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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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403 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Overcoming the Entropy Penalty of Direct Air Capture for Efficient Gigatonne Removal of Carbon Dioxide

Atmospheric carbon poses an existential threat to civilization via global climate change. Hundreds of gigatonnes of carbon dioxide must be removed from earth’s atmosphere in the next three decades, necessitating a low-cost, energy-efficient process to extract low concentrations of carbon dioxide for conversion to a stable material permanently stored for thousands of years. In this work, the challenge of removing gigatonnes of CO 2 is described via the scale of effort and the thermodynamics of collecting and reducing this diffuse chemical, the accumulation of which imparts a substantial entropy penalty on any atmospheric carbon capture process. The methods of CO 2 reduction combined with upstream direct air capture (DAC) including absorption, membrane separation, and adsorption are compared with biomass torrefaction and permanent burial (BTB). A Monte Carlo model assesses the mass, energy, and economics of the full process of biomass torrefaction from biomass collection and transport to stable carbon burial to determine that 95% of scenarios could remove carbon for less than $200 per CO 2 -tonne-equivalent. Torrefied carbon is further discussed for its long-term stability and availability at the scale required to substantially mitigate the threat of climate change.

biomass↗
DOE OSTI2026

Characterization of NBCMA—A DAPO Precursor

As part of our investigation into the process optimization of 2,6-diaminopyrazine-1-oxide (DAPO), small-scale sensitivity testing (impact, friction, and ESD) was conducted on the precursor, N-nitroso-bis(cyanomethyl)amine (NBCMA). NBCMA exhibited moderate sensitivity to friction, whereas no sensitivity to impact or spark was observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2026

Integrated Computational Materials Engineering (ICME) Capability Maturity Levels for Ecosystems Enabling Digital Transformation

Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.

ICME↗
DOE OSTI2025

Exploiting ν-dependence of projected energy correlators in HICs

We extend the recently derived factorization formula for energy-energy correlators to study the analytic structure of general ν-point projected energy correlators in heavy ion collisions. The ν-point projected energy correlators (or, ν-correlators) are an analytically continued family of the integer N-point projected energy correlators, which probe correlations between N final-state particles. By tracking the largest separation (χ) between the N particles, in vacuum, their structure is closely related to the DGLAP splitting functions and exhibits a classical scaling behavior ∼ 1/χ which is modified by resummation through the anomalous dimensions. We show that, in a thermal medium, the ν-correlators display non-trivial angular scaling already at the leading order in perturbation theory. We find that for non-integer values, particularly ν < 1, medium-induced jet function is enhanced compared to ν > 1. This is particularly manifested in the ratios of ν-correlators with respect to the two-point energy correlator, which encodes intrinsic angular information for ν < 1 when compared to large ν values. Moreover, for small-ν values, the ν-correlators appear to saturate at ν = 0.01 . We further confirm our leading-order numerical computations against simulated events from JEWEL for the parton-level production cross-section. Finally, we qualitatively discuss the effect of BFKL resummation for various values of ν.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials↗
DOE OSTI2026

Effect of Oxidizing Impurities on the Corrosion Behavior of Structural Alloys Exposed to MgCl 2 Molten Salt Vapor

The corrosion behavior of structural alloys SS304 and IN617 when exposed to vapors of MgCl 2 molten salt at 764 °C for 100 h in an argon atmosphere was investigated as a function of the level of oxidizing impurities (e.g., NaOH) present in the salt. Increasing the concentration of oxidizing impurities in the salt caused an increase in corrosion in both structural alloys, as measured by Cr depletion layers. A poorly adhered oxide scale layer containing Mg, Al, and Cr was observed on the surface of the metals, and local attack was observed as well. The Ni-based IN617 showed lower Cr depletion and less scale formation than the Fe-based SS304. These results demonstrate that oxidizing impurities in the molten salt will impact the vapor phase corrosion for structural members exposed to the molten salt headspace. This finding is highly relevant for understanding the effects of the vapor phase in molten salt applications, including molten salt thermal energy storage, molten salt nuclear reactors, and molten salt electrochemistry.

25 ENERGY STORAGE↗
NASA NTRS1986

A 65 Ah rechargeable lithium molybdenum disulfide battery

A rechargeable lithium molybdenum disulfide battery which has a number of superior performance characteristics which includes a high energy density, a high power density, and a long charge retention time was developed. The first cell sizes developed included a C size cell and an AA size cell. Over the last two years, a project to demonstrate the feasibility of the scale up to this technology to a BC size cell with 65 Ah capacity was undertaken. The objective was to develop, build, and test a .6 kWh storage battery consisting of 6 BC cells in series.

Brandt, K.↗
DOE OSTI2023

Challenges and Prospects of Sodium‐Ion and Potassium‐Ion Batteries for Mass Production

The exponential growth of the lithium‐ion (LIB) market is causing a significant disparity between the supply chain and demand for its resources. In this regard, sodium‐ion and potassium‐ion batteries are promising alternatives to LIBs due to their low cost. However, the larger sizes of Na + and K + ions create challenges that prevent them from achieving energy densities comparable to LIBs while maintaining an acceptable cycle life. Here, in this perspective, the aim is to evaluate the status of Na‐ion and K‐ion batteries and the challenges associated with them on both fundamental and commercial levels. The focus is on the structural instability arising from phase transitions during cycling, intricate chemical degradation processes, and potential avenues for enhancing their performance with a specific goal of improving their viability for grid‐scale energy storage. Materials production and abundance limitations for the chemistries of the state‐of‐the‐art materials and account for critical parameters from both the perspective of researchers and investors are analyzed. This analysis aims to provide insights into the strategic trade‐offs required to effectively implement the technology in real‐world applications, such as grid‐scale storage and other areas. Furthermore, the utilization of metals with low or no supply‐chain problems as an important aspect of these trade‐offs is considered.

25 ENERGY STORAGE↗
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↗
DOE OSTI2026

Influence of Powder Characteristics and Processing Methods on Creep Performance of Powder Metallurgy Hot Isostatic Pressed SS316

The U.S. nuclear energy expansion goals are driving the demand for manufacturing routes that can rapidly produce large, complex, near net shape components. Powder metallurgy hot isostatic pressing (PM HIP) is an advanced manufacturing technique that can be economically scaled-up, while alleviating the supply chain challenges that forging and casting face in terms of cost and lead time constraints. This makes PM-HIP a viable technology to aid and accelerate large-scale part manufacturing for nuclear applications. However, large-scale qualification and deployment of this technology require a thorough understanding of the influence of powder feedstock quality, powder handling history, hot isostatic pressing (HIP) parameters, and subsequent heat treatment on microstructural evolution and elevated temperature mechanical performance. The present work focusses on 316 austenitic stainless steel (SS316) which is most commonly used in high temperature environments for nuclear applications Results from this study show that PM HIPed SS316 meets ASME tensile requirements at room temperature and at elevated temperature. However, creep performance of PM-HIPed SS316 remains inferior to its wrought counterpart, demonstrating that tensile performance alone is not a reliable metric for long duration high temperature integrity. Further, this report delineates powder derived microstructural features that govern creep damage, with key evidences pointing to “microstructural inheritance” from gas atomized powder feedstocks. Commercial SS316 powders of varying chemical compositions and recycling histories were studies, and the results showed large differences in elemental segregation, oxide surface layers and secondary phase distributions. Multi-scale characterization revealed segregation of chromium, molybdenum, manganese and silicon at the boundaries and the precipitation of manganese-, silicon-, and molybdenum-oxides. During HIP consolidation, these surface oxides transform into decorated prior particle boundaries (PPBs) and grain boundary inclusions that persist through conventional post-HIP solution annealing treatment. The retained oxides in post-HIP microstructures were found to influence grain growth, precipitation behavior, and ultimately creep cavitation and fracture. Such post-HIP heat treatments are therefore limited by a complex trade-off between grain growth, and oxide coarsening which aggravate creep damage by acting as nucleation sites for cavities. The objective of this work is to establish an integrated processing–structure–property framework for PM-HIP 316 stainless steel by investigating the influence of powder feedstock characteristics in pre- and post-HIP processing as well as to understand the significance of post-HIP heat treatment on microstructural evolution and creep properties. The results from this report emphasize the significance of powder feedstock integrity in improving creep performance of PM-HIPed SS316, by highlight the effect of rapid solidification, elemental segregation, oxide formation and powder recycling on microstructural defect inheritance following HIP consolidation. Rather than considering HIP processing, solution annealing, and mechanical performance independently, this report treats powder production, HIP consolidation, post-HIP thermal processing, and creep deformation as interconnected stages within a continuous metallurgical process. The resulting framework will provide a scientific basis for developing feedstock engineering strategies capable of improving long-term reliability of PM-HIP stainless steels and accelerating their qualification for advanced nuclear applications.

Ajjarapu, Pavan [Oak Ridge National Laboratory (OR↗
NASA NTRS2000

The NASA Inductrack Model Rocket Launcher at the Lawrence Livermore National Laboratory

The Inductrack magnetic levitation system, developed at the Lawrence Livermore National Laboratory, is being studied for its possible use for launching rockets. Under NASA sponsorship, a small model system is being constructed at the Laboratory to pursue key technical aspects of this proposed application. The Inductrack is a passive magnetic levitation system employing special arrays of high-field permanent magnets (Halbach arrays) on the levitating carrier, moving above a "track" consisting of a close-packed array of shorted coils with which are interleaved with special drive coils. Halbach arrays produce a strong spatially periodic magnetic field on the front surface of the arrays, while canceling the field on their back surface. Relative motion between the Halbach arrays and the track coils induces currents in those coils. These currents levitate the carrier cart by interacting with the horizontal component of the magnetic field. Pulsed currents in the drive coils, synchronized with the motion of the carrier, interact with the vertical component of the magnetic field to provide acceleration forces. Motional stability, including resistance to both vertical and lateral aerodynamic forces, is provided by having Halbach arrays that interact with both the upper and the lower sides of the track coils. In its completed form the model system that is under construction will have a track approximately 100 meters in length along which the carrier cart will be propelled up to peak speeds of Mach 0.4 to 0.5 before being decelerated. Preliminary studies of the parameters of a full-scale system have also been made. These studies address the problems of scale-up, including means to simplify the track construction and to reduce the cost of the pulsed-power systems needed for propulsion.

L S Tung↗
DOE OSTI2026

Simulation to a Newborn Supernova Remnant from a Low-mass Iron Core Star

Supernova remnant observations show a high degree of asymmetry, mixing, and inhomogeneity. These asymmetries are seeded during the early seconds of the explosion and are further enhanced and modified as the shock and ejecta move through the stellar progenitor and into the circumstellar medium. We present simulations of a 9.6 M⊙ zero-metallicity progenitor initialized after shock revival and evolved for several years when the ejecta is in the circumstellar medium. A suite of 1D and 2D simulations examines the effects of neutron-star wind and radioactive decay heating. In 1D, decay heating forms a low-density bubble that suppresses the reverse shock. While in 2D, the heating is localized to metal-rich pockets, inflating them and compressing the surrounding material into dense shells. In 3D, the neutron-star wind and decay heating modify the plume morphology, producing more large-scale structures. The extended plume morphology leads to an asymmetrical shock breakout. After breakout, the leading plumes cannot keep up with the shock front, resulting in deceleration and fragmentation by the reverse shock while retaining the large-scale asymmetry. The projected ejecta morphology and velocities are strongly viewing angle dependent. The relatively uniform metal-rich distribution does not resemble the strongly inhomogeneous ejecta structure of Cas A. The 160-isotope decay network shows that 24.4% of the radioactive heating comes from decay chains other than the canonical 56Ni chain. The low explosion energy, low 56Ni yield, and Ni/Fe ratio greater than unity suggest an observational signature similar to an electron capture supernova.

Neopane, Sudarshan [University of Tennessee (UT)]↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS2026

CH3OH and HCN in Interstellar Comet 3I/ATLAS Mapped with the ALMA Atacama Compact Array: Distinct Outgassing Behaviors and a Remarkably High CH3OH/HCN Production Rate Ratio

We report the detection of methanol (CH3OH) toward interstellar comet 3I/ATLAS using the At-acama Compact Array of the Atacama Large Millimeter/Submillimeter Array (ALMA) on UT 2025 August 28, September 18 and 22, and October 1, and of hydrogen cyanide (HCN) on September 12 and 15. These observations spanned pre-perihelion heliocentric distances (r H ) of 2.6 – 1.7 au. The molecules showed outgassing patterns distinct from one another, with HCN production being depleted in the sunward hemisphere of the coma, whereas CH3OH was enhanced in that direction. Statistical analysis of molecular scale lengths in 3I/ATLAS indicated that CH3OH included production from coma sources at Lp > 258 km at 99% confidence. However low signal-to-noise on long baselines, which sample emission on small spatial scales closest to the nucleus, prevented definitively ruling out CH3OH as purely a parent species. In contrast, HCN production was indistinguishable from direct nucleus sublimation. The CH3OH production rate increased sharply from August through October, including an uptick near the inner edge of the H2O sublimation zone at rH = 2 au. Compared to comets measured to date at radio wavelengths, the derived CH3OH/HCN ratios in 3I/ATLAS of 124+30−34 and 79+11−14on September 12 and 15, respectively, are among the most enriched values measured in any comet, surpassed only by anomalous solar system comet C/2016 R2 (PanSTARRS)

Comae↗
NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗
DOE OSTI2016

Chevron Natural Gas Carbon Capture Technology Testing Project (Final Technical Report)

The objective of this project was to design, construct, commission, and operate an engineering scale post combustion carbon capture system to validate the technical maturity, operability, and scalability of Svante’s VeloxoTherm™ solid sorbent carbon capture technology under representative flue gas conditions. The project was executed at Chevron’s Kern River oil field in the San Joaquin Valley of California and evaluated carbon capture performance using slipstream flue gas from natural gas fired once through steam generators (OTSG), including indicative coal and natural gas combined cycle (NGCC) operating scenarios.

03 NATURAL GAS↗
DOE OSTI2025

Photon-Counting Interferometry to Detect Geontropic Space-Time Fluctuations with GQuEST

The gravity from the quantum entanglement of space-time (GQuEST) experiment uses tabletop-scale Michelson laser interferometers to probe for fluctuations in space-time. We present a practicable interferometer design featuring a novel photon-counting readout method that provides unprecedented sensitivity, as it is not subject to the interferometric standard quantum limit. We evaluate the potential of this design to measure space-time fluctuations motivated by recent “geontropic” quantum gravity models. The accelerated accrual of Fisher information offered by the photon-counting readout enables GQuEST to detect the predicted quantum gravity phenomena within measurement times at least 100 times shorter than equivalent conventional interferometers. The GQuEST design, thus, enables a fast and sensitive search for signatures of quantum gravity in a laboratory-scale experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Air-Breathing Aerospace Plane Development Essential: Hypersonic Propulsion Flight Tests

Hypersonic airbreathing propulsion utilizing scramjets can change transatmospheric accelerators for low earth-to-orbit and return transportation. The value and limitation of ground tests, of flight tests, and of computations are presented, and scramjet development requirements are discussed. It is proposed that near full-scale hypersonic propulsion flight tests are essential for developing computational design technology so that it can be used for designing this system. In order to determine how these objectives should be achieved, some lessons learned from past programs are presented. A conceptual two-stage-to-orbit (TSTO) prototype/experimental aerospace plane is recommended as a means of providing access-to-space and for conducting flight tests.

Unmeel B Mehta↗