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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 OSTI2022

A Bioinspired Artificial Injury Response System Based on a Robust Polymer Memristor to Mimic a Sense of Pain, Sign of Injury, and Healing

Abstract Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human–robot interactions. However, more advanced capabilities, such as human‐like self‐protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK‐800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK‐800/Pt have outstanding switching endurance >10 6 cycles, orders of magnitude higher than any other two‐terminal polymer/organic memristors in literature (typically 10 2 –10 3 cycles). In situ conductive atomic force microscopy is employed to dynamically switch individual filaments, which demonstrates that conductive filaments correlate with polymer grain boundaries and FK‐800 has superior morphological stability under repeated switching cycles. It is hypothesized that the high thermal stability and high elasticity of FK‐800 contribute to the stability under local Joule heating associated with electrical switching. To mimic biological nociceptors, four signature nociceptive characteristics are demonstrated: threshold triggering, no adaptation, relaxation, and sensitization. Lastly, by integrating a triboelectric generator (artificial mechanoreceptor), memristor (artificial nociceptor), and light emitting diode (artificial bruise), the first bioinspired injury response system capable of sensing pain, showing signs of injury, and healing, is demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗
DOE OSTI2025

Accelerated and heterogeneous corrosion of Cr-doped uranium nitride fuel pellets

The steam oxidation of Cr-doped UN fuel pellets is analyzed during sequential isothermal holds up to 720 °C. In situ neutron diffraction results show how Cr is accommodated in a secondary U 2 CrN 3 phase, leading to the formation of a duplex UN/U 2 CrN 3 microstructure. Under corrosion, the oxidation of the two phases begins at 400 °C for UN and 430 °C for U 2 CrN 3 , respectively. Because the UN phase is preferentially oxidized in the presence of U 2 CrN 3 , addition of Cr in UN based nuclear fuel is found to accelerate the corrosion rate. At 430 °C the oxidation of UN in the UN/U 2 CrN 3 microstructure is ~ 5 times faster than pure UN, increasing to ~19 times faster at 460 °C. The oxidation of U 2 CrN 3 produces UO 2 via the formation of two transient intermediate phases. In situ neutron diffraction enables oxidation processes of UN and U 2 CrN 3 components to be followed separately within the two-phase system.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Livermore tomography tools: Accurate, fast, and flexible software for tomographic science

Livermore Tomography Tools (LTT) is a customizable scientific software package that enables a broad range of research and development efforts into computed tomography (CT). Here, it was developed to process x-ray and neutron CT data accurately and rapidly from raw detector counts to reconstructed volumes with the flexibility to handle many special cases. LTT fulfills long-term CT software goals to provide quantitatively accurate results reported in physical units (e.g., mm -1 or cm -1 ) while exploiting all available computational advantages to maximize speed. Written in C/C++ with support for multiple CPUs and GPUs, LTT runs on many computing platforms (Linux/Unix, Windows, and Mac; laptops to supercomputers). As a result, LTT can:process data acquired from various custom-built and commercially available CT scanners, model and simulate x-ray and neutron interactions to encourage algorithm prototyping, and allow for rapid insertion of the latest algorithms.We describe LTT’s software architecture, user interfaces, and its 88 algorithms (as of this writing) for pre-processing, reconstruction, post-processing, and simulation that support many scanner geometries (parallel-, fan-, cone-beam, and custom). Several applications are presented that illustrate LTT’s accuracy, speed, and flexibility relative to other solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A compact light shield for the Psyche gamma-ray spectrometer

A compact, low-mass light shield has been designed for the Psyche space mission high-purity germanium gamma-ray spectrometer. The spectrometer will be vented to space, which can allow solar photons to enter the cryostat and cause charge-induced noise. The light shield was designed to block more than 99.9% of solar photons while maintaining high molecular conductance to space vacuum. COMSOL simulations and experiments were performed to characterize light shield photon attenuation and molecular conductance. Finally, the light shield was integrated onto the gamma-ray spectrometer and photon suppression and vacuum performance were demonstrated.

(16) Psyche↗
DOE OSTI2024

The role of AI in detecting and mitigating human errors in safety-critical industries: A review

For safety-critical industries, human error (HE) presents continual risks to system productivity, reliability and safety. Artificial intelligence (AI) and machine learning (ML) methods have emerged as promising approaches to understand, categorize and mitigate the risk of HE in safety-critical industries. Furthermore, this review offers an examination of the current landscape regarding the utilization of AI/ML with regards to HE in safety-critical industries, categorizing literature into descriptive modeling, predictive modeling, prescriptive modeling, and generative modeling techniques. Additionally, the review aims to provide insights regarding themes in literature, challenges, and future research directions. Findings of the review suggest that AI/ML methods can prove useful in addressing the HE problem across safety-critical industries.

42 ENGINEERING↗
DOE OSTI2025

Leveraging Radiofrequency Identification Success Beyond Hazardous Material Inventory Management at a National Laboratory

Effective inventory management can be overshadowed by conflicting priorities in organizational procedures, particularly in research-focused institutions such as national laboratories that handle expensive, delicate, and hazardous materials. Here, this study investigated the potential of radiofrequency identification (RFID) technology, currently used for hazardous chemical inventory, in applications with higher metal interference and absorption, specifically pressure release device (PRD) compliance and nuclear container management, at Lawrence Livermore National Laboratory (LLNL). This study was done to document best practices to enhance inventory identification speeds for inventory reconciliation and inventory recall and to explore optimal configurations for RFID implementation compared to traditional manual methods of equipment management. Tests were conducted to determine the ideal RFID tag orientation (read at angles of 0°, 90°, and 270°), various container layouts (linear, separated, curved, operational), and ID methods such as manual, barcode, and RFID performing three trials per method per orientation. Results indicated that 0° was the optimal read angle for minimizing metallic interference, and the operational and curved arrangements significantly outperformed the linear and separated configurations in read speed. 3D printed mounts were developed and tested, increasing the read range of the RFID reader by up to 235% in cases of high metallic interference. The RFID technology demonstrated an average speed increase of 65% over a simplified manual identification, which supports the conclusion that RFID is a more efficient method for large hazardous inventory management and equipment reconciliation. Additionally, capturing meta-data, such as location and date, can be used to query for inventory recall and automated updating of record information.

42 ENGINEERING↗
DOE OSTI2023

Remote inspection of adversary-controlled environments

Remotely monitoring the location and enduring presence of valuable items in adversary-controlled environments presents significant challenges. In this article, we demonstrate a monitoring approach that leverages the gigahertz radio-wave scattering and absorption of a room and its contents, including a set of mirrors with random orientations placed inside, to remotely verify the absence of any disturbance over time. Our technique extends to large physical systems the application of physical unclonable functions for integrity protection. Its main applications are scenarios where parties are mutually distrustful and have privacy and security constraints. Examples range from the verification of nuclear arms-control treaties to the securing of currency, artwork, or data centers.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Optical recognition of constructs using hyperspectral imaging and detection (ORCHID)

Abstract Challenges to deep sample imaging have necessitated the development of special techniques such as spatially offset optical spectroscopy to collect signals that have travelled through several layers of tissue. However, these techniques provide only spectral information in one dimension (i.e., depth). Here, we describe a general and practical method, referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID). The sensing strategy integrates (1) the spatial offset detection concept by computationally binning 2D optical data associated with digital offsets based on selected radial pixel distances from the excitation source; (2) hyperspectral imaging using tunable filter; and (3) digital image binding and collation. ORCHID is a versatile modality that is designed to collect optical signals deep inside samples across three spatial (X, Y, Z) as well as spectral dimensions. The ORCHID method is applicable to various optical techniques that exhibit narrow-band structures, from Raman scattering to quantum dot luminescence. Samples containing surface-enhanced Raman scattering (SERS)-active gold nanostar probes and quantum dots embedded in gel were used to show a proof of principle for the ORCHID concept. The resulting hyperspectral data cube is shown to spatially locate target emitting nanoparticle volumes and provide spectral information for in-depth 3D imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Device response principles and the impact on energy resolution of epitaxial quantum dot scintillators with monolithic photodetector integration

Abstract Epitaxial quantum dot (QD) scintillator crystals with picosecond-scale timing and high light yield have been created for medical imaging, high energy physics and national security applications. Monolithic photodetector (PD) integration enables the sensing of photons generated within the waveguiding crystal and allows a wide range of scintillator-photodetector coupling geometries. Until recently, these doubly novel devices have suffered from complex, high variance responses to monoenergetic sources which significantly reduces their precision and accuracy. The principles governing the overall device response have now been discerned and embodied by an expression derived within a geometrical optics framework which considers optical properties, surface roughness and photodetector coupling geometry. Response variation due to these factors was sufficiently reduced to obtain material-related energy resolution values of 2.4% with alpha particles. These findings place energy resolution alongside luminescence timescale, photon yield, and radiation hardness as outstanding properties of these engineered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Experimental investigation of internal two-phase flow structures and dynamics of quasi-stable sheet cavitation by fast synchrotron x-ray imaging

The quasi-stable sheet cavitation produced in a small Venturi channel is investigated using a fast synchrotron X-ray imaging technique aided with conventional high speed photography. The use of X-rays instead of visible light solves cavitation opacity related issues, and X-ray phase contrast-based edge enhancement enables high-definition visualization of the internal two-phase morphology. The simultaneous acquisition of time-resolved velocity and void fraction fields through post-processing the recorded X-ray images reveals, for the first time, the complex diphasic flow structures inside the sheet cavity, which is essentially divided into 6 characteristic parts. Distinct from the current mainstream view, the globallysteady sheet cavitation is found to be characterized by a weak but constantly-existing re-entrant flow that can penetrate the entire cavity. The turbulent velocity fluctuations inside the sheet cavity are also investigated. The turbulence level in the reverse flow region is observed to be as low as in the outer main flow demonstrating the relatively steady status of the reentrant flow. Unlike the streamwise and cross-stream fluctuations, the shear stress appears to be weakly correlated with the velocity gradient. The collapse of vapor phase and the vaporization at the upstream cavity interface are found to be the primary causes of shear stress intensification.

42 ENGINEERING↗
DOE OSTI2024

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗
DOE OSTI2025

Ultra-fast single-crystal CVD diamonds in the particle time-of-flight (PTOF) detector for low yield burn-history measurements on the NIF (invited)

The Particle Time of Flight (PTOF) diagnostic is a chemical vapor deposition diamond-based detector and is the only diagnostic for measuring nuclear bang times of low yield (<1013) shots on the National Ignition Facility. Recently, a comprehensive study of detector impulse responses revealed certain detectors with very fast and consistent impulse responses with a rise time of <50 ps, enabling low yield burn history measurements. At the current standoff of 50 cm, this measurement is possible with fast 14 MeV neutrons from deuterium–tritium (DT) fusion plasmas. PTOF-inferred DT burn width numbers compare well with widths inferred from the gamma reaction history diagnostic on mid-yield (1013–1015) shots, where both systems are capable of making this measurement. These new capabilities could be extended to 2.5 MeV deuterium–deuterium neutrons from D plasmas and to even lower yield by reducing the detector standoff distance to 10 cm; a design for this is also presented.

42 ENGINEERING↗
DOE OSTI2025

Fiber-optic bolometers with high-temperature tolerance and reduced time constants for fusion plasma diagnostics

Fiber-optic bolometers (FOBs) designed for plasma radiation measurement in magnetically confined fusion environments have been previously developed and tested at the DIII-D tokamak. These FOBs utilize a silicon Fabry–Perot interferometer at the fiber tip for temperature measurement and a gold disk as a radiation absorber. This paper presents recent advancements in the development of FOBs with reduced cooling time constants and enhanced temperature tolerance. We also demonstrate high-temperature operation and report findings from irradiation tests. By incorporating a copper sensor holder as a thermal sink and integrating two closely packed sensor heads into a compact design, the cooling time constants were reduced to ∼100 ms in vacuum, while minimizing uncertainties caused by temperature gradients. The FOBs were subjected to heating at 400 °C for five hours, with no observed degradation in noise performance post-heating. High-temperature operation tests were conducted at ∼220 °C using a 404 nm square-wave modulated laser to simulate the plasma radiation. In addition, four FOBs constructed from copper-coated pure-silica fibers were fabricated and underwent irradiation testing, enduring a total γ-radiation dose of 15.2 MGy and a neutron fluence of 1.6 × 10 18 n/cm 2 . As a result, the FOBs maintained their physical integrity and the optical signal shows high visibility throughout the test.

42 ENGINEERING↗