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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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2,912 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Preliminary Dynamic Modeling of the Quarter-Scale Distributed Electric Propulsion Aircraft

This presentation describes the early-stage modeling of a quarter-scale distributed electric propulsion aircraft, based on the SUbsonic Single Aft eNgine (SUSAN) Electrofan, a transformative concept aircraft for which a model exists. The full-scale 180 passenger SUSAN concept has a single turbofan engine in the tail that both produces thrust and provides electrical power to 16 electric fans distributed across the wings utilizing a series/parallel hybrid architecture. The quarter-scale version would have an internal combustion piston engine to provide power to 17 electric fans–16 on the wings, one in the tail–in a series hybrid configuration, and no vertical or horizontal stabilizers. It would also have a reduced flight envelope in terms of both altitude and speed. The initial modeling approach is to scale down the original airframe model to capture the dynamic behavior of a much smaller aircraft, albeit with an empennage. The original powertrain model is then replaced with one representing the physical components of that of the quarter-scale vehicle. This powertrain model is suitable for control design and analysis, and the fully integrated, although preliminary, aircraft model allows flight simulator testing and evaluation. Results from simulations are presented.

electrified aircraft propulsion↗
NASA NTRS2026

Preliminary Dynamic Modeling of the Quarter-Scale Distributed Electric Propulsion Aircraft

This paper describes the early-stage modeling of a quarter-scale distributed electric propulsion aircraft, based on the SUbsonic Single Aft eNgine (SUSAN) Electrofan, a transformative concept aircraft for which a model exists. The full-scale 180 passenger SUSAN concept has a single turbofan engine in the tail that both produces thrust and provides electrical power to 16 electric fans distributed across the wings utilizing a series/parallel hybrid architecture. The quarter-scale version would have an internal combustion piston engine to provide power to 17 electric fans–16 on the wings, one in the tail–in a series hybrid configuration, and no vertical or horizontal stabilizers. It would also have a reduced flight envelope in terms of both altitude and speed. The initial modeling approach is to scale down the original airframe model to capture the dynamic behavior of a much smaller aircraft, albeit with an empennage. The original powertrain model is then replaced with one representing the physical components of that of the quarter-scale vehicle. This powertrain model is suitable for control design and analysis, and the fully integrated, although preliminary, aircraft model allows flight simulator testing and evaluation. Results from simulations are presented.

Electrified powertrain↗
NASA NTRSDate not supplied

Assembly and Integration Status of a High Fidelity Ground Test Bed for the Water Processor Assembly

The Water Recovery System (WRS) is a critical component of life support aboard the International Space Station (ISS) and will play an essential role in future missions beyond Low Earth Orbit (LEO). Its primary functional units – the Urine Processor Assembly (UPA), Brine Processor Assembly (BPA), and Water Processor Assembly (WPA) – must be evaluated for extended operation, dormancy resilience, material obsolescence, and reliability under exploration-driven constraints. Ground testing is vital for developing these technologies and generating statistically relevant reliability assessments, which requires extended runtime under integrated, Flight-like conditions. Currently, no high-fidelity, fully integrated WPA ground test bed exists to support these objectives. To address this gap, NASA is developing a WPA test bed at Marshall Space Flight Center (MSFC) that combines downgraded ISS flight hardware with functionally flight-like components in a cost-effective configuration while maintaining priority hardware investigations. This paper describes the current status of hardware assembly and integration, outlines key challenges such as simulating microgravity effects and mitigating obsolescence, and presents future test objectives including software development, reliability assessments, dormancy studies, and exploration-oriented upgrades.

Water Processor Assembly↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗
DOE OSTI2025

An attention-based neural ordinary differential equation framework for modeling inelastic processes

To preserve strictly conservative behavior as well as model the variety of dissipative behavior displayed by solid materials, we propose a significant enhancement to the internal state variable-neural ordinary differential equation (ISV-NODE) framework. In this data-driven, physics-constrained modeling framework internal states are inferred rather than prescribed. The ISV-NODE consists of: (a) a stress model dependent on observable deformation and inferred internal state, and (b) a model of the evolution of the internal states. The enhancements to ISV-NODE proposed in this work are multifold: (a) a partially input convex neural network stress potential provides polyconvexity in terms of observed strain while leaving the inferred state unconstrained, and (b) an internal state flow model uses common latent features to inform novel attention-based gating and drives the flow of internal state only in dissipative regimes. We demonstrated that this architecture can accurately model dissipative and conservative behavior across an isotropic, isothermal elastic-viscoelastic-elastoplastic spectrum with three exemplars, while maintaining fundamental principles by design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Effect of Thermodynamic and Environmental Factors on Crystallization of DNA‐Origami Superlattices

The directed self‐assembly of nanoscale materials into ordered superlattices presents a powerful strategy for creating next‐generation materials with programmable mechanical, optical, and photonic properties. Deoxyribonucleic acid (DNA) origami has emerged as a versatile scaffold for encoding nanoscale geometry and guiding the crystallization of complex 3D architectures. However, a systematic understanding of the parameters that govern the efficiency and quality of superlattice formation remains limited. In this study, we utilize octahedral DNA nanoscale frames as a model system to investigate the relative influence of key factors, including buffer composition, ionic strength, frame concentration, and thermal annealing protocols, on the size, order, and reproducibility of the resulting superlattices. Our findings provide a quantitative framework to rationally optimize DNA‐based assembly pathways. Structural characterization via small‐angle x‐ray scattering (SAXS), scanning electron microscopy (SEM), and optical microscopy validates the quality and fidelity of the assembled lattices. Moreover, by templating these DNA frameworks into inorganic replicas, we establish general design principles that extend beyond biomolecular systems, providing a foundation for the synthesis of programmable materials in broader nanofabrication contexts.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Phonon screening and dissociation of excitons at finite temperatures from first principles

The properties of excitons, or correlated electron–hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron–hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening of excitonic properties. While these model approaches tend to improve agreement with experiment, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio GW -Bethe–Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO, and SrTiO 3 . We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron–hole pairs.

Science & Technology - Other Topics↗
DOE OSTI2024

Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning

The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional analysis methods. In this study, we present a machine learning framework designed to reveal obscured phonon dynamics from powder spectra. Using a variational autoencoder, we obtain a disentangled latent representation of spectra and successfully extract force constants for reconstructing phonon dispersions. Notably, our model demonstrates effective applicability to experimental data even when trained exclusively on physics-based simulations. The fine-tuning with experimental spectra further mitigates issues arising from domain shift. Analysis of latent space underscores the model’s versatility and generalizability, affirming its suitability for complex system applications. Furthermore, our framework’s two-stage design is promising for developing a universal pre-trained feature extractor. This approach has the potential to revolutionize neutron measurements of phonon dynamics, offering researchers a potent tool to decipher intricate spectra and gain valuable insights into the intrinsic physics of materials.

domain adaptation↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2026

Design of monolithic piezoelectric bimorph mirrors made from lithium niobate

Recent advances in deformable mirrors based on monolithic piezoelectric substrates, such as lithium niobate, have the potential to improve the image quality of X-ray optical systems on synchrotron and free-electron laser beamlines and microscopes. However, the quantitative relationship between design parameters and the deformed shape has not been readily available in the literature. We present an analytical model, validated through finite element analysis, enabling calculation of tangential and sagittal curvatures based on mirror dimensions, crystallographic orientation, and applied voltage. We demonstrate that through the selection of material orientation, it is possible to achieve different deformed shapes (sphere, cylinder, or hyperbolic paraboloid). This methodology can be generalized to other piezoelectric materials and substrate-integrated actuator systems.

Marzari, Francesco [University of Trento (Italy); ↗
DOE OSTI2025

Robust Biaxial Anisotropy and Switchable Néel Vectors in LaFeO 3 Epitaxial Films

Antiferromagnets with highly stable but switchable Néel vectors are desired for antiferromagnetic spintronics with ultrafast speed and terahertz frequencies. Electrical switching of antiferromagnetic insulators has been demonstrated using binary antiferromagnets, while large families of complex antiferromagnets such as perovskites are largely unexplored. Here, we show that epitaxial LaFeO 3 thin films on SrTiO 3 (001) exhibit clear, robust biaxial anisotropy with a spin-flop field of a few tesla. Angular-dependent spin-Hall magnetoresistance (SMR) characterizations of Pt/LaFeO 3 bilayers with the current channel along SrTiO 3 [100] and [110] reveal distinct, intriguing shapes and field dependence. Simulations using a macrospin model accurately describe the main behavior and fine features of the SMR data from which key antiferromagnetic parameters are extracted. Furthermore, remanent SMR measurement confirms the high fidelity of the Néel vector along either easy axis of the biaxial anisotropy, indicating that epitaxial films of LaFeO 3 and potentially other perovskite antiferromagnets offer an attractive platform for antiferromagnetic spintronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

High-Fidelity Modeling Approach for Coupling Thermal, Fluid, and Neutronic Analysis in an NTP Engine

Nuclear thermal propulsion (NTP), with its increased efficiency compared to traditional rocket engines, is a potentially enabling technology for space missions of higher complexity, such as delivering heavy machinery or crew to the moon or other planets. Thus, exploring modeling approaches that can effectively couple the thermal, fluid, and neutronic behaviors of NTP reactors is essential to mitigate cost and schedule challenges with hardware development. This paper details one such approach which utilizes Cardinal to unify reactor physics analysis performed using OpenMC, heat transfer analysis performed using the MOOSE framework, and thermal hydraulic analysis performed using the MOOSE Thermal Hydraulic Module. This approach is demonstrated with a proof of concept that focuses on a legacy reactor geometry from the historic NERVA program. This preliminary model found an overprediction in, when compared to the reference data, axial power peaking and the temperatures of both solids and fluids by roughly 20%. It is clear, however, that the model conserved a number of broad trends, and a few model refinements should reduce the observed error. This approach has definite merit and should enable the production of informative results for more modern NTP systems. This work is a first step in creating a transient reactor model that can be updated across a sequence of time steps based on continually fluctuating, time-dependent boundary conditions.

Nuclear Thermal Propulsion↗
DOE OSTI2026

Tunable magnetic excitations in the honeycomb antiferromagnet (Co,Ni)⁢TiO3

The solid solution of the honeycomb antiferromagnet (AFM) Co0.5⁢Ni0.5⁢TiO3 (CNTO) was synthesized by mixing a 1:1 molar ratio of CoTiO3 (CTO) and NiTiO3 (NTO). Powder neutron scattering was used to determine the structure and magnetic spectrum, where the nuclear and magnetic structures resemble those of the end members. The Néel temperature (T𝑁 = 27 ± 1 K), the ordered magnetic moment (M = 2.29 ± 0.03 𝜇𝐵 per magnetic ion), and lattice parameters are intermediate between those of the two. From inelastic neutron scattering, it is observed that the magnon density of states (MDOS) extends up to 13 meV, and the interaction can be described by an XXZ-type magnetic Hamiltonian. Above 15 meV, spin-orbit excitons (SOEs) are observed similarly to those in CTO, but with modified spin-orbit crystal-field splitting because of the substitution of Ni at Co sites, and the disorder induced by the Ni substitution modifies the spin-orbit crystal field. Thus, the magnetic dynamics of the CNTO cannot be described as a simple average of the two parent compounds.

Rathnayaka, Srimal [University of Virginia, Charlo↗
DOE OSTI2026

Extreme confinement of hydrogen gas within fullerenelike nanoporous carbon

Nanoporous carbons and carbon nanostructures can store hydrogen at cryogenic temperatures but lack the volumetric and gravimetric capacity to be industrially significant. Recent inelastic neutron scattering experiments suggest a highly dense phase of hydrogen at temperatures well above the melting point of solid hydrogen. However, it remains unclear how pore geometry and intermolecular interactions enable these dense phases to exist, with dispersion (van der Waals) or electrostatic/induction suggested to be the key effects in slit and curved pores but their relative contributions have yet to be quantified. In this paper, we perform benchmark electronic structure calculations allowing the interactions between planar and curved aromatic molecules with hydrogen to be accurately determined. Dispersion was found to dominate over electrostatic and inductive effects with some many-body charge transfer (Dobson type-A) effects needed to capture the most highly curved structures. Density functional methods that include type-A many-body effects were found to accurately describe the intermolecular interactions at a fraction of the cost of coupled-cluster simulations and these approaches were used to calculate the energies inside large carbon bowl and slit pores. The interaction energies inside the bowl pores were found to depend on the orientation of the hydrogen molecule. This rotational barrier, modeled as a quantum hindered rotor, could reproduce the peak splitting observed in inelastic neutron scattering experiments, with weak splitting arising from bowl-like fullerene pores and strong splitting from highly confining nanotubelike pores. Increasing the fraction of such curved pores in nanoporous carbons may therefore offer a pathway to enhance their hydrogen-storage capacity. Moreover, the preferential adsorption of ortho hydrogen on nanotubelike pores could enable the storage of high-density hydrogen without the need to remove heat produced during the ortho-para hydrogen conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Search for New Physics via Low-Energy Electron Recoils with a 4.2 Tonne-Year Exposure from the LZ Experiment

We report results from searches for new physics models through electron recoils using data collected by the LUX-ZEPLIN experiment during its first two science runs, with a total exposure of 4.2 tonne−years. The observed data are consistent with a background-only hypothesis. Constraints are derived for electromagnetic interactions of solar neutrinos, solar axionlike particles (ALPs), mirror dark matter, and the absorption of bosonic dark matter candidates. The inverse Primakoff process for 57 Fe deexcitation solar ALPs is considered for the first time. These results represent the most stringent constraints to date on keV-scale Primakoff and 57 Fe solar ALPs, bosonic dark matter, mirror dark matter, and neutrino millicharge, while remaining competitive for the other signal models investigated.

Axion-like particles↗
DOE OSTI2026

A parametric study of slow dynamic nonlinear elasticity with comparisons to models

Several phenomenological models that aspire to quantitative description of anomalous nonlinear mesoscopic elasticity are reviewed and compared with laboratory measurements. This class of nonlinearity, best known perhaps for slow dynamics and aging, is seen widely in imperfectly consolidated granular solids but is not well understood. Typical slow dynamic tests show that a modest conditioning oscillatory "pump" strain depresses material stiffness, which then recovers like the logarithm of time after conditioning ceases. Several phenomenological models based on physical arguments have been proposed that predict the material stiffness response to arbitrary pump strain histories during conditioning and recovery. Approximate closed form and numerical solutions to the models are presented that predict the quantitative influence of three key pump parameters: the pump's strain amplitude, the pump's strain rate, and the pump’s duration. Laboratory measurements on Berea sandstone, concrete and a confined single aluminum bead find that slow dynamic responses are linear in pump strain and independent of pump frequency. Measurements also show that, after pump-off, stiffness recovers over times far longer than the pump duration. These observations and others are compared to model predictions. One of the considered models, based on a picture of fast brittle damage and slow healing, successfully matches all these behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗
DOE OSTI2026

Atomic Evolution of Hydrogen Intercalation Wave Dynamics in Palladium Nanocrystals Revealed by Liquid-Phase Transmission Electron Microscopy

Solute-intercalation-induced phase separation creates spatial heterogeneities in host materials, a phenomenon ubiquitous in batteries, hydrogen storage, and other energy devices. Despite many efforts, probing intercalation processes at the atomic scale has been a significant challenge. By utilizing liquid-phase transmission electron microscopy (TEM), we study hydrogen (de)intercalation in palladium nanocrystals as a model system and have achieved unprecedented atomic-resolution imaging of hydrogen intercalation wave dynamics. Our observations reveal that intercalation wave mechanisms, instead of shrinking-core mechanisms, prevail at ambient temperature for palladium nanocubes ranging from ∼60 nm down to ∼10 nm. Systematic image analysis uncovers the atomic evolution of the hydrogen intercalation wave, transitioning from nonplanar and inclined boundaries to those closely aligned with {100} planes. Our kinetic Monte Carlo simulations demonstrate that the observed intercalation wave dynamics correspond to sorption pathways minimizing the lattice mismatch strain at the phase boundary. In conclusion, unveiling the atomic intercalation pathways holds profound implications for engineering intercalation-mediated devices and advancements in energy sciences.

Lee, Daewon [Lawrence Berkeley National Laboratory↗