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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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Temperature modulation was demonstrated as a novel way to control water partitioning during the reaction of silicate minerals with water-saturated supercritical carbon dioxide.
Abstract Numerous solids including gas hydrates, waxes, and asphaltenes have the potential to form in the production lines of gas and oil fields. This creates a highly non-ideal scenario as the accumulation of said species leads to flow assurance issues, especially with long-term processes like deposition. Since an ever-increasing amount of material is deposited in place at the pipe surface, production stoppage or active mitigation efforts become inevitable. The latter production issues result in increased safety risks and operational expenditures. Therefore, a cost-effective, passive deposition mitigation technology, such as a pipeline coating or surface treatment is especially appealing. The ability to address multiple pipeline flow assurance issues simultaneously without actively disrupting production would represent a dramatic step forward in this area. This study is part of a long-term ongoing effort that evaluates the performance and application of an omniphobic surface treatment for solids deposition prevention in industrially relevant systems. In particular, this specific work concentrates on the efficacy and robustness of the treatment under fully flowing conditions. The apparatuses utilized for this include two flowloops: a lab-scale, high-pressure flowloop for gas hydrate and surface treatment durability studies, and a bench-scale, atmospheric pressure loop for crude oil and asphaltene experiments. Film growth in high-pressure flowloop tests corroborated previous reports of delayed gas hydrate nucleation observed in rocking cells. Without the aid of the memory effect, treated oil-dominated experiments never experienced hydrate formation, spending upwards of a week in the hydrate stability zone (at the subcooled/fluid test conditions). Subsequent tests which utilized the memory effect then revealed that the hydrate formation rate reduced in the presence of the surface treatment compared to a bare stainless-steel surface. This testing was part of a larger set of trials conducted in the flowloop, which lasted about one year. The surface treatment durability under flowing conditions was evaluated during this time. Even after experiencing ∼4000 operating hours and 2 full pressure cycles, no evidence of delamination or damage was detected. Finally, as part of an extension to previous work, corroded surface asphaltene deposition experiments were performed in a bench-top flowloop. Treated experiments displayed an order of magnitude reduction in both total oil (all fractions of crude oil) and asphaltene fraction deposited.
Land surface evapotranspiration (ET) is one of the main energy sources for atmospheric dynamics and a critical component of the local, regional, and global water cycles. Consequently, accurate measurement or estimation of ET is one of the most active topics in hydro-climatology research. With massive and spatially distributed observational data sets of land surface properties and environmental conditions being collected from the ground, airborne or space-borne platforms daily over the past few decades, many research teams have started to use big data science to advance the ET estimation methods. The Geostationary satellite Evapotranspiration and Drought (GET-D) product system was developed at the National Oceanic and Atmospheric Administration (NOAA) in 2016 to generate daily ET and drought maps operationally. The primary inputs of the current GET-D system are the thermal infrared (TIR) observations from NOAA GOES satellite series. Because of the cloud contamination to the TIR observations, the spatial coverage of the daily GET-D ET product has been severely impacted. Based on the most recent advances, we have tested a machine learning algorithm to estimate all-weather land surface temperature (LST) from TIR and microwave (MW) combined satellite observations. With the regression tree machine learning approach, we can combine the high accuracy and high spatial resolution of GOES TIR data with the better spatial coverage of passive microwave observations and LST simulations from a land surface model (LSM). The regression tree model combines the three LST data sources for both clear and cloudy days, which enables the GET-D system to derive an all-weather ET product. This paper reports how the all-weather LST and ET are generated in the upgraded GET-D system and provides an evaluation of these LST and ET estimates with ground measurements. The results demonstrate that the regression tree machine learning method is feasible and effective for generating daily ET under all weather conditions with satisfactory accuracy from the big volume of satellite observations.
An improved fine-scale soil moisture (SM) dataset at 1 km grid spacing, covering much of the eastern continental US, was generated by assimilating 9 km Soil Moisture Active Passive (SMAP) SM data into the v4.0.1 Noah-MP land surface model. With 12 ensemble members, the assimilation was carried out using the ensemble Kalman filter algorithm within NASA's Land Information System. The SM analysis for 2016 was fully validated against in situ observations from four different networks and compared with four other existing datasets. Results indicate that this SM analysis surpasses other datasets in top-layer SM distribution, including a machine-learning-based product, despite all SM estimates being less heterogeneous than observed. The analysis of anomalous errors suggests that large similarity in intrinsic errors is likely due to overlapping data sources among the selected SM datasets. More detailed evaluations were performed over two geographic areas. The observations collected by the Atmospheric Radiation Measurement facility in Oklahoma suggest that soil temperature and surface heat fluxes are concurrently simulated with good accuracy. Investigation into the 2016 southeastern US drought response further indicates drier conditions and higher evapotranspiration estimates compared to GLEAMv4.1. Notably, large errors are associated with grids having clay soil textures, underscoring the need for refined model treatments for specific soil types to further improve SM estimates. The dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.14370563 (Tai et al., 2024).
Nanoparticle organic hybrid materials (NOHMs) are liquid-like materials composed of an inorganic core to which a polymeric canopy is ionically tethered. NOHMs have unique properties including negligible vapor pressure, high oxidative thermal stability, and the ability to bind to reactive species of interest due to the tunability of their polymeric canopy. This makes them promising multifunctional materials for a wide range of energy and environmental technologies, including electrolyte additives for electrochemical energy storage (e.g., flow batteries) and the electrochemical conversion of CO 2 to chemicals and fuels. Due to their unique transport behaviors in fluid systems, an understanding of the near-electrode surface behavior of NOHMs in electrolyte solutions and their effect on electrochemical reactions is still lacking. In this work, the complexation of zinc (Zn) by NOHMs with an ionically tethered polyetheramine canopy (HPE) (NOHM-I-HPE) was studied using attenuated total reflectance Fourier transform infrared and Carbon-13 nuclear magnetic resonance spectroscopy. Additionally, various electrochemical techniques were employed to discern the role of NOHM-I-HPE during zinc electrodeposition, and the results were compared to those of the electrochemical system containing untethered HPE polymers. Our findings confirmed that NOHM-I-HPE and HPE reversibly complex zinc in the aqueous electrolyte. NOHM-I-HPE and HPE were found to block some of the electrode active sites, reducing the overall current density during electrodeposition, while facilitating the formation of smooth zinc deposits, as revealed by surface imaging and diffraction techniques. Observed variations in the current density responses and the degree of passivation created by the NOHM-I-HPE and HPE adsorbed on the electrode surface revealed that their different packing behaviors at the electrode–electrolyte interface influence the zinc deposition mechanism. The presence of the nanoparticle and ordering offered by the NOHMs as well as the structured conformation of the polymeric canopy allowed the formation of void spaces and free volumes for enhanced transport behaviors. Furthermore, these findings provided insights into how structured electrolyte additives such as NOHMs can allow for advancements in electrolyte design for controlled deposition of metal species from energy-dense electrolytes or for other electrochemical reactions.
Typical commercial construction inherently contains large surface areas of relatively thin mass located in the floor slabs. This research asks how effective this mass could be for passive cooling, relative to other mass depths, if it were to be exposed and used as thermal mass. Although much of the rich literature on thermal mass has been conducted with far greater mass depths, a more limited amount of research suggests that because the surface heat transfer rate is limited, the focus should be on the surface area of exposed mass, not its depth. This presents an opportunity for more buildings to behave more thermally massively, if the mass inherent in typical floor slabs contains utility, particularly over diurnal cycles. In all climates analyzed, it was found that there is a pronounced shoulder where energy savings from passive cooling of increasing mass depths was steep until roughly 7.5–10 cm, and beyond this point the achieved energy savings diminished rapidly. When considering the embodied energy of concrete, the incremental benefit of added mass beyond a typical topping slab of 10 cm does not justify the incremental embodied energy cost from a total energy standpoint alone.
We investigated the chemistry and structure of the solid electrolyte interphase (SEI) grown over a silicon anode as a function of the lithium salt concentration. In these experiments, in situ neutron reflectivity measurements were performed to measure the thickness and composition of the SEI formed from 1.0 and 5.5 M lithium bis(trifluoromethane)sulfonimide (LiTFSI) in standard ethylene carbonate:dimethyl carbonate electrolytes. These measurements reveal the formation of a 350+ Å thick SEI layer that is predominantly organic (∼80%) and dimensionally stable when using a 1.0 M salt solution. In contrast, increasing the salt concentration to 5.5 M resulted in an SEI that exhibited thickness changes from 100 to 375 Å and became up to 30% inorganic. In conclusion, these compositional and structural changes point to the role of salt speciation on the resulting passivation of silicon electrodes and indicate the need to form more organic-like passivation layers to promote the calendar life of silicon anodes.
Cadmium chalcogenide quantum dots (QDs) passivated by thiol-based ligands exhibit several advantages in their applications in lighting, sensing, and imaging technologies. However, their emission is sensitive to thiol concentrations, pH conditions, and temperatures. Using calculations based on the density functional theory, we identify conditions for thiol/thiolate equilibrium at the CdS QD surface that either eliminate or introduce optically inactive hole trap states favoring or disfavoring the emission. Our calculations indicate much weaker interactions between the QD and protonated species (thiols), compared to their deprotonated counterparts (thiolates). Additionally, the surface of CdS QD facilitates the partial deprotonation of thiols, leading to the formation of an additional stable networking conformation where the proton is shared between the ligand and the QD surface. Thiolates strongly reduce the optical intensity of low-energy transitions in CdS QDs, contributing thiolate-localized hole trap states at the QD band gap. However, networking between the thiols and the surface, as well as the presence of native ligands such as primary amines, stabilize such trap states brightening the lowest optical transitions. This explains the increased emission of thiol-passivated QDs at lower concentrations in neutral or acidic solutions. Surface-mediated bias toward deprotonated species and their contribution to optically inactive states also rationalizes irreversible emission quenching and bleaching in the CdSe/CdS QDs exposed to high temperatures or intensive laser pulse.
The thermal energy exchange between a flowing fluid and its confining channel is a ubiquitous process in modern society. To enhance the fluid-to-wall or wall-to-fluid heat transfer, several techniques have been developed to maximize the contact area between the fluid and the inner wall and/or disrupt the flow to enhance circulation or induce turbulence. Deployment of channels having features capable of enhancing heat transfer enables the reduction of heat exchanger size while maintaining performance. Reduction in equipment size is critical due to the ability to minimize the required volume of costly working fluids and to mitigate potential safety concerns associated with total system fluid volume. Here, a comprehensive review of single-phase heat transfer enhancement techniques is presented. The article provides a thorough comparison by analyzing the heat transfer rate, pressure drop, and other operational aspects. Single-phase heat transfer enhancement methods are divided into active and passive techniques. Active methods such as electrohydrodynamic (EHD), magnetohydrodynamics (MHD), or mechanical motion require external power to create enhancement. Passive methods such as dimples, fins, or tape inserts do not require external input and rely only on surface modification. Although active methods are more expensive and difficult to implement compared to passive techniques, it enables active control of heat transfer augmentation. Finally, this review develops and summarizes key learning data for design optimization enabled by additive manufacturing and machine learning algorithms, helping to inform these next-generation heat exchanger design methodologies for a plethora of modern applications such as electrification of vehicles, computing, and classical industries.
Understanding the fundamental properties of buried interfaces in perovskite photovoltaics is of paramount importance to the enhancement of device efficiency and stability. Nevertheless, accessing buried interfaces poses a sizeable challenge because of their non-exposed feature. In this paper, the mystery of the buried interface in full device stacks is deciphered by combining advanced in situ spectroscopy techniques with a facile lift-off strategy. By establishing the microstructure-property relations, the basic losses at the contact interfaces are systematically presented, and it is found that the buried interface losses induced by both the sub-microscale extended imperfections and lead-halide inhomogeneities are major roadblocks toward improvement of device performance. The losses can be considerably mitigated by the use of a passivation-molecule-assisted microstructural reconstruction, which unlocks the full potential for improving device performance. The findings open a new avenue to understanding performance losses and thus the design of new passivation strategies to remove imperfections at the top surfaces and buried interfaces of perovskite photovoltaics, resulting in substantial enhancement in device performance.
The discovery of ferromagnetism in atomically thin layers at room temperature widens the prospects of 2D materials for device applications. Recently, two independent experiments demonstrated magnetic ordering in two dissimilar 2D systems, CrI 3 and Cr 2 Ge 2 Te 6 , at low temperatures and in VSe 2 at room temperature, but observation of intrinsic room-temperature magnetism in 2D materials is still a challenge. Here a transition at room temperature that increases the magnetization in magnetite while thinning down the bulk material to a few atom-thick sheets is reported. DC magnetization measurements prove ferrimagnetic ordering with increased magnetization and density functional theory calculations ascribe their origin to the low dimensionality of the magnetite layers. Additionally, surface energy calculations for different cleavage planes in passivated magnetite crystal agree with the experimental observations of obtaining 2D sheets from non-van der Waals crystals.
Semiconductor saturable absorber mirrors (SESAMs) enable passive modelocking of several ultrafast solid-state lasers. Conventionally, SESAMs in the 1-µm wavelength range have employed InGaAs quantum wells (QWs) as absorbers. Here we demonstrate a SESAM based on InAs/GaAs submonolayer quantum dots (SML QDs) capable of generating femtosecond pulses by passively modelocking a vertical-external-cavity surface-emitting laser (VECSEL). Structural measurements are carried out to verify the quality and composition of the QDs. Modelocking experiments with a VECSEL and the QD SESAM in a ring cavity configuration yield pulses as short as 185 fs at 1025 nm. Compared to a traditional QW absorber, SML QD SESAMs exhibit ~ 25% faster recovery times. This also translates to slower power degradation rates or higher damage thresholds in SML QD SESAMs.
The reliability and durability of lithium metal (Li 0 )–sulfur batteries are largely limited by the undesired Li 0 plating-stripping irreversibility and the detrimental polysulfide dissolution, yet approaches that can simultaneously address the above anodic and cathodic problems are scarce. In this study, we report the stable operation of a Li 0 -SPAN (sulfurized polyacrylonitrile) battery via an anode–cathode dual-passivation approach. By combination of a fluorinated localized high concentration electrolyte (LHCE) and a Li 3 N-forming additive (TMS-N 3 ), robust and highly conductive electrode passivation layers are formed in situ on the surface of both the Li 0 anode and the SPAN cathode. The resulting highly reversible, dendrite-free, and high-density Li 0 plating morphology enables a high Coulombic efficiency of 99.4%. Advanced tender energy X-ray spectroscopy also reveals the eliminated Li 2 S formation and minimized polysulfide dissolution in SPAN cathodes, leading to a high capacity of 580 mAh/g SPAN and stable cycling with negligible capacity decay (0.7%) for 800 cycles. This electrode–electrolyte interphase engineering strategy has tackled the major limitations of Li–S batteries in both ether- and carbonate-based electrolyte systems and under a wide temperature range from –10 to +50 °C, thus providing insightful guidelines for the rational design of highly durable and high-energy-density Li 0 -S batteries.
Field studies that simulate the effects of climate change are important for a predictive understanding of ecosystem responses to a changing environment. Among many concerns, regional warming can result in advanced timing of spring snowmelt in snowpack dependent ecosystems, which could lead to longer snow-free periods and drier summer soils. Past studies investigating these impacts of climate change have manipulated snowmelt with a variety of techniques that include manual snowpack alteration with a shovel, infrared radiation, black sand and fabric covers. Within these studies however, sufficient documentation of methods is limited, which can make experimental reproduction difficult. Here, we outline a detailed plot-scale protocol that utilizes a permeable black geotextile fabric deployed on top of an isothermal spring snowpack to induce advanced snowmelt. The method offers a reliable and cost-effective approach to induce snowmelt by passively increasing solar radiation absorption at the snow surface. In addition, control configurations with no snowpack manipulation are paired adjacent to the induced snowmelt plot for experimental comparison. Past and ongoing deployments in Colorado subalpine ecosystems indicate that this approach can accelerate snowmelt by 14-23 days, effectively mimicking snowmelt timing at lower elevations. This protocol can be applied to a variety of studies to understand the hydrological, ecological, and geochemical impacts of regional warming in snowpack dependent ecosystems.
The combination of elevated temperature and tribo-corrosion leads to the accelerated degradation of structural components used in many extreme environments. Recently developed high-entropy alloys (HEAs) with multiple principal elements have the potential for superior degradation resistance compared with presently used structural alloys. Here, we demonstrate the microstructural stability, pitting resistance, and superior tribo-corrosion degradation resistance of the AlCoCrFeNi 2.1 eutectic HEA in comparison with duplex stainless steel 2205 in deionized water (controlled low-ionic-strength electrolyte) at 25 °C, 50 °C and 100 °C. The AlCoCrFeNi 2.1 HEA showed excellent microstructural stability and tribo-corrosion resistance at all three temperatures, an order-of-magnitude lower wear rate, and a lower coefficient of friction compared with duplex 2205 steel. The lowest wear volume loss and wear rate for both AlCoCrFeNi 2.1 and duplex steel were recorded at 50 °C, which was attributed to temperature-assisted passivation and formation of a comparatively stable tribological surface condition. These results suggest superior performance of eutectic HEAs in tribo-corrosion applications compared with currently used dual-phase steels and motivate future evaluation in ion-containing industrial water chemistries.
Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the above-mentioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.
Harnessing aluminum oxidation energy requires navigating the particle's passivation shell composed of alumina. The shell is a barrier to aluminum oxidation but can also exothermically react with halogenated species and therefore contribute to the overall energy generated during aluminum particle combustion. Fluorination reactions with alumina have been studied because fluorine is abundant in binder formulations that commonly surround aluminum particles in an energetic mixture. However, iodine has emerged as an alternative halogenated-based binder or oxidizer because iodine gas provides ancillary benefits such as chemical neutralization of biological agents or sterilization of contaminated environments. Furthermore, this study used density functional theory (DFT) calculations to evaluate potential reaction pathways for aluminum–iodine combustion. Relative to fluorinated fragments such as HF and F – , the adsorption energies associated with HI and I– are nearly triple the exchange reaction energy available from fluorination reactions with alumina (–189 and –278 kJ mol –1 for HI and I – , respectively). However, exchange reactions between iodinated species and the alumina surface are energetically unfavorable. These results explain that through adsorption, alumina surface exothermic reactions with iodine are more energetic than with fluorine fragments. Experiments performed with differential scanning calorimetry (DSC) confirm the higher magnitude of energy generated for iodination compared with fluorination reactions with alumina. Additionally, strong adsorption energies can promote synthesis of new shell chemistries. Adsorption in solution will promote alumina dissolution and iodine precipitation reactions to produce hydroxyl complexes and iodinated species synthesized on the surface of the particle, thereby replacing alumina with alternative passivation shell chemistry.
CdZnTeSe (CZTS) is a next gen replacement room temperature radiation detector that solves common issues with modern CZT detectors. • Surface states can trap radiation induced carriers and can act as leakage current pathways requiring detectors to passivated for optimal performance. • In this work, we seek to identify the best passivation technique for CZTS detectors.