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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Enhancing actuation control in monolithic liquid crystal elastomer films with dual heat and light responsiveness

This study presents a dual heat and light-responsive monolithic liquid crystal elastomers (LCEs) film designed to enhance actuation control. The LCE films were capable of various motion types, including curvature reversal, oscillation, and sustainable flipping. By incorporating an azobenzene compound, the films exhibited additional functionalities such as enhanced curvature reversal, accelerated oscillation, and the ability to lock continuous flipping motion upon light stimulation. Furthermore, by adjusting the aspect ratio (AR) of a single film, different thermal motion states were realized, demonstrating the flexibility of this approach. Observations using an NIR camera confirmed temperature fluctuations corresponding to thermal exchange, and the influence of UV light on motion regulation was quantitatively analyzed. In conclusion, the ability to regulate motion through dual stimuli paves the way for improved dynamic motion control and thermal management in advanced robotic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Numerical Simulation of Light to Heat Conversion by Plasmonic Nanoheaters

Plasmonic nanoparticles are widely recognized as photothermal conversion agents, i.e., nanotransducers or nanoheaters. Translation of these materials into practical applications requires quantitative analyses of their photothermal conversion efficiencies (η). However, the value of η obtained for different materials is dramatically influenced by the experimental setup and method of calculation. Here, we evaluate the most common methods for estimating η (Roper’s and Wang’s) and compare these with numerical estimates using the simulation software ANSYS. Experiments were performed with colloidal gold nanorod solutions suspended in a hanging droplet irradiated by an 808 nm diode laser and monitored by a thermal camera. The ANSYS simulations accounted for both heating and evaporation, providing η values consistent with the Wang method but higher than the Roper approach. This study details methods for estimating the photothermal efficiency and finds ANSYS to be a robust tool where experimental constraints complicate traditional methods.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Solution-Processed Temperature-Adaptive Radiative Paint as a Thermal Imaging Sensitizer

Thermography detects mid-infrared radiation from surfaces based on the Stefan-Boltzmann law, mapping surface temperatures and potentially revealing subsurface thermal activity. Recent developments offer an alternative strategy to traditional camera-based improvements: a thermal imaging sensitizer (TIS) coating whose emissivity increases sharply with local temperature, amplifying small thermal variations into high-contrast signals. Existing TIS structures are nanofabricated solid membranes and face significant challenges in fabrication complexity. Here, in this study, we present a solution-processed, liquid form of TIS, termed temperature-adaptive radiative paint (TARP), to address these limitations. TARP offers drastically reduced fabrication costs, scalability to large areas, applicability to curved surfaces, and an extended operating temperature range, while maintaining the function of temperature amplification. Application of TARP enhances small temperature contrast by more than 3 times, substantially improving ambient thermography and enabling broader applications such as detection of structural defects and hot spots in electronic components.

paint↗
DOE OSTI2025

Automation-Accelerated Electrolyte Design Mitigates Solubility Competition between Redox-Active Molecules and Supporting Salts

In nonaqueous redox-flow batteries (NRFBs), redox-active organic molecules (ROMs) and supporting salts compete for solvation sites, limiting achievable energy density. We combine automated high-throughput experimentation (HTE) with camera-based saturation monitoring and quantitative NMR to measure paired (ROM, salt) solubilities across single and mixed organic solvents. Using 2,1,3-benzothiadiazole (BTZ) with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) as a model system, we find that a binary m-xylene/acetonitrile mixture dissolves ≈3 M of both BTZ and LiTFSI─surpassing the previously reported 2 M ceiling for neat acetonitrile─by leveraging complementary solvation (MX is BTZ-philic and salt-phobic; ACN stabilizes LiTFSI). A random-forest model (RMSE ≈ 0.24) trained on solvent descriptors highlights log P and salt concentration as dominant predictors and predicts MX/ACN ≈0.3/0.7 (v/v) to be near-optimal. These formulations retain practical viscosity and ∼5 mS·cm –1 conductivity at high loading. In conclusion, the workflow provides a reproducible, data-centric route to NRFB electrolyte design and motivates an open, standardized dual-solute solubility resource for accelerated electrolyte discovery.

Electrolytes↗
DOE OSTI2025

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗
DOE OSTI2024

Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama

Abstract Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309 , 2022, https://doi.org/10.1029/2021gl097070 ). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Integrated photonic encoder for low power and high-speed image processing

Abstract Modern lens designs are capable of resolving greater than 10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made data acquisition rates of Terapixel/second a real possibility. The main bottlenecks preventing such high data-rate systems are power consumption and data storage. In this work, we show that analog photonic encoders could address this challenge, enabling high-speed image compression using orders-of-magnitude lower power than digital electronics. Our approach relies on a silicon-photonics front-end to compress raw image data, foregoing energy-intensive image conditioning and reducing data storage requirements. The compression scheme uses a passive disordered photonic structure to perform kernel-type random projections of the raw image data with minimal power consumption and low latency. A back-end neural network can then reconstruct the original images with structural similarity exceeding 90%. This scheme has the potential to process data streams exceeding Terapixel/second using less than 100 fJ/pixel, providing a path to ultra-high-resolution data and image acquisition systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

In situ electron microscopy: atomic-scale dynamics of metal oxidation and corrosion

Corrosion degrades metals through complex microscopic processes that traditional methods often fail to capture. In-situ transmission electron microscopy (TEM) bridges this gap by providing real-time atomic-scale imaging of oxidation and corrosion dynamics. Gas-phase TEM uncovers critical oxidation mechanisms like oxide nucleation and alloying effects, while liquid-phase TEM tracks corrosion initiation. Coupled with emerging techniques like ultrafast direct electron detection cameras, these advancements promise unprecedented resolution in understanding material degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhancing spectroscopy and microscopy with emerging methods in photon correlation and quantum illumination

Quantum optics has led to important advancements in our ability to prepare and detect correlations between individual photons. Its principles are increasingly translated into nanoscale characterization tools, furthering methods in spectroscopy, microscopy and metrology. Here, in this Review, we discuss the rapid progress in this field driven by advanced technologies of single-photon detectors and quantum-light sources, including time-resolved single-photon counting cameras, superconducting nanowire single-photon detectors and entangled photon sources of increasing brightness. We emphasize emerging applications in super-resolution microscopy, measurements below classical noise limits and photon-number-resolved spectroscopy—a powerful paradigm for the characterization of nanoscale electronic materials. We conclude by discussing key technological challenges and future opportunities in materials science and bionanophotonics alike.

Tsao, Chieh [University of California, Berkeley, C↗
DOE OSTI2024

Image processing tools for petabyte-scale light sheet microscopy data

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson–Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantifying motion blur by imaging shock front propagation with broadband and narrowband X-ray sources

Time-integrated radiography using MeV Bremsstrahlung X-ray sources is the norm for imaging during system-level testing of components and structures under dynamic condition. One source of error in the analysis of the time-integrated radiography data sets stems from motion blur which smears out sharp interfaces to a greater degree with longer exposure times, which become necessary to provide sufficient signal-to-noise with low X-ray penetration of objects of interest. To quantify motion blur, a 1D shock wave through PMMA was investigated experimentally at The Dynamic Compression Sector at The Advanced Photon Source (DCS@APS) with tapered broadband and 25.46 ± 1.06 keV narrowband X-rays. Four cameras with different exposure times were used for each experiment to compare the effect that exposure time has on motion blur. In addition, our methodology to accurately simulate motion blur in terms of transmission and shape is presented and compared to our experimental results and quantified. There is a high level of agreement between the experimental and simulation results across the range of data sets investigated in this study with a percent difference range of 0.29–1.31% for the four shots. The methodology of this work serves as a steppingstone towards a physically validated model that could be used in conjunction with experimental results to deconvolve physical parameters, densities, and interfaces of interest in a way that would not be possible with experimental results alone.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Advances in detection for neutron reflectometry with time-resolved imaging detectors

Thermal neutron detection in neutron scattering science is a challenging endeavour due to a limited number of technologies which are sensitive to these weakly interacting particles. While many improvements to conventional detectors are underway at various facilities, there is a great opportunity to make a leap in performance by combining the spatial resolution benefits of imaging and the temporal resolution and background discrimination of event-driven radiation detectors. This idea has been realized by using a neutron sensitive scintillator read out by a single-photon sensitive camera based on a Timepix3 ASIC. We demonstrate how such data-driven imaging sensors can enable unprecedented performance in neutron reflectometry using the ASTERIX instrument at the Los Alamos Neutron Scattering Center. Several samples were measured with both the new and a conventional 3 He detector systems. The results from this work demonstrate that these imaging based systems can satisfy performance parameters for the future QIKR reflectometer to be built at the Second Target Station at Oak Ridge National Laboratory. Further improvements to the detector are already underway which will allow streamlined and expedited experiments. We demonstrate at least a two order of magnitude increase in detection rate at an acceptable dead time and introduce a new way of tuning the detector efficiency using light collecting optics to accommodate highly intense direct beams which cannot be measured with any current detectors without severe attenuation. This will allow measurements of complete reflectometry profiles and using a single sample measurement combined with fewer direct beam calibration measurements on QIKR and potentially other reflectometers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Magnetocaloric effect in Mn-rich Heusler-derived alloys for room temperature-based applications

Magnetic refrigeration-based technologies rely on the magnetocaloric properties of materials and are crucial for improving energy efficiency and for supporting clean environments. However, materials possessing significant magnetocaloric properties that can be used for room temperature-based applications are still lacking. Heusler alloys (such as Mn–Ni–Ga) show giant magnetocaloric effects, which can be further improved by tuning their composition. Herein, we optimized the ratio of Ni to Ga to achieve an alloy with unique magnetocaloric properties. Here, the alloy demonstrated a substantial magnetocaloric effect, attributed to its narrow temperature range for structural and magnetic phase transitions (near room temperature with minimal hysteresis). Structural phase changes were also observed through high-resolution transmission electron microscopy. Optimum entropy changes, calculated from isothermal magnetization curves (4 Tesla magnetic field), were found to be 24.50 J kg −1 K −1 , which is higher than that of state-of-the-art alloys. Experimental demonstration of the magnetocaloric effect (refrigeration cycle) was also carried out using a thermal imaging camera. Furthermore, first-principles calculations were conducted to validate the experimental findings, specifically focusing on the compositional effects on the structural transitions and magnetic properties of the investigated MNG alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗
DOE OSTI2023

AutoSourceID-Classifier: Star-galaxy classification using a convolutional neural network with spatial information

Aims.Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods.The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results.We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Astronomy & Astrophysics↗
DOE OSTI2024

The impact of environment on size: Galaxies are 50% smaller in the Fornax Cluster compared to the field

Size is a fundamental parameter for measuring the growth of galaxies and the role of the environment on their evolution. However, the conventional size definitions used for this purpose are often biased and miss the diffuse, outermost signatures of galaxy growth, including star formation and gas accretion. We address this issue by examining low surface brightness truncations or galaxy ‘edges’ as a physically motivated tracer of size based on star formation thresholds. Our total sample consists of ∼900 galaxies with stellar masses ranging from 10 5 M ⊙ < M ⋆ < 10 11 M ⊙ . This sample of nearby cluster, group satellite, and nearly isolated field galaxies was compiled using multi-band imaging from the Fornax Deep Survey, deep IAC Stripe 82, and Dark Energy Camera Legacy Surveys. We find that the edge radii scale as R edge ∝ M ⋆ 0.42 , with a very small intrinsic scatter (∼0.07 dex). The scatter is driven by the morphology and environment of galaxies. In both the cluster and field, early-type dwarfs are systematically smaller by approximately 20% compared to late-type dwarfs. However, galaxies in the Fornax cluster are the most impacted. At a fixed stellar mass, edges in the cluster can be found at about 50% smaller radii, and the average stellar surface density at the edges is a factor of two higher, ∼1 M ⊙ /pc 2 . Our findings support the rapid removal of loosely bound neutral hydrogen (H I ) in hot, crowded environments, which truncates galaxies outside-in earlier, preventing the formation of more extended sizes and lower density edges. Our results highlight the importance of deep imaging surveys to the study of low surface brightness imprints of the large-scale structure and environment on galaxy evolution.

Astronomy & Astrophysics↗
DOE OSTI2025

Millimeter-wave observations of Euclid Deep Field South using the South Pole Telescope: A data release of temperature maps and catalogs

Context. The South Pole Telescope third-generation camera (SPT-3G) has observed over 10,000 square degrees of sky at 95, 150, and 220 GHz (3.3, 2.0, 1.4 mm, respectively) and will significantly overlap the ongoing 14,000 square-degree Euclid Wide Survey. The Euclid collaboration recently released Euclid Deep Field South (EDF-S) observations of 23 square degrees at wide field depths in the first quick data release (Q1). Aims. With the goal of releasing complementary millimeter-wave data and encouraging legacy science, we performed dedicated observations of a 57-square-degree field overlapping the EDF-S. Methods. The observing time totaled 20 days, and we reached noise depths of 4.3, 3.8, and 13.2 $μ$K-arcmin at 95, 150, and 220 GHz, respectively. Results. In this work we present the temperature maps and two catalogs constructed from these data. The emissive source catalog contains 601 objects (334 inside EDF-S) with 54% synchrotron-dominated sources and 46% thermal dust emission-dominated sources. The 5$σ$ detection thresholds are 1.7, 2.0, and 6.5 mJy in the three bands. The cluster catalog contains 217 cluster candidates (121 inside EDF-S) with median mass $M_{500c}=2.12 \times 10^{14} M_{\odot}/h_{70}$ and median redshift $z$ = 0.70, corresponding to an order-of-magnitude improvement in cluster density over previous tSZ-selected catalogs in this region (3.81 clusters per square degree). Conclusions. The overlap between SPT and Euclid data will enable a range of multiwavelength studies of the aforementioned source populations. This work serves as the first step toward joint projects between SPT and Euclid and provides a rich dataset containing information on galaxies, clusters, and their environments.

Archipley, M. [Chicago U., Astron. Astrophys. Ctr.↗
DOE OSTI2024

Source localization for neutron imaging systems using convolutional neural networks

The nuclear imaging system at the National Ignition Facility (NIF) is a crucial diagnostic for determining the geometry of inertial confinement fusion implosions. The geometry is reconstructed from a neutron aperture image via a set of reconstruction algorithms using an iterative Bayesian inference approach. An important step in these reconstruction algorithms is finding the fusion source location within the camera field-of-view. Currently, source localization is achieved via an iterative optimization algorithm. In this paper, we introduce a machine learning approach for source localization. Specifically, we train a convolutional neural network to predict source locations given a neutron aperture image. We show that this approach decreases computation time by several orders of magnitude compared to the current optimization-based source localization while achieving similar accuracy on both synthetic data and a collection of recent NIF deuterium–tritium shots.

47 OTHER INSTRUMENTATION↗