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At least 397 records · Page 22

Discovery, Design, Synthesis and Testing of High Performance Structural Alloys (Final Technical Report)

The overarching goal of this project is to understand the phase stability and mechanical behavior of non-stoichiometric multi-principal element alloy (MPEA) materials. In order to identify suitable alloys, we plan to use a combinatorial thin film screening approach, in collaboration with scientists at Lawrence Berkeley National Laboratory who are performing computational work as well as complementary experimental work. Specific tasks within the scope of this project include the fabrication, using thin film deposition from six sputtering targets, of combinatorial samples with multi-dimensional gradients in composition and microstructure. These samples are studied to screen MPEA systems for promising candidate alloys with specific composition(s), based on characterization of composition, structure and mechanical behavior across the thin film. We want to produce single-phase MPEAs with chemical homogeneity in a given thin film region, simple grain structures, and no intermetallic phases present. Gradient films facilitate first-pass screening for desirable characteristics and inform the next stage of work that involves fabrication of bulk MPEA specimens for (tensile) mechanical testing and characterization. To make the bulk alloys, metal (elemental) pieces are melted to form MPEAs, followed by heat treatment to homogenize the composition and microstructure. A subset of alloys is also cast, using vacuum arc melting, to yield larger samples (diameter ~1 cm and length ~5-10 cm) and these allow us to assess viability of scale-up for the alloys in structural applications. Further processing plans include rolling and heat treatment to recrystallize selected bulk MPEAs and grow grains to different extents, in order to investigate size effects in the mechanical behavior of MPEAs. Microspecimen testing will be performed (primarily in tension) to assess the mechanical behavior over a range of temperatures. The deformation microstructure of mechanically tested alloys will be characterized using transmission electron microscopy (TEM) to provide a scientific basis for understanding the structure-property relationships in MPEA mechanical behavior.

36 MATERIALS SCIENCE↗

Measurement of the top-quark pole mass in dileptonic $t\overline{t}$ + 1-jet events at $\sqrt{s}=13$ TeV with the ATLAS experiment

A measurement of the top-quark pole mass $m$$^{pole}_{t}$ is presented in $t\bar{t}$ events with an additional jet, $t\bar{t}$+ 1-jet, produced in pp collisions at $\sqrt{s} = 13 TeV. The data sample, recorded with the ATLAS experiment during Run 2 of the LHC, corresponds to an integrated luminosity of 140 fb −1 . Events with one electron and one muon of opposite electric charge in the final state are selected to measure the $t\bar{t}$ + 1-jet differential cross-section as a function of the inverse of the invariant mass of the $t\bar{t}$ + 1-jet system. Iterative Bayesian Unfolding is used to correct the data to enable comparison with fixed-order calculations at next-to-leading-order accuracy in the strong coupling. The process pp → $t\bar{t}$j(2 → 3), where top quarks are taken as stable particles, and the process pp → $b\bar{b}$l + vl – $\overline{ν}$j (2 → 7), which includes top-quark decays to the dilepton final state and off-shell effects, are considered. The top-quark mass is extracted using a χ 2 fit of the unfolded normalized differential cross-section distribution. The results obtained with the 2 → 3 and 2 → 7 calculations are compatible within theoretical uncertainties, providing an important consistency check.

Hadron-Hadron Scattering↗

Design and Validation of a High-Throughput Reductive Catalytic Fractionation Method

Reductive catalytic fractionation (RCF) is a promising method to extract and depolymerize lignin from biomass, and bench-scale studies have enabled considerable progress in the past decade. RCF experiments are typically conducted in pressurized batch reactors with volumes ranging between 50 and 1000 mL, limiting the throughput of these experiments to one to six reactions per day for an individual researcher. Here, we report a high-throughput RCF (HTP-RCF) method in which batch RCF reactions are conducted in 1 mL wells machined directly into Hastelloy reactor plates. The plate reactors can seal high pressures produced by organic solvents by vertically stacking multiple reactor plates, leading to a compact and modular system capable of performing 240 reactions per experiment. Using this setup, we screened solvent mixtures and catalyst loadings for hydrogen-free RCF using 50 mg poplar and 0.5 mL reaction solvent. The system of 1:1 isopropanol/methanol showed optimal monomer yields and selectivity to 4-propyl substituted monomers, and validation reactions using 75 mL batch reactors produced identical monomer yields. To accommodate the low material loadings, we then developed a workup procedure for parallel filtration, washing, and drying of samples and a 1H nuclear magnetic resonance spectroscopy method to measure the RCF oil yield without performing liquid-liquid extraction. As a demonstration of this experimental pipeline, 50 unique switchgrass samples were screened in RCF reactions in the HTP-RCF system, revealing a wide range of monomer yields (21-36%), S/G ratios (0.41-0.93), and oil yields (40-75%). These results were successfully validated by repeating RCF reactions in 75 mL batch reactors for a subset of samples. We anticipate that this approach can be used to rapidly screen substrates, catalysts, and reaction conditions in high-pressure batch reactions with higher throughput than standard batch reactors.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Electromagnetic Shower Reconstruction and Identification in FASER's Emulsion Detector for LHC Forward Neutrino Measurements

We present methods for electromagnetic shower reconstruction and identification in the FASERnu emulsion detector using 100 GeV and 200 GeV electron test-beam data from the CERN SPS H4 beamline. The reconstruction employs a clustering-based algorithm without energy-dependent tuning to determine shower axes. A multi-level identification chain comprising track pre-selection, a cut-based selection, and a BDT classifier achieves combined background rejection rates of 99.99% (100 GeV) and 99.94% (200 GeV). The method reaches total reconstruction and identification efficiencies of 58.9% (100 GeV) and 70.8% (200 GeV) evaluated from simulated samples. Energy reconstruction using the total number of reconstructed segments as the calorimetric estimator yields relative biases of +0.6% (100 GeV) and -0.8% (200 GeV), with resolutions of 25.4% and 22.6%, respectively. Systematic uncertainties on the energy reconstruction are dominated by variations in emulsion film detection efficiency, contributing (+10.9%/-8.2%) at 100 GeV and (+10.3%/-6.9%) at 200 GeV. The methodology provides a validated framework for electron neutrino identification with the FASERnu detector at the LHC.

Mammen Abraham, Roshan [UC, Irvine]↗

Functionalized Porous Polymer Networks as High-Performance PFAS Adsorbents

Toxic per- and polyfluoroalkyl substances (PFAS) are now found in nearly every water source on the planet. Exposure to these molecules can have negative health consequences, but the low concentration of PFAS relative to other solutes in water makes their removal challenging. Adsorbents offer a promising treatment route, but often exhibit low selectivities and removal capacities, as well as slow kinetics. The performance in these metrics can be improved by chemically optimizing PFAS binding sites and maximizing PFAS-adsorbent interactions. To explore how to achieve this, a porous polymer network solid (PPN-6, also known as PAF-1) was postsynthetically modified with various chemical moieties capable of leveraging unique combinations of electrostatic, hydrogen-bonding, hydrophobic, and fluorophilic interactions with PFAS molecules. Batch adsorption experiments and computational studies revealed that electrostatic and hydrogen-bonding interactions drive short-chain PFAS adsorption, while hydrophobic and fluorophilic interactions improve long-chain PFAS adsorption. In complex water matrices, a combination of electrostatic and fluorophilic interactions led to the greatest total PFAS removal. The best-performing material, functionalized with a fluorinated alkylammonium (PPN-6-FNDMB), selectively adsorbs PFAS with high capacity (up to 4.0 mmol/g) and rapid kinetics (equilibrium reached in <30 s). Furthermore, PPN-6-FNDMB outperforms several commercial adsorbents, achieving near-complete removal of 21 different PFAS from a groundwater sample collected at a US Air Force base. The PFAS could subsequently be desorbed from PPN-6-FNDMB, concentrating them by a factor of over 50 times. The recycled PPN-6-FNDMB could then be reused with minimal losses in long-chain PFAS adsorption capacity over four cycles.

Pezoulas, Ethan R↗

Quasiclassical sampling and Wigner sampling of initial vibrational coordinates and momenta for polyatomic molecules in Monte Carlo molecular dynamics simulations

In a quasiclassical trajectory simulation, the vibrational modes are initialised with quantised vibrational energies, but vibrational phases are sampled by Monte Carlo. This requires an algorithm to assign coordinates and momenta to the various atoms. In this work, we present two methods for implementing this for nonrotating polyatomic molecules, namely, fixed-energy vibrational-state-selected initial conditions and thermal initial conditions. We also present a method for initiating classical trajectories with a ground-state Wigner distribution. These vibrational treatments are sufficient to initialise trajectories for unimolecular processes, and we also show how they can be applied to simulate bimolecular collision processes. The treatments of unimolecular and bimolecular collision processes are available in two Python codes called wigner_state_selected.py and bimolecular_collision.py, respectively, which will generate initial condition files that are recognisable by the SHARC and SHARC-MN computer programs for dynamics calculations. Both codes are available as standalone programs, as well as being included in SHARC-MN, and they will be included in future versions of SHARC. Here, the methods implemented in these codes are mostly also available in the ANT computer program, and those that are not available in ANT will be incorporated in future versions of ANT.

Wigner distribution↗

Search for the lepton-flavor violating decay B s 0 → ϕ μ ± τ ∓

A search for the lepton-flavor violating decays B s 0 → ϕ μ ± τ ∓ is presented, using a sample of proton-proton collisions at center-of-mass energies of 7, 8, and 13 TeV, collected with the LHCb detector and corresponding to a total integrated luminosity of 9 fb − 1 . The τ leptons are selected using decays with three charged pions. No significant excess is observed, and an upper limit on the branching fraction is determined to be B ( B s 0 → ϕ μ ± τ ∓ ) < 1.0 × 10 − 5 at 90% confidence level. © 2024 CERN, for the LHCb Collaboration 2024 CERN

Aaij, R. (ORCID:0000000305331952)↗

Network of Modified Portable Optical Particle Spectrometers Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s portable optical particle spectrometer (POPS) network (Figure 1) provides an aerosol size distribution spectrum from 150 nm to 5 μm in 16 logarithmically spaced bins. The data emanating from this network of up to four matching POPS in weatherproof enclosures comprises one-minute averages of the aerosol size and number spectrum and the co-located temperature and relative humidity. The total particle concentration and sample flow rate are also provided. The sample stream is not dried before its measurement. Two size spectra are provided: the default size distribution corresponds to the calibration using polystyrene latex spheres (PSL), while the second size distribution corresponds to the calibration using size-selected dry ammonium sulfate aerosol. The principal scientific application of the data provided by the ARM POPS is to determine the aerosol size distribution across a region in three disparate locations – the size distribution is broadly relevant to studies of pollution and of conditions in the boundary layer. A high particle concentration can be an indicator of unhealthy levels of pollution; the dispersion of particles in the atmosphere is a predictor of long-range visibility; and particles serve as collectors of condensing gases including water vapor, and thus are a factor in the formation and properties of fogs and clouds, and in the initiation of precipitation.

54 ENVIRONMENTAL SCIENCES↗

Mitigation of Cu-Induced Grain Boundary Sensitization in Steel Wire Rods Through a Desensitization Heat Treatment

Steel wire rods are essential for manufacturing high-strength steel tire cords. Yet, the presence of residual copper (Cu) in recycled steel can cause grain-boundary sensitization, embrittlement, and deterioration of the mechanical performance of the final product. This study introduces a desensitization heat treatment step designed to redistribute Cu away from austenite grain boundaries after sensitization occurs. The treatment consists of a 10 min dwell at 1000 °C in a 5%H 2 -Ar reducing atmosphere followed by quench. The temperature and hold time were selected based on diffusion calculations to promote solid-state back diffusion of Cu without altering grain morphology. Experimental validation showed that the dwell step reduced the length of Cu-rich sensitized zones of steel wire rod samples containing 0.21 wt.% Cu by approximately 89% and restored the mechanical properties to nearly 95–98% relative to low-Cu baseline steel (0.01 wt.% Cu). Compared with sensitized and as-obtained samples, these results highlight the effectiveness of the proposed method in improving both the microstructure and tensile performance of recycled steel wire rods, enabling their potential application in tire manufacturing.

copper↗

SAGAbg. II. The Low-mass Star-forming Sequence Evolves Significantly between 0.05 < z < 0.21

The redshift-dependent relation between galaxy stellar mass and star formation rate (SFR), known as the star-forming sequence (SFS), is a key observational yardstick for galaxy assembly. We use the SAGAbg-A sample of background galaxies from the Satellites Around Galactic Analogs (SAGA) Survey to model the low-redshift evolution of the low-mass SFS. The sample is comprised of 23,258 galaxies with Hα-based SFRs spanning 6 < log 10 (M * /[M ⊙ ]) < 10 and z < 0.21 (t < 2.5 Gyr). Although it is common to bin or stack galaxies at z ≲ 0.2 for galaxy population studies, the difference in lookback time between z = 0 and z = 0.21 is comparable to the time between z = 1 and z = 2. We develop a model to account for both the physical evolution of low-mass SFS and the selection function of the SAGA Survey, allowing us to disentangle redshift evolution from redshift-dependent selection effects across the SAGAbg-A redshift range. Our findings indicate significant evolution in the SFS over the last ∼2.5 Gyr, with a rising normalization: $\langle$SRF(M * = 10 8.5 M ⊙ )$\rangle$ (z) = 1.24$^{+0.25}_{–0.23}$z – 1.47$^{+0.03}_{–0.03}$. We also identify the redshift limit at which a static SFS is ruled out at the 95% confidence level, which is z = 0.05 based on the precision of the SAGAbg-A sample. Comparison with cosmological hydrodynamic simulations reveals that some contemporary simulations underpredict the recent evolution of the low-mass SFS. This demonstrates that the recent evolution of the low-mass SFS can provide new constraints on the assembly of the low-mass Universe and highlights the need for improved models in this regime.

79 ASTRONOMY AND ASTROPHYSICS↗

Selection of a Pair of Experiments to Optimally Reduce Uncertainty in Targeted Nuclear Data

We propose a novel process to select a pair of differential and integral experiments that best reduce uncertainties in targeted 239 ⁢Pu nuclear data while compressing the current nuclear data pipeline from 20 to 3 years. 239⁢ Pu nuclear data are poorly understood for neutrons in the intermediate energy range due to sparsity and uncertainty in historical experiments. New experiments targeting this range will enable better understanding of these nuclear data, but choosing the ideal experiments to conduct is challenging. Beginning with a prior distribution represented by samples of nuclear data generated from theory, generalized least squares adjustments are made to incorporate data from historical experiments. To quantify potential uncertainty reduction obtainable from a pair of candidate experiments, we compute the D-optimality criterion of the posterior covariance of intermediate energy range nuclear data compared to the equivalent covariance after additional adjustment to the pair of candidate experiments. Repeating the process for each of many candidate pairs facilitates the final selection. Results support 63⁢ Cu total cross section measurements for differential experiments and alumina and alumina/graphite configurations for integral experiments. This analysis enables choosing differential and integral experiments to be executed concurrently while shortening decision times relative to the current nuclear data pipeline.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Restructuring of Benzimidazole-Based Copper Complexes during Electrochemical CO 2 Reduction

Copper-based molecular catalysts have been widely used for the electrochemical reduction of carbon dioxide (ERCO 2 ). However, establishing a correlation between structure and catalytic performance has been challenging due to the dynamic nature of these materials under ERCO 2 working conditions. Here, we report on the restructuring of the copper complexes [Cu(bzimpy)Cl 2 ] and [Cu(pyrben) 2 (NO 3 )]NO 3 during ERCO 2 in an acidic medium, evidencing its effects on the observed activity, selectivity, and stability. In situ X-ray absorption spectroscopy (XAS) suggested that, at sufficiently negative potentials, the Cu 2+ centers of both complexes are reduced to undercoordinated Cu 0 species. Pb underpotential deposition of post-ERCO 2 samples indicated that such Cu 0 species also present a dominant contribution of the (100) domain, which is in line with the high Faradaic efficiency toward C 2 products (∼45%) shown by both complexes at −1.24 V vs RHE. By combining online electrochemical mass spectrometry, in situ XAS, electron paramagnetic resonance (EPR), and quantitative product analysis, we found that [Cu(bzimpy)Cl 2 ] exhibits a partially reversible restructuring, regenerating the main complex moiety, [Cu(bzimpy)] 2+ , and its geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of branching fractions, C P asymmetry, and isospin asymmetry for B → ρ γ decays using Belle and Belle II data

We present measurements of B + → ρ + γ and B 0 → ρ 0 γ decays using a combined data sample of 772 × 10 6 B B ¯ pairs collected by the Belle experiment and 387 × 10 6 B B ¯ pairs collected by the Belle II experiment in e + e − collisions at the ϒ ( 4 S ) resonance. After an optimized selection, a simultaneous fit to the Belle and Belle II datasets yields 114 ± 12 B + → ρ + γ and 99 ± 12 B 0 → ρ 0 γ decays. The measured branching fractions are ( 13.1 − 1.9 − 1.2 + 2.0 + 1.3 ) × 10 − 7 and ( 7.6 ± 1.3 − 0.8 + 1.0 ) × 10 − 7 for B + → ρ + γ and B 0 → ρ 0 γ decays, respectively, where the first uncertainty is statistical and the second is systematic. We also measure the isospin asymmetry A I ( B → ρ γ ) = ( 10.9 − 11.7 − 7.3 + 11.2 + 7.8 ) % and the direct C P asymmetry A C P ( B + → ρ + γ ) = ( − 8.2 ± 15.2 − 1.3 + 2.0 ) % . Published by the American Physical Society 2025

Adachi, I. (ORCID:0000000322870173)↗

Wide bandgap photoconductor (SiC:V)-based optically addressed light valve for high fluence operation

Optically addressable light valves based on wide bandgap 4H- and 6H-SiC as photoconductors were designed to withstand higher operational laser fluences than the state of-the-art bismuth silicon oxide (BSO; Bi 12 SiO 20 ) based devices. Vanadium-doped SiC was selected as the photoconductors due to their reasonable photoresponsivity while many fold improvement in laser induced damage threshold as compared to BSO. The laser induced damage threshold values of the materials were measured after exposing ~ 200 sites on the samples to increasing levels of fluence of a gaussian pulsed Nd: YAG laser system (1064 nm) with a 5 Hz repetition rate. The measured damage threshold values for BSO, 4H- and 6H-SiC were 0.4 J/cm 2 , 1.75 J/cm 2 and 1.8 J/cm 2 , respectively. Photoconductive switches based on 4H and 6H-SiC samples were characterized at wavelengths of 380 nm, 405 nm, and 447 nm. The peak photoresponsivity values of the 4H- and 6H-SiC materials were measured to be under 380 nm and 405 nm, respectively. The photoconductor was bonded to a BK7 optical window with 5 μm diameter microspheres as spacers. A twisted nematic type E7 liquid crystal (LC) was filled in the 5 μm gap in a vacuum chamber. The desired alignment of the liquid crystal was achieved by mutually orthogonal orientation of LC alignment layers on the two mating faces (SiC and BK7). The fabricated devices were modulated using address beams of wavelengths 380 nm, 405 nm, and 447 nm. In conclusion, required transmission levels of > 90% was achieved for the fabricated OALVs for a sinusoidal voltage waveform that meets the lifetime requirement of the device.

36 MATERIALS SCIENCE↗

Optical design for the single crystal neutron diffractometer Pioneer

Pioneer is a single-crystal neutron diffractometer optimized for small-volume samples and weak signals at the Second Target Station at Oak Ridge National Laboratory. This paper presents the preliminary optical design progress, focusing on the rationale behind key design choices. It covers the T 0 and bandwidth disk choppers, guide and beam control system, incident-beam polarizer, scattering beam collimators, and additional strategies. The chopper locations are selected to maximize neutron transport while taking advantage of standardized shielding structures. To accommodate the maintenance shield, operational shutter, and polarizing V-cavity, the guide design includes significant gaps. When these optical components are moved out of the beam path, oversized collimators, rather than guides, will be translated in. Pioneer will utilize slit packages to control beam size and divergence and a translatable polarizing V-cavity. Absorbing panels are strategically placed near the end station to minimize background. An oscillating radial collimator, operating in a shift mode, will be used with the vertical cylindrical detector, while a fixed multi-cone collimator will be used with the bottom flat detector. In conclusion, these collimators will enable the detection of weak signals when complex sample environments are used.

47 OTHER INSTRUMENTATION↗

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Heterogeneous Catalyst Discovery

Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We demonstrate that hierarchical agentic large language model reasoning can efficiently drive simulation and scientific exploration. Across two chemical applications, CO adsorption on Cu surface transition metal adatoms and on M–N–C catalysts, reasoning-guided exploration reduces required atomistic simulations by up to 90% relative to heuristic or random selection. Comparisons across single-agent, multi-agent, and stochastic baselines show that hierarchical strategies yield more coherent and information-efficient search trajectories. Reasoning traces reveal chemically grounded decisions that cannot be explained by semantic bias or stochastic sampling. We realize these agentic reasoning strategies in Materials Agents for Simulation and Theory in Electronic-structure Reasoning (MASTER), a multimodal system that translates natural language into density functional theory workflows. Altogether, multi-agent collaboration accelerates heterogeneous catalyst discovery and marks a step toward more autonomous, reasoning-guided scientific exploration.

30 DIRECT ENERGY CONVERSION↗

Are light curve classification metrics good proxies for SN Ia cosmological constraining power?

Context. When selecting a light curve classifier for use as part of a photometric supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, such as the contamination within the photometrically classified SN Ia sample, rather than a measure of cosmological constraining power. If the former is an appropriate proxy for the latter, this practice would eliminate the computational expense of a full cosmology forecast in the analysis pipeline design process. Aims. This study tests the assumption that light curve classification metrics are an appropriate proxy for cosmology metrics. Methods. We emulated photometric SN Ia cosmology light curve samples with controlled contamination rates of individual contaminant classes and evaluated each of them under a set of classification metrics. We then derived cosmological parameter constraints from all samples under two common analysis approaches and quantified the impact of contamination by each contaminant class on the resulting cosmological parameter estimates. Results. We observe that cosmology metrics are sensitive to both the contamination rate and the class of the contaminating population, whereas the classification metrics are shown to be insensitive to the latter. Conclusions. Based on these findings, we discourage any exclusive reliance on light curve classification-based metrics for analysis design decisions, which (counterintuitively) include but are not limited to the classifier choice. Instead, we recommend optimising science analysis pipeline design choices using a metric of the information gained about the physical parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗