Search NASA⌕ Search

SEARCH · Search NASA

Results for “trigger efficiency”

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.

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

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mitigating the allergenicity of peanut allergen Ara h 1 by cold atmospheric pressure argon plasma jet

Abstract BACKGROUND Peanut allergy is recognized as a major food allergy that triggers severe and even fatal symptoms. Avoidance of peanuts in the diet is the main option for current safety management. Processing techniques reducing peanut allergenicity are required to develop other options. Cold plasma is currently considered as a novel non‐thermal approach to alter protein structure and has the potential to alleviate immunoreactivity of protein allergen. RESULTS The application of a cold argon plasma jet to peanut protein extract could reduce the amount of a 64 kDa protein band corresponding to a major peanut allergen Ara h 1 using sodium dodecyl sulfate–polyacrylamide gel electrophoresis, but the overall protein size distribution did not change significantly. A decrease in peanut protein solubility was a possible cause that led to the loss of protein content in the soluble fraction. Immunoblotting and enzyme‐linked immunosorbent assay elucidated that the immunoreactivity of Ara h 1 was significantly decreased with the time treated with plasma. Ara h 1 antigenicity reduced by 38% after five scans (approximately 3 min) of cold argon plasma jet treatment, and the reduction was up to 66% after approximately 15 min of treatment. CONCLUSION The results indicate that cold argon plasma jet treatment could be a suitable platform for alleviating the immunoreactivity of peanut protein. This work demonstrates an efficient, compact, and rapid platform for mitigating the allergenicity of peanuts, and shows great potential for the plasma platform as a non‐thermal technique in the food industry. © 2023 Society of Chemical Industry.

Hsu, Fu‐Chiun↗
DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [U. Chicago (main)] (ORCID:00090002189↗
DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [Chicago U.] (ORCID:0009000218901379)↗
DOE OSTI2018

An experimental study of ovarian cancer imaging and therapy by paclitaxel-loaded phase-transformation lipid nanoparticles combined with low-intensity focused ultrasound

Highlights: • PTX-anti-LHRHR-PTNPs is expected to become a new type of ultrasound contrast agent. • LIFU can enhance the efficiency of PTX-anti-LHRHR-PTNPs. • For ovarian cancer, PTX-anti-LHRHR-PTNPs has a good therapeutic effect. Drug-loaded phase-transformation lipid nanoparticles (NPs) combined with low-intensity focused ultrasound (LIFU) for ultrasound molecular imaging and therapy, which is a very promising drug carrier and can provide both physical and chemical therapeutics, simultaneously. We successfully prepared the paclitaxel (PTX) loaded anti-LHRHR targeted phase-transformation lipid nanoparticles (PTX-anti-LHRHR-PTNPs) for ovarian cancer in this study combined with LIFU has the following characteristics: On the one hand, it showed smaller size and greater stability than blood cells, which significantly prolonged its half-life in the body, and can actively target ovarian cancer OVCAR-3 cells, and smoothly penetrate the endothelial gap into the tumor site for specifically killing the ovarian cancer cells. Thereby, the special drug carrier improved the therapeutic effect and reduced toxic and side effects, maximized the protection of normal tissues and minimized adverse reactions. On the other hand, PTX-anti-LHRHR-PTNPs can be targeted to focus after being injected intravenously and remain in the tumor target tissue for a long time. At the same time, liquid-gas phase-transformation can occur under LIFU triggering, resulting in more ideal and sustained ultrasound imaging effects. Then acoustic contrast agent is used to develop the molecular level of ultrasound scattering, so as to evaluate the diseased tissue from the molecular level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Experimental measurement of energy release from an initiating layer in an insensitive explosive

When subjected to a shock of insufficient strength to trigger prompt reaction, heterogenous condensed phase explosives can form regions where significant amounts of the explosive remain unreacted for times much greater than the reaction time of the detonating explosive. This phenomena is observed for the explosive PBX 9502 (95 wt% TATB) both for planar and oblique input shocks. Here, we build on previous results by performing cylinder expansion (CYLEX) tests where the explosive charge is comprised of a faster core of PBX 9501 (95 wt% HMX) inside a slower annulus of PBX 9502. The detonation in the faster PBX 9501 drives an oblique shock into the adjacent PBX 9502, and an annular transverse initiating layer (IL) results. In the test geometry, the IL travels steadily down the length of the test after a short run distance. At radial positions beyond the IL, an annular region of detonating PBX 9502 is observed. Using standard CYLEX test diagnostics, we infer the total energy release of this experiment. By making the assumptions that (1) the combined energy release is comprised of contributions from detonating PBX 9501, detonating PBX 9502, and the IL in the PBX 9502 and (2) mass-specific energy release for the detonating explosives is approximately the same as typically observed for each explosive, the IL energy release and reaction efficiency can be computed. Results are compared to prior results for a similar geometry, and indicate that while shock deadened PBX 9502 does not detonate promptly, it does eventually release a significant portion of its chemical potential energy over longer timescales on the order of 10 µs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Dynamical Instabilities in Systems of Multiple Short-period Planets Are Likely Driven by Secular Chaos: A Case Study of Kepler-102

We investigated the dynamical stability of high-multiplicity Kepler and K2 planetary systems. Our numerical simulations find instabilities in ∼20% of the cases on a wide range of timescales (up to 5 × 10{sup 9} orbits) and over an unexpectedly wide range of initial dynamical spacings. To identify the triggers of long-term instability in multiplanet systems, we investigated in detail the five-planet Kepler-102 system. Despite having several near-resonant period ratios, we find that mean-motion resonances are unlikely to directly cause instability for plausible planet masses in this system. Instead, we find strong evidence that slow inward transfer of angular momentum deficit (AMD) via secular chaos excites the eccentricity of the innermost planet, Kepler-102 b, eventually leading to planet–planet collisions in ∼80% of Kepler-102 simulations. Kepler-102 b likely needs a mass ≳0.1 M {sub ⊕}, hence a bulk density exceeding about half Earth’s, in order to avoid dynamical instability. To investigate the role of secular chaos in our wider set of simulations, we characterize each planetary system’s AMD evolution with a “spectral fraction” calculated from the power spectrum of short integrations (∼5 × 10{sup 6} orbits). We find that small spectral fractions (≲0.01) are strongly associated with dynamical stability on long timescales (5 × 10{sup 9} orbits) and that the median time to instability decreases with increasing spectral fraction. Our results support the hypothesis that secular chaos is the driver of instabilities in many nonresonant multiplanet systems and also demonstrate that the spectral analysis method is an efficient numerical tool to diagnose long-term (in)stability of multiplanet systems from short simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗
DOE OSTI2026

Toward a Climate OSSE Framework for Satellite Mission Design

The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Exploring the Longwave Radiative Effects of Dust Aerosols

Dust aerosols not only affect air quality and visibility where they pose a significant health and safety risk, but they can also play a role in modulating the energy balance of the Earth-atmosphere system by directly interacting with local radiative fields. Consequently, dust aerosols can impact regional climate patterns such as changes in precipitation and the evolution of the hydrological cycle. Assessing the direct effect of dust aerosols at the solar wavelengths is fairly straightforward due in part to the relatively large signal-to-noise ratio in broadband irradiance measurements. The longwave (LW) impacts, on the other hand, are rather difficult to ascertain since the measured dust signal level (10 Wm-2) is on the same order as the instrumental uncertainties. Moreover, compared to the shortwave (SW), limited experimental data on the LW optical properties of dust makes it a difficult challenge for constraining the LW impacts. Owing to the strong absorption features found in many terrestrial minerals (e.g., silicates and clays), the LW effects, although much smaller in magnitude compared to the SW, can still have a sizeable impact on the energetics of the Earth-atmosphere system, which can potentially trigger changes in the heat and moisture surface budgets, and dynamics of the atmosphere. The current endeavor is an integral part of an on-going research study to perform detailed assessments of dust direct aerosol radiative effects (DARE) using comprehensive global datasets from NASA Goddards mobile ground-based facility (cf. http://smartlabs.gsfc.nasa.gov/) during previous field experiments near key dust source regions. Here we examine and compare the results from two of these studies: the 2006 NASA African Monsoon Multidisciplinary Activities and the 2008 Asian Monsoon Years. The former study focused on transported Saharan dust at Sal Island (16.73N, 22.93W), Cape Verde along the west coast of Africa while the latter focused on Asian dust at Zhangye China (39.082N, 100.276E), a semi-arid region between the Taklimakan and Gobi deserts. NASA Goddards Giovanni system is used to help map out the spatial distribution of retrieved aerosol optical depths across the latter desert regions. 1-D radiative transfer model constrained by local measurements, including spectral photometry/interferometry and lidar for characterizing the spatiotemporal variability in dust properties and atmospheric conditions, is employed to evaluate the local instantaneous LW DARE of dust both at the surface and at the top of the atmosphere along with heating rate profiles for cloud-free atmospheres. The efficiency in LW DARE and its significance relative to the diurnally averaged SW effects are explored and compared in both studies. Found to be non-negligible, LW DARE is an important component in the study of regional climate variation with important implications for more detailed global assessments.

Hansell, Richard A., Jr.↗
NASA NTRS2008

Irrigation Requirement Estimation using MODIS Vegetation Indices and Inverse Biophysical Modeling; A Case Study for Oran, Algeria

Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over the study site, for the month of July, spray irrigation resulted in an irrigation amount of about 1.4 mm per occurrence with an average frequency of occurrence of 24.6 hours. The simulated total monthly irrigation for July was 34.85 mm. In contrast, the drip irrigation resulted in less frequent irrigation events with an average water requirement about 57% less than that simulated during the spray irrigation case. The efficiency of the drip irrigation method rests on its reduction of the canopy interception loss compared to the spray irrigation method. When compared to a country-wide average estimate of irrigation water use, our numbers are quite low. We would have to revise the reported country level estimates downward to 17% or less

Bounoua, L.↗
DOE OSTI2026

Impacts of Pasture Conversion to Sugarcane on Water Fluxes and Water Use Efficiency in the Southeastern US

The expansion of sugarcane (cane), a high-yielding perennial crop, will likely reshape the bioenergy landscape in the Southeastern US. However, its ecohydrological implications, particularly following conversion from grazed pastures, a dominant land use in the region, remain highly uncertain. We investigated the impact of cane expansion on evapotranspiration (ET) and its partitioning, and the mechanisms influencing both ET components and water use efficiency (WUE) across multiple scales and growth cycles in subtropical Florida. We combined eddy covariance, biometric measurements, and process-based stomatal conductance (g s ) models. ET was 1.7% lower in cane than in improved pasture (IMP) but exceeded that in semi-native pasture (SN) by 21%. Transpiration (T) followed a similar pattern, consistent with lower g s in cane relative to IMP. Cane had more conservative water use and greater sensitivity of g s to vapor pressure deficit (VPD) compared to IMP pasture, suggesting cane may be more tolerant of increasing atmospheric water demand. In contrast, SN showed lower g s and weaker stomatal sensitivity to VPD compared to cane, resulting in lower T. In cane, stomatal regulation and T varied across growth cycles, with stomata becoming less water conservative as stands matured, highlighting the importance of incorporating stand age-dependent stomatal regulation into hydrological models. Evaporation (E) was higher in cane than pastures (19%–26%), partially offsetting WUE gains. Cane exhibited higher intrinsic WUE (GPP/g s ; Gross Primary Productivity), ecosystem WUE (GPP/ET), and harvest WUE (harvest/ET) than both pasture types. Large-scale pasture-to-cane conversion could produce widely contrasting hydrological outcomes. The net regional impact will depend on the proportion of each pasture type converted and on cane's high g s sensitivity to VPD, which triggers tight stomatal regulation and conservative water use, both of which will become increasingly consequential under intensifying atmospheric water demand.

bioenergy↗
NASA NTRS2010

Trace Gas Measurements on Mars and Earth Using Optical Parametric Generation

Trace gases and their isotopic ratios in planetary atmospheres offer important but subtle clues as to the origins of a planet's atmosphere, hydrology, geology, and potential for biology. An orbiting laser remote sensing instrument is capable of measuring trace gases on a global scale with unprecedented accuracy, and higher spatial resolution that can be obtained by passive instruments. We have developed an active sensing instrument for the remote measurement of trace gases in planetary atmospheres (including Earth). The technique uses widely tunable, seeded optical parametric generation (OPG) to measure methane, CO2, water vapor, and other trace gases in the near and mid-infrared spectral regions. Methane is a strong greenhouse gas on Earth and it is also a potential biogenic marker on Mars and other planets. Methane in the Earth's atmosphere survives for a shorter time than CO2 but its impact on climate change can be larger than CO2. Methane levels have remained relatively constant over the last decade around 1.78 parts per million (ppm) but recent observations indicate that methane levels may be on the rise. Increasing methane concentrations may trigger a positive feedback loop and a subsequent runaway greenhouse effect, where increasing temperatures result in increasing methane levels. The NRC Decadal Survey recognized the importance of global observations of greenhouse gases and called for simultaneous CH4, CO, and CO2 measurements but also underlined the technological limitations for these observations. For Mars, methane measurements are of great interest because of its potential as a strong biogenic marker. A remote sensing instrument that can measure day and night over all seasons and latitudes can identify and localize sources of biogenic gas plumes produced by subsurface chemistry or biology, and aid in the search for extra-terrestrial life. It can identify the dynamics of methane generation over time and latitude and identify future lander mission sites for more detailed in-situ analysis. In this paper we report on remote sensing measurements of methane using a high peak power, widely tunable optical parametric generator (OPG) operating at 3.3 micron and 1.65 micron. The OPG is pumped by a passively q-switched single frequency laser (3ns, 5KHz, 50uJ) and seeded by a diode laser. The spectral width of both signal and idler of seeded OPG is nearly Fourier transform limited. The output of seeded OPG is single frequency with high spectral purity and is widely tunable. Both 1650 nm and 3300 nm can be generated with a conversion efficiency of more than 30%. We have demonstrated detection of methane at 3274 nm and 1650 nm in a cell and also performed open path atmospheric measurements of methane at the same wavelengths. Finally, we were able to demonstrate simultaneous detection of methane at 3270.4 nm and CO2 at 1578.2 nm. In this paper we will discuss the OPG performance and atmospheric open path measurement results.

Numata, Kenji↗
DOE OSTI2018

COOLR: A New System for Dynamic Thermal-Aware Computing

Extreme-scale systems need to walk a fine line between the amount of cooling they receive and the thermal-induced performance and reliability degradation they can sustain. System managers are extremely motivated to battle cooling-energy cost: the largest line item in their total operating cost. On the other hand, pushing the nodes to peak performance in tightened cooling regimes places the burden on the dynamic thermal management (DTM) to protect the hardware. DTM schemes throttle performance to relieve heat accumulation within nodes when cooling cannot mitigate the problem. These interventions prevent fatal failures but introduce inevitable performance degradations and variations. Such variations can have drastic consequences on the performance of extreme-scale systems. Furthermore, distribution of heat across different system nodes depends not only on the amount of workload. Even if a strictly equal share of computational load is assigned to all nodes, there are physical attributes and topological features of each system that inherently cause uneven accumulation of heat. These can cause one subcomponent to trigger DTM prematurely and penalize the overall system. Our goal in this project is to create a holistic thermal-aware view of the system, capturing both inherent physical attributes and dynamic system state. We developed COOLR, a dynamic system with the ability to evaluate the interplay between management of computation, data, power dissipation, and thermal state. Thereby, COOLR will achieve higher overall performance at the same energy and cooling cost. First, we performed a systematic power and thermal modeling and of high performance computing architectures. Analytical and empirical techniques were blended to generate a light-weight thermal model of target systems. Second, we developed a thermal-aware OS and runtime system. Policies for managing resources and schedules for processes has been designed to co-optimize the thermal state and performance of the system. The main outcome of our proposed thermal-aware dynamic computing system are scheduling and allocation of processes and memory accesses leading to an appropriately “skewed” distribution of activity across the system. The ultimate result of this new arrangement resulted in reduced occurrences of hotspots and reduced episodes of DTM intervention, leading to improvements in performance. The overall thermal characterization and modeling methodology (thermal instrumentation techniques, model building, and systematic model reduction) resulting from this project can be applied to systems beyond our immediate scope and will be applicable to future scaling. The thermal-aware dynamic computing paradigm will impact the efficiency of extreme-scale systems. The gained “thermal slack” can be given back to further tighten the cooling budget, benefiting the management cost of next generation extreme-scale systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Electrocatalytic water oxidation performance in an extended porous organic framework with a covalent alliance of distinct Ru sites

The rational synthesis of durable, earth-abundant efficient electrocatalysts for the oxygen evolution reaction (OER) from water is one of the most important routes for storing renewable energy and minimizing fossil fuel combustion. The prime hurdles for effectively utilizing commercial RuO 2 as (OER) electrocatalysts are its very low stability, catalyst deactivation, and high cost. In this work, we explored a Ru-integrated porous organic polymer (Ru@Bpy-POP) by a facile one-pot Friedel–Crafts alkylation strategy between redox-active (Ru(demob) 3 Cl 2 ) and a carbazole unit, which is composed of unique features including an extended framework unit, isolated active sites, and tunable electrode kinetics. Ru@Bpy-POP can serve as a bridge between a Metal–Organic Framework (MOF) and POP-based catalytic systems with a balanced combination of covalent bonds (structural stability) and open metal sites (single site catalysis). Ru@Bpy-POP, deposited on a three-dimensional nickel foam electrode support, exhibits a promising electrocatalytic OER activity with an ultra-low ruthenium loading compared to a benchmark RuO 2 catalyst, providing an overpotential of about 270 mV to reach 10 mA cm –2 in an alkaline medium. Moreover, a high current density of 248 mA cm –2 was achieved for the Ru@Bpy-POP catalyst at only 1.6 V (vs. RHE), which is much higher than 91 mA cm –2 for commercial RuO 2 . The robust, albeit highly conjugated, POP framework not only triggered facile electro-kinetics but also suppressed aggregation and metallic corrosion during electrolysis. In particular, the benefits of covalent integration of distinct Ru sites into the framework can modulate intermediate adsorption and charge density, which contributes to its exceptional OER activity. All of the critical steps involved in OER are complemented by Density Functional Theory (DFT) calculations, which suggest that electrocatalytic water oxidation proceeds from a closed-shell configuration to open-shell electronic configurations with high-spin states. Finally, these open-shell configurations are more stable than their closed-shell counterparts by 1 eV, improving the overall catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Direct and Sensitive Electrochemical Evaluation of Pramipexole Using Graphitic Carbon Nitride (gCN) Sensor

Pramipexole (PMXL) belongs to the benzothiazole class of aromatic compounds and is used in treating Parkinson’s disease; however, overdosage leads to some abnormal effects that could trigger severe side effects. Therefore, it demands a sensitive analytical tool for trace level detection. In this work, we successfully developed an electrochemical sensor for the trace level detection of PMXL, using the voltammetric method. For the analysis, graphitic carbon nitride (gCN) was opted and synthesized by using a high-temperature thermal condensation method. The synthesized nanoparticles were employed for surface characterization, using transmission electron microscopy (TEM), X-ray diffraction (XRD), and atomic force microscopy (AFM) techniques. The electrochemical characterization of the material was evaluated by using the electrochemical impedance spectroscopy (EIS) technique to evaluate the solution–electrode interface property. The cyclic voltammetry (CV) behavior of PMXL displayed an anodic peak in the forward scan, indicating that PMXL underwent electrooxidation, and an enhanced detection peak with lower detection potential was achieved for gCN-modified carbon paste electrode (gCN·CPE). The influence of different parameters on the electrochemical behavior was analyzed, revealing the diffusion governing the electrode process with an equal number of hydronium ions and electron involvement. For the fabricated gCN·CPE, good linearity range was noticed from 0.05 to 500 µM, and a lower detection limit (L D ) of 0.012 µM was achieved for the selected concentration range (0.5 to 30 µM). Selectivity of the electrode in PMXL detection was investigated by conducting an interference study, while the tablet sample analysis demonstrates the sensitive and real-time application of the electrode. The good recovery values for the analysis illustrate the efficiency of the electrode for PMXL analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting cutoff L-shells of solar protons using the GPPSn particle dataset

Solar energetic protons (SEPs) arriving at the Earth trigger severe radiation storms in the near-Earth space, directly impacting space missions operating at various altitudes. Therefore, monitoring SEP events and predicting the penetration depths of solar protons are critical for aerospace sectors. Building on previous efforts, here we demonstrate the feasibility of using proton measurements from the Global Prompt Proton Sensor network (GPPSn), enabled by Los Alamos National Laboratory developed combined X-ray dosimeters aboard GPS satellites, to characterize and predict the penetration of solar protons into the geomagnetic field. The inclined medium-Earth-orbits (MEOs) of the global GPS constellation offer a unique advantage of allowing simultaneous measurements of penetrating solar protons inside both open- and closed-field line regions. Therefore, the L-profiles of ∼10s–100 MeV solar protons and their associated cutoff L-shells can be determined from the GPPSn dataset, using predefined threshold proton flux values rather than traditional flux ratios. After examining a list of SEP event intervals across solar cycles 23, 24 and 25—including the 2024 Mother’s Day superstorm, we showcase how the latest GPPSn proton dataset (release v1.10), reprocessed and calibrated, can not only be used to monitor solar proton distributions inside the dynamic geomagnetic field for individual events, but also to derive a new empirical model linking cutoff L-shells with several key space weather parameters. This newly developed SEPCL-MEO model demonstrates high predictive performance; for example, predictions for > 30 MeV solar protons yield a correlation coefficient of 0.85 and performance efficiency of 0.67 when validated against GPPSn observations. Results from this pilot study underscores the scientific and operational value of the GPPSn dataset, and this dataset—when paired with machine-learning techniques—can play a critical role in observing and predicting the effects of future incoming SEP events, including extreme ones.

58 GEOSCIENCES↗
DOE OSTI2023

Annual cycle of aerosol properties over the central Arctic during MOSAiC 2019–2020 – light-extinction, CCN, and INP levels from the boundary layer to the tropopause

Abstract. The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition was the largest Arctic field campaign ever conducted. MOSAiC offered the unique opportunity to monitor and characterize aerosols and clouds with high vertical resolution up to 30 km height at latitudes from 80 to 90∘ N over an entire year (October 2019 to September 2020). Without a clear knowledge of the complex aerosol layering, vertical structures, and dominant aerosol types and their impact on cloud formation, a full understanding of the meteorological processes in the Arctic, and thus advanced climate change research, is impossible. Widespread ground-based in situ observations in the Arctic are insufficient to provide these required aerosol and cloud data. In this article, a summary of our MOSAiC observations of tropospheric aerosol profiles with a state-of-the-art multiwavelength polarization Raman lidar aboard the icebreaker Polarstern is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties such as the number concentration of cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) are discussed, separately for the lowest part of the troposphere (atmospheric boundary layer, ABL), within the lower free troposphere (around 2000 m height), and at the cirrus level close to the tropopause. In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. A strong decrease in the aerosol amount with height in winter and moderate vertical variations in summer were observed in terms of the particle extinction coefficient. The 532 nm light-extinction values dropped from >50 Mm−1 close to the surface to <5 Mm−1 at 4–6 km height in the winter months. Lofted, aged wildfire smoke layers caused a re-increase in the aerosol concentration towards the tropopause. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1–5 Mm−1, were observed in the ABL. Aerosol removal, controlled by in-cloud and below-cloud scavenging processes (widely suppressed in winter and very efficient in summer) in the lowermost 1–2 km of the atmosphere, seems to be the main reason for the strong differences between winter and summer aerosol conditions. A complete annual cycle of the AOT in the central Arctic could be measured. This is a valuable addition to the summertime observations with the sun photometers of the Arctic Aerosol Robotic Network (AERONET). In line with the pronounced annual cycle in the aerosol optical properties, typical CCN number concentrations (0.2 % supersaturation level) ranged from 50–500 cm−3 in winter to 10–100 cm−3 in summer in the ABL. In the lower free troposphere (at 2000 m), however, the CCN level was roughly constant throughout the year, with values mostly from 30 to 100 cm−3. A strong contrast between winter and summer was also given in terms of ABL INPs which control ice production in low-level clouds. While soil dust (from surrounding continents) is probably the main INP type during the autumn, winter, and spring months, local sea spray aerosol (with a biogenic aerosol component) seems to dominate the ice nucleation in the ABL during the summer months (June–August). The strong winter vs. summer contrast in the INP number concentration by roughly 2–3 orders of magnitude in the lower troposphere is, however, mainly caused by the strong cloud temperature contrast. A unique event of the MOSAiC expedition was the occurrence of a long-lasting wildfire smoke layer in the upper troposphere and lower stratosphere. Our observations suggest that the smoke particles frequently triggered cirrus formation close to the tropopause from October 2019 to May 2020.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Swift Burst Alert Telescope (BAT) Instrument Response

The Burst Alert Telescope (BAT), a large coded aperture instrument with a wide field-of-view (FOV), provides the gamma-ray burst triggers and locations for the Swift Gamma-Ray Burst Explorer. In addition to providing this imaging information, BAT will perform a 15 keV - 150 keV all-sky hard x-ray survey based on the serendipitous pointings resulting from the study of gamma-ray bursts and will also monitor the sky for transient hard x-ray sources. For BAT to provide spectral and photometric information for the gamma-ray bursts, the transient sources and the all-sky survey, the BAT instrument response must be determined to an increasingly greater accuracy. In this talk, we describe the BAT instrument response as determined to an accuracy suitable for gamma-ray burst studies. We will also discuss the public data analysis tools developed to calculate the BAT response to sources at different energies and locations in the FOV. The level of accuracy required for the BAT instrument response used for the hard x-ray survey is significantly higher because this response must be used in the iterative clean algorithm for finding fainter sources. Because the bright sources add a lot of coding noise to the BAT sky image, fainter sources can be seen only after the counts due to the bright sources are removed. The better we know the BAT response, the lower the noise in the cleaned spectrum and thus the more sensitive the survey. Since the BAT detector plane consists of 32768 individual, 4 mm square CZT gamma-ray detectors, the most accurate BAT response would include 32768 individual detector response functions to separate mask modulation effects from differences in detector efficiencies! We describe OUT continuing work to improve the accuracy of the BAT instrument response and will present the current results of Monte Carlo simulations as well as BAT ground calibration data.

Parsons, A.↗