-assisted pre-chamber ignition system that could deliver at least a 2% increase in brake thermal efficiency (BTE) and a 4% decrease in total cost of ownership (TCO) compared to a typical multi-cylinder engine with three-way catalyst aftertreatment, ensuring compatibility with the expected 2027 EPA/CARB regulations. In the first half of the project, the research team concentrated on developing and testing plasma-assisted pre-chamber ignition using nanosecond pulsed discharges. Extensive experiments were conducted in an optically accessible rapid-compression and expansion machine, a constant-volume chamber, and an optical single-cylinder engine. Experiments were coupled with CFD simulations. The work produced unique insights into pre-chamber flame formation, jet ignition, dilution effects, and flame quenching at pressures, temperatures, and dilution levels relevant to engines. Although plasma-assisted ignition showed promise in controlled lab settings, the research also identified fundamental and practical challenges when applying this technology to real engine conditions. Midway through the project, a crucial pivot was made, guided by three key findings. First, the power electronics required for nanosecond plasma discharges were found to be too costly for commercial use, undermining the project’s cost-of-ownership goals. Second, nanosecond plasma ignition was highly sensitive to turbulent flow in the pre-chamber, resulting in lower ignition reliability than traditional spark under engine-like conditions. Third, achieving a truly diffuse low-temperature plasma at high pressures near top dead center was not possible, reducing the anticipated chemical enhancement benefits. These results collectively suggested that continuing with plasma-assisted ignition was unlikely to meet both efficiency and cost objectives. In response, the project shifted focus to a more realistic approach: enhancing traditional spark-based pre-chamber ignition with significantly less spark energy. Using insights gained earlier in the project, the team redesigned the pre-chamber to maintain high dilution tolerance and quick combustion, even with lower ignition energy. Testing confirmed that with optimized pre-chamber design and combustion timing, a lower-energy spark could reliably ignite highly diluted stoichiometric mixtures, reduce burn time, and boost thermal efficiency. Final engine testing and techno-economic analysis verified that this revised approach successfully achieved the project goals. The optimized pre-chamber ignition system provided over a 2% increase in calculated brake thermal efficiency compared to the baseline engine. Notably, the lower ignition energy and simplified hardware reduced component stress, extended maintenance intervals, and lowered the total cost of ownership. When used with stoichiometric operation and traditional three-way aftertreatment, the system remained compatible with near-zero NOx emissions targets without increasing cost or complexity in the emissions control system. In summary, although the project deviated from its initial plasma-assisted ignition idea, the work produced a more practical and commercially viable solution. The results show that precisely optimized, low-energy pre-chamber spark ignition can significantly improve efficiency and reduce overall ownership costs for heavy-duty natural gas engines. This directly aligns with DOE goals for cleaner, more efficient, and cost-effective transportation technologies.
The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance. Comparisons were made between ultralow-sulfur diesel and a blend of 25% hexyl hexanoate with diesel. Model validation data were informed by 2019 model year Cummins ISB 6.7 L diesel engine maps and transient validation data in a pre-production hybrid configuration and a direct dyno coupled configuration with diesel fuel and a blend of 25% hexyl hexanoate with diesel.
In this paper, we develop an exact analytical quantum theory for field emission from surfaces with a nearby quantum well, by solving the one-dimensional time-independent Schrödinger equation. The quantum well, which may be introduced by ions, atoms, nanoparticles, etc., is simplified as a square potential well with depth H, width d, and distance to the surface L. The theory is used to analyze the effects of the quantum well (d, H, and L), the cathode properties (work function W and Fermi energy E F ), and dc field F. It is found that the quantum well can lead to resonant tunneling enhanced field emission up to several orders of magnitude larger than that from bare cathode surfaces. In the meantime, the electron-emission-energy spectrum is significantly narrowed. The strong enhancement region is bounded by the conditions eFL + H ≥ W + C and eFL ≤ W, with e being the elementary charge (positive) and C a constant dependent on dc field F. It is also found that the linear shift of resonance peaks in the electron-emission-energy spectrum with dc field F follows ε p =ε p0 –eFL, with ε p0 being approximately the eigenenergies for electrons confined in a square potential well without a dc field. Finally, the theory provides insights for the design of high-efficiency field emitters, which can produce a high current and highly collimated electron beams.
Polycyclic aromatic hydrocarbons such as perylene, pyrene, and their derivatives are highly emissive fluorophores in solution. Furthermore, the practical applications of these materials in the field of molecular electronic and light emitting devices are often hindered by self-quenching effects due to the formation of non-fluorescent aggregates in concentrated solutions or in the solid state. Herein, we demonstrate that aggregation caused quenching of perylenes can be minimalized by molecular incorporation into metalorganic frameworks (MOFs). This study utilized a stable Zr 6 cluster-based MOF, UiO-67, as a matrix. Linear linkers containing the photo-responsive moieties were designed and incorporated into the parent UiO-67 scaffold through the partially replacement of the non-fluorescent linkers of a similar length, forming mixed-linker MOFs. Here, the average distance between perylene moieties was tuned by changing the linker ratios, thus controlling the fluorescence intensity, emission wavelength, and quantum yield. Molecular modeling was further adopted to correlate the number of isolated perylene linkers within the framework to the ratio between the two linkers, therefore rationalizing the change in the observed fluorescent properties. Taking advantage of the tunable fluorescence, inherent porosity, and high chemical stability of this MOF platform, it was applied as a fluorescent sensor for oxygen detection in the gas phase, a model reaction, showing fast response and good recyclability.
Short-period sub-Neptunes with substantial volatile envelopes are among the most common type of known exoplanets. However, recent studies of the Kepler population have suggested a dearth of sub-Neptunes on highly irradiated orbits, where they are vulnerable to atmospheric photoevaporation. Physically, we expect this "photoevaporation desert" to depend on the total lifetime X-ray and extreme ultraviolet flux, the main drivers of atmospheric escape. In this work, we study the demographics of sub-Neptunes as a function of lifetime exposure to high-energy radiation and host-star mass. We find that for a given present-day insolation, planets orbiting a 0.3 solar mass star experience approximately 100 times more X-ray flux over their lifetimes versus a 1.2 solar mass star. Defining the photoevaporation desert as a region consistent with zero occurrence at 2 sigma, the onset of the desert happens for integrated X-ray fluxes greater than 1.43 times 10 (sup 22) to 8.23 times 10 (sup 20) as a function of planetary radii for 1.8 to 4 Earth radius. We also compare the location of the photoevaporation desert for different stellar types. We find much greater variability in the desert onset in the bolometric flux space compared to the integrated X-ray flux space, suggestive of photoevaporation driven by steady-state stellar X-ray emissions as the dominant control on desert location. Finally, we report tentative evidence for the sub-Neptune valley, first seen around Sun-like stars, for M&K dwarfs. The discovery of additional planets around low-mass stars from surveys such as the Transiting Exoplanet Survey Satellite (TESS) mission will enable detailed exploration of these trends.
It is evident from extreme weather patterns that climate change is impacting the whole world. The consequences in the form of unpredicted severe weather conditions, hurricanes, floods, and wildfires have been disrupting national economies and affecting lives across the globe. As the global economy is recovering from the COVID-19 pandemic, the temporary drop in greenhouse gas (GHG) emissions mainly caused due to travel bans and economic slowdowns is no longer the case and, moving forward, controlling the increase in GHG emissions has emerged as a global challenge. The impact of climate change has enabled an acknowledgement of the challenge and this coincided with the rapid development of clean energy technologies for buildings, transportation, and industrial sectors, while ensuring a significant reduction in costs for their wide implementation.
Solid oxide fuel cells (SOFCs) have been deployed in hybrid decentralized energy systems, in which they are directly coupled to internal combustion engines (ICEs). Prior research indicated that the anode tailgas exiting the SOFC stack should be additionally exploited due to its high energy value, with typical ICE operation favoring hybridization due to matching thermodynamic conditions during operation. Consequently, extensive research has been performed, in which engines are positioned downstream the SOFC subsystem, operating in several modes of combustion, with the most prevalent being homogeneous compression ignition (HCCI) and spark ignition (SI). Experiments were performed in a 3-cylinder ICE operating in the latter modus operandi, where the anode tailgas was assimilated by mixing syngas (H 2 : 33.9%, CO: 15.6%, CO 2 : 50.5%) with three different water vapor flowrates in the engine’s intake. While increased vapor content significantly undermined engine performance, brake thermal efficiency (BTE) surpassed 34% in the best case scenario, which outperformed the majority of engines operating under similar operating conditions, as determined from the conducted literature review. Nevertheless, the best performing application was identified operating under HCCI, in which diesel reformates assimilating SOFC anode tailgas, fueled a heavy duty ICE (17:1), and gross indicated thermal efficiency ([Formula: see text]) of 48.8% was achieved, with the same engine exhibiting identical performance when operating in reactivity-controlled compression ignition (RCCI). Overall, emissions in terms of NO x and CO were minimal, especially in SI engines, while unburned hydrocarbons (UHC) were non-existent due to the absence of hydrocarbons in the assessed reformates.
The demand for ultranarrow spectral emission below 10 nm is critical for next-generation displays. Although current colloidal nanocrystals are successful in light down-conversion applications, they fall short in matching the stringent color purity requirements set by standards like Rec. 2020. Achieving such narrow linewidths through material engineering alone remains elusive, necessitating innovative light management strategies that avoid optical losses and maintain device efficiency. Here, in this work, we present a novel 2D colloidal heterostructure design, combining a CdSe core nanoplatelet, a CdS crown, and a CdZnS shell, to achieve bright bicolor emission in the solid state (green/red) emission with tunable intensity ratios controlled by excitation power (either optical or electrical). Integration of these nanoplatelets into a dielectric cavity further narrows the emission linewidth to sub-2 nm while enhancing the photoluminescence intensity by up to 200 times, meeting the Rec. 2020 color purity targets. This approach paves the way for a strategy avoiding complex laser-based solutions.
Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality and atmospheric chemistry. The understanding and ability to model the horizontal and vertical structure of O3 mixing ratios is difficult due to the complex formation/destruction processes and transport pathways that cause large variability of O3. The Environmental Protection Agency has National Ambient Air Quality Standards for O3 set at 75 ppb with future standards proposed to be as low as 65 ppb. These lower values emphasize the need to better understand/simulate the transport processes, emission sources, and chemical processes controlling precursor species (e.g., NOx, VOCs, and CO) which influence O3 mixing ratios. The uncertainty of these controlling variables is particularly large in the southeast United States (US) which is a region impacted by multiple different emission sources of precursor species (anthropogenic and biogenic) and transport processes resulting in complex spatio-temporal O3 patterns. During this work we will evaluate O3 and precursor species in the southeast US applying models, ground-based and airborne in situ data, and lidar observations. In the summer of 2013, the UAH O3 Differential Absorption Lidar (DIAL) (part of the Tropospheric Ozone Lidar Network (TOLNet)) measured vertical O3 profiles from the surface up to approximately 12 km. During this period, the lidar observed numerous periods of dynamic temporal and vertical O3 structures. In order to determine the sources/processes impacting these O3 mixing ratios we will apply the CTM GEOS-Chem (v9-02) at a 0.25 deg x 0.3125 deg resolution. Using in situ ground-based (e.g., SEARCH Network, CASTNET), airborne (e.g., NOAA WP-3D - SENEX 2013, DC-8 - SEAC4RS), and TOLNet lidar data we will first evaluate the model to determine the capability of GEOS-Chem to simulate the spatio-temporal variability of O3 in the southeast US. Secondly, we will perform model sensitivity studies in order to quantify which emission sources (e.g., anthropogenic, biogenic, lighting, wildfire) and transport processes (e.g., stratospheric, long-range, local scale) are contributing to these TOLNet-observed dynamic O3 patterns. Results from the evaluation of the model and the study of sources/processes impacting observed O3 mixing ratios will be presented.
2D hybrid perovskites are attractive for optoelectronic devices. In thin films, the color of optical emission and the texture of crystalline domains are often difficult to control. Here, a method for extinguishing or enhancing different emission features is demonstrated for the family of 2D Ruddlesden-Popper perovskites (EA(1-)(x)FA(x))(4)Pb3Br10 (EA = ethylammonium, FA = formamidinium). When grown from aqueous hydrobromic acid, crystals of (EA(1-)(x)FA(x))(4)Pb3Br10 retain all the emission features of their parent compound, (EA)(4)Pb3Br10. Surprisingly, when grown from dimethylformamide (DMF), an emission feature, likely self-trapped exciton (STE), near 2.7 eV is missing. Extinction of this feature is correlated with DMF being incorporated between the 2D Pb-Br sheets, forming (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y). Without FA, films grown from DMF form (EA)(4)Pb3Br10, retain little solvent, and have strong emission near 2.7 eV. Slowing the kinetics of film growth strengthens a different emission feature, likely a different type of STE, which is much broader and present in all compositions. Films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) have large, micron-sized domains and homogeneous orientation of the semiconducting sheets, resulting in low electronic disorder near the absorption edge. The ability to selectively strengthen or extinguish different emission features in films of (EA(1-)(x)FA(x))(4)Pb3Br10 center dot(DMF)(y) reveals a pathway to tune the emission color in these compounds.
Measurements of biogenic soil emissions of nitric oxide (NO) and nitrous oxide (N2O) before and after a controlled burn conducted in a chaparral ecosystem on June 22, 1987, showed significantly enhanced emissions of both gases after the burn. Mean NO emissions from heavily burned and wetted (to simulate rainfall) sites exceeded 40 ng N/sq m s, and increase of 2 to 3 compared to preburn wetted site measurements. N2O emissions from burned and wetted sites ranged from 9 to 22 ng N/sq m s. Preburn N2O emissions from these wetted sites were all below the detection level of the instrumentation, indicating a flux below 2 ng N/sq m s. The flux of NO exceeded the N2O flux from burned wetted sites by factors ranging from 2.7 to 3.4. These measurements, coupled with preburn and postburn measurements of ammonium and nitrate in the soil of this chaparral ecosystem and measurements of NO and N2O emissions obtained under controlled laboratory conditions, suggest that the postfire enhancement of NO and N2O emissions is due to production of these gases by nitrifying bacteria.