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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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101 records · Page 6

The cosmic DANCe of Perseus

Context. Star-forming regions are excellent benchmarks for testing and validating theories of star formation and stellar evolution. The Perseus star-forming region, being one of the youngest (< 10 Myr), closest (280-320 pc), and most studied in the literature, is a fundamental benchmark. Aims. We aim to study the membership, phase-space structure, mass, and energy (kinetic plus potential) distribution of the Perseus star-forming region using public catalogues (Gaia, APOGEE, 2MASS, and Pan-STARRS). Methods. We used Bayesian methodologies that account for extinction to identify the Perseus physical groups in the phase-space, retrieve their candidate members, derive their properties (age, mass, 3D positions, 3D velocities, and energy), and attempt to reconstruct their origin. Results. We identify 1052 candidate members in seven physical groups (one of them new) with ages between 3 and 10 Myr, dynamical super-virial states, and large fractions of energetically unbounded stars. Their mass distributions are broadly compatible with that of Chabrier for masses ≳0.1 M ⊙ and do not show hints of over-abundance of low-mass stars in NGC 1333 with respect to IC 348. These groups’ ages, spatial structure, and kinematics are compatible with at least three generations of stars. Future work is still needed to clarify if the formation of the youngest was triggered by the oldest. Conclusions. The exquisite Gaia data complemented with public archives and mined with comprehensive Bayesian methodologies allow us to identify 31% more members than previous studies, discover a new physical group (Gorgophone: 7 Myr, 191 members, and 145 M ⊙ ), and confirm that the spatial, kinematic, and energy distributions of these groups support the hierarchical star formation scenario.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Trends and 2025 Insights on the Rise of Electric Vehicles in the USA

Plug-in electric vehicles (EVs) are reshaping the transportation energy landscape, providing a practical alternative to petroleum fuels for a growing number of applications. EV sales grew 55x in the past decade (2014-2024) and 6x since 2020, driven by technological progress enabled by policies to reduce transportation emissions as well as industrial plans motivated by strategic value of EVs for global competitiveness, jobs and geopolitics. In 2024, 22% of passenger cars sold globally were EVs and opportunities for EVs beyond on-road applications are growing, including solutions to electrify off-road vehicles, maritime and aviation. This Review updates and expands our 2020 assessment of the scientific literature and describes the current status and future projections of EV markets, charging infrastructures, vehicle-grid integration and supply chains in the USA. EV is the lowest-emission motorized on-road transportation option, with life-cycle emissions decreasing as electricity emissions continue to decrease. Charging infrastructure grew in line with EV adoption but providing ubiquitous reliable and convenient charging remains a challenge. EVs are reducing electricity costs in several US markets and coordinated EV charging can improve grid resilience and reduce electricity costs for all consumers. The current trajectory of technology improvement and industrial investments points to continued acceleration of EVs.

33 ADVANCED PROPULSION SYSTEMS↗

Mechanistic and Kinetic Analysis of Complete Methane Oxidation on a Practical PtPd/Al 2 O 3 Catalyst

A PtPd/Al 2 O 3 catalyst developed for the complete oxidation of methane from the ventilation air of underground coal mines is compared against a model PdO/Al 2 O 3 catalyst. Although the PtPd/Al 2 O 3 catalyst is substantially more active and stable than the model catalyst, the nature of active sites between the two catalysts is deemed to be fundamentally the same based on their response to different feed gas compositions and the evolution of surface CO adsorption complexes during time-resolved CO adsorption DRIFTS experiment. For both catalysts, coordinatively unsaturated Pd sites are considered the active centers for methane activation and the subsequent oxidation reaction. H 2 O competes with CH 4 for the same active sites, resulting in severe inhibition. Additionally, the CH 4 oxidation reaction also causes self-inhibition. Taking both inhibition effects into consideration, a relatively simple kinetic model is developed. The model provides a good fit of the 72 sets of kinetic data collected on the PtPd/Al 2 O 3 catalyst under practically relevant reaction conditions with CH 4 concentration in the range of 0.05–0.4%, H 2 O concentration of 1.0–5.0%, and reaction temperatures of 450–700 °C. Kinetic parameters based on the model suggest that the CH 4 activation energy on the PtPd/Al 2 O 3 catalyst is 96.7 kJ/mol, and the H 2 O adsorption energy is –31.0 kJ/mol. Both values are consistent with the parameters reported in the literature. The model can be used to develop catalyst sizing guidelines and be incorporated into the control algorithm of the catalytic system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrothermal solubility of Dy hydroxide as a function of pH and stability of Dy hydroxyl aqueous complexes from 25 to 250 °C

The rare earth elements (REE) have important applications in green energy technologies. The formation of mineral deposits in geologic systems commonly involves hydrothermal fluids which can mobilize the REE. However, the REE speciation is not well known as a function of pH. The thermodynamic properties of REE hydroxyl complexes used in geochemical models are based on the Helgeson-Kirkham-Flowers (HKF) equation of state parameters which were derived by extrapolation of low temperature experimental and estimated data. In this study, Dy hydroxide solubility experiments are combined with available literature data to improve these models from 25 to 250 °C and optimize the thermodynamic properties of Dy 3+ and Dy hydroxyl complexes using GEMSFITS. Batch-type solubility experiments were conducted from 150 to 250 °C and at saturated water vapor pressure in perchloric acid solutions with initial pH values of 2 to 5 in 0.5 pH unit increments. The measured solubility of Dy hydroxide is retrograde with temperature and decreases with pH. The logarithm of total dissolved Dy molality ranges from –2.3 to –5.3 at 150 °C (pH 4.7–5.5), from –2.4 to –5.6 at 200 °C (pH 3.9–5.1), and from –3.7 to –6.9 at 250 °C (pH of 3.4 and 5.0). The optimized standard partial molal Gibbs energies of formation (Δ f G° T ) derived for Dy 3+ and DyOH 2+ display a close to linear relationship with temperature, fitting with previous optimizations based on DyPO 4 solubility data in the literature. A comparison of the optimized ΔfG°T values for aqueous Dy species with predictions from available HKF parameters indicates significant differences ranging from +11 to –26 kJ/mol between 25 and 250 °C. The experimental fits are used to derive the Dy hydroxide solubility products (K s0 ) and formation constants for the hydrolysis of Dy (β n with n = 1 to 3; Dy 3+ + nOH – = DyOH n 3-n ) as a function of temperature. The optimization method presented yields accurate thermodynamic properties for the Dy 3+ aqua ions and the DyOH 2+ species at the acidic to mildly acidic pH studied whereas more experimental work is needed at near-neutral and alkaline conditions to better constrain the other hydroxyl complexes. Furthermore, the optimized thermodynamic data have a significant impact on geochemical modeling of the mobility and solubility of REE minerals in acidic hydrothermal fluids.

58 GEOSCIENCES↗

Critical minerals lists for low-carbon transitions: Reviewing their structure, objectives, and limitations

Critical minerals lists have flourished in the past decade, in particular linked to the importance of critical minerals for low-carbon transitions. We identified 27 critical minerals or materials lists across 15 countries and the European Union (EU). These lists are designed to attract public and private attention and investments to secure both domestic and foreign supplies. This review article fills a gap in the existing literature by analyzing the ways in which these lists are defined and utilized by countries engaged in a mineral rush. We focus our attention on three categories of minerals – battery minerals, platinum-group metals (PGMs), and rare earth elements (REEs) that are particularly important to energy transitions. We situate this research in the broader legal and administrative developments that have driven critical minerals policies in the past decade. We provide an in-depth analysis of the commonalities and variations in the raw materials included in these lists, and identify six core limitations of critical minerals lists: (1) unclear links between criticality assessments and mineral prioritization (2) failure to account for the full mineral value-chain; (3) limited strategic alignment between allied nations; (4) limited flexibility in dynamic environments (5) limited consideration for recycling and by-product sourcing; and (6) reliance on incomplete reserve and resource data.

Battery minerals↗

Sedimentary Geothermal Resources in Nevada, Utah, Colorado, and Texas

The objectives of this project were to (1) perform a literature review of sedimentary geothermal resources, (2) identify data sources and develop data-collection methodologies that characterize selected resources, (3) screen sedimentary basins and formations for sedimentary geothermal potential, and (4) evaluate the technical feasibility of one or more selected locations. Numerous publications have characterized geothermal resources within sedimentary basins. A literature search reviewed publications describing resources located in Colorado, Louisiana, Nevada, Texas, Utah, and Wyoming. The most attractive resources have high temperature gradients, low drilling costs, and reservoir permeabilities greater than 10 millidarcies (mD). Prospects in Colorado, Nevada, Texas, and Utah exhibit attractive characteristics and were chosen for further analysis. Sedimentary resources in Nevada and Utah are most attractive, followed by tested resources in Texas and untested resources in Colorado. The identified resources in Wyoming and Louisiana had lower geothermal gradients and were not evaluated. Reservoir modeling and techno-economic analysis were performed at Marys River Basin–North in Nevada. Geothermal energy production at this location is expected to have a levelized cost of energy (LCOE) ranging between 10 and 20 cents/kWh. Additional work may result in lower LCOE estimates at this location and at other attractive prospects in these three regions. The Great Basin carbonate and alluvial aquifer system of eastern Nevada and western Utah includes a lower carbonate aquifer unit, which has the potential for hosting both conduction- and convection-dominated geothermal systems. Mapping has identified lateral thickness variability expressed as a roughly 120–150-km-wide central corridor, which hosts the thickest and most continuous formations and extends from near Las Vegas north to the Idaho border. Purchase and analysis of privately held legacy seismic data could potentially compensate for the lack of sufficient data documenting measured depth to the lower carbonate aquifer unit. Multiple orogenies, extension episodes, and intrusive events have deformed and displaced the target formations of the lower carbonate aquifer unit. This structural complexity and potential for dipping reservoirs emphasizes the need for detailed geological, geophysical, and reservoir modeling. Heat flow within three Colorado sedimentary basins reviewed as part of this study was calculated in targeted studies by the Colorado Geologic Survey and Colorado School of Mines. These calculations are based on bottom-hole temperature data sets with significant limitations and some variability but produce values consistently higher than the global continental average of 65 mW/m2 for all three basins. Heat flow in the Raton Basin is the highest; however, permeability measurements from specific sedimentary formations with high heat flow have not been obtained. Promising formations for sedimentary geothermal systems were found in all three regions studied—Nevada-Utah, Colorado, and Texas. The next steps for developing sedimentary geothermal resources vary due to differences in available data and resource uncertainties. Additional scopes of work are recommended for identified basins in these three regions.

15 GEOTHERMAL ENERGY↗

Mineral Scale Formation during Crossflow Reverse Osmosis at Constant Flux and Constant Transmembrane Pressure Conditions

Mineral scale formation on membrane surfaces is a significant challenge in reverse osmosis water purification. Laboratory fouling experiments are typically run such that the transmembrane pressure (TMP) is fixed, and the permeate flux decreases over time as scales accumulate on the membrane surface. However, this change in flux means that the hydrodynamic conditions at the membrane surface are continuously changing, which could affect crystallization and foulant deposition processes. Operating under constant permeate flux conditions, in contrast, is advantageous because it keeps the hydrodynamic conditions relatively consistent, making it possible to compare how membrane properties (e.g., surface chemistry) affect fouling propensity. Industrial reverse osmosis operations are not run strictly in either constant TMP or constant flux mode; while they may start at a constant TMP, feed pressure may be periodically adjusted to maintain permeate water production within a specified range. Here, the scarcity of constant permeate flux reverse osmosis scaling experiments reported in the literature frustrates efforts to compare membrane fouling processes under constant TMP and constant flux conditions. For the first time, the evolution of the fouling layer resistance was compared as a function of cumulative permeate volume per membrane area during constant TMP and constant flux reverse osmosis filtrations. Scaling experiments were conducted by challenging commercial reverse osmosis membranes with a model feed solution nearly saturated with calcium sulfate dihydrate (gypsum). At low fluxes, the increase in fouling layer resistance was quantitatively similar for the two operational modes. In contrast, at high fluxes, the fouling layer resistance increased more rapidly in constant flux filtration than in constant TMP filtration. The mechanism of scale formation in constant TMP and constant flux operation was self-limiting and self-reinforcing, respectively.

36 MATERIALS SCIENCE↗

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗

Models and Processes to Extract Drug-like Molecules From Natural Language Text

Researchers worldwide are seeking to repurpose existing drugs or discover new drugs to counter the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A promising source of candidates for such studies is molecules that have been reported in the scientific literature to be drug-like in the context of viral research. However, this literature is too large for human review and features unusual vocabularies for which existing named entity recognition (NER) models are ineffective. We report here on a project that leverages both human and artificial intelligence to detect references to such molecules in free text. We present 1) a iterative model-in-the-loop method that makes judicious use of scarce human expertise in generating training data for a NER model, and 2) the application and evaluation of this method to the problem of identifying drug-like molecules in the COVID-19 Open Research Dataset Challenge (CORD-19) corpus of 198,875 papers. We show that by repeatedly presenting human labelers only with samples for which an evolving NER model is uncertain, our human-machine hybrid pipeline requires only modest amounts of non-expert human labeling time (tens of hours to label 1778 samples) to generate an NER model with an F-1 score of 80.5%—on par with that of non-expert humans—and when applied to CORD’19, identifies 10,912 putative drug-like molecules. This enriched the computational screening team’s targets by 3,591 molecules, of which 18 ranked in the top 0.1% of all 6.6 million molecules screened for docking against the 3CLPro protein.

60 APPLIED LIFE SCIENCES↗

Disentangling error structures of precipitation datasets using decision trees

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60 binary decision trees, this study disentangles the error characteristics of precipitation products in terms of their spatiotemporal patterns and geographical factors. Three independent precipitation products - two satellite-based and one reanalysis datasets: the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) late run (IMERG-L), Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 uncorrected precipitation output (MERRA2-UC), are evaluated across the contiguous United States from 2010 to 2019. Here, the ground-based Stage IV precipitation dataset is used as the ground truth. Results indicate that the MERRA2-UC outperforms the IMERG-L and SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the analysis period. Decision trees cross-assess three spatiotemporal factors and find that the underestimation of MERRA2-UC occurs in the east of the Rocky Mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine different geographical characteristics, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover type, topography position index, and aspect are three relatively weak factors.

54 ENVIRONMENTAL SCIENCES↗

High Temperature Erosion Modeling in Particle Based CSP Systems

1. Introduction. Wear and erosion damage of materials from solid particle and surface interactions is a major issue in various industries. Although more common in mining and oil and gas production, erosion is becoming a critical issue in renewable technologies as well such as particle based concentrated solar thermal power (CSP) systems. In particle based CSP systems, solid particles are used to absorb solar energy and as thermal storage. However, these particles may cause significant amount of wear to system components while through the system at high temperatures. This damage can be costly, and therefore, requires a greater understanding of solid particle erosion in CSP systems. Throughout the years, models and tools have been developed to predict and control erosion in industries such as oil and gas production. However, these erosion models and erosion prediction tools have been mainly developed based on erosion data for much higher velocities and lower temperatures, i.e. the operating conditions for which the existing models have been built are not pertinent to those expected in CSP system. It is known that erosion depends on many factors such as material properties, erodent particle properties, and particle impact speed and angle. However, the effect of temperature on erosion is not vastly investigated. In this work, a temperature-based correlation is introduced that will be used to modify the existing erosion models to predict erosion rates at velocities and temperatures relevant to Gen3 CSP systems. The existing models are first validated against erosion experiments run at low temperatures and low velocities. Subsequently, a temperature correction term is developed that can extend the existing models to high temperatures, based on the available experimental data showing the effect of temperature on impact erosion. 2. Erosion Models. Continuing sequence of impacts from solid particles on surfaces would result in loss of material due to mechanical interaction between solid surface and particles. Erosion equations have been developed to predict erosion under different conditions and erosion mechanism, including cutting and deformation erosion. These models are mainly either mechanistic, empirical, and semi-mechanistic models, when the latter combine the theory of the erosion mechanism and particle motion with the available experimental data. One of the first empirical correlation was introduced by American Petroleum Institute (API) Recommended Practice (RP) 14E [1]. This correlation was very conservative, and several improved empirical and semi-mechanistic equations were developed in the years following. More recently, the models introduced by Erosion/Corrosion Research Center (E/CRC) at the University of Tulsa and Arabnejad. et al. [2] are frequently used in the literature and industry, as they account for many parameters affecting erosion including particle impact speed and angle, material density and hardness, and particle size and shape. However, both these models were developed based on data at relatively high velocities and also do not take into account any mechanical changes in material associated with thermal cycling at high temperatures. 3. Erosion Prediction at High Temperatures. In this work, the accuracy of Arabnejad et al. model and E/CRC model is investigated to predict impact erosion at conditions relevant to Gen3 CSP systems. Two significant deviations expected in Gen3 systems compared to operating conditions used to build these models are particle impact velocities and system temperature. As a first step, the performance of these models was validated at low velocities and temperatures. Impact erosion experiments were conducted on SS316 coupons using HSP 40/70 ceramic particles. Assuming particle rate of 1 kg/s/m, 0.0254 m of particle curtain thickness, and particle velocity of 1.5 m/s in the system, an overall erosion of 0.59 mm/year was calculated. The experimental results were subsequently compared to those from computational simulations and erosion of 0.47 mm/year was obtained using the Arabnejad et al. model. The results indicated that the models work well at low velocities and low temperature conditions. To account for temperature effect, a mathematical correlation was developed using data published by DUCOM [3] for Inconel 600 eroded by alumina particles at high velocities. The correlation was applied to both Arabnejad et. al model and the E/CRC model. The prediction results from these modified models were within 20% of this experimental data. Predictions of of erosion by the modified E/CRC model at three different temperatures are made. Similar to the calculation at low temperature, a typical CSP system with 1 kg/s/m of particle flow rate per unit length of the particle curtain and a curtain thickness of 0.0254 m is assumed. The annual thickness loss calculations were run for different particle impact velocities, assuming a uniform particle impact area equal to the cross-sectional area of the curtain (particle-particle interactions and dispersion of particles are not considered in obtaining the results). It is observed that erosion increases exponentially as temperature increases. Furthermore, it is also noted that, erosion changes non-linearly with impact velocity. Currently, experiments are also being conducted to measure erosion of SS316 at 800 ºC with HSP 40/70 particles at low impact velocities. We expect to use the results from high temperature testing to further improve the temperature correlation function. Similar models are also being developed for abrasion erosion resulting from particle sliding along the surfaces as well as attrition from particle to particle and particle to surface interactions. References. [1] Institute, A. P. (1991). API Recommended Practice for Design and Installation of Offshore Production Platform Piping System, API RP 14E. [2] Arabnejad, H., Mansouri, A., Shirazi, S. A., and McLaury, B. S. (2015a). Development of mechanistic erosion equation for solid particles. Wear, 332–333, 1044–1050. http://doi.org/10.1016/j.wear.2015.01.031. [3] https://ducom.com/high-temperature-erosion-evaluating-sample-wear/

14 SOLAR ENERGY↗