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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 1,063 records · Page 59

An Approach to Evaluating the Impact of Small-Core Turbofan Technologies on Engine and Aircraft Performance

NASA’s Hybrid Thermally Efficient Core (HyTEC) project aims to accelerate the development of small-core turbofan engine technologies to enable a fuel burn reduction of 5 to 10 percent for next-generation aircraft, compared to 2020s best-in-class technology. This paper presents a demonstration of methods for evaluating the potential performance impact of small-core engine technologies developed under Phase 1 of the HyTEC project. The approach involves model-based systems analysis, where small-core innovations are integrated into baseline turbofan and aircraft systems models, creating a notional vision system. Performance of the vision system is examined at both the engine and vehicle level. The examined performance metrics include: engine bypass ratio, overall pressure ratio, high pressure compressor exit corrected mass flow, and aircraft fuel burn. The CFM LEAP-1B28 and Boeing 737 MAX 8 are chosen as the baseline state-of-the-art systems. Preliminary results map a design space for the small-core vision system and quantify the distinct effects of technologies on the key metrics.

Michael A Bennett↗

An Approach to Evaluating the Impact of Small-core Turbofan Technologies on Engine and Aircraft Performance

NASA’s Hybrid Thermally Efficient Core (HyTEC) project aims to accelerate the development of small-core turbofan engine technologies to enable a fuel burn reduction of 5 to 10 percent for next-generation aircraft, compared to 2020s best-in-class technology. This paper presents a demonstration of methods for evaluating the potential performance impact of small-core engine technologies developed under Phase 1 of the HyTEC project. The approach involves model-based systems analysis, where small-core innovations are integrated into baseline turbofan and aircraft systems models, creating a notional vision system. Performance of the vision system is examined at both the engine and vehicle level. The examined performance metrics include: engine bypass ratio, overall pressure ratio, high pressure compressor exit corrected mass flow, and aircraft fuel burn. The CFM LEAP-1B28 and Boeing 737 MAX 8 are chosen as the baseline state-of-the-art systems. Preliminary results map a design space for the small-core vision system and quantify the distinct effects of technologies on the key metrics.

Michael Bennett↗

Annealing of ion tracks in apatite under pressure characterized in situ by small angle x-ray scattering

Fission track thermochronology is routinely used to investigate the thermal history of sedimentary basins, as well as tectonic uplift and denudation rates. While the effect of temperature on fission track annealing has been studied extensively to calibrate the application of the technique, the effect of pressure during annealing is generally considered to be negligible. However, a previous study suggested elevated pressure results in a significantly different annealing behaviour that was previously unknown. Here, we present a method to study track annealing in situ under high pressure by using synchrotron- based small angle x-ray scattering (SAXS). To simulate fission tracks in a controlled environment, ion tracks were created in apatite from Durango, Mexico using 2 GeV Au or Bi ions provided by an ion accelerator facility. Samples were annealed at 250°C at approximately 1 GPa pressure using diamond anvil cells (DAcs) with heating capabilities. Additional in situ annealing experiments at ambient pressure and temperatures between 320 and 390°C were performed for comparison. At elevated pressure a significantly accelerated annealing rate of the tracks was observed compared with annealing at ambient pressure. However, when extrapolated to geologically relevant temperatures and pressures, the effects become very small. The measurement methodology presented provides a new avenue to study materials behaviour in extreme environments.

58 GEOSCIENCES↗

Correlating Surface Processing of Nb Superconducting RF Cavities with the Evolution of Surface Electronic States

Superconducting-radio frequency (RF) cavities provide an efficient way to accelerate particle beams with extremely high acceleration gradients while generating very small power dissipation. The few nanometers of the surface play a critical role in defining the RF performance of superconducting Nb based cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in superconducting cavity performance by simultaneously achieving high quality factors with increasing maximum acceleration gradients. These processing approaches include chemical polishing, distinct multi-step thermal treatments under ultra-high vacuum (UHV) conditions over low to high temperature regimes, as well as high-temperature treatments under controlled nitrogen atmospheres. Beyond their macroscopic impact on RF performance, these methods produce distinct surface oxide configurations characterized by different valence states, oxide thicknesses, chemical uniformity, and oxygen concentration profiles extending into the near-surface bulk of niobium. In this work, we are trying to understand how the surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity. Using a combination of X-ray photoemission and X-ray absorption spectroscopies, we investigate how the valence-band structure and the electronic density of states (DoS) near the Fermi level evolve under different surface treatments. By employing tunable photon energies across multiple elemental absorption edges, we use resonant photoemission to disentangle and identify the elemental contributions to specific valence-band features. Our observations show that different surface-processing methods lead to distinct temperature evolutions of the DoS and valence-band states near the Fermi level. Our results suggest variations in different Nb-O orbital hybridizations in distinct processes and point towards the possibility of different underlying mechanisms of superconductivity governed by surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in superconducting RF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of superconducting RF cavities.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

Experimental Investigation on Heating Performance of a Cold Climate Thermoelectric-Assisted Heat Pump

To accelerate the electrification of air source heat pumps (ASHPs) in cold climates across the United States, various initiatives have been launched to enhance the effectiveness of ASHPs. One avenue of research involves incorporating thermoelectric (TE) technology into vapor compression refrigeration cycles. This study aims to assess the heating performance of a cold climate ASHP by employing TE modules as a liquid line subcooler. The tested system is a nominal 4.5-ton split heat pump utilizing R410A, equipped with a scroll compressor and an accumulator. An electronic expansion valve was employed for both cooling and heating modes. Two configurations of TE sub-coolers, one utilizing 2 TE bundles and the other 4 TE bundles, were integrated into the liquid line of the tested system. The heating performance of these configurations was evaluated. The results revealed that activating the TE subcooler led to a notable increase in total heat capacity, reaching 1318 W at -15.0 °C and 1164 W at -19.0 °C. The corresponding TE coefficients of performance (COPs) were 1.76 and 1.63, respectively. The activation of the TE sub-cooler resulted in a slight reduction in the overall system COP, with a decrease ranging from -2.6% to -4.2% for these two temperatures. The system COPs were measured at 2.10 and 1.86 for -15.0 °C and -19.0 °C, respectively. This prototype demonstrated a significant augmentation in heating capacity with a minimal sacrifice in COP.

Hu, Yifeng↗

Sensitivity of Force Specifications to the Errors in Measuring the Interface Force

Force-Limited Random Vibration Testing has been applied in the last several years at NASA/GSFC for various programs at the instrument and system level. Different techniques have been developed over the last few decades to estimate the dynamic forces that the test article under consideration will encounter in the operational environment. Some of these techniques are described in the handbook, NASA-HDBK-7004, and the monograph, NASA-RP-1403. A key element in the ability to perform force-limited testing is multi-component force gauges. This paper will show how some measurement and calibration errors in force gauges are compensated for w en tie force specification is calculated. The resulting notches in the acceleration spectrum, when a random vibration test is performed, are the same as the notches produced during an uncompensated test that has no measurement errors. The paper will also present the results of tests that were used to validate this compensation. Knowing that the force specification can compensate for some measurement errors allows tests to continue after force gauge failures or allows dummy gauges to be used in places that are inaccessible.

Worth, Daniel↗

Product Reliability Trends, Derating Considerations and Failure Mechanisms with Scaled CMOS

As microelectronics is scaled into the deep sub-micron regime, space and aerospace users of advanced technology CMOS are reassessing how scaling effects impact long-term product reliability. The effects of electromigration (EM), time-dependent-dielectric-breakdown (TDDB) and hot carrier degradation (HCI and NBTI) wearout mechanisms on scaled technologies and product reliability are investigated, accelerated stress testing across several technology nodes is performed, and FA is conducted to confirm the failure mechanism(s).

CMOS integrated circuits↗

Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis

Domain-specific designs offer greater energy efficiency and performance gain than general-purpose processors. For this reason, modern system-on-chips have a significant portion of their silicon area with custom accelerators. However, designing hardware by hand is laborious and time-consuming, given the large design space and the performance, power, and area constraints that are not realized in the software. Moreover, domain-specific algorithms (e.g., machine learning models) are evolving quickly, challenging the accelerator design further. To address these issues, this paper presents SODA Synthesizer, an automated open-source high-level ML framework to Verilog modular compiler targeting AI/ML Application-Specific Integrated Circuits (ASICs) accelerators. SODA tightly couples the Multi- Level Intermediate Representation (MLIR) compiler infrastructure [24] and open-source HLS approaches. Thus, SODA can support various ML frameworks and algorithms and can perform optimizations that combine specialized architecture templates and conventional HLS to generate the hardware modules. In addition, SODA’s closed-loop design space exploration (DSE) engine allows developers to perform end-to-end design space explorations on different metrics and technology nodes.

Zhang, Jeff↗

Operator-level quantum acceleration of non-logconcave sampling

Sampling from probability distributions of the form 𝝈 ∝ e −𝜷V , where V is a continuous potential, is a fundamental task across physics, chemistry, biology, computer science, and statistics. However, when V is nonconvex, the resulting distribution becomes non-logconcave, and classical methods such as Langevin dynamics often exhibit poor performance. We introduce a quantum algorithm that provably accelerates a broad class of continuous-time sampling dynamics. For Langevin dynamics, our method encodes the target Gibbs measure into the amplitudes of aquantum state, identified as the kernel of a block matrix derived from a factorization of the Witten Laplacian operator. This connection enables Gibbs sampling via singular value thresholding and yields up to a quartic quantum speedup over best-knownclassical Langevin-based methods in the non-logconcave setting. Building on this framework, we further develop the first quantum algorithm that accelerates replica exchange Langevin diffusion, a widely used method for sampling from complex, rugged energy landscapes.

97 MATHEMATICS AND COMPUTING↗

Scalable, low-cost ink-based processing of high-performance silver selenide thermoelectrics

The growing global energy demand and its accelerating contribution to climate change emphasize the urgent need for sustainable energy conversion/harvesting technologies. Thermoelectric (TE) devices offer a compelling route to directly convert waste heat into electricity and enable solid-state cooling without moving parts or harmful refrigerants. Achieving their full potential requires not only higher TE performance (zT) but also scalable, low-cost manufacturing processes. Here, we introduce a transformative ink-based processing approach for scalable manufacturing of high-performance silver selenide-based TE materials and devices. Using a simple, high-throughput ink-mixing and blade coating strategy, our Ag 2 Se-based materials under the optimized composition and processing conditions yield an ultrahigh room-temperature power factor of 2.8 mW m −1 K −2 , over 100% higher than baseline samples and a reproducible figure of merit zT of 1 at room temperature. A thermoelectric generator (TEG) achieves a very competitive power density of 112 mW cm −2 at a 90 °C temperature difference between the hot and cold sides of the device, which is among the highest reported for silver selenide-based TE devices to date. This facile, scalable ink-based processing establishes a practical pathway toward industrial-scale manufacturing and widespread adoption of thermoelectric devices, advancing sustainable energy technologies.

Bappy, Md. Omarsany [University of Notre Dame, IN ↗

Representations and strategies for transferable machine learning improve model performance in chemical discovery

Strategies for machine-learning (ML)-accelerated discovery that are general across material composition spaces are essential, but demonstrations of ML have been primarily limited to narrow composition variations. By addressing the scarcity of data in promising regions of chemical space for challenging targets such as open-shell transition-metal complexes, general representations and transferable ML models that leverage known relationships in existing data will accelerate discovery. Over a large set (~1000) of isovalent transition-metal complexes, we quantify evident relationships for different properties (i.e., spin-splitting and ligand dissociation) between rows of the Periodic Table (i.e., 3d/4d metals and 2p/3p ligands). We demonstrate an extension to the graph-based revised autocorrelation (RAC) representation (i.e., eRAC) that incorporates the group number alongside the nuclear charge heuristic that otherwise overestimates dissimilarity of isovalent complexes. To address the common challenge of discovery in a new space where data are limited, we introduce a transfer learning approach in which we seed models trained on a large amount of data from one row of the Periodic Table with a small number of data points from the additional row. We demonstrate the synergistic value of the eRACs alongside this transfer learning strategy to consistently improve model performance. Analysis of these models highlights how the approach succeeds by reordering the distances between complexes to be more consistent with the Periodic Table, a property we expect to be broadly useful for other material domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First Experience with Liquid Nitrogen Cleaning

Field emission caused by microscopic particulate contamination is a limiting factor for the performance of superconducting RF (SRF) cavities. In an SRF based accelerator, particulates may be transported over the surface of an operational SRF cavity, becoming field emitters and consequentially degrading the performance of the SRF cavity. The most commonly used method for removing particulates from cavity surfaces is high-pressure ultra-pure water rinsing. We are developing a novel high-pressure liquid nitrogen cleaning technique that may possibly enable superior cleaning power and particulate removal from cavities in a cryomodule without taking apart the cryomodule components. This technique provides cleaning mechanisms beyond what are accessible by its high-pressure water rinsing counterpart and leaves no residues on the cleaned surface.

Ruber, R.J.M.Y.↗

An 8-cm ion thruster characterization

The performance of the Ion Auxiliary Propulsion System (IAPS) thruster was increased to thrust T = 32 mN, specific impulse I sub sp = 4062 s, and thrust-to-power ratio T/P = 33 mN/kW. This performance was obtained by increasing the discharge power, accelerating voltage, propellant flow rate, and chamber magnetic field. Adding a plenum and main vaporizer for propellant distribution was the only major change required in the thruster. The modified thruster characterization is presented. A cathode magnet assembly did not improve performance. A simplified power processing unit was designed and evaluated. This unit decreased the parts count of the IAPS power processing unit by a factor of ten.

Wessel, F. J.↗

Atomic- and Molecular-Scale Interphase Engineering for High-Performance Solid-State Batteries

Solid-state batteries (SSBs) promise a decisive advance beyond conventional Li-ion systems, yet their development remains constrained by persistent solid–solid interfacial instabilities that degrade performance and durability. Interfaces between solid electrolytes and both cathodes and Li metal often exhibit poor wettability, limited physical contact, and high charge–transfer resistance, leading to chemical decomposition, mechanical failure, and impedance growth. Overcoming these limitations requires interphase engineering with atomic-scale precision—capabilities that conventional coating methods cannot reliably deliver. Atomic layer deposition (ALD) and molecular layer deposition (MLD) uniquely meet this need by enabling ultrathin, conformal, and composition-tunable films that stabilize reactive surfaces, suppress parasitic reactions, and regulate Li-metal morphology. Importantly, this Perspective highlights ALD/MLD systems that have already demonstrated effectiveness in liquid-electrolyte cells and discusses how these validated strategies can be deliberately translated to solid-state architectures. By grounding future directions in experimentally proven concepts rather than speculative hypotheses, we outline how atomic- and molecular-scale design principles can accelerate the development of robust, high-performance SSB technologies.

atomic and molecular layer deposition↗

AMReX: Block-structured adaptive mesh refinement for multiphysics applications

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

Zhang, Weiqun↗

Demonstration of a tandem lens for producing shaped laser-ionized plasmas for plasma wakefield acceleration

We demonstrate a tandem lens optical setup, comprising two diffractive optics, that focuses a high-power ultrafast laser with a shaped on-axis intensity profile, producing a meter-long Bessel focus. The intended use of the optical setup is to produce a laser-ionized plasma source for plasma wakefield acceleration. By controlling the on-axis intensity, the density profile of the plasma ramps at the entrance and exit of the plasma can be tailored to optimize the matching of the electron beam into the plasma. In addition to demonstrating the optical system, we describe the algorithm used to calculate the lens phases and present detailed calculations of the lenses’ expected performance.

Ariniello, Robert [SLAC National Accelerator Labor↗

Handbook for the study of electric propulsion systems

A compendium of techniques and basic information useful to the preliminary performance analysis of power-limited (low-acceleration, electric) propulsion systems applied to space missions is presented. The material is in handbook form and is reasonably complete within itself insofar as a basic understanding of the techniques and procedures is required for one to acquire facility in computing performance. This, in essence, is the objective of the handbook. The accumulation and organization of the material selected for inclusion was guided by the desire for simplicity and computational ease while maintaining a sufficient level of completeness for a general understanding.

Ragsac, R. V.↗

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗