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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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At least 73 records · Page 4

A constitutive structural parameter c b for the work hardening behavior of additively manufactured Ti-6Al-4V

The mechanical behavior of Ti-6Al-4V produced by additive manufacturing processes is assessed as based on a model derived from the Kocks–Mecking relationship. A constitutive parameter c b is derived from a linear Kocks–Mecking relationship for the microstructure that is characteristic of the work hardening behavior. The formulation for c b is determined by considering the plastic strain between the strengths at the proportional limit and the plastic instability. In this way, the model accommodates the variation in work hardening behavior observed when evaluating material as produced and tested along different orientations. The modeling approach is presented and evaluated for the case of Ti-6Al-4V additively manufactured materials as tested under quasi-static uniaxial tension. It is found that different test specimen orientations, along with postbuild heat treatments, produce a change in the microstructure and plasticity behavior which can be accounted for in the corresponding change of the c b values.

36 MATERIALS SCIENCE↗

SITCOMTN-162: Testing the implementation of Metadetection and Cell-Based Coadds on Abell 360 LSSTComCam data

The purpose of this technote is to test the technical quality of LSSTComCam commissioning data, specifically the Rubin_SV_38_7 field, by utilizing cell-based coadds and Metadetection by measuring the tangential and cross weak lensing shear profiles of the massive cluster Abell 360 (called A360 throughout the technote). The process entails generating the cell-based coadds for Metadetection to run on, identifying and removing cluster member galaxies, applying quality cuts, calibrating the shear measurements, and validation. Cell-based coadds and Metadetection are both currently in the process of being implemented within the LSST Science Pipelines at the time of this technote. There is substantial technical value in attempting a difficult measurement prior to full implementation. Measuring the tangential shear around A360 will showcase the current abilities of these algorithms, as well as highlight where work is still needed. As seen from the resulting shear profile of A360, the cell-based coadds and Metadetection are able to work in tandem to produce a shear catalog and resulting reduced shear profile. This technote is one part of a series studying A360 in order to both stress test the commissioning camera and demonstrate the technical capabilities of the Vera Rubin Observatory. We study the quality of the PSF modeling and impact it can have on cluster WL in [Combet et al., 2025], implementation of cell-based coadds and subsequent use for Metadetect [Sheldon et al., 2023] in this technote, photometric calibration in (in prep), source selection and photometric redshifts in [Adari et al., 2025], use of Anacal [Li et al., 2024] to produce a cluster shear profile in [Li et al., 2025], and background subtraction in this field and Fornax in [Zhou et al., 2025].

79 ASTRONOMY AND ASTROPHYSICS↗

Water quality data collected from the Muskegon River (MI, USA) using AquaBOT June-July 2024.

This dataset contains processed output from AquaBOT, which combines 30-second interval measurements of GPS location and YSI water quality parameters (temperature (degrees Celsius), dissolved oxygen (mg/l), specific conductance(microSiemens/cm at 25 degrees Celsius), and turbidity (NTU)), for 3 sections of the Muskegon River in Michigan, USA. The file aquabot2024_MuskegonRiver.csv has information on locations, dates and times, and observations. The data were processed by removing observations recorded before and after AquaBOT was in the water and observations where no data values were recorded. No other QA/QC was done. This research was performed as part of the DOE Research Development and Partnership Pilot award “Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region”, which aims to expand collaborations between researchers at Central Michigan University and U.S. Department of Energy labs and projects focused on enhancing climate resilience in Great Lakes communities and ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Comparing Life Histories of the Shortest-Lived Turtle Known (Chicken Turtles, Deirochelys reticularia ) with Long-Lived Blanding's Turtles ( Emydoidea blandingii )

Evolutionary theories predict major differences in life-history trait values of long- and short-lived organisms. Such comparisons have not been possible for chelonians because no shortlived turtle was known until research revealed that chicken turtles (Deirochelys reticularia; DR) have a maximum longevity of 21 yrs. Life-history trait values of DR females are 1) age at maturity of females = 5–6 yrs; 2) clutches per season = 1.6; 3) annual fecundity = 6–8 female eggs per female; 4) average juvenile survivorship from age 1 to maturity = 0.60; and 5) low average annual adult survivorship = 0.66. We compared DR with the very long-lived Blanding’s turtles (Emydoidea blandingii; EB) in Michigan. Over 14 yrs with no mortality (the minimum age at maturity of EB), the maximum potential fecundity produced by a single female embryo and her mature female offspring was 5 female eggs for EB and 1040 eggs for DR. Comparisons of life table output for approximately stable populations of DR and EB resulted in cohort generation times of 7 and 37 yrs, respectively. The life-history prediction that short-lived organisms should produce smaller offspring was not supported. Average wet mass of eggs is 10 g (8.4–11.3 g) for DR and 12 g (10–14 g) for EB; and average wet mass of hatchlings is 7.3 g (6–9 g) for DR and 9.3 g (6–13 g) for EB. Both differences are smaller than expected based on the difference in longevity. Here, short-lived female DR have an unusual tactic of investing in high fecundity and making substantial body sizespecific investment in large eggs, which may reflect why juvenile survivorship had greater influence on population change rates than did adult survivorship. In contrast, adult survivorship had the greatest influence on population change rates of EB. Comparison of cohorts of 1000 female DR and EB hatchlings highlights the differences in life histories of short- and long-lived turtles: all DR would be dead by the time the last female EB had reached maturity at 21 yrs of age.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing the solid hydrolysis product, UF 4 (H 2 O) 2.5 , generated from neat water reactions with UF 4 at room temperature

Uranium tetrafluoride (UF 4 ) is an important intermediate in the production of UF 6 and uranium metal. Room temperature hydrolysis of UF 4 was investigated using a combination of Fluorine-19 nuclear magnetic resonance spectroscopy ( 19 F NMR), Raman and infrared spectroscopy, powder X-ray diffraction, and microscopy measurements. UF 4 (H 2 O) 2.5 was identified as the primary solid hydrolysis product when anhydrous UF 4 was stirred in deionized water. Static NMR and 19 F magic angle spinning NMR measurements revealed that a small amount of uranyl fluoride can also form when anhydrous UF 4 is left in water, although this species comprises less than 5% of the total sample with the remaining parts being UF 4 (H 2 O) 2.5 . Since UF 4 is generally considered to be stable under ambient conditions, these findings mark the first time that a room temperature reaction between UF 4 and water has been detected and analyzed without interference from additional chemical reagents. The Raman characterization of UF 4 (H 2 O) 2.5 presented herein is the first on record. Since UF 4 is one of the most used intermediates during chemical conversion of uranium ore to uranium metal for nuclear fuel and weapons, the results presented herein are applicable to numerous nuclear science fields where solid state detection of uranium is of value, including nuclear nonproliferation, nuclear forensics, and environmental remediation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Critical Infrastructure Decision-Making under Long-Term Climate Hazard Uncertainty: The Need for an Integrated, Multidisciplinary Approach

U.S. critical infrastructure assets are often designed to operate for decades, and yet long-term planning practices have historically ignored climate change. With the current pace of changing operational conditions and severe weather hazards, research is needed to improve our ability to translate complex, uncertain risk assessment data into actionable inputs to improve decision-making for infrastructure planning. Decisions made today need to explicitly account for climate change – the chronic stressors, the evolution of severe weather events, and the wide-ranging uncertainties. If done well, decision making with climate in mind will result in increased resilience and decreased impacts to our lives, economies, and national security. We present a three-tier approach to create the research products needed in this space: bringing together climate projection data, severe weather event modeling, asset-level impacts, and contextspecific decision constraints and requirements. At each step, it is crucial to capture uncertainties and to communicate those uncertainties to decision-makers. While many components of the necessary research are mature (i.e., climate projection data), there has been little effort to develop proven tools for long-term planning in this space. The combination of chronic and acute stressors, spatial and temporal uncertainties, and interdependencies among infrastructure sectors coalesce into a complex decision space. By applying known methods from decision science and data analysis, we can work to demonstrate the value of an interdisciplinary approach to climate-hazard decision making for longterm infrastructure planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SAIL Field Campaign X-Band Precipitation Radar Surface Quantitative Precipitation Estimation (SQUIRE) Value-Added Product Report

In 2010, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility procured 3- and 5-cm wavelength radars for documenting the macrophysical, microphysical, and dynamical structure of precipitating systems. In order to maximize the scientific impact, ARM supported the development of an application chain to correct for various phenomena in order to retrieve the lowest retrieved value on a Cartesian grid. This report details the motivation, science, and progress to date, as well as charting a path forward.

54 ENVIRONMENTAL SCIENCES↗

Finding Peas in the Early Universe with JWST

The Early Release Observations (EROs) of JWST beautifully demonstrate the promise of JWST in characterizing the universe at Cosmic Dawn. We analyze the Near Infrared Spectrograph ERO spectra of three z ~ 8 galaxies to determine their metallicities, gas temperatures, and ionization. These galaxies offer the first opportunity to understand the physical properties of Epoch-of-Reionization galaxies through detailed rest-optical emission-line spectroscopy. We show that these objects have metal abundances $12+\mathrm{log}[{\rm{O}}/{\rm{H}}]\,\approx$ 6.9–8.3, based on both the T e method and on a recent calibration of the R 23 metallicity indicator. Since the spectra are some of the earliest science data from JWST, we compare several line ratios with values expected from robust physics, to validate our measurement procedures. We compare the abundances and emission-line ratios to a nearby sample of Green Pea galaxies—a population of nearby emission-line galaxies whose UV properties resemble Epoch-of-Reionization galaxies, and which often have large Lyman continuum escape fractions. The JWST data show striking further similarities between these high-redshift galaxies and nearby Green Peas. The z ~ 8 galaxies span the metallicity range covered by Green Peas. They also show the compact morphology that is typical of emission-line-dominated galaxies at all redshifts. Based on these similarities with Green Peas, it is likely that these are the first rest-optical spectra of galaxies that are actively driving cosmological reionization.

79 ASTRONOMY AND ASTROPHYSICS↗

A framework for forming thermoset polymer networks during laser powder bed fusion additive manufacturing

It is commonly reported that the limited availability of material types is a major barrier to widespread adoption for polymer laser powder bed fusion (PBF/L) additive manufacturing (AM). A deeper understanding of the physico-chemical relationships between AM process stimuli and polymer responsive behavior is needed to make data-driven decisions for PBF/L specific material development and formulation. Many researchers have cumulatively built the current state of PBF/L “science-based manufacturing” framework where an initial guess for process parameter values can be determined from measured polymer properties and the first-principles of physics. However, published literature has focused on developing this framework for thermoplastic processing of polymers omitting many specific concerns unique to processing thermosetting materials. The authors consider in the present work the implications of many specific aspects unique to thermosetting polymers during PBF/L manufacturing. These aspects are contextually discussed according to the five sub-functions of PBF/L and are described mathematically where appropriate alongside example data from thermosetting materials commercially available in powder form. Further, this expansion of the prevailing material development framework to include thermosetting polymers paves the way for the unique performance properties offered by that class to be manifest through AM’s geometric freedom.

36 MATERIALS SCIENCE↗

Pervasive Warming Bias in CMIP6 Tropospheric Layers

Abstract The tendency of climate models to overstate warming in the tropical troposphere has long been noted. Here we examine individual runs from 38 newly released Coupled Model Intercomparison Project Version 6 (CMIP6) models and show that the warm bias is now observable globally as well. We compare CMIP6 runs against observational series drawn from satellites, weather balloons, and reanalysis products. We focus on the 1979–2014 interval, the maximum span for which all observational products are available and for which models were run using historically observed forcings. For lower‐troposphere and midtroposphere layers both globally and in the tropics, all 38 models overpredict warming in every target observational analog, in most cases significantly so, and the average differences between models and observations are statistically significant. We present evidence that consistency with observed warming would require lower model Equilibrium Climate Sensitivity (ECS) values.

54 ENVIRONMENTAL SCIENCES↗

Exploring Fabrication of Ultra-low Absorption, Multilayer, Hafnium High Reflectors

Ultra-low absorption, high damage threshold coatings are critical for the advancement of the high power CW laser technologies, and in most cases, are a limiting factor for the output power. Since high power CW laser systems enable extremely high power irradiances, when the light is incident on an HR mirror, part of the energy is absorbed and converted into heat, which can have many detrimental side effects. The worst-case scenarios are optical distortion and laser-induced damage. These optics must operate reliably with irradiances of 100's kW/cm 2 to MW/cm 2 . The highest pulsed laser damage threshold high reflectors are consistently fabricated with hafnia material. However, hafnia is not the material of choice for high power CW laser systems because of very high absorption and scatter properties, factors of >100x higher than tantala-silica, due to its poly crystalline nature. This study focuses on CW laser use applications, where the coatings’ laser damage resistance is largely limited by the inherent absorption of the coating materials. The goal is to study the feasibility of utilizing a “composite” hafnium-silica and a “doped” hafnia-silica target materials to prohibit crystallization. The results from the study were extremely successful. Hafnia high reflectors coatings generated from this study exhibited one micron absorption values of approximately 1 ppm, which are the lowest reported values to date.

36 MATERIALS SCIENCE↗

Planning for the storm: Considering renewable energy for critical infrastructure resilience

This study uses the renewable energy optimization model to assess three critical facilities in North Carolina. Techno-economic results were then compared to analyses completed for critical facilities in California and New York to assess energy system cost effectiveness. Though solar photovoltaic (PV) arrays are cost-effective across each of the three North Carolina facilities, adopting battery storage to enable PV to operate with existing diesel generators in a hybrid energy system reduces the economic value of the system. This is in contrast to more economically viable systems in California and New York. All of these systems also offer unquantified resilience benefits by extending operation from hours to weeks across the facilities. If decision makers were able to value the resilience benefits offered by each system or utility rate structures were changed to incentivize battery storage during normal operations, it would impact these assessments. Even so, this analysis provides decision makers a key set of cost benchmarks when considering how they might improve resilience at their critical operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Portlandite solubility and Ca2+ activity in presence of gluconate and hexitols

The current paper investigates the impact of gluconate, D-sorbitol, d-mannitol and D-galactitol on calcium speciation at high pH values by i) solubility measurements of portlandite (Ca(OH){sub 2}) and ii) potentiometric titration measurements of calcium salt solutions. Thermodynamic modelling was used to fit the chemical activities of Ca{sup 2+} and OH{sup −} ions and thus to determine the strength and kind of the different Ca-organic-hydroxide complexes. The strength of complex formation with Ca{sup 2+} decreases in the order gluconate ≫ sorbitol > mannitol > galactitol, which follows the same order as sorption on portlandite. Heteropolynuclear gluconate complexes with calcium and hydroxide dominate the Ca-speciation in the presence of portlandite, while for sorbitol ternary CaSorbOH{sup +} complexes were dominant under alkaline conditions. We expect that these results will help in better understanding the influence of gluconate and hexitols on the hydration of alite and Portland cement.

36 MATERIALS SCIENCE↗

Data-driven upper bounds and event attribution for unprecedented heatwaves

The last decade has seen numerous record-shattering heatwaves in all corners of the globe. In the aftermath of these devastating events, there is interest in identifying worst-case thresholds or upper bounds that quantify just how hot temperatures can become. Generalized Extreme Value theory provides a data-driven estimate of extreme thresholds; however, upper bounds may be exceeded by future events, which undermines attribution and planning for heatwave impacts. Here, we show how the occurrence and relative probability of observed yet unprecedented events that exceed a priori upper bound estimates, so-called “impossible” temperatures, has changed over time. We find that many unprecedented events are actually within data-driven upper bounds, but only when using modern spatial statistical methods. Furthermore, there are clear connections between anthropogenic forcing and the “impossibility” of the most extreme temperatures. Robust understanding of heatwave thresholds provides critical information about future record-breaking events and how their extremity relates to historical measurements.

54 ENVIRONMENTAL SCIENCES↗

Comparisons of the v11.1 Orbiting Carbon Observatory‐2 (OCO‐2) X CO2 Measurements With GGG2020 TCCON

The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first Earth observation satellite mission dedicated to studying the sources and sinks of carbon dioxide (CO 2 ) on a global scale. The observations of reflected sunlight are inverted in a retrieval algorithm to produce estimates of the dry air mole-fractions of CO 2 (X CO2 ). The OCO-2 Level 2 data release, version 11.1 (v11.1) retrievals from the Atmospheric Carbon Observations from Space (ACOS) algorithm, includes significant improvements in the X CO2 data product compared to older OCO-2 data versions. This work compares the v11.1 X CO2 from OCO-2 against X CO2 estimates collected from a global ground-based network known as the Total Carbon Column Observing Network (TCCON), OCO-2's primary validation source. The OCO-2 project provides a version of the Level 2 data product, called “lite” files that include calibrated and bias-corrected XCO2 values, accessible together with all OCO-2 data products through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). This work shows that OCO-2 X CO2 observations made between September 2014 and December 2023, after quality filtering and the application of an averaging kernel correction, agree well with coincident TCCON data for all OCO-2 observational modes of land (nadir, glint, target) and ocean (glint). The aggregated, bias-corrected, and quality-filtered absolute average bias values are less than or equal to 0.20 parts per million (ppm) globally for all OCO-2 observation modes, where the biases do not indicate a statistically significant time dependence. The land nadir/glint mode has the lowest bias value of −0.03 ± 0.85 ppm.

54 ENVIRONMENTAL SCIENCES↗

Physics-Informed Deep Learning for Reconstruction of Spatial Missing Climate Information in the Antarctic

Understanding the influence of the Antarctic on the global climate is crucial for the prediction of global warming. However, due to very few observation sites, it is difficult to reconstruct the rational spatial pattern by filling in the missing values from the limited site observations. To tackle this challenge, regional spatial gap-filling methods, such as Kriging and inverse distance weighted (IDW), are regularly used in geoscience. Nevertheless, the reconstructing credibility of these methods is undesirable when the spatial structure has massive missing pieces. Inspired by image inpainting, we propose a novel deep learning method that demonstrates a good effect by embedding the physics-aware initialization of deep learning methods for rapid learning and capturing the spatial dependence for the high-fidelity imputation of missing areas. We create the benchmark dataset that artificially masks the Antarctic region with ratios of 30%, 50% and 70%. The reconstructing monthly mean surface temperature using the deep learning image inpainting method RFR (Recurrent Feature Reasoning) exhibits an average of 63% and 71% improvement of accuracy over Kriging and IDW under different missing rates. With regard to wind speed, there are still 36% and 50% improvements. In particular, the achieved improvement is even better for the larger missing ratio, such as under the 70% missing rate, where the accuracy of RFR is 68% and 74% higher than Kriging and IDW for temperature and also 38% and 46% higher for wind speed. In addition, the PI-RFR (Physics-Informed Recurrent Feature Reasoning) method we proposed is initialized using the spatial pattern data simulated by the numerical climate model instead of the unified average. Compared with RFR, PI-RFR has an average accuracy improvement of 10% for temperature and 9% for wind speed. When applied to reconstruct the spatial pattern based on the Antarctic site observations, where the missing rate is over 90%, the proposed method exhibits more spatial characteristics than Kriging and IDW.

54 ENVIRONMENTAL SCIENCES↗