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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unraveling Enhanced Superconductivity in Single-Layer FeSe through Substrate Surface Terminations

Single-layer FeSe on SrTiO 3 (001) substrates shows a superconducting transition temperature much higher than that of bulk FeSe, which has been attributed to factors such as electron doping, interfacial electron–phonon coupling, and electron correlations. To pinpoint the primary driver, we grew single-layer FeSe films on SrTiO 3 (001) substrates with coexisting TiO 2 and SrO surface terminations. Scanning tunneling spectroscopy revealed a larger superconducting gap (17.0 meV) on the TiO 2 -termination than on the SrO-termination (10.5 meV). Tunneling spectroscopy also showed a larger work function on the SrO surface, resulting in reduced charge transfer to FeSe, as confirmed by angle-resolved photoemission spectroscopy. Scanning transmission electron microscopy further revealed distinctive interfacial atomic-scale structures, with the Se–Fe–Se tetrahedral angle changing from 109.5° on the SrO-termination to 104.9° on the TiO 2 -termination. Compared to dynamical mean field theory calculations, our results indicate that enhanced superconductivity in single-layer FeSe/TiO 2 arises from optimal electron correlations, in addition to sufficient charge transfer from the substrate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Percolative phase transition in few-layered MoSe 2 field-effect transistors using Co and Cr contacts

The metal-to-insulator phase transition (MIT) in two-dimensional (2D) materials under the influence of a gating electric field has revealed interesting electronic behavior and the need for a deeper fundamental understanding of electron transport processes, while attracting much interest in the development of next-generation electronic and optoelectronic devices. Although the mechanism of the MIT in 2D semiconductors is a topic under debate in condensed matter physics, our work demonstrates the tunable percolative phase transition in few-layered MoSe 2 field-effect transistors (FETs) using different metallic contact materials. Here, we attempted to understand the MIT through temperature-dependent electronic transport measurements by tuning the carrier density in a MoSe 2 channel under the influence of an applied gate voltage. In particular, we have examined this phenomenon using the conventional chromium (Cr) and ferromagnetic cobalt (Co) as two metal contacts. For both Cr and Co, our devices demonstrated n-type behavior with a room-temperature field-effect mobility of 16 cm 2 V −1 s −1 for the device with Cr-contacts and 92 cm 2 V −1 s −1 for the device with Co-contacts, respectively. Further, with low temperature measurements at 50 K, the mobilities increased significantly to 65 cm 2 V −1 s −1 for the device with Cr and 394 cm 2 V −1 s −1 for the device with Co-contacts. By fitting our experimental data to the percolative phase transition theory, the temperature-dependent conductivity data show a transition from an insulating-to-metallic behavior at a bias of ∼28 V for Cr-contacts and ∼20 V for Co-contacts. This cross-over of the conductivity can be attributed to an increase in carrier density as a function of the gate bias in temperature-dependent transfer characteristics. By extracting the critical exponents, we find that the transport behavior in the device with Co-contacts aligns closely with the 2D percolation theory. In contrast, the devices with Cr-contacts deviate significantly from the 2D limit at low temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ForceFinder

SAND2025-11750O ForceFinder extends the Structural Dynamics Python Libraries (SDynPy) with comprehensive tools for inverse source estimation (ISE) tasks via frequency response function (FRF) matrix inversion. The software is designed for transfer path analysis and multiple-input/multiple-output (MIMO) vibration control problems. It allows users to estimate sources through various algorithms, from the basic Moore-Penrose pseudo-inverse to statistical learning methods such as Tikhonov regularization via an L-curve and elastic net regularization via an information criterion. ForceFinder uses an object-oriented framework, where all components of the ISE problem—such as FRFs, responses, and transformations—are stored in a "SourcePathReceiver" object. This software can be applied to any noise and vibration problem. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Carter, Steven [Sandia National Lab. (SNL-CA), Liv↗
DOE OSTI2025

Refining NEAMS MARVEL Reactor Model Accuracy

This report outlines the progress of Idaho National Laboratory (INL) in improving the fidelity of the multiphysics model of the Microreactor Applications Research Validation and Evaluation (MARVEL) reactor developed in FY24. The multiphysics model firstly developed in FY24 leverages three single-physics models coupled via the MOOSE’s MultiApps and Transfer systems. The first single-physics model, that functions as the driver application, leverages Griffin to model the neutron transport in the core through the discontinuous finite element (DFEM) discrete ordinates solver (SN). The second single-physics model uses BISON to compute the solid temperature in the reactor. Finally, the System Analysis Module (SAM) was used to model the flow of the sodium-potassium eutectic in the primary loop. In this report we detail the following improvement and enhancements: • An updated mesh leveraging the latest feature in the reactor module (see Section 3.1.).

42 - ENGINEERING↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2026

Assessing Structural, Thermal, and Functional Characteristics of Marigold Flower Protein as a Sustainable Food Ingredient

The demand for sustainable and alternative protein sources has been on the rise, driving interest in the valorization of underutilized plants. This study evaluated Calendula officinalis (marigold), a common floral waste, as a sustainable alternative protein source for the food industry. The primary objective of this study was to investigate the physicochemical properties of protein fractions from Calendula officinalis flower to evaluate their potential as a novel protein ingredient. Extraction of the Calendula officinalis flower yielded 92.17% of the crude protein. A sequential extraction of albumin, globulin, glutelin, and prolamin from marigold flower revealed albumin as the dominant fraction (65.47%) and exhibited the highest protein functionality, including water-holding capacity (2.37 g/g), oil-holding capacity (2.49 g/g), and emulsifying capacity (65.22 mL/g). Compared with other protein fractions, glutelin showed a relatively high emulsifying and foaming capacity (EC: 59.13 mL/g; FC: 16.23%). Differential scanning calorimetry revealed high thermal stability for albumin (T p = 105.28 °C) and glutelin (T p = 97.6 °C). Sodium Dodecyl Sulfate–Polyacrylamide Gel Electrophoresis (SDS-PAGE) and Liquid Chromatography–Mass Spectrometry (LC-MS) confirmed the presence of abundant low-molecular-weight polypeptides (<37 kDa), which enhanced emulsification, while scanning electron microscopy revealed porous structures aligned with hydration properties. Antioxidant activity was higher in albumin and glutelin, linked to surface hydrophobicity. LC-MS/MS identified 33 short-chain proteins, including oxidoreductase proteins and lipid-transfer proteins. Findings highlight marigold flower proteins as a sustainable, functional ingredient for a diverse range of food applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Designing Physicochemically‐Ordered Interphases for High‐Performance Composites

To enhance the mechanical properties of carbon fiber‐reinforced polymer composites, a physicochemical scaffold is designed incorporating microscopically architected chemically reactive nanofibers that act as a multiscale bridge between the carbon fibers and the matrix. Thermally activated nanofibers leverage their morphologically driven mechanochemical properties to form covalent bonds with adjacent polymer molecules, creating a co‐continuous network that dramatically enhances fiber‐matrix load transfer. By meticulously controlling the nanofiber architecture through variable surface area, functional group availability, and polymer chain alignment effects, the extent of covalent bonding between nanofibers and the matrix is manipulated ultimately resulting in improved carbon fiber‐matrix adhesion. Further, the concept was validated using polyacrylonitrile nanofibers within an acrylonitrile butadiene styrene matrix in a discontinuous carbon fiber‐reinforced composite system. Nanomechanical studies using atomic force microscopy and low‐field nuclear magnetic resonance spectroscopy confirmed immobilized, chemically transferred, and ordered nanostructures at the interphase. The resulting composites demonstrated ≈56% and ≈175% improvements in tensile strength and toughness, respectively, compared to composites without nanofiber. Comprehensive thermal, rheological, and X‐ray scattering analyses, along side all‐atomic molecular dynamics simulations, revealed the fundamental mechanisms behind these improvements in mechanical behavior. The versatility and efficacy of the approach have the potential to address longstanding interphase challenges in the composite industry.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Chirality transfer from chiral perovskite to molecular dopants via charge transfer states

Chiral perovskites are semiconductors with broken mirror symmetries. Their photo responses are often constrained in the UV range. In this work, we demonstrate that doping 2,3,5,6-Tetrafluoro-7,7,8,8-tetracyanoquinodimethane in the chiral perovskite matrix introduces a visible light absorption feature through the emerging charge-transfer electronic states. These charge-transfer states exhibits circular dichroism inherited from the chiral host, indicating effective chirality transfer from host to guest component via electronic coupling. Quantum-chemical modeling identifies a strong wave function overlap between an electron and a hole of the guest-host in a closely packed crystal configuration promoting the charge transfer state’s optical activity. We further integrate the doped chiral perovskite film into photodetectors and demonstrate a selective detection of circularly polarized light in both UV and visible regions. Our results suggest a universal approach of introducing visible photo absorption states to the chiral matrix to broaden the optical active range while enhancing the electrical conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effects of Proton Irradiation on the Performance of Skipper CCDs

Skipper CCDs are a mature detector technology that has been suggested for future space telescope instruments requiring sub-electron readout noise in the near-ultraviolet to the near-infrared. While modern skipper CCDs inherit from the radiation-tolerant p-channel detectors developed by LBNL, the effects of high doses of ionizing radiation on skipper CCDs (such as those expected in space) remains largely unmeasured. We report preliminary results on the performance of p-channel skipper CCDs following irradiation with 217-MeV protons at the Northwestern Medicine Proton Center. The total nonionizing energy loss (NIEL) experienced by the detectors exceeds 6 years at the Sun-Earth Lagrange Point 2 (L2). We demonstrate that the skipper amplifier continues to function as expected following this irradiation. Owing to the low readout noise of these detectors, controlled irradiation tests can be used to sensitively characterize the charge transfer inefficiency, dark current, and the density and time constants of charge traps as a function of proton fluence. We conclude with a brief outlook toward future tests of these detectors at other proton and gamma-ray facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Peregrine Software Development: Report on the Code Conversion From Python to C++

This work package seeks to convert the Peregrine software tool from its original Python implementation to a production version based on the C++ language. Peregrine is a powerful research platform with a multitude of advanced data analytics and data visualization functionalities. Developed by scientists to explore multimodal and multidimensional data related to the production of components using powder bed additive manufacturing processes, the tool implements state-of-the-art algorithms to assist machine users in making build or part quality determinations. Given that Peregrine is data-intensive, the goal of this conversion is to enhance the tool’s flexibility and interactivity and reduce the number of code dependencies to facilitate its deployment as part of the ongoing technology transfer campaign. This brief document provides an overview of Peregrine’s functionalities and capabilities, along with a detailed description of the core functionalities that have been implemented to date in the new C++ version. This document serves as a development update at the end of the first year of the ongoing conversion and will be regularly updated as progress continues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tuning the Lifetimes of Photoinduced Deligation in a Metal–Organic Framework via Linker Functionalization

Recently photoinduced dynamic ligation in a metal–organic frameworks (MOFs) was reported, where a long-lived charge-transfer excited state (ca. 30 μs) featuring partial dissociation between the carboxylate linker and metal-based node was probed by time-resolved infrared (TRIR) spectroscopy. The study offers a new mechanistic perspective to evaluate the potential contribution from the excited state molecular configuration to the performance of MOF photocatalysts. In this work, by employing MIL-101(Fe) as the study platform, we have further explored the influence of intramolecular interactions on the stability of relevant excited states and demonstrated the effective tuning of their lifetimes through the incorporation of different functional groups into the system. The correlations between the varied excited state lifetimes and coordination configurations with specific functional groups (−NH 2 or −NO 2 ) was inferred from the analyses of infrared spectroscopic data and theoretical calculations, revealing the essential role of the intramolecular interactions (i.e., between the added functional groups and the carboxylate group) in the modulation of system energetics. Overall, the work presents a pathway to tune the excited state dynamics and expands the knowledge regarding the photoinduced dynamic ligation in carboxylate-based MOFs.

excited states↗
DOE OSTI2024

Real-space local self-motion of protonated and deuterated water

Here, we report on the self-part of the Van Hove correlation function, the correlation function describing the dynamics of a single molecule, of water and deuterated water. The correlation function is determined by transforming inelastic scattering spectra of neutrons or x rays over a wide range of momentum transfer Q and energy transfer E to space R and time t. The short-range diffusivity is estimated from the Van Hove correlation function in the framework of the Gaussian approximation. The diffusivity has been found to be different from the long-range macroscopic diffusivity, providing information about local atomic dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A novel transient infrared imaging method for non-intrusive, low-cost, fast, and accurate air leakage detection in building envelopes

Air leakage through the building envelope in the U.S. accounts for about four quads of energy annually, costing approximately $40 billion per year. However, a high-fidelity and non-intrusive method to detect air leakage has not been demonstrated to date. Here, in this paper, we propose a novel non-intrusive and low-cost method called Transient Infrared (IR) Imaging (TIRI) that can rapidly and accurately identify air leakage locations and relative rates on building envelopes. When the interior and exterior temperatures are different, and a small internal pressure pulse is created by HVAC, the temperature at locations with air leakages will change rapidly, while the areas without a leakage do not change. Based on a heat transfer model, we have derived the temperature change as a function of time after the HVAC is turned on. By tracking the temperature change, which depends on leakage rate and size, we have obtained the air leakage map in the case studies. Using an exterior door as an example, we took transient IR images in different seasons and different times of the day, and successfully obtained the leakage map in all the scenarios. Successfully obtained the air leakage map even when the indoor-outdoor air temperature difference is as small as 2 °C. We have also realized a detection speed of 10s and demonstrated that this method also worked for windows, which have mirror-like IR reflections. Our TIRI method will accelerate the improvement of airtightness in buildings, save building energy, and help reduce greenhouse gas emissions.

42 ENGINEERING↗
DOE OSTI2024

Attosecond Probing of Coherent Vibrational Dynamics in CBr 4

A coherent vibrational wavepacket is launched and manipulated in the symmetric stretch (a1) mode of CBr 4 , by impulsive stimulated Raman scattering (ISRS) from nonresonant 400 nm laser pump pulses with various peak intensities on the order of tens of 10 12 W/cm 2 . Extreme ultraviolet (XUV) attosecond transient absorption spectroscopy (ATAS) records the wavepacket dynamics as temporal oscillations in XUV absorption energy at the bromine M 4,5 3d 3/2,5/2 edges around 70 eV. The results are augmented by nuclear timedependent Schrödinger equation simulations. Slopes of the (Br 3d 3/2,5/2 ) –1 10a 1 * core-excited state potential energy surface (PES) along the a 1 mode are calculated to be –9.4 eV/Å from restricted open-shell Kohn–Sham calculations. Using analytical relations derived for the small-displacement limit and the calculated slopes of the core-excited state PES, a deeper insight into the vibrational dynamics is obtained by retrieving the experimental excursion amplitude of the vibrational wavepacket and the amount of population transferred to the vibrational first-excited state as a function of pump-pulse peak intensity. Experimentally, the results show that XUV ATAS is capable of resolving oscillations in the XUV absorption energy on the order of a few to tens of meV with tens of femtosecond time precision. This corresponds to change in C–Br bond length on the order of 10 –4 to 10 –3 Å. The results and the analytic relationships offer a clear physical picture, on multiple levels of understanding, of how the pump-pulse peak intensity controls the vibrational dynamics launched by nonresonant ISRS in the small-displacement limit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

How Does Water Dissociation Work in Bipolar Membranes?

Bipolar membranes (BPMs) create counteracting spatial gradients of pH and electrostatic potential in electrochemical systems, enabling applications in pH regulation, electrocatalysis, and separations. At the polarized junction of a BPM the water dissociation (WD, 2H2O ⇌ H3O+ + OH-) reaction can be driven, but it remains poorly understood. In this Perspective, we integrate molecular insights from bulk-water autoionization and the associated field effects with continuum descriptions of BPM electrostatics and experimental WD kinetic analyses to describe possible mechanisms of voltage-driven WD. Pristine BPM junctions highlight both the limits of primarily electric-field-driven WD and the practical challenges of junction stability at extreme reverse bias. Introducing heterogeneous catalyst layers, commonly metal oxides and graphene oxides, accelerates WD by orders of magnitude through hypothesized coupled effects in which surface acid-base functionality and high-density hydroxyl sites mediate proton-transfer steps, and catalyst mobile electronic/ionic charges redistribute the junction electric potential drop to shape the local electric fields and reactive microenvironments. Kinetic analyses suggest two regimes of heterogeneous WD mechanism, including field-driven ordering of interfacial water and a Second-Wien-Effect dissociation-barrier lowering. We conclude by defining the key unknown variables (local pH, electrostatic potential, catalyst charge state and relationships among mechanisms) and outlining experimental and multiscale modeling strategies needed for predictive WD catalysis and for controlling related ion-transfer reactions.

Wu, Yifan↗
DOE OSTI2025

Soft X-ray tomography reveals variations in B. subtilis biofilm structure upon tasA deletion

Bacterial biofilms are complex cell communities within a self-produced extracellular matrix, crucial in various fields but challenging to analyze in 3D. We developed a "biofilm-in-capillary" growth method compatible with full-rotation soft X-ray tomography, enabling high-resolution 3D imaging of bacterial cells and their matrix during biofilm formation. This approach offers 50 nm isotropic spatial resolution, rapid imaging, and quantitative native analysis of biofilm structure. Using Bacillus subtilis biofilms, we detected coherent alignment and chaining of wild-type cells towards the oxygen-rich capillary tip. In contrast, the ΔtasA genetic knock-out showed a loss of cellular orientation and changes in the extracellular matrix. Adding TasA protein to the ΔtasA strain restored matrix density and led to cell assembly compaction, but without the chaining observed in wild-type biofilms. This scalable and transferable approach opens new avenues for examining biofilm structure and function across various species, including mixed biofilms, and response to genetic and environmental factors.

59 BASIC BIOLOGICAL SCIENCES↗