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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Review of Grey Box/Black Box Data Contamination Metrics on Open and Commercial Models

Dataset contamination is a problem where benchmarks and tasks used to evaluate the capabilities of Large Language Models (LLMs) have been incorporated into the training dataset of the models. This gives a false sense of performance that can overestimate how these models will function on truly unseen data. This problem becomes worse with commercial LLMs with larger and non-accessible training data, so techniques have been developed to try to measure the degree to which a model is contaminated with a benchmark’s data. To understand the effectiveness of these techniques, particularly when evaluating contamination on coding tasks, we review trends and categorize techniques by the degree of access to the model that is required. The research literature on this topic has reported mixed effectiveness of these techniques, so we select a set of black box (text access only) and grey box (access to model loss/probabilities required) techniques and apply them to both commercial and non-commercial models. We implement these metrics as part of a framework to test the contamination of Python code in LLMs to see to what extent we can replicate the effectiveness (or ineffectiveness) of these contamination detection techniques. Though we find mixed results in the capabilities of these metrics to identify contamination, we do observe evidence that they can identify contamination (broadly) in fine-tuned models when both a baseline and fine-tuned model is present. Additionally, similarity metrics were able to identify between contaminated and uncontaminated data even in situations where the data is distributionally similar (e.g., drawn from the same set of code projects).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2002

Overview of the High Performance Antiproton (HiPAT) Experiment

The annihilation of matter with antimatter represents the highest energy density of any known reaction, producing 10(exp 8) MJ/g, approximately 10 orders of magnitude more energy per unit mass than chemical based combustion. To take the first step towards using this energy for propulsion applications the NASA MSFC Propulsion Research Center (PRC) has initiated a research activity examining the storage of low energy antiprotons. Storage was identified as a key enabling technology since it builds the experience base necessary to understand the handling of antiprotons for virtually all utilization and high-density storage concepts. To address this need, a device referred to as the High Performance Antiproton Trap (HiPAT) is under development at the NASA MSFC PRC. The HiPAT is an electromagnetic system (Penning-Malmberg design) consisting of a 4 Tesla superconductor, a high voltage confinement electrode system (operation up to 20 KV), and an ultra high vacuum test section (operating in the 10(exp -12) torr range). The system was designed to be portable with an ultimate goal of maintaining 10(exp 12) charged particles with a half-life of 18 days. Currently, this system is being experimentally evaluated using normal matter ions which are cheap to produce and relatively easy to handle. These normal ions provide a good indication of overall trap behavior, with the exception of assessing annihilation losses. The ions are produced external to HiPAT using two hydrogen ion sources, with adjustable beam energy and current. Ion are transported in a beam line and controlled through the use of electrostatic optics. These optics serve to both focus and gate the incoming ions, providing microsecond-timed pulses that are dynamically captured by cycling the HiPAT electric containment field like a 'trap door'. The layout of this system more closely simulates the operations expected at an actual antiproton production facility where 'packets' of antiprotons with pulse widths measured in 100's of nanoseconds could be provided. Initial dynamic capture experiments have been performed with both trap and ton source system functioning at approximately 10% of maximum levels, minimizing the potential for extraneous effects. Dynamic trapping techniques demonstrated the successful capture of millions of hydrogen ions with good agreement with the predicted loading based on the timing sequence, trap electric field, and ion beam current. These techniques will be expanded to examine multiple shot capture or 'stacking' to increase the total number of ions stored within HiPAT.

Martin, James J.↗
DOE OSTI2024

Alkaloids are associated with increased microbial diversity and metabolic function in poison frogs

Shifts in host-associated microbiomes can impact both host and microbes. It is of interest to understand how perturbations, like the introduction of exogenous chemicals, impact microbiomes. In poison frogs (family Dendrobatidae), the skin microbiome is exposed to alkaloids that the frogs sequester for defense. These alkaloids are antimicrobial; however, their effect on the frogs’ skin microbiome is unknown. To test this, we characterized microbial communities from field-collected dendrobatid frogs. Then, we conducted a laboratory experiment to monitor the effect of the alkaloid decahydroquinoline (DHQ) on the microbiome of two frog species with contrasting alkaloid loads in nature. In both datasets, we found that alkaloid-exposed microbiomes were more phylogenetically diverse, with an increase in diversity among rare taxa. Further, to better understand the isolate-specific response to alkaloids, we cultured microbial isolates from poison frog skin and found that many isolates exhibited enhanced growth or were not impacted by the addition of DHQ. To further explore the microbial response to alkaloids, we sequenced the metagenomes from high- and low-alkaloid frogs and observed a greater diversity of genes associated with nitrogen and carbon metabolism in high-alkaloid frogs. From these data, we hypothesized that some strains may metabolize the alkaloids. We used stable isotope tracing coupled to nanoSIMS (nanoscale secondary ion mass spectrometry), which supported the idea that some of these isolates are able to metabolize DHQ. Together, these data suggest that poison frog alkaloids open new niches for skin-associated microbes with specific adaptations, such as alkaloid metabolism, that enable survival in this environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Unraveling nonperturbative QCD with transverse momentum hadronic structures

The main purpose of this thesis is to investigate the theoretical foundations of the factorization theorems that involve transverse quark and gluon momentum distributions, and to better understand the interface between foundational questions and phenomenological applications. Many of these applications involve using transverse parton momentum dependent (TMD) correlation functions as tools for probing the complex nonperturbative structures of the hadrons. We first introduce the concepts of collinear and TMD factorization in a toy-model theory and, by leveraging the comparative simplicity of such a model, we test the range of validity and limitations of the factorization approach. At the same time, we introduce the conventional approaches that are adopted for the phenomenological extractions of the TMD distributions, and catalog the advantages and disadvantages. Following the general theoretical framework of factorization, we then develop a different approach to TMD phenomenology that is able to systematically integrate the perturbative and non perturbative information in parametrizations of TMD distributions, while being completely consistent with their operator definitions and the predictions of QCD, including their nontrivial evolution. The name Hadron Structure Oriented approach, or HSO, is coined in order to emphasize the central role of the nonperturbative nature of QCD and its relation to the partonic structure of hadrons. Finally, we provide a first phenomenological implementation of the HSO approach by extracting TMD distributions relying on low-to-moderate energy Drell-Yan data. The quality and robustness of the results are then compared against higher energy processes like high-Q2 Z0 boson production. Our analysis demonstrates the feasibility of this novel approach and points the way toward the improvements it can achieve in future applications.

Rainaldi, Tommaso [Old Dominion Univ., Norfolk, VA↗
DOE OSTI2026

Understanding spectral dependance of laser-induced damage precursors in dielectric materials (Abbreviated report_23-ERD-006)

High peak and average power laser systems are typically limited by the handling fluence of the optical components. In particular, the multilayer dielectric coatings are known to be much lower operational fluence than the more ideal bulk materials. In this project we proposed and succeeded in probing different established classes of damage prone precursors at different wavelengths to understand their fundamental laser damage response as a function of wavelength. This study helped to shed light on the fundamental physics of the non-linear precursors that govern laser damage phenomena for ns-regime pulsed laser damage. In this study, we utilized the onsite coating capabilities (VPL, IBS coating lab) to purposefully generate laser damage-prone precursors in hafnia-based coatings (both single and multi-layer coatings). Specifically, we engineered coatings with craze lines initiated by nodules, generated coatings with our xenon-based coating process to suppress nanobubble formation and generated hafnia coatings under controlled oxygen flow conditions to study hafnia sub-oxides and oxygen flow dependance. In these studies we found that craze lines are rife with precursors that are sensitive to ultra-violet light but not to infrared light; we found that the removal of nanobubbles helps with all wavelengths tested, but is most impactful for ultra-violet light; we also found that ultra-violet laser damage performance of hafnia is closely matched to oxygen flow rate, while the infrared performance may be slightly better at lower flow rates. During this LDRD we also successfully stood up a new laser damage testing capability, namely a wavelength agile damage test station to study the spectral response of known laser-induced damage precursors. This is a unique and important capability for Lawrence Livermore National Lab, allowing us to understand the spectral response of materials under high intensity irradiation and damage. This is a vital tool to understand non-linear optical response at wavelengths that we have previously been unable to test at.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Origin of Metal-Insulator Transition in Rare-Earth Nickelates

Rare-earth nickelates RNiO3 (R=rare-earth element) undergo coupled structural, metal-insulator, and magnetic changes as temperature is lowered. Because the metal-insulator transition often occurs together with a symmetry-lowering distortion, it is commonly viewed as lattice driven. Here we use QSGW calculations to separate the roles of spin and structure. In the high-symmetry Pbnm phase, imposing spin disproportionation already starts to open an electronic gap, although the undistorted lattice cannot stabilize a full insulating state in both spin channels. In the low-symmetry P21/n phase, removing the spin disproportionation destroys the insulating solution even though the bond disproportionation remains. These tests show that spin disproportionation is the primary electronic driver of gap formation, while structural disproportionation acts as the enabler that allows the inequivalent Ni states to become spatially separated and fully insulating. As an explicit finite-temperature example, machine-learned molecular dynamics for NdNiO3 at 220 K shows that a nominally high-symmetry Pbnm structure dynamically samples local Ni-O bond disproportionation, while retaining Pbnm symmetry on average. This illustrates a general structural channel by which thermal fluctuations in the high-symmetry phase can help stabilize locally spin-disproportionated states.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Experimental and Theoretical Thermokinetic Analysis of the Na 3 VO 4 –CO 2 Reaction System under Different Physicochemical Conditions

Sodium vanadate (Na 3 VO 4 ) was synthesized, structural and microstructurally characterized as well as tested as possible carbon dioxide (CO 2 ) captor through thermodynamic calculations in addition to thermogravimetric dynamic and isothermal analyses. Ceramic structural characterization evidenced the formation of the Na 3 VO 4 crystal phase, while microstructural features evidenced dense agglomerates with a poor specific surface area, although synthesis temperature (600 °C) was not as high as that for other sodium ceramics. Na 3 VO 4 was investigated for the CO 2 capture process through dynamic and isothermal experiments, in the presence or absence of oxygen. All these experiments showed that Na 3 VO 4 possesses interesting CO 2 capture properties in a specific temperature range (520 and 600 °C). Isothermal products characterization allowed to elucidate the reaction pathway, implying the Na 4 V 2 O 7 formation, as possible reactive intermediate. In fact, reaction path evolution was supported with theoretical thermodynamic data. Moreover, the kinetic analysis, performed using the Avrami-Erofeev mathematical model and subsequent thermodynamic data obtention, probed the positive influence of the temperature, in both CO 2 superficial and bulk chemical sorption processes, while oxygen addition did not enhance the superficial process. Additionally, as it would be expected, kinetics were enhanced as a function of the CO 2 concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

AOI [1]: Passive Wireless Sensor Systems Fabricated by Direct-Writing for Temperature and Health Monitoring of Energy Systems in Harsh-Environments (Final Report)

Researchers at West Virginia University (WVU) propose to demonstrate a wireless, high-temperature sensor system for monitoring the temperature and health of energy-system components. The active sensor and electronics for wireless communication will be composed entirely of an electroceramic materials (conductive ceramics) which are capable of withstanding the harsh-environments required for fossil energy-based technologies. This work will focus primarily on the fabrication and testing of temperature (thermocouples and thermistors) and health (strain/stress and crack propagation sensors) that function at extreme temperatures (up to 700-1700ºC). The electronics will accompany the high-temperature sensor, which will include a passive wireless communication circuit that allows the transmission of the data based on the LCR resonance principle to a near-by reader antenna. This passive transmission of data will reduce the need for interconnect wires near the active, and possibly rotating, energy-system component. The research will include process development to permit the 2D/3D direct-writing of the entire sensor and communication circuit onto the energy-system component. The direct-writing will be facilitated by using silicon-based polymer-derived precursors to form the high-temperature, stable electroceramic compositions. In addition, methods for direct-writing the circuit onto a fugitive carrier substrate will be completed, which will permit a “peel-and-stick”-like transfer of the sensor circuit to the energy-system component. This feature will allow the economical and precise placement of the sensor circuit onto components of various shapes and locations, without altering the geometry and active features of the manufactured component, or the removal (or decommissioning) of the component for installation. The proposed work will be directed at the following areas: 1) Investigation of phase formation, sintering/grain growth, and electrical properties of polymer-derived electroceramic composites; 2) Definition of processes to direct-write through ink-jet and robo-casting the polymer-derived electroceramic composites onto oxide and polymer surfaces; 3) Development of methods to form monolithic "peel-and-stick" preforms that will efficiently transfer the sensor circuit to ceramic surfaces after thermal treatment; 4) Design of passive wireless LCR circuits and receiver (reader) antennas for communication and testing at high temperatures; 5) Investigation of the passive wireless sensor system developed (and method of transferring sensor system) for temperature and stress/strain measurements on a SOFC repeat unit and a singular gas turbine blade prototype as example applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Tailored Silicone Network Architecture for Ultimate Mechanical Reinforcement

Hydrosilylation cured silicone elastomers are subject to reaction inefficiency, leading to incomplete and non-uniform crosslink networks, restricting the potential of mechanical reinforcement. This work investigates pre-synthesized, functional PDMS architectures as additives to improve ultimate mechanical performance relative to conventional single-step curing. Three custom, functional structures were prepared: a partially crosslinked PDMS scaffold (Structure A), a bottle-brush PDMS (Structure B), and a star-shaped PDMS derived from an MQ resin (Structure C). Rheological characterization was used to identify the ultimate design space and proper stoichiometric ratio for Structure A, and confirm successful formation of all structures for suitable incorporation into a base silicone formulation at 30wt%. Mechanical tests indicated that all three structures increased in ultimate tensile strength relative to their single-step counterparts, with Structure A providing additional improvements to toughness (432 vs. 258 kJ/m3) and ultimate elongation (158 vs. 115%). Furthermore, Structure B remained very soft in the unfilled state, while Structure C provided hardness (23 vs. 18 Shore A) and stiffness (780 vs. 420 kPa Young’s modulus) increases. In silica filled systems, Structure A retained increased strength but reduced elongation, while Structure B indicated strong reinforcement in terms of strength, toughness, and stiffness. Thermal analysis on the cure profiles of these materials suggested that pre-formation of network architectures enable a more complete reaction than a single-step process (15.9 vs. 15.1 J/g). Ultimately, these results indicate that tailoring PDMS architecture before the final cure can improve ultimate mechanical properties via improved network development in silicone elastomers. Furthermore, this work offers a promising strategy for designing higher-performance, more tunable silicone formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2004

Stacking Multiple Ion Captures in The High Performance Antiproton Trap (HiPAT)

The High performance Antiproton Trap (HiPAT) research project was initiated by the Marshall Space Flight Center's propulsion Research Center to examining the fundamental behavior of low energy antiprotons. Stored antiproton would ultimately be used for experimental demonstration of basic propulsive concepts. Matter-antimatter annihilation produces approximately 10(exp 8) MJ/g nearly 10 orders of magnitude more energy per unit mass than chemical based combustion, hence NASA's interest. To achieve containment, HiPAT utilizes a type of electromagnetic bottle know as a Penning trap positioned within an ultrahigh vacuum test section. Recently, the HiPAT hardware configuration has been enhanced to facilitate the capture of multiple normal matter ion burst. This endeavor is often referred to as "stacking" and used to increasing the number of captured particles. A prior normal matter experimental effort, successfully demonstrated the effectiveness of single burst capture. The stacking process is accomplished by manipulating the electric field generated by the confinement electrodes i.e. adjusting the well potential depth. These potential well values are initially configured to maximize the quantity of captured ions per burst; shallow wells with a depth of 100 volt or less (referenced to the incoming ion beam energy) are typically selected. Once captured, a cooling interval is required to reduce the energy of trapped particles below the lower extent of the "trap door" (or leading electrode) ion emitting potential. This is necessary such that a new burst of hot ions can be introduced while preventing those already inside from escaping. The cooling time is driven by a combination of mechanisms such as synchrotron radiation, background gas scattering, and resistive damping in a time scale on the order of minutes. A potential for reducing this hold period is to actively manipulate the electric field shape, using the power supply control system, to produce a deeper potential well. The trapped ions ride down the morphing well to a lower potential energy, leaving margin to once again cycle the "trap door" capturing a new burst while limiting the number of escaping ions. By adjusting the magnitude and timing of the potential well shaping, subsequent shots from the ion beam can be captured on a time scale shorter then that dictated by the standard inject, capture and cool technique. Currently, experimental tests are under way examining the functionally of this system for stacking multiple ions bursts within the HiPAT system.

Martin, James J.↗
NASA NTRS2014

Controllable Multi-Functional Heat Exchanger for Space Applications

Team Spacering will design SpaceRing, a cooling and waste heat recycling system that addresses NASA’s interest for a cooling and power-generating unit in its prototype deep space habitat[1]. The merits of this system are as follows: - Controllable cooling is critical in maintaining a habitable environment and in the functionality of life support systems, powering electronics and other devices in a spacecraft. - Power is expensive to produce in a space environment. Converting wasted thermal energy into electricity will save energy and money for the space station. Space habitation is a highly complex endeavor. Consequently, the SpaceRing must adhere to additional constraints, which include: - Lack of natural fluid or gas convection due to micro-gravity environment - Limited range for heat source and cold sink temperature - Subject to high fluctuations of incoming thermal energy - Minimal weight due to the high cost of transporting items into space After consulting with NASA and experts in thermal studies, several design objectives were identified and are listed below in order of importance: - High cooling capacity - Reliable safety control and alert system - Maximization of energy generation from wasted heat - Optimization of cooling capability and power generation - Long operational life and minimization of maintenance In space, conventional cooling systems utilize passive heat pipe systems for small-scale heat rejection and pumped pipes with heat exchangers for large-scale heat rejection. Thermal power generation in space is mainly achieved by using thermoelectric material that produces electric energy from temperature differentials. We propose a design that combines cooling and thermoelectric power generation. Using a hot pipe connected to a heat source, a cold pipe connected to a radiator, a heat exchanger in contact with both pipes, and a pump in each pipe to move the fluid, we make an active cooling system. The thermoelectric material is inserted in the heat exchanger between the hot and cold pipes to extract energy from the maximum temperature difference coming from the two pipes. It also provides controllable cooling capacity through the use of the thermoelectric material as cooling modules. We have tested our system under target heat source and sink conditions and measured the temperatures and flow rates. Our preliminary results are promising, demonstrating the output of 25 Watts of power on average. We are in the process of running control tests to compare the heat transfer performance without the thermoelectric generators, which is vital in determining whether or not the generators introduce an unacceptable amount of thermal resistance. While some control tests have been run already, the results have been noisy. We have modified our testing environment and data acquisition methods to allow for simple comparison between the control test results and thermoelectric performance results. Lastly, we have modified the heat exchanger design slightly to include acrylic baffles. This will allow the heat to flow through the heat exchanger more efficiently. We have presented our preliminary results to NASA and will deliver the final product by the end of May 2014.

Lee Xiong↗
DOE OSTI2025

Computational Optimization of 133m Xe Production via Neutron Irradiation in a TRIGA Reactor

Here, the Comprehensive Nuclear-Test-Ban Treaty bans all nuclear tests worldwide. As part of treaty compliance, the concentration of radioactive nuclides in the atmosphere is monitored to detect nuclear weapons tests. Radioactive noble gas fission products, specifically radioxenon, can vent into the atmosphere after a nuclear weapons test, even if the test is well contained underground or underwater. Radioxenon thus serves as a signal for nuclear weapons tests. All atmospheric monitoring systems require samples of radioxenon isotopes for detector calibration, quality control, and certification. Here, we present a novel, improved method for creating samples of 133m Xe via neutron irradiation of 132 Xe in the Washington State University TRIGA reactor. 132 Xe neutron absorption results in either 133 Xe or 133m Xe—thermal neutron absorption results in 133m Xe 12% of the time, while fast neutron absorption (above ~1 MeV) results in 133m Xe ~50% of the time. To optimize the production of 133m Xe via neutron absorption in 132 Xe in the thermal TRIGA reactor, spectral tuning using an irradiation chamber is required to maximize the fraction of fast neutrons being absorbed and minimize the number of thermal neutrons interacting with the 132 Xe. We used MCNP to tally 132 Xe absorptions with the isotopic tally function, flux tallies and neutron attenuation to estimate the number of neutrons reaching the 132 Xe through the irradiation chamber, and the adjoint importance function to improve the source strength estimate. Additionally, we performed a heat transfer analysis for safety considerations. It was determined that the use of a 96% enriched 10 B boron carbide chamber, placed next to the fuel elements in reactor position D8, increases the 133m Xe/ 133 Xe activity ratio from a baseline value of 0.3 to 1.0, a 233% increase. Additionally, it was determined that the alpha heating produced in the boron does not become an unmanageable problem in the Washington State University reactor.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2025

Using leaf and stomatal traits to predict biomass production and water use efficiency in Populus

Climate change is reshaping ecosystems, driving plants to adapt through leaf-trait plasticity that reflects strategies for growth and water use. Predicting biomass production and intrinsic water use efficiency (iWUE) remains challenging because of genetic, taxonomic, and environmental variability. Here, we used eastern cottonwood and Populus hybrids as a model system to test whether easily measurable leaf traits can serve as reliable predictors of performance, and whether adding stomatal and biochemical traits improves predictive power. Across two field sites in Mississippi, leaf mass per area (LMA), biomass production, iWUE, leaf area, and foliar nitrogen ( N %) differed significantly among taxa and sites, while other traits were conserved. Factorial analysis of mixed data (FAMD) revealed distinct clustering of taxa and sites, indicating coordinated variation among leaf and stomatal traits. Pairwise correlations highlighted fundamental trade-offs, with biomass positively related to LMA and petiole length but negatively associated with iWUE, N %, and carbon isotopic ratios (δ 13 C). Leaf temperature and leaf angle varied among taxa and were significantly correlated with LMA and petiole length, suggesting mechanisms of heat dissipation and leaf movability that link simple traits to gas exchange and productivity. Weighted multiple linear regression models explained 80%–91% of variation in biomass production and iWUE. Models using only LMA, petiole length, and stomatal metrics performed nearly as well as those incorporating N %, and δ 13 C, with complex traits adding approximately 10% explanatory power. These results demonstrate that simple morphological traits capture integrated functional trade-offs, while complex traits refine predictions. This tiered approach provides an efficient framework for selecting high-yielding, water-efficient genotypes of Populus and other hardwood species, offering practical pathways to enhance carbon uptake and iWUE under climate change.

biomass production↗
NASA NTRS2019

Lightning Strike Distance Distribution Beyond a Preexisting Lightning Area

The 45th Weather Squadron (45 WS) asked the Applied Meteorology Unit (AMU) to review the 30-year-old, lightning stand-off distances of 5 nautical miles (nmi) for applicability to today's operations. This was based on the realization that previous lightning strike distance studies did not match how 45 WS issues lightning warnings (Roeder, 2008). The previous lightning distance studies were from the point of origin of the lightning or the average starting location that would tend to be in the core of the thunderstorm. However, the 45 WS issues lightning warnings based on the edge of a preexisting lightning area. Before beginning the AMU project, it took several years to develop a method to calculate a distance distribution beyond a preexisting area (Roeder, 2015). The AMU pulled Lightning Detection and Ranging (LDAR) sensor data from 1/1/2013 to 12/31/2013. This dataset consisted of 37 million individual source data points from the LDAR sensors. Only sources within 50 km north, south, east or west of the LDAR grid center were included in the dataset. This limited the use of LDAR data to that with the greatest accuracy of source detection and increased data processing. Points were grouped into flashes based on spatial and temporal criteria. Based on the sensitivity analysis the AMU performed on the flash clustering algorithm, a time value of 0.3 seconds was found to model flashes adequately. Distance parameters were tested from 1,500 to 7,500 meters (m) in 500 m increments. Distance parameters of both 3,000 m and 4,000 m produced results in the plotting tool that were most representative of the physical behavior of lightning. Thus statistics were gathered for the most representative of these spatial and temporal criteria on the flash size and the polygon expansion distance in order to find the correct data distributions. The best fit curves for the LDAR polygon expansion frequency vs. distances for both the 3 kilometer (km) and 4 km distance threshold values were exponential decay functions and had R2 values of > 0.998, indicating good model fits. The equations of the best fit curves were then used to calculate a desired safety radius of 4 nmi for either 3 km or 4 km distance threshold criteria. The AMU analysis concludes the safe reduction of the 5 nmi lightning warning circles to 4 nmi should improve the operational impact by 36% if based on distance from the center of the property area being protected. If based on the edge of the property being protected, then the reduction is 4.5 nmi to 4 nmi and the operational impact is decreased by 21%. For the 6 nmi lightning warning circles, the recommended 4 nmi stand-off distance will result in a safe reduction of operational impact of 31% if based on the center of the area being protected, or 16% if based on the edge of the property.

Flash clustering algorithm↗
NASA NTRS2011

From Paper to Production to Test: An Update on NASA's J-2X Engine for Exploration

The NASA/industry team responsible for developing the J-2X upper stage engine for the Space Launch System (SLS) Program has made significant progress toward moving beyond the design phase and into production, assembly, and test of development hardware. The J-2X engine exemplifies the SLS Program goal of using proven technology and experience from more than 50 years of United States spaceflight experience combined with modern manufacturing processes and approaches. It will power the second stage of the fully evolved SLS Program launch vehicle that will enable a return to human exploration of space beyond low earth orbit. Pratt & Whitney Rocketdyne (PWR) is under contract to develop and produce the engine, leveraging its flight-proven LH2/LOX, gas generator cycle J-2 and RS-68 engine capabilities, recent experience with the X-33 aerospike XRS-2200 engine, and development knowledge of the J-2S tap-off cycle engine. The J- 2X employs a gas generator operating cycle designed to produce 294,000 pounds of vacuum thrust in primary operating mode with its full nozzle extension. With a truncated nozzle extension suitable to support engine clustering on the stage, the nominal vacuum thrust level in primary mode is 285,000 pounds. It also has a secondary mode, during which it operates at 80 percent thrust by altering its mixture ratio. The J-2X development philosophy is based on proven hardware, an aggressive development schedule, and early risk reduction. NASA Marshall Space Flight Center (MSFC) and PWR began development of the J-2X in June 2006. The government/industry team of more than 600 people within NASA and PWR successfully completed the Critical Design Review (CDR) in November 2008, following extensive risk mitigation testing. Assembly of the first development engine was completed in May 2011 and the first engine test was conducted at the NASA Stennis Space Center (SSC), test stand A2, on 14 July 2011. Testing of the first development engine will continue through the autumn of 2011, be paused for test stand modifications to the passive diffuser, and then restart in the spring of 2012. This testing will be followed by specialized powerpack testing intended to examine the design and operating margins of the engine turbomachinery. The development plan beyond this point leads through more system-level, engine testing of several samples, analytical model validation activities, functional and performance verification, and then ultimate certification to support human spaceflight. This paper will discuss the J-2X development background, provide top-level information on design and development planning, and will explore some of the development challenges and mitigation activities pursued to date.

Kynard, Michael↗
DOE OSTI2025

Engineering PdAu/CeO 2 Alloy/Oxide Interfaces for Selective Methane‐to‐Methanol Conversion with Water

The direct conversion of methane-to-methanol remains a critical challenge in methane valorization. In this study, we unveil the crucial role of PdAu/CeO 2 catalysts in enabling selective methane transformation under mild conditions, using only water as the sole oxidant. Through a combination of experimental techniques, including XPS and catalytic testing, alongside density functional theory (DFT) calculations, we demonstrate that a Pd 0.3 Au 0.7 /CeO 2 catalyst, which predominantly exposes isolated Pd atoms, achieves remarkable methanol selectivity (∼80%) at 500 K with a 1:1 methane-to-water ratio. While Pd/CeO 2 efficiently activates methane, its tendency for overreaction leads to complete methanol decomposition, thereby limiting selectivity. Alloying Pd with Au on ceria mitigates this over-reactivity, preventing methanol degradation while maintaining sufficient catalytic activity. The PdAu/CeO 2 composite exhibits a synergistic effect: Pd in contact with the ceria support facilitates methane activation and water dissociation, while Au fine-tunes reactivity to promote methanol formation. DFT calculations confirm that isolated Pd sites at the PdAu/CeO 2 interface play a key role in balancing activity and selectivity. This work underscores the importance of alloy/oxide interfaces in controlling selective methane conversion with water and offers valuable insights for designing highly efficient catalysts for methanol synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗