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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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The use of remote sensing techniques for collecting bacteriological, physical, and chemical water quality data, locating point and nonpoint sources of pollution, and developing hydrological data was found to be valuable to the Maryland program if it could be produced effectively and rapidly with a minimum amount of ground corroboration.
A wide column test of a composite isogrid panel subjected to quasi-static, axial compression is modeled with a hybrid-static dynamic computational method. The data from the test panel exhibited discontinuous responses in the compressive load for slowly increased end-shortening. The computational model was developed to corroborate these discontinuities with the phenomenon of mode jumping. Mode jumping refers to the transient response of the panel from an unstable bifurcation point on a postbuckled equilibrium path to a second stable equilibrium state on a new equilibrium path. On the new equilibrium path, both the analysis and test show that the panel can resist increased endshortening beyond that of the unstable critical point. Fair agreement is achieved between the analysis and test.
Absorption bands of both aliphatic and aromatic organic molecules are found in the reflectance spectra of Saturn satellites Iapetus, Phoebe, and Hyperion obtained with the Cassini Visible-Infrared Mapping Spectrometer (VIMS). The VIMS data do not fully resolve the individual bands of C-H functional groups specific to particular molecules, but instead show absorption envelopes representing blended clusters of the bands of aromatic (approximately 3.28 microns) and aliphatic (approximately 3.4 microns) hydrocarbons known in spectra of interstellar dust. In Cruikshank et al. (2014), we matched components of the unresolved hydrocarbon band envelopes with clusters of bands of a range of functional groups in specific types of organic compounds (e.g., normal and N-substituted polycyclic aromatic hydrocarbons, olefins, cycloalkanes, and molecules with lone-pair interactions of N and O with CH3+). In the work reported here, we revisit the spectra of Iapetus and Phoebe using VIMS data processed with improved radiometric and wavelength calibration (denoted RC19). The band envelopes of both aromatic and aliphatic hydrocarbons are now more clearly defined, corroborating the provisional assignment of specific classes of molecules in Cruikshank et al. 2014, but permitting a more reliable quantitative assessment of the relative contributions of those classes, and a revision to the earlier estimate of the ratio of the abundances of aromatic to aliphatic molecules.
Energy savings performance contracts (ESPCs) offer an opportunity to tremendously scale decarbonization projects, given their paid-from-savings premise. However, prospective customers still question whether ESPC is worth the effort and expense. This study evaluates the savings realization rates of ESPCs compared to direct-funded projects using ENERGY STAR Portfolio Manager (ESPM) benchmarking data. It compares normalized EUIs from ESPM before and after energy conservation projects implemented via ESPC or direct funding in roughly 450 federal buildings. This documented change, ideally a savings, can then be compared to the estimated savings from the energy conservation initiative in order to generate a rough realization rate. Preliminary results indicate a notably greater savings realization rate for the ESPC buildings (median = 105% of estimated savings) than those that underwent direct-funded projects (median = 46%). Because of a shortage of good quality data and the wide range in results, the difference is only significant at the p < 0.20 level. However, the higher savings realization of ESPCs corroborates the authors’ 2014 findings using a different comparison method. With continued soft government funding and regulatory impediments for climate change mitigation in the U.S., financed, paid-from-savings project models (e.g., ESPC, PACE, EaaS and others) certainly merit more attention. This study’s results are particularly compelling (and encouraging) given the country’s likely reliance on these vehicles to address existing building retrofits.
Thermodynamic properties of Ca–Pb alloys are investigated by electromotive force (emf) measurements to determine equilibrium cell potentials and phase properties for their application in energy storage systems such as liquid metal batteries. Using the electrochemical cell Ca(s) | CaF 2 (s) | Ca(in Pb) at 700–1060 K, cell emf is measured for thirteen Ca–Pb alloys at mole fractions, x Ca = 0.06–0.80. At 873 K, the equilibrium potentials of liquid Ca–Pb alloys are 0.57–0.62 V versus Ca and the activity values are as low as a Ca = 6.2 × 10 -8 at x Ca = 0.06. In addition, the emf values as a function of temperature provide partial molar quantities (entropy and enthalpy) as well as phase transitions which are corroborated by determining transition temperatures and phase constituents using differential scanning calorimetry (DSC) and powder X-ray diffraction (XRD). This study establishes the fundamental data necessary for the design of Pb-containing liquid metal electrodes through the integration of electrochemical, thermal, and structural properties of Ca–Pb electrodes.
Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.
Superconducting circuit testing and materials loss characterization requires robust and reliable methods for the extraction of internal and coupling quality factors of microwave resonators. Additionally, a common method, imposed by limitations on the device design or experimental configuration, is the single-port reflection geometry, i.e. reflection-mode. However, impedance mismatches in cryogenic systems must be accounted for through calibration of the measurement chain while it is at low temperatures. In this paper, we demonstrate a data-based, single-port calibration using commercial microwave standards and a vector network analyzer with samples at millikelvin temperature in a dilution refrigerator, making this method useful for measurements of quantum phenomena. Finally, we cross reference our data-based, single-port calibration and reflection measurement with over-coupled 2D- and 3D-resonators against well established two-port techniques corroborating the validity of our method.
The concept of fluidic viscosity is ubiquitous in condensed-matter systems hosting a continuum where macroscopic properties can emerge. While an important property of liquids and some solids, only recently was the viscosity of an electron shown to play a role in electronic transport experiments. In this Letter, we present nonlocal electronic transport measurements in concentric annular rings formed in high-mobility two-dimensional electron gases, and the resulting data show that viscous hydrodynamic flow can occur far away from the source-drain current region. Our conclusion of viscous electronic transport is further corroborated by simulations of the Navier-Stokes equations that are found to be in agreement with our measurements below T = 1 K . Finally, this work emphasizes the key role played by viscosity via electron-electron ( e − e ) interaction even when the electronic transport is restricted radially, and for which it should have played no major role. Published by the American Physical Society 2025
Classical machine learning (ML) provides a potentially powerful approach to solving challenging quantum many-body problems in physics and chemistry. However, the advantages of ML over traditional methods have not been firmly established. In this work, we prove that classical ML algorithms can efficiently predict ground-state properties of gapped Hamiltonians after learning from other Hamiltonians in the same quantum phase of matter. By contrast, under a widely accepted conjecture, classical algorithms that do not learn from data cannot achieve the same guarantee. We also prove that classical ML algorithms can efficiently classify a wide range of quantum phases. Extensive numerical experiments corroborate our theoretical results in a variety of scenarios, including Rydberg atom systems, two-dimensional random Heisenberg models, symmetry-protected topological phases, and topologically ordered phases.
The variations in the near-infrared brightness of Neptune observed during July and August 1980 show a well-defined, large-amplitude variation in Neptune's J-K color, with a period of 17.73 + or - 0.1 hour. These results are interpreted as diurnal variations resulting from the 17.73-hour rotation period of the Neptune upper atmosphere in the presence of inhomogeneous weather, and are found to qualitatively corroborate those of Cruikshank (1978). It is also noted that Smith and Slavsky (1980) report a 17.7-hour component as a secondary periodicity in their data. Variations were observed in the 5-0-micron spectral region which are in phase with the variations seen at shorter wavelengths.
Understanding the temperature dependence of functional properties of high-T gas sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we assess the temperature dependence of band gap renormalization in metal oxides and perovskites by employing Allen-Heine-Cardona theory with first-principles simulations and corroborate with experimental observation. The calculated temperature-dependent band gap changes of these materials studied are in good agreement with in-house experimental data, proving that the theory can adequately predict renormalization on the band gap in the system of interest. The predicted and measured band gap variations are characterized using an analytical model, which can provide useful insights on the simulated zero-temperature band gaps. Based on the available data, a set of 53 metal oxides and perovskites were identified as potential high-T gas sensors. A machine learning model has been developed to predict the band-gap change by capturing the overall trend of the empirical parameters with respect to a reduced feature obtained by transforming the set of available physical features.
Over the last decade, significant progress has been made in managing radioisotopes generated in the PWR primary systems. These include limiting the use of cobalt containing materials, along with improved fuel performance and zinc injection to passivate the corrosion layers to limit the accumulation of Co-58 and Co-60 on primary coolant surfaces. Attention here is directed to the spent fuel pool where accumulation of spent fuel and activated material represents a growing source of mobile radioactivity supplemented with periodic exchanges of water from the reactor cooling system. Characterization of this source is increasingly important to effective management of disposal options. This paper examines the radioactive resin source term as determined from routine sampling of the coolant and fuel pool liquids. Targeted resin stream sampling and radiochemical analyses conducted at Diablo Canyon serve to inform and provide context for this examination. This examination is supplemented with computer modelling using the DW James Consulting computer program, 3R-SCAN. At most operating plants daily reactor coolant samples are counted using gamma spectroscopy and recorded. These samples serve to track fuel performance and maintain water chemistry. A secondary use for this data is to maintain a day to day tracking of releases of radioisotopes important to waste disposal. Given the coolant concentrations, plant operating history, and corroborative mathematical models and sampling, accumulation of these radioisotopes in coolant cleanup system ion-exchangers can be predicted. Fuel pool sampling is less frequent, but at the same time, things change more slowly there. The fuel pool contains about ten times the volume of the reactor coolant but its cleanup system process rate is comparable to reactor coolant letdown, i.e. 5.047 - 8.833 liters per second [lps] (80-140 gallons per minute [gpm]). A spent fuel pool clean-up demineralizer flow rate is typically about 5.047 lps (80 gpm). Concentrations of longer lived radioisotopes in the spent fuel pool can be comparable to those in reactor coolant. Releases of corrosion products and fission products from the stored fuel occur at a low rate but given the overall inventory can be significant. Recognized scaling factor ratios, particularly those to Co-60, are skewed by the aging of the material in the pool. An additional consideration stems from refueling operations themselves. Prior to refueling, it is common practice to conduct a forced oxidation of the corrosion films within the reactor. This spikes the activity within the reactor coolant. Most of this activity is removed by the reactor coolant purification system prior to removing the reactor head. This paper examines the accumulation of activity in the fuel pool purification ion exchange resins and how it impacts the overall classification of those ion exchange resins. The following discussion focuses on the transport of nickel and cobalt isotopes particularly as it relates to determination of Ni-63 which has become increasingly prominent in disposal classification. (authors)
We present an updated study of the Collins azimuthal asymmetries for pion-in-jet production in polarized pp collisions. To this aim, we employ a recent extraction of the transversity and Collins fragmentation functions from semi-inclusive deep inelastic scattering and e + e - annihilation into hadron pairs processes, obtained within a simplified transverse momentum dependent (TMD) approach at leading order in the strong coupling constant α s . In the present case we adopt a collinear configuration for the initial state, keeping transverse momentum effects only in the fragmentation mechanism. Our theoretical estimates, when compared against 200 GeV and 510 GeV data from the STAR Collaboration, show a generally good agreement for the distributions in the transverse momentum of the jet, the pion longitudinal momentum fraction and its transverse momentum with respect to the jet direction. While not being a proof, due the assumptions and limitations behind the entire approach, these findings corroborate the hypothesis of TMD factorization for such processes as well as of the universality of the Collins function and, once again, of a reduced impact of the proper TMD evolution on azimuthal asymmetries. We will also present predictions based on an extraction of the Collins and transversity distributions where information from data on single spin asymmetry for inclusive pion production in p ↑ p collisions is included through a Bayesian reweighting procedure.
Here, we investigate the local nanoscale changes of the magnetic anisotropy of a Ni film subject to an inverse magnetostrictive effect by proximity to a V 2 O 3 layer. Using temperature-dependent photoemission electron microscopy (PEEM) combined with X-ray magnetic circular dichroism (XMCD), direct images of the Ni spin alignment across the first-order structural phase transition (SPT) of V 2 O 3 were obtained. We find an abrupt temperature-driven reorientation of the Ni magnetic domains across the SPT, which is associated with a large increase of the coercive field. Moreover, angular dependent ferromagnetic resonance (FMR) shows a remarkable change in the magnetic anisotropy of the Ni film across the SPT of V 2 O 3 . Micromagnetic simulations based on these results are in quantitative agreement with the PEEM data. Direct measurements of the lateral correlation length of the Ni domains from XMCD images show an increase of almost one order of magnitude at the SPT compared to room temperature, as well as a broad spatial distribution of the local transition temperatures, thus corroborating the phase coexistence of Ni anisotropies caused by the V 2 O 3 SPT. We show that the rearrangement of the Ni domains is due to strain induced by the oxide layers’ structural domains across the SPT. Our results illustrate the use of alternative hybrid systems to manipulate magnetic domains at the nanoscale, which allows for engineering of coercive fields for novel data storage architectures.
Mitigation of the global climate change via sequestration of anthropogenic carbon dioxide (CO2) in geologic formations requires assessment of the reservoir storage capacity and cap rock seal integrity. The typical cap rock is shale or mudstone rich in clay minerals that may significantly affect the effectiveness of the CO2 trapping. Specific objectives of this study were to conduct experimental investigation into the processes associated with CO2 and H2O trapped in swelling clay, namely, Wyoming and Texas montmorillonite powder. Combined (same-sample) multi-technique data ? manometric sorption isotherm hysteresis, diffuse reflectance infrared spectroscopy ?trapped CO2? fingerprints, irreversible X-ray diffraction patterns for the clay interlayer in intermediate hydration state, and HF acid digestion resulting in formation of non-extractable F:CO2 adducts ? corroborate a hypothesis that carbon dioxide molecules can be irreversibly trapped via anomalous extreme confinement in the galleries associated with montmorillonite interlayer, which may result in formation of carbonates in the longer term. Validation on Arizona montmorillonite lumps substantiated the evidence that such processes may occur in natural clay deposits but possibly on a different scale and at a different rate.
Mediterranean-climate regions like California's San Joaquin Valley are subject to severe wintertime particulate pollution affecting public health. We present maps of episodes and particulate diagnostics to aid diagnosis and amelioration. For abatement at sources, we require an understanding of sources and transport. Remote sensing should be of aid, but radiance-to-particle relationships are far different from methods which have been of use in the Eastern USA, Northern and Central Europe. Here are the problems: (a) Thin if very polluted mixed layers (MLs) yield optical depths, AOD, near the detection level, (b) bright and quite variegated surfaces (c) Unusual particle composition (e.g., predominance of NH4NO3 and fireplace buning aerosol), which complicate the relationship of AOD to PM2.5. Specialized analysis of MODIS-Aqua data to obtain AOD using the multi-angle (MAIAC) technique employed by Lyapustin and Wang. Meteorological analyses like NOAA's Rapid Analysis Product (RAP, or newer products like HRRR), which are formulated to remain close to observations (e.g. of water), provide useful ML information corroborated by DISCOVER-AQ in-situ and lidar observations. The many PM2.5 measurements allow a calibration of these products and thus maps of aerosol on many successive aerosol buildups. These calibrations also allow insight into compositional information relevant to MODIS retrievals, the product of aerosol density and specific scattering. We have found that the rich in-situ, lidar, and sun-photometer data sets of NASA'S DISCOVER-AQ data set (2013) of great aid. We will highlight the most interesting of many intercomparisons possible with this rich data set. We conclude with a description of new work to extend these insights to similar regions, e.g. the Imperial Valley of California, the Po Valley and maritime Southern Europe, and the litoral regions of Israel.
The most important factor undercutting optimal waste management in the nuclear industry is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For almost 35 years since the publishing of 10CFR61, waste characterization has relied on building its basis from samples collected from the final waste product as it is drawn from service or as it is packaged for disposal. This practice of sampling the product after it was collected continues to be followed to this day; 35 years after the publication of 10CFR61. This process, as it is followed, relies on minimum information and plant knowledge to formulate the characterization. While 10CFR61 and additional guidance documents promote the approach of using anticipated and statistically based scaling factors in addition to using data collected over time and a finite grouping of waste streams encompassing plant wastes, this guidance is often ignored in favor of using the earlier fallback options in the case of a limited sample base. The fallback allows the use of a final sample drawn from the waste when other data was not sufficiently available to be aligned to develop meaningful statistics. The determination of representativeness is obviated by the single sample resulting in a new waste stream being declared with every package. The sample used without statistical corroboration often is not representative. It would be unexpected if that sample were actually representative of anything more than itself. This paper discusses viable options for developing the basis for characterization through direct process monitoring to follow the accumulation of activity at the point of generation relying on hundreds of measurements being collected on a daily and weekly basis that can provide a much more reliable result along with significant cost savings. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality and track fuel performance. The discussion in this paper will focus on resin bed tracking and how process knowledge drawn from routinely collected chemistry data can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in the paper include application and expansion of the fission product release computer program 3R-STAT, the importance of the spent fuel pool in radioactivity generation and its influence on the overall source term, and results from sample measurements collected over several years to corroborate using direct process measurements for the primary characterization basis. (authors)