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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Distinct Mechanisms and Hydricities of Cp*Ir-Based CO 2 Hydrogenation Catalysts in Basic Water

Transition metal-catalyzed reversible hydrogenation of CO 2 to formate in aqueous solutions under ambient conditions is an attractive environmentally friendly strategy for the storage and transportation of H 2 in a liquid chemical form. Here, mechanistic details for the CO 2 hydrogenation by a series of pentamethylcyclopentadienyl iridium(III) (Cp*Ir) complexes with picolinamidate ligands are investigated through density functional theory and kinetic isotope effects (KIEs) calculations. Additionally, adopting a speciation approach at a pH of 8.2, CO 2 hydrogenation mechanisms of 37 distinct protonation states and conformers of Cp*Ir type complexes are investigated. This imposes a challenging test for the computational modeling in terms of providing a consistent correlation with experimental kinetics and KIE studies of multiple catalysts instead of a single complex. Overall, H 2 heterolysis to generate an iridium hydride intermediate was demonstrated to be the rate determining step, which proceeds via distinct pathways depending on the stereoelectronic properties of the ligand. A peculiar iridium dihydride route was also uncovered, which could be optimized to accelerate the H 2 heterolysis. We have further computed the thermodynamic and kinetic hydricities of 74 complexes with [Cp*Ir(L)(H)] q ( q = -1, 0, 1 depending on the ligand charge by deprotonation or protonation events) general formula. Hydricity values do not show any noticeable correlation with the thermodynamics (Δ G ) of [Cp*Ir(L)(HCO 2 – )] formation but exhibit linear correlation with the kinetics (Δ G ‡ ) of electrophilic CO 2 attack to iridium hydride species, especially when the charges and local structural effects of the metal hydrides are considered. Insights gained in this study on (i) the factors determining the preferred pathway for the rate-limiting H 2 heterolysis step, (ii) the correlation between thermodynamic hydricity and the kinetics of CO 2 insertion to iridium hydride species, and (iii) mechanistic analysis via combination of free energy profiles and KIE studies for a series of iridium catalysts will provide guidelines for the design of next-generation catalysts for the reversible H 2 storage through CO 2 utilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Search for Pulsars around Sgr A* in the First Event Horizon Telescope Data Set

In 2017 the Event Horizon Telescope (EHT) observed the supermassive black hole at the center of the Milky Way, Sagittarius A* (Sgr A*), at a frequency of 228.1 GHz (λ = 1.3 mm). The fundamental physics tests that even a single pulsar orbiting Sgr A* would enable motivate searching for pulsars in EHT data sets. The high observing frequency means that pulsars—which typically exhibit steep emission spectra—are expected to be very faint. However, it also negates pulse scattering, an effect that could hinder pulsar detections in the Galactic center. Additionally, magnetars or a secondary inverse Compton emission could be stronger at millimeter wavelengths than at lower frequencies. We present a search for pulsars close to Sgr A* using the data from the three most sensitive stations in the EHT 2017 campaign: the Atacama Large Millimeter/submillimeter Array, the Large Millimeter Telescope, and the IRAM 30 m Telescope. We apply three detection methods based on Fourier-domain analysis, the fast folding algorithm, and single-pulse searches targeting both pulsars and burst-like transient emission. We use the simultaneity of the observations to confirm potential candidates. No new pulsars or significant bursts were found. Being the first pulsar search ever carried out at such high radio frequencies, we detail our analysis methods and give a detailed estimation of the sensitivity of the search. We conclude that the EHT 2017 observations are only sensitive to a small fraction (≲2.2%) of the pulsars that may exist close to Sgr A*, motivating further searches for fainter pulsars in the region.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Simulation of gallium nitride vertical fin-shaped field effect transistor for use as thermal neutron detector

Through the use of a radiation detection system simulation framework, a gallium nitride vertical fin-shaped field effect transistor (FinFET) was studied for output response when utilized as a thermal neutron detector. The FinFET was assumed to had been backfilled with boron carbide, reactive to thermal neutrons. The GaN FinFET was modeled with radiation transport from MCNP, and the electronic transport from COMSOL Multiphysics. Fabricated FinFET devices (not neutron reactive) were tested to aid in the tuning of the COMSOL FinFET model. Through time-depenent studies, the drain current response pulse to simulated ionization due to single events lead to building of a database of device responses to radiation. By integrating the current pulses over time, the induced charge was calculated. Using the results of the radiation transport PTRAC file in combination with the induced charge database, an integrated charge spectrum was calculated.

Davidson, Bryce L.↗
DOE OSTI2023

Fourier coefficients of noninterdependent collective motions in heavy-ion collisions

Here, we present a scenario in heavy-ion collisions where different modes of collective motions are noninterdependent, driven by factorized actions in the created nuclear medium. Such physics mechanisms could each dominate at a distinct evolution stage, or coexist simultaneously. If the probability of particle emission is modulated by each nondependent collective motion with a single-harmonic Fourier expansion, the particle azimuthal distribution should be the product of all these expansions. Consequently, nonleading cross terms between collectivity modes appear, and their contributions to experimental observables could be significant. In particular, we argue that the chiral magnetic effect (CME) and elliptic flow can develop separately, with their convolution affecting the observable that is sensitive to the shear-induced CME. We will use the event-by-event anomalous-viscous fluid dynamics model to illustrate the effects of this scenario. Besides giving insights into searches for the CME, we also propose feasible experimental tests based on conventional flow harmonics, and demonstrate the emergence of nonleading cross terms with a multiphase transport model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Register-Like Storage Block Used as Histograms, Cluster Buffers, and Hough Transform Accumulators for HEP Trigger Systems

In high energy physics experiment trigger systems, block memories are utilized for various purposes, especially in binned searching algorithms. In these algorithms, the storages are demanded to perform like a large set of registers. The writing and reading operation must be performed in single clock cycle and once an event is processed, the memory must be globally reset. These demands can be fulfilled with registers but the cost of using registers for large memory is unaffordable. Another common requirement is the boundary coverage feature during reading process. Additionally, when a memory bin is addressed, the stored contents in the addressed bin and its neighboring bin must be output simultaneously. In this paper, a register-like block storage design scheme is described, which allows updating memory locations in single clock cycle, reading two adjacent bins, and effectively refreshing entire memory within a single clock. The implementation and test results are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗
DOE OSTI2023

Dirty bomb source term characterization and downwind dispersion: Review of experimental evidence

Dirty bombs are considered one of the easiest forms of radiological terrorism, a form of terrorism based on the deliberate use of radiological material to cause adverse effects in a target population. One U.S. Government official has even described a dirty bomb attack as “all but inevitable”. While people in the vicinity of the blast may experience acute radiation effects, people downwind may unknowingly be contaminated by the radioactive airborne particulate and face increased long-term cancer risk. The likelihood of increased cancer risk depends on the radionuclide used and its specific activity, its aerosolization potential, the particle sizes generated in the blast, and where a person is with respect to the detonation. Different studies have reported that plausible radionuclides for dirty bomb include 60 Co, 90 Sr, 137 Cs, 192 Ir, 241 Am based on their availability in commercial sources as well as safeguards, the amount needed for adverse health effects, previous mishandling of radionuclides and malicious uses. In order to have increased long-term cancer risk, the radionuclide would have to deposit inside the body by entering the respiratory tract and then possibly migrate to other organs or bones (ground shine is not considered in this paper because areas affected by the event will likely become inaccessible). This implies that the particles will have to be smaller than 10 μm to be inhaled. Experiments involving the detonation of dirty bombs have shown that particles or droplets smaller than 10 μm are generated, independently from the initial radionuclide or its state (e.g., powder, solution). Atmospheric tests have shown that in unobstructed terrain, the radionuclide laden cloud can travel kilometers downwind even for relatively small amounts of explosives. Furthermore, buildings in the path of the cloud can change the dose rate. For instance, in one experiment with a single building, the dose rate was 1–2 orders of magnitude lower behind the obstacle compared to its front face. For people walking around, the amount of particulate deposited on them and inhaled will depend on their path relative to the cloud, resulting in the counterintuitive result that the closer people may actually not be the ones more at risk because they could simply miss the bulk of the cloud in their wandering. In summary, the long-term cancer risk for people caught in a dirty bomb cloud away from the detonation requires considering where and when the people are, which radionuclide was used, and the layout of the obstacles (e.g., buildings, vegetation) in the path of the cloud.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Improved Heralded Single-Photon Source with a Photon-Number-Resolving Superconducting Nanowire Detector

Deterministic generation of single photons is essential for many quantum information technologies. A bulk optical nonlinearity emitting a photon pair, where the measurement of one of the photons heralds the presence of the other, is commonly used with the caveat that the single-photon emission rate is constrained due to a trade-off between multiphoton events and pair emission rate. Using an efficient and low noise photon-number-resolving superconducting nanowire detector we herald, in real time, a single photon at telecommunication wavelength. We perform a second-order photon correlation g 2 ( 0 ) measurement of the signal mode conditioned on the measured photon number of the idler mode for various pump powers and demonstrate an improvement of a heralded single-photon source. We develop an analytical model using a phase-space formalism that encompasses all multiphoton effects and relevant imperfections, such as loss and multiple Schmidt modes. We perform a maximum-likelihood fit to test the agreement of the model to the data and extract the best-fit mean photon number μ of the pair source for each pump power. A maximum reduction of 0.118 ± 0.012 in the photon g 2 ( 0 ) correlation function at μ = 0.327 ± 0.007 is obtained, indicating a strong suppression of multiphoton emissions. For a fixed g 2 ( 0 ) = 7 × 10 − 3 , we increase the single pair generation probability by 25%. Our experiment, built using fiber-coupled and off-the-shelf components, delineates a path to engineering ideal sources of single photons.

Davis, Samantha I.↗
DOE OSTI2023

Calibration of the ProtoDUNE Horizontal-Drift position reconstruction using a laser system

Forthcoming in the next decade of neutrino physics advancements is the construction of the Deep Underground Neutrino Experiment (DUNE), a long baseline neutrino oscillation experiment which has the potential to answer fundamental questions such as why there is more matter than antimatter in the universe, and ultimately why we exist at all. A prototype of this experiment, ProtoDUNE, sits in a charged particle test beam at the European Organization for Nuclear Research (CERN) and uses Liquid Argon time projection chambers to image interactions of these particles. ProtoDUNE Single-Phase (ProtoDUNESP) had positively charged hadrons as well as positrons in its initial 2018 beam data run. Because ProtoDUNE is a surface-based time projection chamber, it experiences a constant influx of cosmic rays. These cosmic rays ionize the liquid argon within the detector, resulting in an accumulation of slow moving positive ions towards the cathode. This local charge distribution results in electric field non uniformities, which can have a significant effect on the accuracy of the event reconstruction. This paper outlines a monte carlo simulation study which adapts methodology from the MicroBooNE experiment, another neutrino oscillation experiment, to derive electric field correction maps which can correct for distortions of the electric field within the detector. These correction maps accurately estimate the electric field throughout the detector volume and correct for uncertainties in reconstructed event data enabling for physics discoveries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Advanced Diagnostics of Broad Spectrum Multipactor

Multipactor is a resonance event between electron emission and RF fields causing exponential secondary electron re-emission growth when the secondary electron yield of the primary electron impact energy exceeds unity. Multipactor is a serious problem in vacuum electron devices (VEDs) such as particle accelerators, radars, electronic warfare systems, directed energy devices, and even Hall effect thrusters. It also poses an even greater threat to space communication systems where high power, multi-channel links are required. The UC Davis and SLAC team will conduct basic research to advance the fundamental understanding of multipactor physics by developing and carrying out full spectrum, radio frequency (RF) laboratory tests aimed at understanding both single and two-surface multipactor phenomena and at evaluating novel multipactor mitigation approaches for accelerator, space-based RF systems, as well as high power microwave (HPM) applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The (Un)reasonable Effectiveness of Neural Network in Cherenkov Calorimetry

We report a greater than factor of two improvement in the hadronic energy resolution of a simulated Cherenkov calorimeter by estimating the energy with machine learning over traditional techniques. The prompt signal formation and energy threshold properties of Cherenkov radiation provide identifiable features that machine learning techniques can exploit to produce a superior model for energy reconstruction. We simulated a quartz-fiber calorimeter via the GEANT4 framework to study the reconstruction techniques in single events. We compared the machine learning-based reconstruction performance to the traditional simple sum of signal and dual-readout techniques that use both Cherenkov and scintillation signals. We describe why this game-changing approach to Cherenkov hadron calorimetry excels and our plans for a dedicated beam test to validate these findings with a fast, radiation-hard hadron calorimeter prototype.

Akchurin, Nural↗
DOE OSTI2022

Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory

The Vera C. Rubin Observatory will increase the number of observed supernovae (SNe) by an order of magnitude; however, it is impossible to spectroscopically confirm the class for all SNe discovered. Thus, photometric classification is crucial, but its accuracy depends on the not-yet-finalized observing strategy of Rubin Observatory's Legacy Survey of Space and Time (LSST). We quantitatively analyze the impact of the LSST observing strategy on SNe classification using simulated multiband light curves from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC). First, we augment the simulated training set to be representative of the photometric redshift distribution per SNe class, the cadence of observations, and the flux uncertainty distribution of the test set. Then we build a classifier using the photometric transient classification library snmachine, based on wavelet features obtained from Gaussian process fits, yielding a similar performance to the winning PLAsTiCC entry. We study the classification performance for SNe with different properties within a single simulated observing strategy. We find that season length is important, with light curves of 150 days yielding the highest performance. Cadence also has an important impact on SNe classification; events with median inter-night gap <3.5 days yield higher classification performance. Interestingly, we find that large gaps (>10 days) in light-curve observations do not impact performance if sufficient observations are available on either side, due to the effectiveness of the Gaussian process interpolation. This analysis is the first exploration of the impact of observing strategy on photometric SN classification with LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

FY24 Report on Water NSTF Testing: Lower Tank Inlet Piping Configuration

The following report serves as a summary of the accomplishments and testing results by the Natural convection Shutdown heat removal Test Facility (NSTF) experimental program over the past 12-month period. A major activity included reconfiguration of the chimney piping geometry which altered the discharge position into the tank from the original 50% tank height to a new lower position at a 10.9% tank height. This modification increases the volume of available coolant thus extending long-term operating capacity, however also results in a decreased liquid driving head which has the potential to reduce the natural circulation efficiency and decrease overall performance. Examination of the tradeoffs for these two configurations is an area of interest for RCCS designers and drove planned test activities this year. Ten matrix tests were performed in FY24, totaling 195 hours of heated operations and 12.9 MWh of electrical heating throughout the year, with eight classified as Accepted per NQA-1 and two classified as Trending. Testing prior to the facility reconfiguration examined the facility response to throttling at the tank inlet, demonstrating increased sensitivity of flow instabilities to throttling within the two-phase region when compared to throttling at the lower sensitivity single-phase inlet region. Testing after the chimney reconfiguration began with a baseline test at conditions of 80% inventory fill and prototypic thermal power input of 2.1 MW t . In addition to establishing a reference for nominal system behavior and performance, repeat testing with multiple subsequent runs demonstrated strong repeatability between tests performed at the same conditions in this new configuration. These tests also examined if influences would occur to system behavior with installation of new higher-resolution instrumentation within the upper chimney. In this critical region where boiling and flashing phenomena dominate, the test results provided confidence that the new instrumentation does not uncharacteristically influence the observed behaviors. An inventory parametric series was then initiated to examine system behavior with the new chimney configuration at six varying initial inventory levels, ranging from high 80% to low 20% fill. Two-phase oscillations with similar peak and mean flow rates were observed when comparing to the previous mid tank configuration. Generally, similar system response trends with inventory were also observed, such as two phase oscillations suppressing as inventories were lowered. However, in one absolute inventory comparison at the highest fill of 80%, flow oscillations saw a gradual growth over the 4 hours of two-phase operation in the new lower tank inlet configuration, opposite of the gradual dampening observed in the mid tank inlet configuration. This can be attributed to, in part, a greater hydrostatic head pressure above the two-phase discharge region where the boiling front is developed. Furthermore, the change resulted in greater sensitivity to liquid degassing phenomena during single-phase heating, causing loop instabilities to form which trigged moderate flow degradation during the period approaching saturation and boiling conditions. This behavior had been observed previously under some conditions but was a common occurrence in recent testing with the newer lower tank inlet configuration. Initial observations from these first data sets suggest an overall larger window of stability for the mid tank inlet configuration compared to the lower tank inlet. Lastly, the lowest inventory fill test was repeated over an extended testing window to examine depletion behavior. Natural circulation flow and effective heat removal performance were observed during most of the testing period; only after the tank became fully drained (0% fill) did flow stagnate and violent geysering events occur. This early observation confirms one relative advantage over the mid tank inlet configuration, which stagnated under comparable conditions at ~20% inventory remaining in the tank.

42 ENGINEERING↗
DOE OSTI2022

A Multi-Model Framework for Assessing Long- and Short-Term Climate Influences on the Electric Grid

Climate change influences many aspects of the electric grid, but prior work and industry practices often ignore the potential effects of changing climate, or they only consider a single effect or individual effects in isolation. Challenges vary with each grid and include adapting to long-term trends such as changing temperature and precipitation or shorter-term events such as drought or storms that could increase in frequency or intensity. Here we present a multi-model framework designed to analyze the effects of long and short-term climate impacts in combination. This framework couples capacity expansion and production cost models with hydrologic models and future climate scenario data to analyze alternative climate and energy futures at high spatial, temporal, and process resolutions. Furthermore, we constructed and evaluated the results of a suite of simulated scenarios exploring climate impacts on capacity investment and stress-tested the resulting future infrastructures using hourly dispatch modeling under alternative drought and load conditions. We demonstrate the approach through a case study of the U.S. Western Interconnection, where climate impacts depend on interactions between temperature-induced load, water availability for hydropower, technology competitiveness, and demand flexibility. Changes in 2038 generating capacity range from -8.5-16.6 GW, and changes in 2038 transmission capacity range from -1-2 GW. Capacity increases are driven by higher load from higher temperatures, while capacity reductions can be achieved in scenarios with higher future hydropower availability and increased demand flexibility. Scenarios requiring additional capacity cost an additional $\$5$-$\$17$ billion (discounted) from 2018 to 2038; however, scenarios with capacity reductions cost $\$1$-$\$18$ billion less. Stress tests on four 2038 infrastructures demonstrated that the identified systems were able to serve at least 99.999% of load and 99.96% of reserves. However, drought and unexpected high-load conditions can result in reduced capacity to respond to contingency events we did not model. Although these results are system and scenario specific, they highlight the importance of considering multiple climate change impacts simultaneously in long-term planning efforts and demonstrate a multi-model, multiscale approach that can be flexibly applied to any system and set of climate change concerns.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A User Guide to PARET/ANL

PARET was originally created in 1969 at what is now Idaho National Laboratory (INL), to analyze reactivity insertion events in research and test reactor cores cooled by light or heavy water, with fuel composed of either plates or pins. The use of PARET is also appropriate for fuel assemblies with curved fuel plates when their radii of curvatures are large with respect to the fuel plate thickness. The PARET/ANL version of the code has been developed at Argonne National Laboratory (ANL) under the sponsorship of the U.S. Department of Energy/NNSA since the inception of the Reactor Conversion Program. Since Reduced Enrichment for Research and Test Reactors (RERTR) began in 1978, PARET/ANL has been benchmarked to experimental data including SPERT testing, and used to determine the expected transient behavior of a large number of reactors regardless of enrichment both inside and outside the Reactor Conversion Program. This document provides the pertinent information for the use of PARET/ANL Version 7.6. PARET/ANL models the various fueled regions of a reactor core as channels. Each of these channels consists of a single flat fuel plate/pin (including cladding and, optionally, a gap) with water coolant on each side. In slab geometry the coolant channels for a given fuel plate are of identical dimensions (mirror symmetry), but they can be of different thickness in each channel. There can be many channels, but each channel is independent and coupled only through reactivity feedback effects to the whole core. The time-dependent differential equations that represent the system are replaced by an equivalent set of finite-difference equations in space and time, which are integrated numerically. PARET/ANL uses fundamentally the same numerical scheme as RELAP5 for the time-integration of the point-kinetics equations. The one-dimensional thermal-hydraulic model includes temperature-dependent thermal properties of the solid materials, such as heat capacity and thermal conductivity, as well as the transient heat production and heat transfer from the fuel meat to the coolant. Temperature- and pressure-dependent thermal properties of the coolant such as enthalpy, density, thermal conductivity, and viscosity are also used in determining parameters such as friction factors and heat transfer coefficients. The code first determines the steady-state solution for the initial state. Then the solution of the transient is obtained by integration in time and space. Multiple heat transfer, DNB and flow instability correlations are available. The code was originally developed to model reactors cooled by an open loop, which was adequate for rapid transients in pool-type cores. An external loop model appropriate for Miniature Neutron Source Reactors (MNSR’s) was also added to PARET/ANL to model natural circulation within the vessel, heat transfer from the vessel to pool and heat loss by evaporation from the pool. PARET/ANL also contains models for decay heat after shutdown, control rod reactivity versus time or position, time-dependent pump flow, and loss-of-flow event with flow reversal as well as logic for trips on period, power, and flow. Feedback reactivity effects from coolant density changes and temperature changes are represented by tables. Feedback reactivity from fuel heat-up (Doppler Effect) is represented by a four-term polynomial in powers of fuel temperature. Photo-neutrons produced in beryllium or in heavy water may be included in the point-kinetics equations by using additional delayed neutron groups.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Testing and Design of Discriminants for Local Seismic Events Recorded during the Redmond Salt Mine Monitoring Experiment

The Redmond Salt Mine (RSM) Monitoring Experiment in Utah was designed to record seismoacoustic data at distances less than 50 km for algorithm testing and development. During the experiment from October 2017 to July 2019, six broadband seismic stations were operating at a time, with three of them having fixed locations for the duration, whereas the three other stations were moved to different locations every one-and-half to two-and-half months. RSM operations consist of nighttime underground blasting several times per week. The RSM is located in proximity to a belt of active seismicity, allowing direct comparison of natural and anthropogenic sources. Using the recorded data set, we built 1373 events with local magnitude (M L ) of -2.4 and lower to 3.3. For 75 blasts (RMEs) from the Redmond Salt Mine and 206 tectonic earthquakes (EQs), both M L and the coda duration magnitude (MC) are well constrained. We used these events to test and design discriminants that separate the RMEs from the EQs and are effective at local distances. The discriminants consist of M L -M C , low-frequency Sg to high-frequency Sg, Pg/Sg phase-amplitude ratios, and Rg/Sg spectral amplitude ratios, as well as different combinations of two or more of these classifiers. The areas under the receiver operating characteristic curves (AUCs) of 0.92–1.0 for M L -M C , low-frequency Sg to high-frequency Sg, and Rg/Sg indicate that these discriminants are very effective. Conversely, the AUC of only 0.57 for Pg/Sg suggests that this discriminant is only slightly better than a random classifier. Among the effective classifiers, Rg/Sg, shows the lowest likelihood of misclassification (4.3%) for the populations. In conclusion, results of joint discriminant analyses suggest that even the arguably ineffective single classifier, like Pg/Sg in this case, can provide some value when used in combination with others.

58 GEOSCIENCES↗
DOE OSTI2026

Phase Picking Beyond Local Distances: Where Waveform Filtering Still Matters for Deep Learning Models

Waveform filtering is a standard step in traditional seismic phase picking but often receives little attention in deep learning workflows, where models are typically trained on raw or minimally processed waveforms. Although this strategy performs well for local events, we show that performance can degrade substantially at regional distances. To address this limitation, we introduce two ways to incorporate multiband-filtered waveforms into deep learning phase pickers. The stacking approach concatenates filtered inputs along the channel dimension, while the branching approach processes each frequency band through a dedicated network branch before feature fusion. Both approaches can substantially improve performance across epicentral distances of 0° to 20°, but their effectiveness depends strongly on the selected frequency bands. Tests with multiple filter banks show that filter-bank design should be treated as part of model optimization rather than as a fixed preprocessing choice. Grad-CAM analysis of the branching model indicates that band importance varies among waveform samples and across training realizations, with only a weak overall preference for the 0.25 to 0.5 Hz band. These results show that no single filter band is consistently optimal and demonstrate that explicit feature engineering remains valuable for robust deep learning-based seismic phase picking.

58 GEOSCIENCES↗
DOE OSTI2025

Nanoscale interfacial melting enables bonding during high velocity microparticle impacts

Melting during high-velocity particle impact has been understood to be typically detrimental to bonding by lowering the strength at the interface and promoting rebound before solidification can occur. Here we establish a possible remedy to this challenge: by dramatically restricting the volume of molten material, its resolidification is accelerated, effectively forming a nanoscale, braze-type joint during impact. In-situ single particle impact imaging is combined with post-mortem structural and chemical analyses to reveal a regime where adhesion is governed not by extensive plastic deformation, but by the kinetics of melt layer resolidification. Furthermore, these findings redefine the role of melting in impact-based processes, establishing transient melting and rapid solidification as a viable strategy for engineering successful adhesion events.

Additive manufacturing↗