SEARCH · Engineering Papers

Results for “Advanced Measurement Technique”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Neutron-induced capture-to-fission cross section ratio measured at LANSCE

Capture-to-fission cross section ratios are used as an alternative to absolute cross section measurements. This is due to the simplification on the calculations and the reduction of the uncertainties with respect to an absolute measurement of the cross section by eliminating experimental complications like self-absorption, beam/target overlap and non-uniformities. Different capture-to-fission reactions have been measured through the years at the Los Alamos Neutron Science Center (LANSCE) at Los Alamos National Laboratory (LANL) using the Detector for Advanced Neutron Capture Experiments (DANCE) combined with different fission detectors. Some of these are a Parallel Plate Avalanche Counter (PPAC) to detect fission fragments (FF), and the NEUtron detector array at DANCE (NEUANCE) to detect fission neutrons. As DANCE detects the γ-rays produced in capture and fission reactions, the fission instrument placed inside the DANCE cavity is used to tag the fission γ-rays for background identification and subtraction. Some examples of capture-to-fission ratio measurements performed with DANCE in the last years are the 233 U, 235 U and 239 Pu. The measurement technique, the different setups, and other potential applications of the instruments will be explained.

Nuclear Criticality Safety Program (NCSP)↗

DOE OSTI2023

Effects of knock intensity measurement technique and fuel chemical composition on the research octane number (RON) of FACE gasolines: Part 2 – Effects of spark timing

The Research and Motor Octane Number (RON, MON) characterize a fuel’s knock resistance by rating the knock intensity of a sample fuel relative to that of Primary Reference Fuels (PRF) in a Cooperative Fuel Research (CFR) Engine. A fuel’s octane number is regulated to prevent damage from autoignition leading to knocking combustion in spark-ignition engines. The operational differences between the standard RON rating and modern engine operation are explored in a three-part publication series. The previous study focused on the effects of lambda and knock characterization. This second study primarily focuses on the effects of spark timing on RON determination. Following the findings from the first publication, the knock intensity was captured by the knockmeter and by the maximum amplitude of pressure oscillations (MAPO) at the lambda of peak knock intensity and stoichiometry. Knock-limited spark advance tests were conducted for a set of seven Fuels for Advanced Combustion Engines (FACE) from the Coordinating Research Council (CRC) with varying chemical composition, PRFs, and Toluene Standardization Fuels (TSFs). For retarded spark timings, pre-spark low-temperature heat release was found for low RON PRFs. Low RON PRFs also showed knocking characteristics before reaching the center of combustion suggesting that the use of knock-limited spark advance (KLSA) was preferred over the knock-limited combustion phasing. Primarily paraffinic fuels tended towards increased pressure oscillations while dominantly aromatic fuels experienced higher pressure rise rates. A MAPO-based KLSA correlated best to Octane Index at a negative K-factor suggesting beyond RON operation despite being at otherwise RON conditions. At stoichiometry, the MAPO-based KLSA did neither correlate to RON nor Octane Index. Finally, good agreement was found between KLSA-based effective RON from this study to the MAPO-based effective RON from the first study.

10 SYNTHETIC FUELS↗

DOE OSTI2022

Sample-Efficient Adaptive Calibration of Quantum Networks Using Bayesian Optimization

All physical systems employed for quantum information tasks must act as unbiased carriers of encoded quantum states. Ensuring such indistinguishability of information carriers is a major challenge in many quantum information applications, including advanced quantum communication protocols. For photons, the workhorses of quantum communication networks, it is difficult to obtain and maintain their indistinguishability because of environment-induced transformations and loss imparted by communication channels, especially in noisy scenarios. Conventional strategies to mitigate these transformations often require hardware or software overhead that is restrictive (e.g., adding noise), infeasible (e.g., on a satellite), or time-consuming for deployed networks. In this work we propose and develop resource-efficient Bayesian optimization techniques to rapidly and adaptively calibrate the indistinguishability of individual photons for quantum networks using only information derived from their measurement. To experimentally validate our approach, we demonstrate the optimization of Hong-Ou-Mandel interference between two photons-a central task in quantum networking- finding rapid, efficient, and reliable convergence towards maximal photon indistinguishability in the presence of high loss and shot noise. We expect our resource-optimized and experimentally friendly methodology will allow fast and reliable calibration of indistinguishable quanta, a necessary task in distributed quantum computing, communications, and sensing, as well as for fundamental investigations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Low Cost (CAPEX and variable): Tool design for cell and module fabrication with thin, free-standing silicon wafers

This project aimed to develop technologies that can potentially enable free-standing thin (<80 μm) wafer in today’s manufacturing lines with high production yield, and thereby reduce capex barriers of silicon photovoltaics cells and modules. One of the major benefits is that thin wafer dramatically reduces the amount of polysilicon required. As a result, it can lead to reduction in the capital expenditures associated with polysilicon refining and wafer fabrication, which together are more than half of the total capital expenditure to manufacture Si PV module. We focused our efforts on developing the tools needed to enable high yield fabrication of wafer, cell, and module with thin silicon wafers. However, as the wafer thickness reduces, the major challenge is that wafer breakage increases significantly. Three technological areas were explored in this project to improve the production yield of the silicon wafer, namely detection of edge cracks via dark-field near-infrared (NIR) scattering; (2) wafer handling using controlled temperature profiles; (3) manufacturable low-stress cell interconnection for multiwire. First, the formation of wafer cracks in submillimeter length is one of the reasons that causes wafer breakages. Crack detection tools are needed to enable us to locate and track the wafer crack during manufacturing, so that we can improve the process to reduce initialization. The state-of-the-art crack detection technique cannot fulfill the need for measuring submillimeter edge cracks detrimental for thin wafers. The prototype developed in this project demonstrates the scanning of microcracks near wafer edges. With a semi-automatic laboratory setup, the submillimeter cracks were reliably detected near the edges in multi-Si wafers. The smallest detectable crack is 200 µm in length in slow scans; and submillimeter cracks are detected in high-throughput scans at the scan speed of >0.5 m/s, which is compatible with the inline detection of a manufacturing line at least 1 sec/wafer. This detection limit is a significant advancement in comparison to the benchmarked industrial tool. Second, wafer handling with the well-controlled temperature profile was thought to be the solution to reduce crack initiation and propagation during the manufacturing. However, without crack detection being widely adopted in production line, we did not find a strong industrial pull toward this technology. We did an initial literature survey and then diverted our efforts to the other tasks. Third, the innovation on low-stress multi-wire interconnection tackles a fundamental problem in the standard interconnection scheme. The standard over-under “zig-zag” interconnection induces a significant amount of stress into the soldering point on the cell whenever PV module is under stress, e.g., thermal cycling, transportation, and installation. Therefore, the interconnection process was re-designed in this project to allow for significant movement between adjacent solar cells, e.g., due to thermal expansion, without building up stresses on the solar cells or solder joints. The new interconnection method with the cross-connect wire also simplifies the tabbing and stringing process by replacing the standard over-under method with an off-cell interconnect from top to bottom. A manual tabbing and stringing tool for this new process was prototyped in the lab to demonstrate the fabrication of this new interconnection design. During the test with brass sheets as our “testing cells”, it was found that the mechanical cycling test only broke the interconnection after more than 50,000 cycles, which is equivalent to more than 130 years of the day-and-night thermal cycles. Lastly, throughout the project, we continuously analyzed the PV market with techno-economic analysis to identify the opportunity for thin Si adoption. Even though the drastic cost reduction has already happened in the past five years, our analysis results indicated that we can still save quite significantly in both manufacturing cost and factory capex, Particularly, in order to grow the PV manufacturing capacity to multi-terawatt level, reducing the thickness of silicon wafer is one of the most effective ways to quickly reduce factory capex, and sustain the high growth rate. The technologies developed in this project are readily available to provide some assistances in tackling the production yield problem.

14 SOLAR ENERGY↗

DOE OSTI2020

A Novel Laser 3D Printing Method for the Advanced Manufacturing of Protonic Ceramics

Protonic ceramics (PCs) with high proton conductivity at intermediate temperatures (300–600 °C) have attracted many applications in energy conversion and storage devices such as PC fuel/electrolysis cells, PC membrane reactors, hydrogen pump, hydrogen or water-permeable membranes, and gas sensors. One of the essential steps for fulfilling the practical utilization of these intermediate-temperature PC energy devices is the successful development of advanced manufacturing methods for cost-effectively and rapidly fabricating them with high energy density and efficiency in a customized demand. In this work, we developed a new laser 3D printing (L3DP) technique by integrating digital microextrusion-based 3D printing and precise and rapid laser processing (sintering, drying, cutting, and polishing), which showed the capability of manufacturing PCs with desired complex geometries, crystal structures, and microstructures. The L3DP method allowed the fabrication of PC parts such as pellets, cylinders, cones, films, straight/lobed tubes with sealed endings, microchannel membranes, and half cells for assembling PC energy devices. The preliminary measurement of the L3DP electrolyte film showed a high proton conductivity of ≈7 × 10−3 S/cm. This L3DP technique not only demonstrated the potential to bring the PCs into practical use but also made it possible for the rapid direct digital manufacturing of ceramic-based devices.

08 HYDROGEN↗

DOE OSTI2021

Unbalancing Symbiotic Nitrogen Fixation: Can We Make Effectiveness More Effective?

One of the most critical uses of carbon fuels is in generating nitrogen fertilizer. Atmospheric dinitrogen is too stable to be used directly by plants, so plants need other chemical forms of nitrogen. Nitrogen fertilizer production uses ~4% of the world’s natural gas. Making N fertilizers leverages methane’s energy content by enabling additional energy to be captured into food and fiber through increased photosynthesis. Manufacturing fertilizer is essential—without it there would only be enough combined nitrogen to feed ~3 billion of the world’s ~7 billion people. How to alter this addiction is not obvious, but the best chance to secure substantial and sustainable amounts of future N might be through symbiotic nitrogen fixation (SNF). SNF describes mutualistic interactions where nitrogen-fixing bacteria provide fixed nitrogen to their plant hosts, freeing them from the need for nitrogen fertilizers. SNF already occurs on a large scale; "biological nitrogen” contributes about 5 Tg N/yr to American agriculture, a quarter of the nitrogen needed. Improving SNF and replacing inorganic fertilizers are both important goals in establishing sustainable and more energy-efficient farming. SNF has been used in agriculture for millennia, largely by using legumes like beans or alfalfa in mixed cropping systems. Legume SNF occurs in root nodules, organs that develop after a growing root is infected by bacteria called rhizobia. In the plant cells of a legume nodule, specialized forms of rhizobia fix nitrogen and can produce enough ammonia to supply the growing plant. The exchange of photosynthetically derived plant carbon compounds for nitrogen reduced by the bacteria is the engine that drives the symbiosis. Important details about the organization of development and metabolism in SNF remain to be determined, such as how plant and bacterial metabolism are coordinated as nitrogen is being fixed and what governs the overall level of nitrogen fixation. Most bacterial mutations that affect SNF completely block fixation (e.g. are Fix – ), providing a limited window into the feedback interactions that must be part of the process. We have investigated an unusual mutant of Sinorhizobium meliloti, a symbiotic partner of alfalfa, that fixes dinitrogen at a normal rate (i.e., it is Fix + ) but is not effective in supporting plant growth (i.e., it is ineffective or Eff – ). We have shown that the mutant has a specific mutation in the glnD gene, which codes for a protein that regulates the bacterial response to nitrogen stress, among other key pathways. A Fix + Eff – phenotype contains an unavoidable puzzle—how is it possible for the bacteria to fix nitrogen at a normal rate and without benefiting the nitrogen starved plant host? After eliminating other possibilities, we proposed that the bacteria synthesize a nitrogen-containing compound that the plant can’t use so that acquiring this compound does not relieve plant nitrogen stress. Extracts of nodules made by glnD mutant strains have high concentrations of pyruvate canaline oxime (PCO), a derivative of the plant defensive compound canaline, a toxic analog of ornithine, an amino acid. Many legumes produce canaline and the related arginine mimic canavanine. For reasons we do not yet understand, the mutation in glnD appears to trigger significant overproduction of canaline in a defense response that leads to substantial synthesis of PCO. We expected the bacteria to be able to use PCO, but we have not been able to grow S. meliloti on PCO under several conditions. PCO thus appears to be a metabolic dead end for both the plant and bacteria. We also examined bacterial catabolic pathways that degrade arginine and canavanine and showed that mutation of these did not alter the symbiosis in an obvious way. In related experiments to examine the metabolic development of root nodules, we carried out an ambitious experiment to simultaneously measure metabolites and protein changes during nodule maturation. For these experiments we used a related symbiotic interaction between S. medicae and Medicago truncatula. M. truncatula has a simpler genome than alfalfa so we could identify plant proteins based on predictions from the DNA sequence. Nodules formed on Medicago grow linearly, with the least mature tissues at the tip. Because development of nitrogen fixation is accompanied by the production of the pigmented plant oxygen carrier protein leghemoglobin, we were able to locate and manually separate the tip, transitional, and mature nitrogen-fixing regions from each other. Advances in proteomic and metabolomic techniques allowed us to analyze these tissues from a pool of as few as 10 nodules. We observed correlated transitions of various enzymes in the plant and bacterial proteomes from those characteristic of free-living metabolism to the microaerobic metabolism of the nitrogen-fixing tissues. The metabolome could not be separated into plant and bacterial domains but was consistent with this overall transition. A subsequent paper examined proteolysis in nodule bacteria. Protein turnover in mature regions of the nodule is significant. We were able to show complexes between various proteins and important proteases, using precipitation capture techniques to isolate the proteases and sensitive proteomic analysis to reveal the associated proteins.

09 BIOMASS FUELS↗

DOE OSTI2024

EXPLORING INTERFEROMETRY DIAGNOSTICS FOR OPTICAL STOCHASTIC COOLING AT FAST/IOTA

Optical Stochastic Cooling (OSC) is an advanced beam-cooling technique that will advance the traditional stochastic cooling. This method leverages optical radiation and high-precision feedback to cool the particles more efficiently than traditional stochastic methods by more than three orders of magnitude. As such, it is an enabler for the development of next generation discovery science machines at the frontiers of energy and intensity. This paper focuses on the development of the second phase of OSC and improving extreme beam cooling techniques in accelerators. The goal was to build and characterize a Mach-Zehnder Interferometer (MZI) in the FAST laser lab using known glass plates thickness which will allow future measurements of unknown phase change due to nonlinear amplification processes.

Teriba, Folashade↗

DOE OSTI2021

Ribbon Wrinkling Origin and Its Effect on Tape-Wound Core Shape

Improved understanding of advanced manufacturing techniques is needed to fabricate next- generation soft magnetic tape-wound cores. These utilize metal amorphous nano-composites (MANCs) in the form of long thin ribbons. MANCs exhibit attractive soft magnetic properties for use in high frequency and high power density magnetic components. Of particular interest here, the permeability and hysteresis of MANC ribbons can be tuned in a strain annealing process. An unexpected consequence is that wider ribbons develop longitudinal wrinkle patterns. This can substantially reduce the tape-wound core stacking factor. However, when winding a wrinkled ribbon into a toroidal core, the wrinkles can completely flatten, or crinkle. By this phenomenon, the stacking factor can be recovered. To understand the crinkling effect we have developed analytical and finite element analysis (FEA) models. Experiments with known boundary conditions demonstrate the transition from wrinkled to crinkled versus winding curvature. The models utilize an elastic modulus measured via ribbon tensile testing and a ribbon thickness value measurement made by profilometry. The analytical model provides insight into the crinkling effect but cannot explain the length of the transition region from wrinkling to crinkling. With FEA, we successfully predict the transition region and depending on wrinkling amplitude can determine when a ribbon will wind into a useable core. Such mechanics-based insight provides critical feedback for allowable processing parameters in the strain annealing process.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Trace Impurities Identified as Forensic Signatures in CMX-5 Fuel Pellets Using X-ray Spectroscopic Techniques

We report that small-particle analysis is a highly promising emerging forensic tool for analysis of interdicted special nuclear materials. Integration of microstructural, morphological, compositional, and molecular impurity signatures could provide significant advancements in forensic capabilities. We have applied rapid, high-sensitivity, hard X-ray synchrotron chemical imaging to analyze impurity signatures in two differently fabricated fuel pellets from the 5th Collaborative Materials Exercise (CMX5) of the IAEA Nuclear Forensics International Working Group. The spatial distributions, chemical compositions, and morphological and molecular characteristics of impurities were evaluated using X-ray absorption near-edge structure (XANES) and X-ray fluorescence chemical imaging to discover principal impurities, their granularity, particle sizes, modes of occurrence (distinct grains vs incorporation in the UO 2 lattice), and sources and mechanisms of incorporation. Differences in UO 2+x stoichiometry were detected at the microscale in nominally identical UO 2 ceramics (CMX5-A and CMX5-B), implying the presence of multiple UO 2 host phases with characteristic microstructures and feedstock compositions. Al, Fe, Ni, W, and Zr impurities and integrated impurity signature analysis identified distinctly different pellet synthesis and processing methods. For example, two different Al, W, and Zr populations in the CMX5-B sample indicated a more complex processing history than the CMX5-A sample. K-edge XANES measurements reveal both metallic and oxide forms of Fe and Ni but with different proportions between each sample. Altogether, these observations suggest multiple sources of impurities, including fabrication (e.g., force-sieving) and feedstock (mineral oxides). This study demonstrates the potential of synchrotron techniques to integrate different signatures across length scales (angstrom to micrometer) to detect and differentiate between contrasting UO 2 fuel fabrication techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Optical tuning of the diamond Fermi level measured by correlated scanning probe microscopy and quantum defect spectroscopy

Quantum technologies based on quantum point defects in crystals require control over the defect charge state. Here we tune the charge state of shallow nitrogen-vacancy and silicon-vacancy centers by locally oxidizing a hydrogenated surface with moderate optical excitation and simultaneous spectral monitoring. The loss of conductivity and change in work function due to oxidation are measured in atmosphere using conductive atomic force microscopy and Kelvin probe force microscopy (KPFM). We correlate these scanning probe measurements with optical spectroscopy of the nitrogen-vacancy and silicon-vacancy centers created via implantation 15–25 nm beneath the diamond surface and annealing. The observed charge state of the defects as a function of optical exposure demonstrates that laser oxidation provides a way to precisely tune the Fermi level over a range of at least 2.00 eV. We also observe a significantly larger oxidation rate for implanted surfaces compared to unimplanted surfaces under ambient conditions. Here, combined with knowledge of the electron affinity of a surface, these results suggest KPFM is a powerful, high-spatial-resolution technique to advance surface Fermi level engineering for charge stabilization of quantum defects.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hearing carrier-envelope offset frequency and phase in air with a microphone

Attosecond science and frequency metrology rely on the precise measurement and control of the laser pulse waveform, a feat traditionally achieved using optoelectronic techniques. In this study, we conducted a laser-induced acoustic experiment in air ionized by carrier-envelope phase (CEP)-stabilized sub-4 fs pulses. Our results reveal that the acoustic signal exhibits CEP dependence in few-cycle pulses, primarily through amplitude modulation from laser-driven ionization. This optoacoustic phenomenon is, to the best of our knowledge, a novel phenomenon that enables not only the measurement of the carrier-envelope offset frequency but also the direct characterization of the waveform of optical pulses through a microphone. Our study highlights the potential of laser-induced acoustic waves for advancing ultrafast science.

Han, Meng [Kansas State University, Manhattan, KS ↗

DOE OSTI2023

Eco-Friendly High-Performance Carbon Building Material Development from Coal

The development of eco-friendly high-performance building materials based on coal-derived materials is greatly beneficial for promoting environmental sustainability and the coal industry. This project focused on advancing technology to create innovative and scalable construction materials from two domestic sources: (1) coal-derived pyrolyzed char (PC), and (2) solvent-extracted coal deposit, extracts, and residue (CDER). It aimed to simultaneously develop and produce two types of coal-derived building products: (1) char-based concrete bricks (CCB) for wall construction in buildings, and (2) carbon-based structural units (CSU) intended as alternatives to traditional wood, concrete, or steel framing structures. The project team has successfully developed methods for manufacturing CCB samples. Extensive experiments were conducted to assess various manufacturing techniques for these samples. This included measuring their physical properties such as thermal conductivity (ranging from 0.26 to 0.38 W/mK) and bulk density (ranging from 0.85 to 1.15 g/cm 3 ), along with their mechanical properties (e.g., compressive strength ranging from 14 to 16 MPa at 28 days) for samples with a PC composition of 70%. Quality assurance and quality control tests, focusing on density and compressive strength, were also performed on samples selected randomly from pilot-scale production, and cured for a long term (over three months). The average long-term compressive strength of two randomly selected CCB samples was measured as 15.1 MPa, which was higher than the required target strength of 14 MPa. This indicates that the manufactured CCB samples from the preliminary pilot scale production run have good quality control and long-term strength performance.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Cross-Feature Transfer Learning for Efficient Tensor Program Generation

Tuning tensor program generation involves navigating a vast search space to find optimal program transformations and measurements for a program on the target hardware. The complexity of this process is further amplified by the exponential combinations of transformations, especially in heterogeneous environments. This research addresses these challenges by introducing a novel approach that learns the joint neural network and hardware features space, facilitating knowledge transfer to new, unseen target hardware. A comprehensive analysis is conducted on the existing state-of-the-art dataset, TenSet, including a thorough examination of test split strategies and the proposal of methodologies for dataset pruning. Leveraging an attention-inspired technique, we tailor the tuning of tensor programs to embed both neural network and hardware-specific features. Notably, our approach substantially reduces the dataset size by up to 53% compared to the baseline without compromising Pairwise Comparison Accuracy (PCA). Furthermore, our proposed methodology demonstrates competitive or improved mean inference times with only 25–40% of the baseline tuning time across various networks and target hardware. The attention-based tuner can effectively utilize schedules learned from previous hardware program measurements to optimize tensor program tuning on previously unseen hardware, achieving a top-5 accuracy exceeding 90%. This research introduces a significant advancement in autotuning tensor program generation, addressing the complexities associated with heterogeneous environments and showcasing promising results regarding efficiency and accuracy.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Enhancing Responsiveness and Resilience with Distributed Applications in the Grid

A number of trends are increasing the variability in electric power systems resulting in a need for new approaches in control. The increased variability is originating from distributed energy resources and an increasing demand for personalized energy choice from customers grid-edge. Electricity distribution systems continue to incorporate increasing numbers of intelligent end devices, automated switchgear, and sensing and measurement devices which are providing more visibility and control at the grid-edge. Traditional distribution system planning and operations techniques must evolve to meet the new complexity while continuing to deliver safe, reliable, and cost-effective energy. New technologies are enabling new capabilities at the grid-edge to respond to these needs. Distributed applications can deploy intelligence across the distribution grid with peer-to-peer communications and a shared data context for their local environment. These applications can cooperate with each other to respond quickly to changing grid conditions. This enables a layered coordination framework spanning the centralized Advanced Distribution Management System functions with wide area visibility to these new distributed applications running at intelligent devices and meters throughout the distribution system. This paper describes an open-architecture, open-source system approach for commercial scale integration of devices and intelligence at the grid-edge.

Ogle, James P.↗

DOE OSTI2024

UN-SiC TRISO Post Irradiation Examination Developmental Work

As part of efforts to strengthen INL?s post irradiation analysis capabilities with non-Advanced Gas Reactor (AGR) tristructural isotropic (TRISO) fuels, two developmental activities were conducted. The first activity was to determine how best to analyze uranium nitride TRISO fuel kernels using electron probe microanalysis, while the second activity focused on developing a method to deconsolidate TRISO fuel particles that have been encased in a silicon carbide matrix. Because these two activities were unrelated, they have been presented separately in this report. Initial EPMA analyses showed nitrogen contents that far exceeded the concentration expected for UN--a line compound. Further examination showed that current literature values for the mass absorption coefficient (MAC) for the N ka X-ray absorbed by U ranged from approximately 1600 to 9500, with most values tending toward 9500. Measuring UN with five different progressively increasing accelerating voltages followed by using the modeling program xMAC suggests the actual MAC is approximately 2115. Additional MAC modifications were required to produce reasonable analytical results. Because of the inaccuracies of necessary MAC coefficients, UN analysis via scanning electron microscopy (SEM) is likely to produce inaccurate results. This is because SEM software does not typically allow the user to alter MACs. Tests have been performed to examine the feasibility of an electrochemical technique to liberate irradiated TRISO fuel from a SiC matrix without damaging the outer pyrolytic carbon layer of the fuel particle. The method is performed by electrochemically exposing the SiC to magnesium metal forming Mg2Si and C. Following exposure, the small SiC samples showed slight mass increases with no evidence of conversion to Mg2Si and C nor obvious degradation of the SiC samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Binder-Coated Carbon Cloth Electrodes for All-Vanadium Redox Flow Batteries

Vanadium redox flow batteries (VRFBs) are a promising solution for integrating intermittent renewable energy sources into the existing power grid. However, enhancing the electrochemical performance of VRFBs is critical for their widespread adoption in grid-scale energy storage. This study investigates the impact of adding a porous binder to a carbon-cloth electrode, with a focus on optimizing thermal activation conditions. The electrochemical performance of the binder-coated electrodes compared to uncoated electrodes is evaluated through electrochemical impedance spectroscopy, polarization curve measurements, and charge-discharge cycling. The surface morphology and structural integrity of the binder-coated electrodes at each activation stage are examined using various material characterization techniques to assess the effects of thermal activation. The results are benchmarked against the experiments using non-coated electrodes to determine the performance improvements offered by the binder coating. Notably, the study reveals that binder-coated electrodes exhibit significantly lower resistance and improved efficiency compared to their uncoated counterparts, with optimal activation conditions enhancing performance metrics crucial for VRFB applications. These findings provide valuable insights for further optimizing electrode design and activation strategies, advancing the development of more efficient VRFB systems for large-scale energy storage.

Caiado, Ashley A.↗

DOE OSTI2025

Measurement of Close-in Ground Motion from an Underground Chemical Explosion

Understanding the geophysical response near an underground explosion is crucial for generating insights into the source and emplacement conditions that produce distinct observations in monitoring scenarios occurring at greater distances. Recently, Shot A of the Low Yield Nuclear Monitoring (LYNM) Physics Experiment 1 (PE1) series was conducted at the Nevada National Security Site to provide ground truth for subsurface explosion signal models. This experiment resulted in measuring near-source ground motion at distances ranging from 70 to 1000 m/kt with a 99% success rate, yielding high-fidelity knowledge of the near-field response that can serve as benchmarks for future numerical modeling and experiment planning. However, technical challenges exist in observing near-source phenomena while safeguarding sensitive data acquisition components from the detrimental effects of ground motion in the subsurface. This report outlines tools and techniques to address challenges associated with observing near-source accelerations and within the tunnel drift of the PE1 test bed. Additionally, we describe key systems designed with both modern advancements and legacy guidance to maximize the collection of high-quality ground motion data, which may be applied to constitutive and computational models, leading to new or improved understanding of the near- and far-field signals produced by underground explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Machine Learning-Based Technique for Automated Sensor Characterization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert s time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.