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2,087 records · Page 111

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NASA NTRSDate not supplied

Numerical Predictions of the Flow and Heat Transfer Characteristics in the Film Boiling Regime During Tube Quenching

Cryogenic fluid management plays a major role in refueling of spacecrafts while in space for NASA’s future human space exploration missions. Due to the low boiling points of cryogens, storage, transport and handling of these fluids becomes difficult and may result in inefficient operation of the space propulsion systems. For refueling applications in space, the cryogenic fluids have to be transported across different locations and hence, the transfer of cryogenic fluids through pipes become critical. The cryogenic chill-down process is characterized by different regimes of flow boiling, viz., film boiling, transition boiling and nucleate boiling. The prediction of these regimes in a single CFD framework available in the literature is challenging and the present work attempts to address this challenge by initially modeling the film boiling regime accurately and to incorporate an user-defined function for transition and nucleate boiling at a later stage. Hence, the aim of the present work is to numerically model and validate the film boiling regime of the chilldown curve for liquid nitrogen experiments available in the literature. The validations are carried out at different inlet mass fluxes to have a robust simulation methodology. A dispersed mixture model is used to predict the vapor-liquid interface dynamics with the phase change phenomena modeled using the Lee model.

line chilldown↗

DOE OSTI2025

In‐Plane Anisotropy in van der Waals NiTeSe Ternary Alloy

Abstract The anisotropic properties of materials profoundly influence their electronic, magnetic, optical, and mechanical behaviors and are critical for a wide range of applications. In this study, the anisotropic characteristics of Ni‐based van der Waals materials, specifically NiTe 2 and its alloy NiTeSe, utilizing a combination of comprehensive scanning tunneling microscopy (STM), angle‐resolved photoemission spectroscopy (ARPES), and density functional theory (DFT) calculations, are explored. Unlike 1T‐NiTe 2 , which exhibits trigonal in‐plane symmetry, the substitution of Te with Se in NiTe 2 (resulting in the NiTeSe alloy) induces a pronounced in‐plane anisotropy. This anisotropy is clear in the STM topographs, which reveal a distinct linear order of charge distribution. Corroborating these observations, ARPES measurements and DFT calculations reveal an anisotropic Fermi surface centered at the point, which is notably elongated along the k y direction, leading to directional variations in in‐plane carrier velocities. Consequently, the Fermi velocity is highest along the k x direction where the linear charge distribution aligns in real space and is lowest along the k y direction. These findings offer valuable insights into the tunability of anisotropic properties in ternary transition metal dichalcogenide systems, highlighting their potential applications in the development of anisotropic electronic and optoelectronic devices.

Chemistry↗

DOE OSTI2026

Reduced-order CFD modeling of cryogenic hydrogen isotope extrusion for pellet fueling

This study presents a reduced-order model (ROM) for computational fluid dynamics (CFD) simulations of cryogenic hydrogen isotope extrusions, focusing on protium (H₂) and deuterium (D₂) piston extruders. Using a 2D axisymmetric ROM in ANSYS-Polyflow, significant computational savings were achieved (runtime reduced from 9∼24 h to 3∼5 min), with extrusion force discrepancies between the 2D ROM and 3D models being on the order of 1%. Parametric studies identified optimal cutoff shear rates in the viscosity model (0.01/s for H₂ and 0.001/s for D₂), providing recommendations for future simulations. Finally, a comprehensive comparison of ROM results with experimental data was performed across varying geometries, cryogenic materials, temperatures, extrusion lengths, and piston velocities. Predictions at low extrusion temperatures met the objective of providing quick and efficient solutions with an acceptable extrusion force error of approximately 10% or less, validating the effectiveness of the 2D ROM approach. However, at high temperatures closer to the triple point, extrusion force error grows, which necessitates developing an improved model that accounts for temperature effects, e.g. melting. Nevertheless, the findings still represent a significant improvement in efficiency of CFD modeling of cryogenic hydrogenic extrusion. The ROM framework can also be extended to tritium (T2) and screw extruders, which will ultimately provide a fast and effective tool for optimizing pellet injector design for ITER and future reactor systems.

Fan, Joy [ORNL] (ORCID:0000000229751735)↗

DOE OSTI2026

Robust negativity in the quantum-to-classical transition of Kerr dynamics

Here, we quantify the quantum-to-classical transition of the single-mode Kerr nonlinear dynamics in the presence of loss. We establish three timescales that govern the dynamics, each with distinct characteristics. For times short compared with the Ehrenfest time, the evolution is classical, characterized by Gaussian dynamics. For sufficiently long times, as we increase the initial photon number, unitary Kerr evolution would generate macroscopic superpositions of coherent states (so-called kitten states). However, this is severely restricted in the presence of small photon loss, and the expectation values of observables coincide with their classical values. The intermediate timescale, however, shows resilient quantum behavior in the macroscopic limit. We show that in the mean-field non-Gaussian regime, the Kerr Hamiltonian (with small photon loss) generates a significant amount of Wigner-negativity, and classical flow is recovered only if the loss rate grows with system size. Our results broaden the usual understanding of quantum-to-classical transitions and demonstrate the potential for creating robust nonclassical resources for continuous-variable quantum information processing in the presence of loss.

Raza, Mohsin [University of New Mexico, Albuquerqu↗

NASA NTRSDate not supplied

Selecting an Encapsulant for an Aerospace Superconducting Machine

Achieving larger benefits from electrified propulsion in single aisle aircraft (the largest commercial aircraft market segment) necessitates that a significant fraction of their 20 MW or greater propulsion system be electrified. 5 to possibly 20 of the MW-scale electric machines investigated by NASA would be required to meet this need. Approximately 10-20 of NASA’s MW-scale electric machines would be required to reach the necessary power levels. Therefore, electric machines of 5 MW or greater are of interest. However, conventionally cooled high power density MW-scale electric machines still produce a significant amount of waste heat, which makes obtaining these power levels problematic. Highly efficient fully superconducting electric machines (or those with a cryogenically cooled, high purity copper or aluminum stator) are a possible solution but have multiple barriers to be overcome. One such barrier is the durability of superconducting windings. Superconductors are typically brittle, and encapsulants used to hold windings in place are a significant source of stress because of the mismatches in coefficient of thermal expansion at temperatures between room temperature and operational temperatures (20 to 77 K). These encapsulants also form a thermal barrier that can be detrimental to cooling the superconductors. This paper describes an initial study of commercially available encapsulants as it relates to superconducting machine applications along with initial modeling of thermal stress in superconducting windings for a superconducting or cryogenically cooled stator in a 5 MW electric machine.

encapsulant↗

DOE OSTI2025

Thick graded interfaces increase wear resistance in Ti/TiN nanolayered thin films

Multilayered composites with nanoscale layer thickness incorporating titanium and titanium nitride (Ti/TiN) are used as a model system to study the effects of heterophase interface structure on elastic and plastic deformation, as well as wear behavior. Here, in this work, hardness, modulus, and wear rate under dry reciprocating sliding contact are quantified as a function of Ti-TiN heterophase interfacial nitrogen gradient thickness for Ti/TiN multilayers with 10–80 nm layer thickness. Hardness and modulus are found to be inversely proportional to layer thickness and independent of interface gradient for most specimens. Wear rate is found to be inversely proportional to interface gradient thickness at constant layer thickness, demonstrating that control of nanoscale interface structure is a valid approach to enhancing wear behavior. The materials studied in this work wear comparably or slower than other Ti- and TiN-based composites in the literature, providing a promising avenue for engineering wear-resistant materials for use in industrially relevant applications.

Graded interfaces↗

DOE OSTI2026

Magnetism and magnetoelastic effect in the two-dimensional van der Waals multiferroic CuCrP 2 ⁢S 6

Here, we report a magnetic and neutron diffraction study on the ground state magnetism and field evolution of single-crystal van der Waals multiferroic CuCrP 2 ⁢S 6 . The ordered moments align along the 𝑏 axis in the "𝐴-type" antiferromagnetic configuration with a spin-flop transition along the same direction. Field application along 𝑎 introduces a smooth transition to a fully polarized ferromagnetic state via in-plane spin rotation. These findings resolve the ambiguity of the ground state magnetization direction in CuCrP 2 ⁢S 6 and uncover its field responses, providing a firm basis for future magnetoelectric study. A magnetoelastic coupling effect connecting the interlayer spacing and the magnetic order was further revealed, highlighting the out-of-plane strain as an effective control knob for tuning magnetism both in this system and in related van der Waals magnets.

Guo, Jiasen [Oak Ridge National Laboratory (ORNL),↗

DOE OSTI2026

Decadal-Scale Hydrothermal Alteration of Basalt: Implications for Long-Term Reactivity in Subsurface Technologies

Global demands to secure critical mineral supply chains and managing water resources require innovative resource management strategies. Subsurface basalt reservoirs offer a dual-purpose application, where CO2 enhanced critical metal recovery can be coupled with water remediation strategies for the extraction of economically important and environmentally relevant elements. This study utilizes static batch experiments conducted on Columbia River Basalt Group samples to evaluate long-term fluid–rock interactions relevant to coupled subsurface applications. Samples were reacted under elevated temperature and pressure conditions, for 296 and 4,061 days, providing a unique dataset to assess geochemical evolution, element partitioning, and aqueous chemistry over decadal timescales. The alteration was dominated by silicate, aluminosilicate, and oxide phases. Progressive hydrothermal alteration increased the cation exchange capacity through the formation of secondary minerals (e.g. clays and zeolites), influencing solute retention, ion exchange behavior, and aqueous chemistry. Grain-scale and bulk analyses revealed selective cation release and retention patterns, establishing a mechanistic baseline for predicting element mobility. These geochemical constraints inform the prospective use of CO2-enhanced metal recovery for critical resources (e.g. Co, Ni, Mn, Mg, Ti, Fe) and associated water-quality impacts, providing a foundation for the design and management of engineered fluid–rock systems in basalt reservoirs.

Gibson, Marie N.↗

DOE OSTI2026

Multitarget Rydberg gates via spatial blockade engineering

Multi-target gates offer the potential to reduce gate depth in syndrome extraction for quantum error correction. Although neutral-atom quantum computers have demonstrated native multi-qubit gates, existing approaches that avoid additional control or multiple atomic species have been limited to single-target gates. We propose single-control-multi-target CZ^n gates on a single-species neutral-atom platform that require no extra control and have gate durations comparable to standard CZ gates. Our approach leverages tailored interatomic distances to create an asymmetric blockade between the control and target atoms. Using a GPU-accelerated pulse synthesis protocol, we design smooth control pulses for CZZ and CZZZ gates, achieving fidelities of up to 99.55% and $99.24\%$, respectively, even in the presence of simulated atom placement errors and Rydberg-state decay. Our approach is most effective for N=2 (CZZ) and N=3 targets (CZZZ); for larger N, increasing spatial crowding of the targets introduces significant challenges for maintaining the required blockade asymmetry. This work presents a practical path to implementing low-overhead multi-target gates in single-species neutral-atom systems, significantly reducing the resource overhead for syndrome extraction. To motivate the impact of these gates, we apply a greedy scheduling algorithm and we demonstrate that our proposed gates can reduce the number of atom reconfiguration costs by up to 50% for color code syndrome extraction of code distances greater than 5.

Stein, Samuel A.↗

NASA NTRS2026

Artemis Suit Material Optical Property Testing of Dust Exposed Fabrics

This paper highlights one aspect of NASA’s ongoing technology-infusion effort to design, fabricate, and test a next-generation outer shell fabric for a lunar Extravehicular Activity (EVA) space suit, a critical component of sustained lunar exploration. Managing thermal loads on the Moon is essential for astronaut safety and suit performance. The suit’s exterior fabric directly influences heat gain and loss through its optical properties: low solar absorptivity minimizes sunlight absorption, while high infrared emissivity aids radiative cooling. Lunar regolith complicates this balance. Its fine, abrasive particles possess unique optical behavior that can lower reflectivity and raise emissivity when embedded in or adhered to fabric surfaces, degrading thermal control and increasing the risk of overheating or cooling inefficiency. To quantify these effects, the Artemis Suit Materials (ASM) team measured solar absorptance and infrared emissivity of clean and dust-soiled Ortho Fabric, establishing beginning-of-life (BOL) and end-of-life (EOL) benchmarks. EOL conditions were simulated with a rotary tumbler abrasion process using lunar dust simulant and ceramic media to reproduce cumulative wear expected during surface operations. Tests also included unmodified fabrics and a fabric/film laminate system containing titanium dioxide to evaluate potential improvements in dust resistance and optical performance. Results from these evaluations provide critical insight into how lunar dust alters fabric thermal behavior and inform the design of bespoke suit materials that maintain required optical properties throughout mission life, supporting safe and effective long-duration EVA on the lunar surface.

Textile↗

NASA NTRS2026

Artemis Suit Material Optical Property Testing of Dust Exposed Fabrics

space↗

NASA NTRSDate not supplied

Battery Failure Databank

The Battery Failure Databank contains thermal runaway results gathered from nearly 300 small format fractional thermal runaway calorimetry (S-FTRC) experiments. A majority of these experiments were conducted at synchrotron facilities where high-speed x-ray videography was conducted of the cell while tested inside of the S-FTRC. The databank is a two-component system which consists of a Microsoft ExcelTM spreadsheet which provides S-FTRC results in tabular format and a radiographic video library containing the high-speed x-ray videos. Overall, the databank provides thermal results from S-FTRC experiments conducted on a mixture of commercially available lithium-ion (Li-ion) cells and specialized Li-ion test cells with varying cell format (18650, 21700, and D-cell) and trigger mechanism (heaters, heaters plus internal short circuiting device, and nail penetration). The radiography video component provides insight into the initiation and propagation of TR in the cells, in addition to consequences of TR measured by the FTRC. Fractions of mass ejected for the cell types are separated into regimes based on the different failure modes of the cells, such as purely venting, partial ejection, and total ejection. With knowledge of the rate and characterization of the internal degradation of the cells during TR, and the amounts of mass ejected and unrecovered, the extent of TR, and therefore the mitigation of TR, is revealed relative to cell types and failure modes.

Lithium-ion battery↗

DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗

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

Keldysh tuning of photoluminescence in a lead halide perovskite crystal

In 1964, Keldysh laid the groundwork for strong-field physics in atomic, molecular, and solid-state systems by delineating a ubiquitous transition from multiphoton absorption to quantum electron tunneling under intense AC driving forces. While both processes in semiconductors can generate carriers and result in photon emission through electron-hole recombination, the low quantum yields in most materials have hindered direct observation of the Keldysh crossover. Leveraging the large quantum yields of photoluminescence in lead halide perovskites, we show that we can not only induce bright light emission from extreme sub-bandgap light excitation but also distinguish between photon-induced and electric-field-induced processes. Our results are rationalized by the Landau-Dykhne formalism, providing insights into the non-equilibrium dynamics of strong-field light-matter interactions. These findings open new avenues for light upconversion and sub-bandgap photon detection, highlighting the potential of lead halide perovskites in advanced optoelectronic applications.

FOS: Physical sciences↗

DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗

NASA NTRS1996

Planetary and Deep Space Requirements for Photovoltaic Solar Arrays

In the past 25 years, the majority of interplanetary spacecraft have been powered by nuclear sources. However, as the emphasis on smaller, low cost missions gains momentum, more deep space missions now being planned have baselined photovoltaic solar arrays due to the low power requirements (usually significantly less than 100 W) needed for engineering and science payloads. This will present challenges to the solar array builders, inasmuch as planetary requirements usually differ from earth orbital requirements. In addition, these requirements often differ greatly, depending on the specific mission; for example, inner planets vs. outer planets, orbiters vs. flybys, spacecraft vs. landers, and so on. Also, the likelihood of electric propulsion missions will influence the requirements placed on solar array developers. This paper will discuss representative requirements for a range of planetary and deep space science missions now in the planning stages. We have divided the requirements into three categories: Inner planets and the sun; outer planets (greater than 3 AU); and Mars, cometary, and asteroid landers and probes. Requirements for Mercury and Ganymede landers will be covered in the Inner and Outer Planets sections with their respective orbiters. We will also discuss special requirements associated with solar electric propulsion (SEP). New technology developments will be needed to meet the demanding environments presented by these future applications as many of the technologies envisioned have not yet been demonstrated. In addition, new technologies that will be needed reside not only in the photovoltaic solar array, but also in other spacecraft systems that are key to operating the spacecraft reliably with the photovoltaics.

C P Bankston↗

DOE OSTI2025

Multiscale aperture synthesis imager

Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present the multiscale aperture synthesis imager (MASI), which utilizes parallelism to break complex optical challenges into tractable sub-problems. MASI employs a distributed array of coded sensors that operate independently yet coherently to surpass the diffraction limit of single receiver. It combines the propagated wavefields from individual sensors through a computational phase synchronization scheme, eliminating the need for overlapping measurement regions to establish phase coherence. Light diffraction in MASI naturally expands the imaging field, generating phase-contrast visualizations that are substantially larger than sensor dimensions. Without using lenses, MASI resolves sub-micron features at ultralong working distances and reconstructs 3D shapes over centimeter-scale fields. MASI transforms the intractable optical synchronization problem into a computational one, enabling practical deployment of scalable synthetic aperture systems at optical wavelengths.

electrical and electronic engineering↗