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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 469 records · Page 26

A Panoramic View of MXenes via an Atomic Coordination‐Based Design Strategy

Two‐dimensional (2D) transition metal carbides and nitrides, known as MXenes, possess unique physical and chemical properties, enabling diverse applications in fields ranging from energy storage to communication, catalysis, sensing, healthcare, and beyond. Despite extensive research and notable advancements, a fundamental understanding of MXenes’ phase diversity and its connection to their hierarchical precursors, including the intermediate MAX phases and the ancestral bulk phases, remains limited. Here, in this study, it is hypothesized that the atomic coordination environments adopted by transition metal and nonmetallic atoms in their three‐dimensional (3D) bulk precursors may persist in 2D MXenes to govern their phase diversity. Using high‐throughput modeling based on first‐principles density functional theory, a wide range of MXene phases is unveiled and comprehensively evaluate their relative stabilities across a large chemical space. The key to the approach lies in considering various atomic coordination environments drawn from four types of ancestral bulk phases. Through this comprehensive structural library of MXenes, general guiding principles are uncovered, such as a close alignment between the phase stability of MXenes and that of their 3D precursors. These findings introduce a new design strategy in which the atomic coordination environments in bulk phases can serve as reliable predictors for accessing the diverse structural landscape of MXenes.

MXenes↗

Rhodotorula toruloides Nitrogen Limitation PTM Profiling Multi-Omics (TZ-DP1)

The purpose of this experiment was to evaluate the regulatory stress response of Oleaginous yeast species Rhodotorula toruloides NBRC 0880 (JGI strain IFO0880 v4.0) under nitrogen-rich and nitrogen-limited conditions over time. Time course experimental samples (0, 24, 48, and 72 hours after inoculation) were prepared using a semi-automated multi-PTM proteomic approach, using tandem mass tag 18-plex (TMT18), and lipidome remodeling for downstream multi-omics analysis. Processed datasets are openly accessible from PNNL DataHub and contain secondary processed proteomic (redox, phospho, and global TMT) and lipidomic (positive and negative ion mode) results files and experimental design metadata.

59 BASIC BIOLOGICAL SCIENCES↗

NASA Langley/CNU Distance Learning Programs

NASA Langley Research Center and Christopher Newport University (CNU) provide, free to the public, distance learning programs that focus on math, science, and/or technology over a spectrum of education levels from K-adult. The effort started in 1997, and we currently have a suite of five distance-learning programs. We have around 450,000 registered educators and 12.5 million registered students in 60 countries. Partners and affiliates include the American Institute of Aeronautics and Astronautics (AIAA), the Aerospace Education Coordinating Committee (AECC), the Alliance for Community Media, the National Educational Telecommunications Association, Public Broadcasting System (PBS) affiliates, the NASA Learning Technologies Channel, the National Council of Teachers of Mathematics (NCTM), the Council of the Great City Schools, Hampton City Public Schools, Sea World Adventure Parks, Busch Gardens, ePALS.com, and Riverdeep. Our mission is based on the "Horizon of Learning," a vision for inspiring learning across a continuum of educational experiences. The programs form a continuum of educational experiences for elementary youth through adult learners. The strategic plan for the programs will evolve to reflect evolving national educational needs, changes within NASA, and emerging system initiatives. Plans for each program component include goals, objectives, learning outcomes, and rely on sound business models. It is well documented that if technology is used properly it can be a powerful partner in education. Our programs employ both advances in information technology and in effective pedagogy to produce a broad range of materials to complement and enhance other educational efforts. Collectively, the goals of the five programs are to increase educational excellence; enhance and enrich the teaching of mathematics, science, and technology; increase scientific and technological literacy; and communicate the results of NASA discovery, exploration, innovation and research. All pre-college distance learning programs support the national mathematics, science, and technology standards; support K-12 systemic change; involve educators in their development, implementation, and evaluation; and are based on alliances and partnerships. In addition the programs seek to invoke a sense of geographic, ethnic and cultural diversity by featuring schools from all over the U.S.; schools from urban, suburban, and rural areas; public, private, and religious schools; and schools with large populations of African-American, Asian and Hispanic students.

Caton, Randall↗

Splat Quenching as a High Throughput Rapid Solidification Testing Method for Developing Additive Manufacturing Alloys

Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.

Alloy Design↗

Radiation Effects on Uranyl Tetrachloro Coordination Compounds: Impact of Lattice Water

Nuclear materials, such as uranium-bearing solids, are exposed to high levels of ionizing radiation throughout the nuclear fuel cycle; thus, it is important to develop a molecular-level understanding of how these materials behave and degrade in the presence of gamma (γ) irradiation. In the current study, three U(VI) tetrachloride complexes, M 2 [UO 2 Cl 4 ]·xH 2 O (where M = K + , Rb + , or Cs + and x = 0 or 2), and their respective chloride salts were exposed to 1–50 kGy of γ radiation using a 60 Co source. Irradiated materials were evaluated by using electron paramagnetic resonance (EPR) and Raman spectroscopy and were further explored by using density functional theory (DFT) methods. EPR spectra of the irradiated materials suggest the formation of a Cl-based radical for both the alkali salts and the uranyl tetrachloride compounds, and DFT calculations provide evidence that the Cl 2 –• radical is formed within these materials. The presence of water in the K + and Rb + compounds leads to additional spectroscopic signatures that could be traced back to water radiolysis and the formation of peroxide and superoxide species. DFT results support the formation of HO 2 • in the lattice and potentially the formation of a [UO 2 Cl 3 (O 2 )] 3– species, highlighting the impact of water within the hydrated material to alter U(VI) speciation by radiolysis.

36 MATERIALS SCIENCE↗

PPI DataHub Project Data Package: S. elongatus PCC 7942 Circadian Control Bioproduction Transcriptomics (PB-DP3)

The purpose of this experiment was to evaluate how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 in providing insights to strategies for enhanced bioproduction. Sample data was acquired using a Illumina HiSeq sequencer system and processed for RNA sequencing (RNA-Seq) expression analysis. Transcriptomic differential expression analysis revealed coordinated circadian clock-driven adjustment of the cell cycle and rewiring of energy and carbon metabolism. Processed RNA-Seq datasets are openly accessible from the PNNL DataHub project dataset download page and contain secondary processed RNA-seq results files and supporting metadata materials linked to relevant source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗

Crystallographic stability of the BCC phase during quenching of metastable beta titanium alloy Ti-5553 and comparison of structural criteria for the predictive capability of α” martensite

This work evaluates the compositional standard currently developed for Ti-5553 powder and explores the metastable β region for sensitivity to martensitic formation during rapid quenching from the melt. Ti-5553 is a beta-stabilized titanium alloy that is increasingly being used in additive manufacturing applications. A series of alloys within the Ti-5553 compositional space was processed using two-piston spat quenching to perform rapid solidification and quenching for each of these alloy compositions. Typical empirical models such as molybdenum equivalency are not able to fully separate the retained BCC and martensitic compositions. Further, the use of thermodynamic data to estimate the transformation energy needed to form martensite can differentiate the alloys and provide a metric to further develop compositional limits for metastable beta titanium alloy development.

36 MATERIALS SCIENCE↗

Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. Here, we propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

image segmentation↗

Mechanical and Thermal Characterization of Additively Manufactured Carbon/Nylon 12 and Carbon/PEEK Composites

This study explores additive manufacturing of carbon fiber-reinforced thermoplastic composites using the Composite-Based Additive Manufacturing (CBAM) process. Carbon/Nylon 12 and Carbon/PEEK composites were fabricated and evaluated through mechanical (compression, tensile, flexural, and impact) and thermal (DSC and TGA) tests. Carbon/PEEK exhibited superior mechanical performance, with 97.5% higher tensile strength, 79.8% higher elastic modulus, and 59.6% higher flexural strength compared to Carbon/Nylon 12. Thermal testing showed that Carbon/PEEK had higher thermal stability, beginning degradation at 350 °C versus 298 °C for Carbon/Nylon. These results indicate that CBAM-fabricated Carbon/PEEK composites are suitable for applications requiring high strength and temperature resistance.

Additive manufacturing↗

Energy-conserving contact dynamics of nonspherical rigid-body particles

Understanding the contact dynamics of nonspherical particles is crucial for accurately modeling colloidal and granular systems where shape anisotropy dictates structural organization and transport properties. We here introduce an energy-conserving contact dynamics framework for arbitrary convex rigid-body particles by implementing vertex–boundary interactions in 2D and vertex–surface and edge–edge detection in 3D. The established formulation enables continuous force evaluation and prevents particle overlap while conserving total energy during translational and rotational motion. We demonstrate the framework’s stability and its utility to capture packing behavior, anisotropic diffusion, and equations of state of polygonal and polyhedral particles as examples. The framework establishes a robust and extensible foundation for investigating nonequilibrium dynamics of complex nonspherical particulate systems, enabling enhanced understanding of phenomena across spatiotemporal scales in self- and directed-assembly, granular flows, and hydrodynamics, potentially coupled with interactions that represent underlying physical mechanisms.

Discrete element method↗

A Mobile Edge Computing Framework for Traffic Optimization At Urban Intersections Through Cyber-Physical Integration

The stop-and-go traffic pattern on urban roads often results in excessive energy consumption because of unnecessary vehicle braking, idling, and accelerations. With the widespread and increased use of automobiles, this traffic pattern creates many negative impacts (e.g., delayed travel time, air pollution, and additional carbon emission) on the sustainability of our cities. Taking advantage of the recent emerging Internet of Things (IoT) and edge computing paradigms, we propose a mobile edge computing framework that integrates the capability of real-time vehicle-to-infrastructure communication and intelligent speed optimization algorithms into a mobile app to optimize individual vehicles' driving speed at signalized intersections. The optimization aims to mitigate the stop-and-go traffic pattern and its undesirable consequences in urban transportation systems. The framework consists of (1) a cyberinfrastructure-enabled dynamic messaging system for retrieving and delivering real-time traffic and signal phase and timing information from IoT-connected signal controllers and sensors, (2) a real-time speed optimization algorithm for generating intelligent speed advisory using vehicle's information (e.g., GPS and driving directions from mobile sensing) and corresponding signal and traffic information, and (3) an ad-hoc mobile computing environment that converts drivers' smartphones into edge devices to host the speed optimization algorithms for enabling intelligent advisory on the vehicle's driving speed within signalized corridors. The paper presents the design and implementation of the proposed framework. Finally, we demonstrate the feasibility, usefulness, and energy-saving benefits of our proposed framework and its prototyping mobile app on urban transportation systems through traffic simulation, real-vehicle laboratory experiments, an evaluative survey, and field communication tests. The simulation-based energy evaluation results show that the 100% usage of the mobile app can achieve 24% energy savings in the transportation system.

33 ADVANCED PROPULSION SYSTEMS↗

A Unified Framework to Reconcile Different Approaches of Modeling Transpiration Response to Water Stress: Plant Hydraulics, Supply Demand Balance, and Empirical Soil Water Stress Function

Plant responses to water stress is a major uncertainty to predicting terrestrial ecosystem sensitivity to drought. Different approaches have been developed to represent plant water stress. Empirical approaches (the empirical soil water stress (or Beta) function and the supply-demand balance scheme) have been widely used for many decades; more mechanistic based approaches, that is, plant hydraulic models (PHMs), were increasingly adopted in the past decade. However, the relationships between them—and their underlying connections to physical processes—are not sufficiently understood. This limited understanding hinders informed decisions on the necessary complexities needed for different applications, with empirical approaches being mechanistically insufficient, and PHMs often being too complex to constrain. Here we introduce a unified framework for modeling transpiration responses to water stress, within which we demonstrate that empirical approaches are special cases of the full PHM, when the plant hydraulic parameters satisfy certain conditions. We further evaluate their response differences and identify the associated physical processes. Finally, we propose a methodology for assessing the necessity of added complexities of the PHM under various climatic conditions and ecosystem types, with case studies in three typical ecosystems: a humid Midwestern cropland, a semi-arid evergreen needleleaf forest, and an arid grassland. Notably, Beta function overestimates transpiration when VPD is high due to its lack of constraints from hydraulic transport and is therefore insufficient in high VPD environments. With the unified framework, we envision researchers can better understand the mechanistic bases of and the relationships between different approaches and make more informed choices.

54 ENVIRONMENTAL SCIENCES↗

Determination of a suitable molar absorption coefficient (ε) for lignin analysis of fibrous plants using the CASA method

In this study, the benchmarking and applicability of the CASA method for the analysis of fibrous plants, such as flax, hemp, and jute, is evaluated. Lignin is a phenolic biopolymer present in plant cell walls and is composed of three primary monomeric units, designated G, S, and H. Various factors, such as the genetic variability, influence the relative proportions of these units in plant samples. Recently, the cysteine-assisted sulfuric acid (CASA) method has been introduced as a rapid method for the quantification of lignin in wood samples. The aim of this study is to establish a suitable molar absorption coefficient (ε, L·g –1 ·cm –1 ) to adapt the CASA method for use with annual plant fibers. This investigation was motivated by the technical advantages of the CASA method, including higher throughput, lower reaction temperatures, and ecological benefits due to the absence of carcinogenic, mutagenic, or reprotoxic (CMR) substances and the need for minimal sample quantities. In this method, lignin solubilization is facilitated by cysteine, which is an amino acid that enhances the reaction kinetics, using a one-hour incubation period. However, as with any spectrophotometric technique, the CASA method depends on a molar absorption coefficient (ε) that varies according to the ratio of the aromatic units within the polymer. To evaluate the suitability of CASA for quantifying lignin in economically significant plant fibers, we investigate the impact of the unit ratios on the accuracy of ε. The results are compared with those of two widely recognized lignin analytical methods: the Klason method, which is a gravimetric reference method, and the acetyl bromide soluble lignin method, which is the most commonly used spectrophotometric approach. The final ε obtained in this study reveals a relative difference in lignin content ranging from –8 % to +9 % based on a comparison between the CASA and Klason methods across different industrial hemp varieties. As a result, using known G:S ratios in annual fibrous plants, ε can be estimated from our results.

59 BASIC BIOLOGICAL SCIENCES↗

The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

Suppose you are a city planner, regional water manager, or wildlife conservation specialist who is asked to include the potential impacts of climate variability and change in your risk management and planning efforts. What climate information would you use? The choice is often regional or local climate projections downscaled from global climate models (GCMs; also known as general circulation models) to include detail at spatial and temporal scales that align with those of the decision problem. A few years ago this information was hard to come by. Now there is Web-based access to a proliferation of high-resolution climate projections derived with differing downscaling methods.

downscaled projections↗

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗

An evaluation of air quality in major urban areas of India

Rapid economic growth and burgeoning population have contributed to enhanced levels of PM 2.5 concentrations in urban regions of India. Evaluation of ambient air quality facilitates the assessment of effectiveness of emission control measures and early identification of new sources. This study provides a comprehensive statistical analysis of PM 2.5 concentrations in key urban areas across India, including Delhi, Kolkata, Mumbai, Chennai, Hyderabad, and several regional centers. Data from 2017 to 2023 was analyzed using trend analysis, cluster analysis, principal component analysis, and geostatistical interpolation to understand spatiotemporal variations and sources. The analysis reveals significant differences in spatial distribution of PM 2.5 concentrations with high annual averages in urban regions in Indo-Gangetic plain (82–123 μg m −3 ) and relatively lower concentrations (29–46 μg m −3 ) in southern urban areas of Kerala, Tamil Nadu and Andhra Pradesh. Delhi state had the highest 24-averaged PM 2.5 concentrations (112 μg m −3 ) followed by urban regions in Uttar Pradesh, Bihar and West Bengal (94 μg m −3 ). Trend analysis from 2017 to 2023 revealed an overall 2.5% decline in site-wide PM2.5 concentrations, with the exception of Ludhiana, which exhibited a consistent annual increase of 10%. Principal component analysis (PCA) attributes 30% of the variance to wintertime emissions, 13% to biomass burning, and 18% to the regional haze in the northern Indo-Gangetic Plain. Different analyses clearly demonstrates the contribution of biomass burning to pollution in Delhi and surrounding cities. Transboundary pollution to Kolkata is likely from the highly polluted region in Indo-Gangetic Plain. Coastal cities of Mumbai and Chennai has relatively lower pollution attributed to the influence of sea breeze dilution, with mostly local contribution and some potential transport from upwind industry clusters. Hyderabad also has local contribution due to high density of vehicular traffic and local small industries. This study shows that mitigation efforts targeting clusters of regions should be undertaken to curb the high PM2.5 pollution. Policy measures should be implemented both at local and the intra-state level to address shared sources and transport of pollution.

Hysplitbacktrajectories↗

Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these transportation plans will affect fbture air quality.

Quattrochi, Dale A.↗

Effects of He-Ion Radiation on Solid-State Uranyl Nitrate Compounds under Dry and Hydrated Atmospheric Conditions

Radioactive decay of uranium (U) and its related daughter/fission products emit ionizing radiation, including γ (γ) rays and α (α) particles, that result in the formation of radical species and induce chemical reactivity in materials. While radioactivity is inherent to the chemistry of U there are limited studies that detail changes at an atomistic level. Here, this work describes the He-ion radiolysis of four solid-state U(VI) species: [UO 2 (NO 3 ) 2 ]·3(H 2 O) and M[UO 2 (NO 3 ) 3 ] (M = K + , Rb + , Cs + ). These materials were irradiated under different conditions (i.e. closed, open – Ar gas, or open – H 2 O-saturated Ar gas) to further evaluate the impact of water radiolysis on the chemical modification of these materials. Pre- and post-irradiation analyses were conducted using EPR, Raman, and ATR-IR spectroscopy on materials irradiated to 0, 5, 10, and 25 MGy. The results indicated the presence of nitrate radical (NO 3 • ) formation in all solid-state materials with similarities to those observed in γ-radiation studies. Irradiation of [UO 2 (NO 3 ) 2 ]·3(H 2 O) did not show evidence of reactive oxygen species bound to the U(VI) cation under inert conditions; however, surface reactivity was observed for samples irradiated in the H 2 O-saturated environment. Similar chemical changes were observed in the uranyl trinitrato compounds irradiated in the presence of H 2 O vapor and there were observed differences in the reactivity depending on the identity of the alkali cation.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗