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At least 1,351 records · Page 75

Feasibility of Lead Fast Reactor Heat Exchanger Tube Online Monitoring

Within virtually all reactor systems with heat exchangers, the thinnest barriers between primary and secondary fluids are the heat exchanger tubes. Consistent with light water reactor experience, the advanced reactor heat exchangers are the most susceptible regions for corrosion and leakage (NRC, 2019). Moreover, traditional inspections and repairs using robotics will be expensive or impractical. On-line structural health corrosion monitoring (OLSHM) is therefore desirable to detect tube degradation prior to leaks that may allow mixing of heat exchanger fluids. Rhetorically many molten salt reactor (MSR) designers plan for on-line monitoring of critical reactor components including heat exchangers but there are no proven OLSHM sensors or systems for MSR heat exchangers. Guided wave ultrasound from the tube-end or ID using conventional low-temperature piezoelectric sensors has been shown to be sensitive to pits and cracks less than 50% through-wall in long pipes and tubes (Narayanan M.M., 2019) . Mode and frequency selection are important for practical sensor design decisions and ultimate performance. The L-0 wave-mode is easily excited by L-mode transducers but they have surface normal wave motion that will be sensitive to and more attenuative because of fluid interaction with the tube surface (Rose J.L., 1994). Shear Horizontal (SH) wave modes have material motion parallel to the tube surface therefore are virtually unaffected by fluid interaction. For SH-0 to be nondispersive in steel, the frequency-thickness product (MHz-mm) must be less than approximately 1.5. SH mode transducers must be coupled by a material that can support shear stress; a thin layer of honey works well for temporary sensors and an adhesive or a brazed metallurgical bond for permanent sensors. If sensors are incorporated into the fabrication process, the same kinds of SH-0 waves can be generated from the stagnant flow area of the tube OD without compromising the heat-exchange tube function. Piezoelectric materials are also available that can withstand harsh temperatures of molten salt heat exchangers (Stevenson T., 2015) (Machura et al., 2008). Though they may not have as high-performance characteristics, their performance only needs to be good enough to detect flaws of interest. This project attempts to demonstrate feasibility to develop a sensor that can be sensitive to flaws of interest and perform long-term monitoring of a molten salt reactor heat exchanger. Benefits to the advanced reactor system include: • Minimizing the expense of a reactor shut down for periodic inspection—only shutdown for cause. • Reduce risk of unexpected tube rupture by detecting flaws before they grow to through-wall leaks. • Cost reduction by minimizing need to design for manual/robotic inspectability. Transducer design, characterization of the beam profile, wedges vs. direct application of piezoelectric sensors, and ultrasonic pulse-echo responses from a representative heat exchange tube with fabricated flaw types are discussed.

On-Line Tube Monitor, Guided Wave Ultrasound, SH-0↗

The Double-edged Sword of Data-driven Super-Resolution: Adversarial Super-resolution Models

Data-driven super-resolution (SR) methods are often integrated into imaging pipelines as preprocessing steps to improve downstream tasks such as classification and detection. However, these SR models introduce a previously unexplored attack surface into imaging pipelines. In this paper, we present AdvSR, a framework demonstrating that adversarial behavior can be embedded directly into SR model weights during training, requiring no access to inputs at inference time. Unlike prior attacks that perturb inputs or rely on backdoor triggers, AdvSR operates entirely at the model level. By jointly optimizing for reconstruction quality and targeted adversarial outcomes, AdvSR produces models that appear benign under standard image quality metrics while inducing downstream misclassification. We evaluate AdvSR on three SR architectures (SRCNN, EDSR, SwinIR) paired with a YOLOv11 classifier and demonstrate that AdvSR models can achieve high attack success rates with minimal quality degradation. These findings highlight a new model-level threat for imaging pipelines, with implications for how practitioners source and validate models in safety-critical applications.

Sullivan, Haley [ORNL] (ORCID:0000000274069217)↗

First Detection of the GI-type of Intrinsic Alignments of Galaxies Using the Self-calibration Method in a Photometric Galaxy Survey

Weak gravitational lensing is one of the most promising cosmological probes to constrain dark matter, dark energy, and the nature of gravity at cosmic scales. Intrinsic alignments (IAs) of galaxies have been recognized as one of the most serious systematic effects facing gravitational lensing. Such alignments must be isolated and removed to obtain a pure lensing signal. Furthermore, the alignments are related to the processes of galaxy formation, so their extracted signal can help in understanding such formation processes and improving their theoretical modeling. We report in this Letter the first detection of the gravitational shear–intrinsic shape (GI) correlation and the intrinsic shape–galaxy density (Ig) correlation using the self-calibration method in a photometric redshift survey. These direct measurements are made from the KiDS-450 photometric galaxy survey with a significance of 3.65σ in the third bin for the Ig correlation, and 3.51σ for the GI cross-correlation between the third and fourth bins. The self-calibration method uses the information available from photometric surveys without needing to specify an IA model and will play an important role in validating IA models and IA mitigation in future surveys such as the Rubin Observatory Legacy Survey of Space and Time, Euclid, and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗

Observing Charge Separation Distance in Organic Donor-Acceptors with Photoinduced Absorption Detected Magnetic Resonance Spectroscopy

The debatable role of charge transfer states in photoinduced charge separation to useful free carriers has been a long-standing controversy in the field of organic solar cells. In this work, varying charge-pair distances are measured in sensitized donor-acceptor thin films using a photoinduced absorption-detected magnetic resonance (PADMR) technique where nearest-neighbor charge transfer states are identified by their strong magnetic dipole-coupling relative to more distant charges. Correlation with the direct measurement of free carriers using time-resolved microwave conductivity has corroborated a distributed-range electron transfer model in which charges generated at longer distances become free carriers, while shorter transfer distances give only bound charge transfer states that cannot separate to generate photocurrent.

charge transfer↗

Anisotropy in Thermal Conductivity of Ga2O3 under Irradiation: Ab-initio Investigations

Ga2O3 is a wide-bandgap semiconducting material known for its high breakdown electric field and thermal stability. Its various crystalline forms have shown great potential in power electronics, optoelectronics, and high-temperature applications. Specifically, ß-Ga2O3 has been recognized for its suitability in neutron and gamma radiation detection, making it ideal for sensor and detector applications [1]. Notably, ß-Ga2O3 exhibits anisotropic thermal conductivity, meaning that the magnitude of thermal conductivity varies with the crystallographic direction [2]. Under neutron irradiation, Ga2O3 undergoes a significant phenomenon, resulting in the formation of Helium bubbles within its crystalline matrix. The presence of Helium in Ga2O3 has been found to influence the material's anisotropic thermal conductivity. In this study, the objectives were twofold: firstly, to employ Density Functional Theory (DFT) to determine the most probable sites of Helium occupation in ß-Ga2O3, and secondly, to investigate the anisotropic variation in thermal conductivity when Helium is present in the crystalline matrix of ß-Ga2O3. These ab-initio DFT studies provide crucial insights into understanding the behavior of Helium in Ga2O3 and its impact on thermal conductivity, which can contribute to further advancements in sensor and detector applications based on this wide-bandgap semiconductor.

36 MATERIALS SCIENCE↗

Nanopore device for reversible ion and molecule sensing or migration

Disclosed are methods and devices for detection of ion migration and binding, utilizing a nanopipette adapted for use in an electrochemical sensing circuit. The nanopipette may be functionalized on its interior bore with metal chelators for binding and sensing metal ions or other specific binding molecules such as boronic acid for binding and sensing glucose. Such a functionalized nanopipette is comprised in an electrical sensor that detects when the nanopipette selectively and reversibly binds ions or small molecules. Also disclosed is a nanoreactor, comprising a nanopipette, for controlling precipitation in aqueous solutions by voltage-directed ion migration, wherein ions may be directed out of the interior bore by a repulsing charge in the bore.

47 OTHER INSTRUMENTATION↗

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗

Generative AI in Supply Chain Management: Applications, Challenges, and Future Directions

Supply chain management (SCM) is undergoing rapid transformation due to increasing global complexity, demand volatility, and operational disruptions. Generative Artificial Intelligence (GenAI) has emerged as a powerful paradigm capable of synthesizing data, simulating operational scenarios, and enabling adaptive decision-making across supply chain networks. This paper presents a survey of GenAI’s role in SCM, focusing on its applications in predictive analytics, autonomous logistics, and fraud detection. Unlike traditional AI systems that rely primarily on predictive analytics, GenAI models, including large language models, generative adversarial networks, and diffusion-based architectures, enable the creation of synthetic supply chain scenarios and autonomous optimization strategies. This survey provides (1) a taxonomy of GenAI techniques for supply chain applications, (2) a comparative analysis of generative AI approaches with traditional machine learning, reinforcement learning, and blockchain-based methods, and (3) a discussion of key challenges such as data privacy, interpretability, and integration with legacy enterprise systems. Furthermore, we outline open research problems and propose directions for future research toward autonomous, resilient, and sustainable AI-driven supply chains.

15 - GEOTHERMAL ENERGY↗

Discovery of 22 GHz Water Masers in the Serpens South Region

Using the Karl G. Jansky Very Large Array (VLA), we have conducted a survey for 22 GHz, 6{sub 1,6}–5{sub 2,3} H{sub 2}O masers toward the Serpens South region. The masers were also observed with the Very Long Baseline Array following the VLA detections. We detect for the first time H{sub 2}O masers in the Serpens South region that are found to be associated to three Class 0–Class I objects, including the two brightest protostars in the Serpens South cluster, known as CARMA-6 and CARMA-7. We also detect H{sub 2}O masers associated to a source with no outflow or jet features. We suggest that this source is most probably a background asymptotic giant branch star projected in the direction of Serpens South. The spatial distribution of the emission spots suggest that the masers in the three Class 0–Class I objects emerge very close to the protostars and are likely excited in shocks driven by the interaction between a protostellar jet and the circumstellar material. Based on the comparison of the distributions of bolometric luminosity of sources hosting 22 GHz H{sub 2}O masers and 162 young stellar objects covered by our observations, we identify a limit of L {sub Bol} ≈ 10L {sub ⊙} for a source to host water masers. However, the maser emission shows strong variability in both intensity and velocity spread, and therefore masers associated to lower-luminosity sources may have been missed by our observations. We also report 11 new sources with radio continuum emission at 22 GHz.

47 OTHER INSTRUMENTATION↗

Organic contamination detection for isotopic analysis of water by laser spectroscopy

Hydrogen and oxygen stable isotope ratios (δ 2 H, δ 17 O, and δ 18 O values) are commonly used tracers of water. These ratios can be measured by isotope ratio infrared spectroscopy (IRIS). However, IRIS approaches are prone to errors induced by organic compounds present in plant, soil, and natural water samples. A novel approach using 17 O-excess values has shown promise for flagging spectrally contaminated plant samples during IRIS analysis. A systematic assessment of this flagging system is needed to prove it useful. Errors induced by methanol and ethanol water mixtures on measured IRIS and isotope ratio mass spectrometry (IRMS) results were evaluated. For IRIS analyses both liquid- and vapour-mode (via direct vapour equilibration) methods are used. The δ 2 H, δ 17 O, and δ 18 O values were measured and compared with known reference values to determine the errors induced by methanol and ethanol contamination. In addition, the 17 O-excess contamination detection approach was tested. This is a post-processing detection tool for both liquid and vapour IRIS triple-isotope analyses, utilizing calculated 17 O-excess values to flag contaminated samples. Organic contamination induced significant errors in IRIS results, not seen in IRMS results. Methanol caused larger errors than ethanol. Results from vapour-IRIS analyses had larger errors than those from liquid-IRIS analyses. The 17 O-excess approach identified methanol driven error in liquid- and vapour-mode IRIS samples at levels where isotope results became unacceptably erroneous. For ethanol contaminated samples, a mix of erroneous and correct flagging occurred with the 17 O-excess method. Here our results indicate that methanol is the more problematic contaminant for data corruption. The 17 O-excess method was therefore useful for data quality control. Organic contamination caused significant errors in IRIS stable isotope results. These errors were larger during vapour analyses than during liquid IRIS analyses, and larger for methanol than ethanol contamination. The 17 O-excess method is highly sensitive for detecting narrowband (methanol) contamination error in vapour and liquid analysis modes in IRIS.

60 APPLIED LIFE SCIENCES↗

Data-Driven Whole-Genome Clustering to Detect Geospatial, Temporal, and Functional Trends in SARS-CoV-2 Evolution

Current methods for defining SARS-CoV-2 lineages ignore the vast majority of the SARS-CoV-2 genome. We develop and apply an exhaustive vector comparison method that directly compares all known SARS-CoV-2 genome sequences to produce novel lineage classifications. We utilize data-driven models that (i) accurately capture the complex interactions across the set of all known SARS-CoV-2 genomes, (ii) scale to leadership-class computing systems, and (iii) enable tracking how such strains evolve geospatially over time. We show that during the height of the original Omicron surge, countries across Europe, Asia, and the Americas had a spatially asynchronous distribution of Omicron sub-strains. Moreover, neighboring countries were often dominated by either different clusters of the same variant or different variants altogether throughout the pandemic. Analyses of this kind may suggest a different pattern of epidemiological risk than was understood from conventional data, as well as produce actionable insights and transform our ability to prepare for and respond to current and future biological threats.

Jacobson, Daniel↗

Fault Detection in the Solvent Extraction Process with Non-traditional Sensors

Solvent extraction is used to separate metals or other complexes into two different immiscible liquids and is an essential component of the PUREX Process. Improvements to the solvent extraction process can directly contribute to an organization’s ability to ensure the purity and recovery of special nuclear materials from spent nuclear fuel. Such improvements can benefit nuclear reprocessing efforts, increase fuel reutilization, and limit the concentration of actinides in nuclear waste repositories.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Enhanced detection of prion infectivity from blood by preanalytical enrichment with peptoid-conjugated beads

Prions cause transmissible infectious diseases in humans and animals and have been found to be transmissible by blood transfusion even in the presymptomatic stage. However, the concentration of prions in body fluids such as blood and urine is extremely low; therefore, direct diagnostic tests on such specimens often yield false-negative results. Quantitative preanalytical prion enrichment may significantly improve the sensitivity of prion assays by concentrating trace amounts of prions from large volumes of body fluids. Here, we show that beads conjugated to positively charged peptoids not only captured PrP aggregates from plasma of prion-infected hamsters, but also adsorbed prion infectivity in both the symptomatic and preclinical stages of the disease. Bead absorbed prion infectivity efficiently transmitted disease to transgenic indicator mice. We found that the readout of the peptoid-based misfolded protein assay (MPA) correlates closely with prion infectivity in vivo, thereby validating the MPA as a simple, quantitative, and sensitive surrogate indicator of the presence of prions. The reliable and sensitive detection of prions in plasma will enable a wide variety of applications in basic prion research and diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗

Direct observation of the dead-cone effect in quantum chromodynamics

In particle collider experiments, elementary particle interactions with large momentum transfer produce quarks and gluons (known as partons) whose evolution is governed by the strong force, as described by the theory of quantum chromodynamics (QCD). These partons subsequently emit further partons in a process that can be described as a parton shower, which culminates in the formation of detectable hadrons. Studying the pattern of the parton shower is one of the key experimental tools for testing QCD. This pattern is expected to depend on the mass of the initiating parton, through a phenomenon known as the dead-cone effect, which predicts a suppression of the gluon spectrum emitted by a heavy quark of mass m Q and energy E, within a cone of angular size m Q /E around the emitter. Previously, a direct observation of the dead-cone effect in QCD had not been possible, owing to the challenge of reconstructing the cascading quarks and gluons from the experimentally accessible hadrons. We report the direct observation of the QCD dead cone by using new iterative declustering techniques to reconstruct the parton shower of charm quarks. This result confirms a fundamental feature of QCD. Furthermore, the measurement of a dead-cone angle constitutes a direct experimental observation of the non-zero mass of the charm quark, which is a fundamental constant in the standard model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-Frequency Signature-Based Fault Detection for Future MV Distribution Grids

Increasing penetration levels of inverter based distributed energy resources (DERs) impact the legacy distribution system protection. Inverter based DERs provide approximately 1.2-2 pu fault current. In systems with high penetration of inverter based DERs, it is difficult for over-current based protection schemes to differentiate between normal loading conditions and a fault. Directional, distance, and adaptive forms of protection schemes are also affected by low fault currents. This paper analyzes fault generated traveling wave (TW) based high-frequency signatures in the distribution system. In order to simulate such signatures, frequency-dependent distributed parameter line modeling approach is used in this research work to represent distribution lines and underground cables. Modified IEEE 13-bus medium voltage test system is modeled in electromagnetic transient simulation tool and multiple transient scenarios are simulated in this test system. The results are analyzed to understand the high-frequency signatures that can be used to detect and locate faults under high penetration of DERs.

41 EE - Solar Energy Technologies Office (EE-4S)↗

High-Frequency Signature-Based Fault Detection for Future MV Distribution Grids

Increasing penetration levels of inverter based distributed energy resources (DERs) impact the legacy distribution system protection. Inverter based DERs provide approximately 1.2-2 pu fault current. In systems with high penetration of inverter based DERs, it is difficult for over-current based protection schemes to differentiate between normal loading conditions and a fault. Directional, distance, and adaptive forms of protection schemes are also affected by low fault currents. This paper analyzes fault generated traveling wave (TW) based high-frequency signatures in the distribution system. In order to simulate such signatures, frequency-dependent distributed parameter line modeling approach is used in this research work to represent distribution lines and underground cables. Modified IEEE 13-bus medium voltage test system is modeled in electromagnetic transient simulation tool and multiple transient scenarios are simulated in this test system. The results are analyzed to understand the high-frequency signatures that can be used to detect and locate faults under high penetration of DERs.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Organic and Organometallic Chemistry at the Single-Molecule, -Particle, and -Molecular-Catalyst-Turnover Level by Fluorescence Microscopy

Mechanistic studies have historically played a key role in the discovery and optimization of reactions in organic and organometallic chemistry. However, even apparently simple organic and organometallic transformations may have surprisingly complicated multistep mechanisms, increasing the difficulty of extracting this mechanistic information. The resulting reaction intermediates often constitute a small fraction of the total reaction mixture, for example, creating a long-term analytical challenge of detection. This challenge is particularly pronounced in cases where the positions of intermediates on the reaction energy surface mean that they do not “build up” to the quantities needed for observation by traditional ensemble analytical tools. Thus, their existence and single-step elementary reactivity cannot be studied directly. New approaches for obtaining this otherwise-missing mechanistic information are therefore needed. Single-turnover, single-molecule, single-particle, and other subensemble fluorescence microscopy techniques are ideally suited for this role because of their sensitivity and spatiotemporal resolution. Inspired by the robust development of single-molecule fluorescence microscopy tools for studying enzyme catalysis, our laboratory has developed analogous fluorescence microscopy techniques to overcome mechanistic challenges in synthetic chemistry, with sensitivity as high as the single-complex, single-turnover, and single-molecule level. These techniques free the experimenter from the previous restriction that intermediates must “build up” to quantities needed for detection by ensemble analytical tools and are suited to systems where synchronization through flash photolysis or stopped flow would be inconvenient or inaccessible. In this process, the techniques transform certain previously “unobservable” intermediates and their elementary single-step reactivities into “observable” ones through sensitive and selective spectral handles. Our program has focused on imaging reactions in small-molecule, organic, and polymer synthetic chemistry with an accent on the reactivity of molecular transition metal complexes and catalysts. Our laboratory initiated studies in this area in 2008 with the imaging of individual palladium complexes that were tagged with spectator fluorophores. To enable imaging, we started with fluorophore selection and development, overcame challenges with imaging in organic solvents, and developed strategies compatible with air-sensitive chemistry and concentrations of reagents generally used in small-molecule synthesis. These studies grew to include characterization of previously unknown organometallic intermediates in the synthesis of organozinc reagents and the direct study of their elementary-step reactivity. The ability to directly observe this behavior generated predictive power for selecting salts that accelerated organozinc reagent formation in synthesis, including salts that had not yet been reported synthetically. In 2017 we also developed the first single-turnover imaging of molecular (chemo)catalysts, which through the technique’s spatiotemporal resolution revealed abruptly time-variable polymerization kinetics wherein molecular ruthenium ring-opening metathesis polymerization (ROMP) catalysts changed rates independently from other catalysts less than 1 μm away. Individual catalytic turnovers, each corresponding to one single-chain-elongation reaction arising from insertion of single ROMP or enyne monomers at individual Grubbs II molecular ruthenium catalysts, were spatiotemporally resolved as green flashes in growing polymers. In this work, we discuss the development of this technique from idea to application, including challenges overcome and strategies created to image synthetic organic and organometallic molecular chemistry at the highest levels of detection sensitivity. We also describe challenges not yet solved and provide an outlook for this growing field at the intersection of microscopy and synthetic/molecular chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protection schemes used in North American microgrids

This study reviewed existing conventional and nonconventional protection schemes for grid-connected and islanded mode operations in North American microgrid projects. The microgrid projects investigated in this study used different types of distributed energy resources (DERs) and integrated hydropower/diesel generators, gas/steam/wind turbines, and photovoltaic systems with energy storage. In this work, conventional protection schemes were defined as those within the IEEE Standard C37.2-2008, whereas nonconventional schemes were those not defined within this standard. The pros and cons of conventional and nonconventional protection schemes were discussed in detail. The overvoltage, undervoltage, and frequency elements were the most common conventional protection schemes applied in microgrid projects in North America. These protection elements were used to detect the islanded conditions and faults that could not be sensed by overcurrent relays because of small fault currents contributed by low-inertia DERs and power-electronic sources. Directional overcurrent elements were used to distinguish between external (grid) and internal (microgrid) faults. Adaptive protection was the most popular nonconventional protection scheme applied to the microgrid projects. In conclusion, different types of DERs and operational modes must be considered in order to address the protection and control challenges of each microgrid and to obtain the best technical and economical solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗