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At least 163 records · Page 9

SABRE Ir-IMes Catalysis for the Masses

The Signal Amplification By Reversible Exchange (SABRE) technique provides enhancement of Nuclear Magnetic Resonance (NMR) signals up to several orders of magnitude using chemical exchange of a substrate and parahydrogen on an iridium complex. Therefore, the availability of such a catalytic complex to a broader community is an absolutely vital step for dissemination of the groundbreaking SABRE methodology. The most common SABRE catalyst, which is activated in situ, is based on Ir-IMes system (IMes = 1,3-Bis(2,4,6-trimethylphenyl)imidazol-2-ylidene). Earlier approaches for the synthesis of this catalyst often relied on specialized equipment and were limited to a comparatively small scale. This, in turn, increased the barrier of entry for new scientists to the area of SABRE hyperpolarization. Here, we present a robust, inexpensive, and easy to reproduce synthetic procedure for the preparation of this SABRE catalyst, which does not require specialized inert atmosphere equipment like a glove box or Schlenk line. The synthesis was validated on the scale of several grams vs. tens of milligrams scale in the reported approaches. The resulting SABRE catalyst, [Ir(IMes)(COD)Cl], was activated in situ and further evaluated in hyperpolarization experiments resulting in signal enhancements comparable to (or higher than) those for the catalyst prepared using Schlenk line equipment.

Biochemistry & Molecular Biology↗

Improved Regolith-Landform and Geological Mapping using AIRSAR Data as an Aid to Mineral Exploration in the North-Eastern Goldfields Region, Western Australia

The distinctive contribution of AIRSAR data in characterizing the regolith-landforms in a relatively vegetation free environment are discussed. AIRSAR frame processed data were initially MAF-cleaned to enhance the signal content of the data before geocoding to AMG coordinates. Colors in a three frequency single polarization combination image C-, L- P- bands, and in an enhancement of pedestal height, relate directly to the scale of surface roughness of the various regolith units Examination of the AIRSAR enhancements reveals that in mafic terrain, and to a lesser extent, in felsic terrain, AIRSAR data provides discrimination between the principle geomorphic regimes, relict, erosional and depositional. A multivariate statistical technique called an all-possible subsets calculation was used to examine the degree of polarimetric separation between selected regolith-landforms for all combinations of the nine band AIRSAR radar. An unanticipated aspect of the research was the identification on the AIRSAR imagery of previously unmapped structural features.

Tapley, Ian J.↗

Estimation of Orbital Neutron Detector Spatial Resolution by Systematic Shifting of Differential Topographic Masks

We present a method and preliminary results related to determining the spatial resolution of orbital neutron detectors using epithermal maps and differential topographic masks. Our technique is similar to coded aperture imaging methods for optimizing photonic signals in telescopes [I]. In that approach photon masks with known spatial patterns in a telescope aperature are used to systematically restrict incoming photons which minimizes interference and enhances photon signal to noise. Three orbital neutron detector systems with different stated spatial resolutions are evaluated. The differing spatial resolutions arise due different orbital altitudes and the use of neutron collimation techniques. 1) The uncollimated Lunar Prospector Neutron Spectrometer (LPNS) system has spatial resolution of 45km FWHM from approx. 30km altitude mission phase [2]. The Lunar Rennaissance Orbiter (LRO) Lunar Exploration Neutron Detector (LEND) with two detectors at 50km altitude evaluated here: 2) the collimated 10km FWHM spatial resolution detector CSETN and 3) LEND's collimated Sensor for Epithermal Neutrons (SETN). Thus providing two orbital altitudes to study factors of: uncollimated vs collimated and two average altitudes for their effect on fields-of-view.

McClanahan, T. P.↗

Search for Higgs boson decays into a Z boson and a light hadronically decaying resonance in pp collisions at s =13 TeV with the ATLAS detector

A search for decays of the Higgs boson into a Z boson and a light resonance, with a mass of 0.5–3.5 GeV, is performed using the full 140 fb−1 dataset of 13 TeV proton–proton collisions recorded by the ATLAS detector during LHC Run 2. Leptonic decays of the Z boson and hadronic decays of the light resonance are considered. The resonance can be interpreted as a J / ψ or η c meson, an axion-like particle, or a light pseudoscalar predicted in two-Higgs-doublet models. Due to its low mass, this resonance is produced with a high Lorentz boost in the laboratory frame and therefore reconstructed as a single small-radius jet of hadrons. A neural network is used to correct the Monte Carlo simulation of the total expected background using data from sideband regions. Two additional neural networks are used to distinguish signal from background, enhancing the purity of the signal region. A binned profile-likelihood fit is performed on the final-state invariant mass distribution. No significant excess of events relative to the expected background is observed, and upper limits at 95% confidence level are set on the Higgs boson's branching fraction to a Z boson and a light resonance. The exclusion limit is ∼10% for the lower masses, and increases for higher masses. Upper limits on the effective coupling C Z H eff / Λ of an axion-like particle to a Higgs boson and Z boson are also set at 95% confidence level, and range from 0.9 to 2 TeV−1.

Aad, G↗

Head restraint enhances visual monitoring performance

Subjects monitored a visual display for occasional increments in the horizontal movement of a bar of light. When the display was viewed without head restraint, detection probability was directly related to the amplitude of the increments in movement which constituted critical signals and inversely related to background event rate (the frequency of neutral events in which critical signals were embedded). When positioning of the head was restrained by a headrest, the detectability of low-amplitude signals was enhanced considerably and the influence of background event rate was attenuated. The results are considered as providing further support for the importance of sense mode coupling in visual monitoring.

Warm, J. S.↗

Laser Sources for Generation of Ultrasound

Two laser systems have been built and used to demonstrate enhancements beyond current technology used for laser-based generation and detection of ultrasound. The first system consisted of ten Nd:YAG laser cavities coupled electronically and optically to permit sequential bursts of up to ten laser pulses directed either at a single point or configured into a phased array of sources. Significant enhancements in overall signal-to-noise ratio for laser ultrasound incorporating this new source system was demonstrated, using it first as a source of narrowband ultrasound and secondly as a phased array source producing large enhanced signal displacements. A second laser system was implemented using ultra fast optical pulses from a Ti:Sapphire laser to study a new method for making laser generated ultrasonic measurements of thin films with thicknesses on the order of hundreds of angstroms. Work by prior investigators showed that such measurements could be made based upon fluctuations in the reflectivity of thin films when they are stressed by an arriving elastic pulse. Research performed using equipment purchased under this program showed that a pulsed interferometric system could be used as well as a piezoreflective detection system to measure pulse arrivals even in thin films with very low piezoreflective coefficients.

Wagner, James W.↗

Graphical derivations of radar, sonar, and communication signals

The designer of a communication system often has knowledge concerning the changes in distance between transmitter and receiver as a function of time. This information can be exploited to reduce multipath interference via proper signal design. A radar or sonar may also have good a priori information about possible target trajectories. Such knowledge can again be used to reduce the receiver's response to clutter (MTI), to enhance signal-to-noise ratio, or to simplify receiver design. There are also situations in which prior knowledge about trajectories is lacking. The system should then utilize a single-filter pair which is insensitive to the effects induced by relative motion between transmitter, receiver, and reflectors. For waveforms with large time-bandwidth products, such as long pulse trains, it is possible to graphically derive signal formats for both situations (trajectory known and unknown). Although the exact form of the signal is sometimes not specified by the graphical procedure, the problem in such cases is reduced to one which has already been solved, i.e., the generation of an impulse equivalent code.

Altes, R. A.↗

Phase-weighted slant stacking for surface wave dispersion measurement

SUMMARY Surface wave retrieval from ambient noise records using seismic interferometry techniques has been widely used for multiscale shear wave velocity (Vs) imaging. One key step during Vs imaging is the generation of dispersion spectra and the extraction of a reliable dispersion curve from the retrieved surface waves. However, the sparse array geometry usually affects the ability for high-frequency (>1 Hz) seismic signals’ acquisition. Dispersion measurements are degraded by array response due to sparse sampling and often present smeared dispersion spectra with sidelobe artefacts. Previous studies usually focus on interferograms’ domain (e.g. cross-correlation function) and attempt to enhance coherent signals before dispersion measurement. We propose an alternative technique to explicitly deblur dispersion spectra through use of a phase-weighted slant-stacking algorithm. Numerical examples demonstrate the strength of the proposed technique to attenuate array responses as well as incoherent noise. Three different field examples prove the flexibility and superiority of the proposed technique: the first data set consists of ambient noise records acquired using a nodal seismometer array; the second data set utilizes distributed acoustic sensing (DAS) and a marine fibre-optic cable to acquire a similar ambient noise data set; the last data set is a vibrator-based active-source surface wave data. The enhanced dispersion measurements provide cleaner and higher-resolution spectra without distortions which will assist both human interpreters as well as ML algorithms in efficiently picking curves for subsequent Vs inversion.

58 GEOSCIENCES↗

Likelihood-based interactive local docking into cryo-EM maps in ChimeraX

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 Å. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation-search step enhances the signal to noise. A Fourier-space likelihood-based local search approach, based on the previously published em_placement software, has been implemented in the new emplace_local program. Tests confirm that the local search approach enhances the speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular-graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed.

59 BASIC BIOLOGICAL SCIENCES↗

Modulating above-room-temperature magnetism in Ga-implanted Fe 5 GeTe 2 van der Waals magnets

The creation of van der Waals (vdW) ferromagnets with tunable Curie temperature (T C ) and magnetic anisotropy is essential in developing vdW magnet-based devices. Here, we report an effective and reliable method for modulating the magnetic properties of vdW Fe 5 GeTe 2 by site-specific Ga + implantation. In this study, we report an easy axis in the ab-plane for bulk Fe 5 GeTe 2 (T C = 310 K) and an axis out of the plane for thin Fe 5 GeTe 2 flakes (T C = 290 K). Combining element-resolved photoemission electron microscopy and spatially resolved magneto-optic Kerr microscopy, we find that the implantation of a tiny amount of 10 –3 Ga + ·Å –3 in Fe 5 GeTe 2 greatly enhances the T C from 290 to 360 K and switches the magnetic easy axis from the out-of-plane c axis to the ab-plane. The room-temperature x-ray magnetic circular dichroism signal is enhanced from 0% to 9% at an implantation level of 10 –2 Ga + ·Å –3 . These results provide new opportunities for tailoring the magnetic properties of vdW materials beyond room temperature.

36 MATERIALS SCIENCE↗

Distributed Fiber Sensors With High Spatial Resolution in Extreme Radiation Environments in Nuclear Reactor Cores

This paper is a comprehensive experimental report on the neutron radiation effects of distributed optical fiber sensors with enhanced Rayleigh scattering profiles in an in-pile environment. Femtosecond laser direct writing was used to inscribe Type-II modifications in standard telecom fibers and radiation-hardened fibers with fluorine-doped cores. Rayleigh backscattering signals were enhanced for continuous 1.5 m. In-pile lead-out sensors tests were carried out at the MIT Research Reactor for two months, which was operated at a nominal power of 5.7 MW with fast neutron (>0.1 MeV) flux of 1.29 × 1014 n/cm2/s and an in-core temperature of up to 560°C. Using the Optical Frequency Domain Reflectometry technique, the backscattering profiles of fiber sensors were interrogated with a 3-cm spatial resolution to monitor the temperature profile of the reactor. Results show that laser inscribed Type-II modifications in the form of nanogratings are highly stable against extreme temperature and ionizing radiation. Both standard telecom fibers and radiation-hardened fibers with laser-enhanced Rayleigh profiles can continuously perform distributed temperature measurements over the entire duration of the in-pile testing. Temperature coefficients of sensors and spectral shift quality were studied as functions of total radiation fluence. To the best of our knowledge, we present for the first time, the temperature profile of an operating nuclear reactor core with 3-cm spatial resolution, enabled by distributed fiber sensors with laser-enhanced Rayleigh scattering profiles. The high spatial resolution measurements can provide valuable data for the design and validation of digital twin and virtual reality of nuclear energy systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Dimuon production in the MicroBooNE detector

This analysis studies the production of the rare signal with two muons (dimuon) in the finalstate at µB using the Booster Neutrino Beam (BNB) as source of neutrino interactions. Themain background source for the dimuon signal are pions. Differentiating muons and pions hasbeen challenging at µB because the tracks left by these particles are almost identical. Thisanalysis faces this problem using a supervised classifier algorithm called boosted decisiontree (BDT). A Monte Carlo simulation (MC) enhanced dimuon signal sample was producedto train a BDT capable of recognizing this signal. A set of variables that show somediscrimination characteristics was used to perform the training. A MC neutrino interactionsimulation sample was used to estimate the background. Estimations of dimuon productionin real data samples were made for different cases. Additionally, an analysis of the systematicuncertainties, fake data studies, and BDT performance checks were obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

High-Spatial-Resolution Mass Rates From GRACE and GRACE-FO: Global and Ice Sheet Analyses

GRACE and GRACE-FO gravimetry data are unique in its ability to observe global water mass variability and has frequently been applied for the determination of global mass rates to quantify the impacts of climate change and human activity on global freshwater availability and land ice evolution. However, its relatively coarse spatial resolution of ∼300-500 km at monthly intervals precludes its direct use to measure mass changes in smaller drainage basins and individual glacier systems. We present a new global high resolution mascon product that improves spatial resolution and signal recovery by estimating trends directly from more than 16 years of Level 1B GRACE and GRACE-FO data. We compare this product to independent gravimetry spherical harmonic trend estimates and to ice sheet mass rates derived from ICESat and ICESat-2 laser altimetry. We demonstrate enhanced global signal recovery and improved agreement with ICESat/ ICESat-2 and discuss likely causes for the remaining discrepancies between the gravimetry and laser altimetry solutions.

Bryant D. Loomis↗

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗

Search for TeV gamma-ray emission from Hercules X-1

Six years of observations of Hercules X-1 with the Whipple Observatory gamma-ray telescope have been subjected to a Fourier analysis to search for emission at the 0.8079 Hz neutron star frequency. Evidence for a signal is found at the 99.5 percent confidence level for data taken with the medium-resolution imaging camera with some indications of emission at frequencies blueshifted from the fundamental frequency. However, analysis of the high-resolution camera data base have failed to substantiate this effect. Selection of events on the basis of gamma-ray-like image parameters did not enhance the signal from the medium-resolution data nor produce any indication of a signal from the high-resolution data. The overall conclusion is that no statistically significant evidence for TeV gamma-ray emission was found in the Whipple Observatory data base when the 6 years of data are taken as a whole.

Reynolds, P. T.↗

Patterned anodes with sub-millimeter spatial resolution for large-area MCP-based photodetector systems

Micro-channel-plate-based photo-detectors are unique in being capable of covering very large areas such as those required in elementary particle and nuclear physics, while providing sub-millimeter space resolution, time resolutions of less than 10 picoseconds for charged particles, and time resolutions of 30 psec–50 psec for single photons. In such systems the electronic channel count is a major cost driver. Incorporating a capacitively-coupled anode allows the use of external pickup electrodes with patterns of individual channels optimized for occupancy, rate, and time/space resolution. The signal pickup antenna can be economically implemented as a printed circuit card with a 2-dimensional array of pads for high-occupancy/high-rate applications such as in particle colliders and medical imaging, or a 1-dimensional array of strips for a lower channel count in low-occupancy/low-rate applications such as large neutrino detectors. In this paper we present pad patterns that enhance signal-sharing between pads to lower the channel count per unit area in large-area systems by factors up to 4, while maintaining spatial resolutions of approximately 100 to 200 μ m for charged particles and 400 to 1000 μ m for single photons. Patterns that use multiple signal layers in the signal-pickup board can lower the channel count even further, moving the scaling behavior in the number of pads versus total area from quadratic to linear.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗