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At least 415 records · Page 23

Liveness as a factor to evaluate memory vulnerability to soft errors

Memory, used by a computer to store data, is generally prone to faults, including permanent faults (i.e. relating to a lifetime of the memory hardware), and also transient faults (i.e. relating to some external cause) which are otherwise known as soft errors. Since soft errors can change the state of the data in the memory and thus cause errors in applications reading and processing the data, there is a desire to characterize the degree of vulnerability of the memory to soft errors. In particular, once the vulnerability for a particular memory to soft errors has been characterized, cost/reliability trade-offs can be determined, or soft error detection mechanisms (e.g. parity) may be selectively employed for the memory. In some cases, memory faults can be diagnosed by redundant execution and a diagnostic coverage may be determined.

Bramley, Richard Gavin↗

Electron-mediated entanglement of two distant macroscopic ferromagnets within a nonequilibrium spintronic device

Using the nascent concept of quantum spin-transfer torque, we demonstrate that a current pulse can be harnessed to entangle quantum localized spins of two spatially separated ferromagnets (FMs) which are initially unentangled. The envisaged setup is composed of a spin-polarizer (FM p ) and a spin-analyzer (FM a ) FM layers separated by a normal metal (NM) spacer. The injection of a current pulse into the device leads to a time-dependent superposition of many-body states characterized by a high degree of entanglement between the spin degrees of freedom of the two distant FM layers. The nonequilibrium dynamics are due to the transfer of spin angular momentum from itinerant electrons to the localized spins via a quantum spin-torque mechanism that remains active even for collinear but antiparallel arrangements of the FM p and FM a magnetizations (a situation in which the conventional spin torque is absent). We quantify the mixed-state entanglement generated between the FM layers by tracking the time evolution of the full density matrix and analyzing the build-up of the mutual logarithmic negativity over time. The effect of decoherence and dissipation in the FM layers due to coupling to bosonic baths at finite temperature, the use of multielectron current pulses, and the dependence on the number of spins are also considered in an effort to ascertain the robustness of our predictions under realistic conditions. Lastly, we propose a “current-pump–x-ray-probe” scheme, utilizing ultrafast x-ray spectroscopy, that can witness nonequilibrium and transient entanglement of the FM layers by extracting its time-dependent quantum Fisher information.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Optimization and characterization of a silicon photomultiplier-based ZnS(Ag) proton recoil fast neutron detector for nuclear fuel performance monitoring at TREAT

The restart of the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory and consequent refurbishment of the Fuel Motion Monitoring System (FMMS), or Hodoscope, offers the opportunity to upgrade the detector system used for neutron imaging. Silicon photomultipliers (SiPMs) are a viable option for updating the Hodoscope to yield improved fuel monitoring capability. The Hodoscope uses ZnS(Ag) proton recoil scintillators (PRS) that provide good gamma-ray suppression and discrimination. Previous work showed that the Hamamatsu S13360-6075CS SiPM offers the best neutron detection and gamma-ray discrimination capability with the ZnS PRS. This work optimizes a SiPM-based detector and develops a PRS prototype for testing. Specifically, possible overvoltages for use are determined by confirming steady operation over extended measurement times. In addition, various SiPM-circuit implementations are tested to optimize the detector according to desired properties, and ultimately a PRS prototype is developed with modifiable components for versatile testing. Measurements of the neutron detection efficiency and gamma-ray rejection efficiency of SiPM-based PRS detectors and a reference PMT-based detector are also carried out. Neutron detection efficiency ranges between 1-2%, and detected gamma-ray rejection efficiency is on the order of 10 -7 . In conclusion, use of a low-pass filter only or a low-pass filter and 50-ω shunt resistor is recommended for the SiPM-based detector, and both configurations demonstrate improved performance over the PMT-based detector.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

The rate of extreme coronal line emitting galaxies in the Sloan Digital Sky Survey and their relation to tidal disruption events

High-ionization iron coronal lines (CLs) are a rare phenomenon observed in galaxy and quasi-stellar object spectra that are thought to be created by high-energy emission from active galactic nuclei and certain types of transients. In cases known as extreme coronal line emitting galaxies (ECLEs), these CLs are strong and fade away on a time-scale of years. The most likely progenitors of these variable CLs are tidal disruption events (TDEs), which produce sufficient high-energy emission to create and sustain the CLs over these time-scales. To test the possible connection between ECLEs and TDEs, we present the most complete variable ECLE rate calculation to date and compare the results to TDE rates from the literature. To achieve this, we search for ECLEs in the Sloan Digital Sky Survey (SDSS). We detect sufficiently strong CLs in 16 galaxies, more than doubling the number previously found in SDSS. Using follow-up spectra from the Dark Energy Spectroscopic Instrument and Gemini Multi-Object Spectrograph, Wide-field Infrared Survey Explorer mid-infrared observations, and Liverpool Telescope optical photometry, we find that none of the nine new ECLEs evolve in a manner consistent with that of the five previously discovered variable ECLEs. Using this sample of five variable ECLEs, we calculate the galaxy-normalized rate of variable ECLEs in SDSS to be $R_\mathrm{G}=3.6~^{+2.6}_{-1.8}~(\mathrm{statistical})~^{+5.1}_{-0.0}~(\mathrm{systematic})\times 10^{-6}~\mathrm{galaxy}^{-1}~\mathrm{yr}^{-1}$. The mass-normalized rate is $R_\mathrm{M}=3.1~^{+2.3}_{-1.5}~(\mathrm{statistical})~^{+4.4}_{-0.0}~(\mathrm{systematic})\times 10^{-17}~\mathrm{M_\odot ^{-1}}~\mathrm{yr}^{-1}$ and the volumetric rate is $R_\mathrm{V}=7~^{+20}_{-5}~(\mathrm{statistical})~^{+10}_{-0.0}~(\mathrm{systematic})\times 10^{-9}~\mathrm{Mpc}^{-3}~\mathrm{yr}^{-1}$. Our rates are one to two orders of magnitude lower than TDE rates from the literature, which suggests that only 10–40 per cent of all TDEs produce variable ECLEs. Additional uncertainties in the rates arising from the structure of the interstellar medium have yet to be included.

79 ASTRONOMY AND ASTROPHYSICS↗

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗

SOAR/Goodman Spectroscopic Assessment of Candidate Counterparts of the LIGO/Virgo Event GW190814*

On 2019 August 14 at 21:10:39 UTC, the LIGO/Virgo Collaboration (LVC) detected a possible neutron star–black hole merger (NSBH), the first ever identified. An extensive search for an optical counterpart of this event, designated GW190814, was undertaken using the Dark Energy Camera on the 4 m Victor M. Blanco Telescope at the Cerro Tololo Inter-American Observatory. Target of Opportunity interrupts were issued on eight separate nights to observe 11 candidates using the 4.1 m Southern Astrophysical Research (SOAR) telescope’s Goodman High Throughput Spectrograph in order to assess whether any of these transients was likely to be an optical counterpart of the possible NSBH merger. Here, we describe the process of observing with SOAR, the analysis of our spectra, our spectroscopic typing methodology, and our resultant conclusion that none of the candidates corresponded to the gravitational wave merger event but were all instead other transients. Finally, we describe the lessons learned from this effort. Application of these lessons will be critical for a successful community spectroscopic follow-up program for LVC observing run 4 (O4) and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗

Infrared signature of the hydroperoxyalkyl intermediate (·QOOH) in cyclohexane oxidation: An isomer-resolved spectroscopic study

Infrared (IR) action spectroscopy is utilized to characterize carbon-centered hydroperoxy-cyclohexyl radicals (·QOOH) transiently formed in cyclohexane oxidation. The oxidation pathway leads to three nearly degenerate ·QOOH isomers, β-, γ-, and δ-QOOH, which are generated in the laboratory by H-atom abstraction from the corresponding ring sites of the cyclohexyl hydroperoxide (CHHP) precursor. The IR spectral features of jet-cooled and stabilized ·QOOH radicals are observed from 3590 to 7010 cm −1 (∼10–20 kcal mol −1 ) at energies in the vicinity of the transition state (TS) barrier leading to OH radicals that are detected by ultraviolet laser-induced fluorescence. The experimental approach affords selective detection of β-QOOH, arising from its significantly lower TS barrier to OH products compared to γ and δ isomers, which results in rapid unimolecular decay and near unity branching to OH products. The observed IR spectrum of β-QOOH includes fundamental and overtone OH stretch transitions, overtone CH stretch transitions, and combination bands involving OH or CH stretch with lower frequency modes. The assignment of β-QOOH spectral features is guided by anharmonic frequencies and intensities computed using second-order vibrational perturbation theory. The overtone OH stretch (2ν OH ) of β-QOOH is shifted only a few wavenumbers from that observed for the CHHP precursor, yet they are readily distinguished by their prompt vs slow dissociation rates to OH products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tracking animal movements via collaborative acoustic telemetry networks: Multiscale habitat use, phenology, and management insights

Abstract Estuaries support diverse fish and invertebrate communities, including resident species that rely on estuarine habitats year‐round and transient migratory species. The unique movement patterns of these animals connect habitats within and far beyond the estuary and are integrally linked to fisheries management objectives. With a focus on Chesapeake Bay, this study leveraged data from collaborative acoustic telemetry networks in the northwest Atlantic to assess habitat use and phenology of movements for seven species of fish (cownose rays, dusky sharks, smooth dogfish, alewife, striped bass, common carp, and blue catfish) and one invertebrate (horseshoe crabs). A total of 288 acoustically tagged individuals were detected >3.2 million times (6,743 to 2,095,717 detections per species) on receivers across ~20.5 degrees of latitude spanning the North American Atlantic seaboard from Florida, USA, to New Brunswick, Canada. Common metrics of movement and phenology grouped these species as resident (common carp, blue catfish, horseshoe crabs), primarily resident in estuaries (juvenile striped bass), and coastal migrant (cownose rays, dusky sharks, smooth dogfish, alewife); maximum distance traveled varied by three orders of magnitude among these species. Further analysis of phenology for coastal migrants elucidated the timing and duration of these species' use of Chesapeake Bay. Collectively, movements linked habitats within Chesapeake Bay and connected the estuary to coastal ecosystems both to the north (e.g., alewife) and south (e.g., cownose rays), creating networks of fisheries management jurisdictions that varied in complexity and identified opportunities for enhancement to current management or co‐management of some species. Our results elucidate the importance of estuaries to species with diverse movement behaviors, identify scales and pathways of habitat connectivity via animal movements, and highlight the utility of collaborative acoustic telemetry networks for quantifying movements relevant to both ecological research and fisheries management.

Livernois, Mariah C.↗

A Current Limiting Control Strategy for Single-Loop Droop-Controlled Grid-Forming Inverters Under Balanced and Unbalanced Faults

Existing studies reporting current limiting control strategies for grid-forming inverters primarily focus on grid-forming inverters that use a multi-loop control structure. This study reports a current limiting control for grid-forming inverters that uses a single-loop control structure. The proposed current limiting control was implemented at the pulse width modulation (PWM) control layer to guarantee a rapid response. Once an overcurrent caused by severe faults is detected, the proposed control strategy immediately blocks relevant insulated-gate bipolar transistors (IGBTs) using a hysteresis loop, ensuring that the overcurrent is limited within a few PWM cycles. After the fault is cleared, the inverter seamlessly transfers back to droop control mode to maintain stability. The current limiting control has been tested in a microgrid environment operating in the OPAL-RT platform. Study results show that the control strategy can effectively limit the overcurrent under both balanced and unbalanced faults and can maintain system transient stability after the fault is cleared.

Du, Wei↗

Large Angle Deviation in Grid-Following IBRs Upon Grid Voltage Dip

In the 2021 Texas Odessa large-scale solar PV tripping events, phase-locked-loop (PLL) loss of synchronism is identified as a major cause of solar PV tripping. When solar PVs detected a large phase angle deviation (e.g., 10 degrees), tripping commands were initiated. Here, the large phase angle deviation was triggered by a transmission line fault 200 miles away, which in turn led to approximately 30% voltage drop in the 345-kV system. This paper offers a plausible reason why grid-following inverter-based resources (IBRs) may experience a large angle deviation upon grid voltage dip. Critical operating conditions contributing to such phenomena are identified via analysis and their effects are demonstrated using electromagnetic transient (EMT) simulation. Furthermore, the effect of converter control, e.g., grid-following control vs. grid-forming control, is examined. It is found from EMT simulation results that frequency and voltage control are helpful in mitigating angle deviation. Furthermore, linear block diagrams are derived to examine why frequency control can effectively suppress large angle deviation.

14 SOLAR ENERGY↗

Photon-shot-noise-limited transient absorption soft X-ray spectroscopy at the European XFEL

Femtosecond transient soft X-ray absorption spectroscopy (XAS) is a very promising technique that can be employed at X-ray free-electron lasers (FELs) to investigate out-of-equilibrium dynamics for material and energy research. Here, a dedicated setup for soft X-rays available at the Spectroscopy and Coherent Scattering (SCS) instrument at the European X-ray Free-Electron Laser (European XFEL) is presented. It consists of a beam-splitting off-axis zone plate (BOZ) used in transmission to create three copies of the incoming beam, which are used to measure the transmitted intensity through the excited and unexcited sample, as well as to monitor the incoming intensity. Since these three intensity signals are detected shot by shot and simultaneously, this setup allows normalized shot-by-shot analysis of the transmission. For photon detection, an imaging detector capable of recording up to 800 images at 4.5 MHz frame rate during the FEL burst is employed, and allows a photon-shot-noise-limited sensitivity to be approached. The setup and its capabilities are reviewed as well as the online and offline analysis tools provided to users.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Radio and X-Ray Observations of the Luminous Fast Blue Optical Transient AT 2020xnd

We present deep X-ray and radio observations of the fast blue optical transient (FBOT) AT 2020xnd/ZTF 20acigmel at z = 0.2433 from 13 days to 269 days after explosion. AT 2020xnd belongs to the category of optically luminous FBOTs with similarities to the archetypal event AT 2018cow. AT 2020xnd shows luminous radio emission reaching L ν ≈ 8 × 10 29 erg s -1 Hz -1 at 20 GHz and 75 days post-explosion, accompanied by luminous and rapidly fading soft X-ray emission peaking at L X ≈ 6 × 10 42 erg s -1 . Interpreting the radio emission in the context of synchrotron radiation from the explosion's shock interaction with the environment, we find that AT 2020xnd launched a high-velocity outflow (v ~ 0.1c–0.2c) propagating into a dense circumstellar medium (effective $\dot{M}\approx {10}^{-3}\,{M}_{\odot }$ yr -1 for an assumed wind velocity of v w = 1000 km s -1 ). Similar to AT 2018cow, the detected X-ray emission is in excess compared to the extrapolated synchrotron spectrum and constitutes a different emission component, possibly powered by accretion onto a newly formed black hole or neutron star. These properties make AT 2020xnd a high-redshift analog to AT 2018cow, and establish AT 2020xnd as the fourth member of the class of optically luminous FBOTs with luminous multiwavelength counterparts.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance Validation of Pulsed Thermal Imaging System for In-Service Applications

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermography Imaging (PTI) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTI method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTI method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTI system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTI capabilities in detecting microscopic defects in metallic specimens. SS316 and IN718 specimens were developed with a pattern of subsurface calibrated flat bottom hole (FBH) defects with diameters from 500µm to 200µm. FBH’s were created with EDM (electron discharge machining) drill. PTI imaging data was processed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) algorithm. We show that defects as small as 200µm in SS316 and IN718 can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature.

42 ENGINEERING↗

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Origin of proton irradiation-induced deep acceptors in Al 0.70 Ga 0.30 N

Deep level defect introduction and carrier removal were characterized using steady-state photocapacitance (SSPC), deep level transient spectroscopy (DLTS) and lighted capacitance–voltage for proton irradiated n-type Al 0.70 Ga 0.30 N Schottky diodes grown by metal-organic vapor phase epitaxy on AlN-on-sapphire templates. SSPC observed deep levels in the as-grown diode with zero-phonon transition energies of 2.20, 2.65, 3.10, 3.40, and 4.65 eV relative to the conduction band minimum (E c ), and an additional deep level emerged at 1.20 eV with irradiation. Lighted capacitance–voltage measurements quantified the deep level concentration (N t ) of states detected by SSPC, and it was observed that N t increased with proton fluence only for the 1.2 and 4.65 eV levels. Carrier removal was much larger than the increase in N t of the 1.2 and 4.65 eV deep levels, suggesting that radiation-induced deep level compensators existed beyond what was detected with SSPC. DLTS detected additional, proton-induced deep acceptors at E c —0.55, 0.82, and 1.16 eV, the latter of which is likely the same 1.20 eV deep state observed by SSPC. The concentration of the E c —0.82 eV defect state was large enough to reconcile carrier removal with total deep level introduction. Comparing the E c —0.82 and 1.16 eV deep acceptor levels to previous experimental and theoretical reports suggests that their atomistic origins could be the nitrogen vacancy (V N ) and oxygen substituting on the nitrogen sub-lattice (O N ), respectively. This defect behavior contrasts starkly with GaN, where V N and O N are shallow donors, and demonstrates that the electronic properties of defects can evolve drastically within the AlGaN alloy system ranging from wide bandgap GaN to ultra-wide bandgap AlN.

Armstrong, Andrew Michael [Sandia National Laborat↗

SPT-3G+: mapping the high-frequency cosmic microwave background using kinetic inductance detectors

We present the design and science goals of SPT-3G+, a new camera for the South Pole Telescope, which will consist of a dense array of 34100 kinetic inductance detectors measuring the cosmic microwave background (CMB) at 220, 285 and 345 GHz. The SPT-3G+ dataset will enable new constraints on the process of reionization, including measurements of the patchy kinematic Sunyaev-Zeldovich effect and improved constraints on the optical depth due to reionization. At the same time, it will serve as a pathfinder for the detection of Rayleigh scattering, which could allow future CMB surveys to constrain cosmological parameters better than from the primary CMB alone. In addition, the combined, multi-band SPT-3G and SPT-3G+ survey data, will have several synergies that enhance the original SPT-3G survey, including: extending the redshift-reach of SZ cluster surveys to z > 2; understanding the relationship between magnetic fields and star formation in our Galaxy; improved characterization of the impact of dust on inflationary B-mode searches; and characterizing astrophysical transients at the boundary between mm and sub-mm wavelengths. Finally, the modular design of the SPT-3G+ camera allows it to serve as an on-sky demonstrator for new detector technologies employing microwave readout, such as the on-chip spectrometers that we expect to deploy during the SPT-3G+ survey. In this paper, we describe the science goals of the project and the key technology developments that enable its powerful yet compact design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Non-destructive identification of absorptive damage sites by photoluminescence brightening

We present a non-destructive photoluminescence (PL) imaging strategy for probing damage growth behavior in fused silica under laser irradiation. Transient wide-field PL image measurements were conducted at varying excitation intensities to investigate the dynamics of radiative defect generation and annihilation in laser-induced damage sites. Our results reveal that, while low excitation intensities predominantly induce PL quenching due to defect annihilation, high-intensity excitation (>0.3 GW/cm 2 at 532 nm) triggers pronounced PL brightening (PLB), indicative of radiative defect generation. Image analysis demonstrates that PLB events are strongly correlated with subsequent damage growth (10 J/cm 2 at 351 nm), whereas overall PL intensity is not. No optically detectable morphological changes were observed during PLB, confirming the non-destructive nature of the technique. We propose that PLB arises from defect-assisted absorption of multiple photons at pre-existing absorptive centers, which enhances local absorptivity and initiates further defect formation. These findings establish PLB monitoring as a sensitive diagnostic tool for identifying damage sites with elevated absorptivity, enabling targeted maintenance and improved laser damage management in optical materials.

Materials science↗