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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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824 records · Page 36

All sources NASA NTRS DOE OSTI

NASA NTRS2019

Rewet Temperature Correlations for Liquid-Nitrogen Boiling Pipe Flows Across Varying Flow Conditions and Orientations

In many convective liquid-vapor phase change heat transfer engineering applications, cryogenic fluids are widely used in industrial processes, spacecraft and cryosurgery systems, and so on. For example, cryogens are usually used as liquid fuels such as liquid hydrogen and oxygen in the rocket industry, liquid nitrogen (LN2) and helium are frequently used to cool superconducting magnetic device for medical applications. In these systems, proper transport, handling, and storage of cryogenic fluids are of extreme importance. Among all the cryogenic transport processes performed in room temperatures, quenching, also termed chilldown, is a unavoidable initial, transient phase-change heat transfer process that brings the system down to the cryogenic condition. The Leidenfrost temperature or rewet temperature that signals the end of film boiling is practically considered the completion point of a quenching process. Therefore, rewet temperature has been considered the most important parameter for the engineering design of cryogenic thermal management systems. As most of the previous correlations for predicting the Leidenfrost temperature and the rewet temperature have been basically developed for water, they are shown to disagree with recent liquid nitrogen pipe chilldown experiments in upward and downward flow directions over a wide range of flow rates, pressures, and degrees of inlet subcooling. In addition to a complete review of the literature, two new correlations are presented in this work, one based on bubble growth and another based on the theoretical maximum limit of superheat. Each correlation performs well over the entire data set.

liquid nitrogen↗

DOE OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Thermal-Fluid Analysis of a Liquid-Cooled Battery Module for Electrified Aircraft

The development of safe, energy-dense batteries is critical to advancing hybrid electric and fully electrified aircraft propulsion. Achieving this capability requires a thermal management system that can maintain battery performance and safety under demanding operational conditions. The objective of this project is to support the maturation of next-generation lithium-ion batteries for electrified aircraft by conducting performance testing on integrated battery modules, specifically a 2-cell series configuration module housed within an aluminum enclosure. Designed to operate at a nominal 7.2 V with discharge rates up to 2.5C, the module will eventually be used to power an electric motor and DC-DC converter, generating substantial thermal loads that must be effectively managed to increase the usable energy and power density of electrified aircraft. To address these thermal challenges, this study presents the development and thermal-fluid analysis of a liquid-cooled thermal management system. While the full aircraft architecture utilizes an eight-string configuration, the present work evaluates a representative single-string water coolant loop to characterize baseline performance. The active cooling loop circulates water through a reservoir, pump, the battery module, and a variable area flow meter. Key performance metrics including component-level temperatures, mass flow rates, and pressure drops are quantified across the loop. Across discharge rates ranging from 0.5C to 2.5C, the active thermal loop consistently and effectively removed heat from the module, validating the design approach and confirming readiness for further development. The validated thermal performance indicates a path toward scalable battery modules that could enable energy and power dense systems for hybrid electric aircraft.

Electrified Aircraft↗

NASA NTRS1977

The Effect of Temperature and Pressure on the Distribution of Iron Group Elements Between Metal and Olivine Phases in the Process of Differentiation of Protoplanetary Material

The distribution patterns of Ni, Co, Mn, and Cr were studied in olivines of various origins: from meteorites (chondrites, achondrites, pallasites), which are likely analogs of the protoplanetary material, to peridotite inclusions in kimberlite pipes, which are analogs of mantle material. According to X-ray microanalysis data, each genetic group of olivines is characterized by a specific concentration of these elements. Nickel is concentrated (up to 0.34 percent) in peridotite olivines, while manganese is concentrated in meteoritic olivines. The maximum chromium content (0.2 percent) was found in ureilites, which were formed under reducing conditions. Experiments at pressures of 20 to 70 kbar and temperatures of 1100 to 2000°C have shown that in a mixture of olivine and Ni metal or NiO nickel enters the silicate phase (up to 4 percent), displacing Fe into the metallic phase. Equilibrium temperatures were estimated from the Fe, Ni distribution coefficients between the metal and olivine: 1500 K for pallasites, 1600 K for olivine-bronzite H6 chondrites, 1200 K for olivine-hypersthene L6, 900 K for LL6, and 1900 K for ureilites (at P = 1 atm). The equilibrium conditions of peridotites are close to T = 1800 K and P over 100 kbar. The distribution patterns of the transition elements are explained on the basis of physical-chemical properties. It is concluded that there is a sharp difference between the conditions of differentiation of the protoplanetary material at the time meteorites were formed and the conditions of differentiation of the planets into concentric layers.

A P Vinogradov↗

NASA NTRS1967

Guidelines for Schlieren Systems at Langley Research Center

The original Langley Working Paper (LWP 448) published on July 27th, 1967, provided guidance to NASA Langley Research Center personnel on how to set up conventional path-integrated schlieren flow visualization systems and what pitfalls could be expected with such setups. The guidance and information contained in the document continues to be used for schlieren setups at NASA Langley Research Center to this day. The most commonly used method of flow visualization in supersonic wind tunnels is the schlieren method, or method of striae. At the Langley Research Center, this method is so commonly used that it has come to be regarded somewhat as merely another piece of instrumentation which is to be maintained by service people, and which is too mysteriously complicated to be touched by tunnel personnel. This should not be the case. High-quality results from a schlieren system can only be obtained by having personnel on the tunnel staff who are well-informed on the subject and who have the time and the interest to do a good job of adjustment. This paper is a discussion in practical terms, of some of the points to be considered and the pitfalls that may be encountered in designing, setting up and using a working schlieren system. It is directed specifically toward helping specify and install a Z-type mirror system. It is hoped that the material will be of assistance to facilities throughout the Center and NASA and that users of the schlieren method will be inspired to the point of training people in the adjustment of the systems in use at their facilities.

Langley Working Papers↗

DOE OSTI2024

Mitigating Sodium Ordering for Enhanced Solid Solution Behavior in Layered NaNiO 2 Cathodes

The O-type layered nickel oxides suffer from undesired cooperative Jahn–Teller distortion stemming from Ni 3+ ions and undergo multiple biphasic structural transformations during the insertion/extraction of large Na + ions, posing a significant challenge to stabilize the structural integrity. We present here a systematic investigation of the impact of substituting 5 % divalent (Mg 2+ ) or trivalent (Al 3+ or Co 3+ ) ions for Ni 3+ to alleviate Na + ion ordering and perturb the Jahn–Teller effect to enhance structural stability. Here, we gauge a fundamental understanding of the Mg−O and Na−O or Mg−O−Na bonding interactions, noting that the ionicity of the Mg−O bond deshields the electronic cloud of oxygen from Na + ions. Furthermore, calculations of the Van Vleck distortion modes reveal a relaxation of NiO 6 octahedra from Jahn–Teller distortion and a reduced electron density at the interlayer with Mg 2+ substitution. Long-range (operando X-ray diffraction) and short-range (magic angle spinning nuclear magnetic resonance) structural analyses provide insights into reduced ordering, allowing a stable continuous solid solution. Overall, Mg-substitution results in a high-capacity retention of ~96 % even after 100 cycles, showcasing the potential of this strategy for overcoming the structural instabilities and enhancing the performance of sodium-ion batteries.

25 ENERGY STORAGE↗

DOE OSTI2026

Best Practices for Resilience Hub Development and Management

The Carbon League and its community partners in East St. Louis, Illinois, have identified five facilities to serve as resilience hubs. These hubs are intended to support the local community through a range of services and resources during blue-sky (everyday), gray-sky (pre-event), and black-sky (emergency) conditions. Transforming these facilities into fully functional resilience hubs requires a broad operational improvement and programmatic planning roadmap. This memo outlines best practices to guide the development of these resilience hubs in East St. Louis, including recommendations for infrastructure services; safety and physical protection; community services; operational protocols; and a phased implementation strategy aligned with realistic funding and capacity constraints. Infrastructure recommendations include strengthening electric power, communications, water, sanitation, and transportation/logistics capabilities, all of which are essential for hubs that may serve as cooling and warming centers, distribution points, and information hubs during emergencies. Safety recommendations focus on accessibility, emergency action planning, indoor air quality, and secure storage of critical equipment. A phased roadmap provides guidance from immediate, low-cost readiness actions to long-term optimization and community integration. Performance metrics and maintenance protocols ensure continuous improvement and operational readiness. This guidance draws on best practices that can be used to support the development of resilient, community-centered hubs capable of enhancing public safety, health, and well-being during everyday operations and emergencies alike.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Dynamic Diketoenamine Crosslinking Unlocks Vinyl Polymer Vitrimers From β ‐Triketone Chemistry

Covalent adaptable networks (CANs) offer a compelling strategy to unite the mechanical robustness of thermosets with the reprocessability of thermoplastics, yet achieving simultaneous durability, processability, and true recyclability remains challenging. We introduce diketoenamine (DKE) vitrimers derived from β-triketone methacrylate monomers and demonstrate how rational monomer design dictates network processability, viscoelasticity, and recyclability. By systematically varying the spacer length between the β-triketone (TK) moiety and the polymer backbone, we identify a key structure–property relationship that dictates vitrimer behavior. Networks bearing TK pendants minimally displaced from the backbone suppress creep but exhibit limited stress relaxation, whereas extended spacers yield lower glass transition temperatures, higher effective crosslink densities, and efficient stress dissipation, enabling optical transparency and reprocessability. Extending this platform to ultra-high molecular-weight prepolymers introduces physical entanglements as secondary crosslinks, further enhancing dimensional stability without compromising processability. Both mechanical and chemical recycling validate the closed-loop circularity of these materials. Furthermore, these results establish TK methacrylates as a versatile platform for designing high-performance vitrimers that integrate durability, reprocessability, and true closed-loop recyclability.

closed-loop recyclability↗

DOE OSTI2026

Characterization of Flashback and Flame-Holding in a Jet-in-Crossflow Mixing Configuration With Methane–Hydrogen Fuel Blends

An approach that combines experimental and numerical analyses has been implemented to characterize the fundamentals of flashback events and flame-holding phenomena during high-hydrogen combustion in a jet-in-crossflow (JICF) configuration. Such flame dynamics are visualized experimentally using nanosecond (ns)-based hydroxyl planar laser-induced fluorescence (OH-PLIF) and chemiluminescence diagnostics techniques. The JICF burner has an optically accessible premixing tube allowing the optical diagnostics. The testing was conducted for varied premixer velocities (V) and equivalence ratio (ϕ) for 90–100% (H 2 , by mole) H 2 /CH 4 reactant mixtures at atmospheric temperature and pressure conditions. Two distinct flashback events were identified – conventional rich flashback and lean flashback, recorded while increasing ϕ and decreasing ϕ, respectively. The cause of lean flashback was attributed to lower momentum flux ratio which bends the jet sharply, closer toward the injection plane. The mean OH-PLIF images characterized the flame-holding behavior, where the flame was found to be stabilized on the leeward side only or on both windward and leeward sides as a lifted flame near the fuel port. A large eddy simulation (LES) with detailed chemistry combustion modeling approach was implemented along with an OH* submechanism, and it showed qualitative agreement with the integrated line-of-sight chemiluminescence results as well as the planar OH-PLIF measurements.

chemiluminescence diagnostic↗

DOE OSTI2026

Quality and Loss Factor Characterization of YBCO Superconducting Transmission Lines for Axion Dark Matter Detection

Axion haloscope experiments aim to detect the conversion of axions into microwave photons under a strong magnetic field through resonant cavity techniques. The conversion produces an extremely small signal, requiring a cryogenic environment to reduce thermal noise, and low-loss superconducting transmission lines for minimal attenuation in the readout chain. Yttrium barium copper oxide (YBCO) cables are a promising candidate. Unlike commonly used low-loss cryogenic cables such as niobium (Nb) and niobium titanium (NbTi), which have low critical fields, YBCO is a high-temperature superconductor that can remain stable in strong magnetic fields. We characterized the quality and loss of five stripline resonators from the Brookhaven Technology Group: three YBCO, a copper reference, and a silver reference. Experimental methodology included collecting scattering parameter data on a vector network analyzer for the samples at 77 K along with room temperature baseline measurements, and employing both Lorentzian-fit and circle-fitting techniques to confirm the coupling regime and corroborate results. We achieved quality factors on the order of $10^3$ with corresponding loss factors on the order of $10^{-1}$ dB/m. Trends were comparable with literature data on Nb and NbTi at 4 K, which did have lower loss under these conditions, but suggested similar or perhaps better loss for YBCO when accounting for the temperature difference. We also developed a cryogenic probe for future measurements in a 14 T applied field at 30 mK. This will serve to directly evaluate YBCO's durability in magnetic fields, and we expect significantly improved performance at millikelvin temperatures.

Marinos, Z. [UCLA]↗

DOE OSTI2026

Carbon source–driven metabolic and regulatory remodeling defines phenomic states in Lipomyces starkeyi

Lipomyces is a genus of oleaginous yeasts with potential for contributing to reliable biomanufacturing supply chains. However, progress in advanced strain designs and engineering efforts are still constrained by a lack of understanding of the underlying molecular drivers of Lipomyces phenotypes. To address this gap, we collected a suite of multi-omic data to dissect how carbon source availability reshapes the metabolic network, lipid allocation, and regulatory architecture of Lipomyces starkeyi. We observed that glucose promotes biosynthetic and proliferative processes supported by abundant energy and carbon intermediates, xylose enhances redox-balancing mechanisms centered on the pentose phosphate pathway, and glycerol activates respiratory metabolism, ß-oxidation, and the glyoxylate cycle. Lipid species distributions remained consistent in both nitrogen replete and depleted conditions across the carbon sources, indicating robust production mechanisms. Regulatory protein identification and network analysis revealed glycerol-driven respiratory growth favors regulatory programs integrating stress tolerance, redox balance, and lipid-associated metabolism, whereas xylose growth activates compensatory transcriptional responses aimed at maintaining mitochondrial function. Nitrogen limitation modulates the strength of these responses but does not fundamentally alter their direction, reinforcing carbon source as the dominant driver of regulatory architecture. Taken together, this data enhances the understanding of Lipomyces molecular rearrangements and provides a foundation for further development of predictive phenotypic tools in this genus.

Biotechnology↗

DOE OSTI2026

Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling

The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.

09 BIOMASS FUELS↗

DOE OSTI2026

Plasma flow generation and particle acceleration from expanding magnetic bubbles

Impulsive plasma dynamics in the laboratory are often driven by rising electric currents, yet their quantitative plasma response has not been well established. By means of fully kinetic particle-in-cell simulations and laser-driven capacitor-coil experiments, we show that a rising current expels plasma, forming an expanding magnetic bubble and accelerating particles. The expansion front velocity scales with the Alfvén speed determined by the magnetic field at its inner edge and the plasma density at its outer edge. This mechanism establishes impulsive current drive as a fundamental way that generates plasma flows and accelerates particles in laboratory plasmas, with potential relevance to astrophysics.

Zhang, Yang [Princeton University, NJ (United Stat↗

DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗

NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗

NASA NTRS2024

Artemis I Orion ESM Propulsion System Engine Performance

NASA's Orion spacecraft transports humans and cargo into cislunar space for the Artemis program. The European Service Module (ESM), supplied by ESA and its European industry partners, provides Orion with power and in-space propulsion. The Orion-ESM propulsion system is a bipropellant hypergolic propulsion system using monomethyl hydrazine (MMH) and nitrogen tetroxide (MON-3). Primary translational propulsion is provided by the Orbital Maneuvering System Engine(OMS-E), with backup translational propulsion provided by eight Auxiliary thrusters (AUX). Attitude control and small translational maneuvers are provided by twenty four Reaction Control System (RCS) engines. The 2022 Artemis I mission was the first integrated flight test of the Orion-ESM spacecraft and its propulsion system. The OMS-E used on Artemis I was a refurbished Space Shuttle OMS-E that previously flew on nineteen missions ranging from STS-41G in 1984 to STS-112 in 2002. The Auxiliary engines are modified Aerojet Rocketdyne R4D-11 engines produced specifically for the Orion program. The RCS engines are Ariane Group engines originally used for the Automated Transfer Vehicle (ATV) program. This paper will discuss the unique operational requirements for each engine on Orion and the development and qualification effort sat both the engine and system-level that were completed to enable a successful Artemis I mission. Next the paper will evaluate the in-flight performance of the engines during the Artemis I mission showing nominal performance as expected. Additionally, comparisons to models will be presented showing very good correlation. Finally, the paper will address the plan for the engines on future Orion missions and the evolution of the system operation.

Liquid Propulsion Systems↗

NASA NTRS2024

Artemis I Orion ESM Propulsion System Engine Performance

Reuse↗

DOE OSTI2026

SODAs: sparse optimization for the discovery of differential and algebraic equations

Differential-algebraic equations (DAEs) integrate ordinary differential equations (ODEs) with algebraic constraints, providing a fundamental framework for developing models of dynamical systems characterized by time-scale separation, conservation laws and physical constraints. While sparse optimization has revolutionized model development by allowing data-driven discovery of parsimonious models from a library of possible equations, existing approaches for dynamical systems assume DAEs can be reduced to ODEs by eliminating variables before model discovery. This assumption limits the applicability of such methods for DAE systems with unknown constraints and time scales. We introduce sparse optimization for differential-algebraic systems (SODAs), a data-driven method for the identification of DAEs in their explicit form. By discovering the algebraic and dynamic components sequentially without prior identification of the algebraic variables, this approach leads to a sequence of convex optimization problems. It has the advantage of discovering interpretable models that preserve the structure of the underlying physical system. To this end, SODAs improves since SODAs is singular numerical stability when handling high correlations between library terms, caused by near-perfect algebraic relationships, by iteratively refining the conditioning of the candidate library. We demonstrate the performance of our method on biological, mechanical and electrical systems, showcasing its robustness to noise in both simulated time series and real-time experimental data.

DAE↗