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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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At least 271 records · Page 15

Parametric optimization of the liquid sampling-atmospheric pressure glow discharge ionization source coupled to an Orbitrap mass spectrometer for neodymium isotope ratio determinations

Isotope ratio determinations are a valuable tool in several application areas. In nuclear forensics, the isotope ratios of uranium and plutonium are commonly used as a signature for the nuclear material's provenance and processing history. However, signatures from other coexisting elements, such as neodymium and samarium, can offer additional insights. Here, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) ionization source coupled to an Orbitrap mass spectrometer (MS) has demonstrated its utility for actinide measurements. This instrumental platform can leverage the high resolution offered by the Orbitrap MS to overcome potential isobaric interferences, such as 144 Nd- 144 Sm, 148 Nd- 148 Sm, and 150 Nd- 150 Sm pairs. The work presented herein demonstrates the rapid, accurate, and precise determination of the isotope ratios for neodymium using the LS-APGD/Orbitrap MS. Both the LS-APGD and Orbitrap MS parameters were optimized systematically, with NdO + found to be the most abundant, most reduced species after applying the optimal collision-induced dissociation modalities. A limit of detection of 3 pg of 142 Nd was achieved when data was acquired and processed using the FTMS Booster, an external data acquisition and processing system offered by Spectroswiss. Excellent accuracy of better than 99 % and precision of <1 % RSD were achieved when a solution of the well-characterized neodymium standard (JNdi-1 standard) was analyzed under the optimized condition, indicating the LS-APGD/Orbitrap's great potential for isotope ratio analysis of Nd and other REEs for diverse applications.

47 OTHER INSTRUMENTATION↗

Source term estimation using noble gas and aerosol samples

Algorithms that estimate the location, time, and magnitude of a point-source atmospheric release using remotely sampled air concentrations typically use data for a single chemical or radioactive isotope. Here, a Bayesian algorithm is presented that uses data from multiple radioactive isotopes that are all released in the same short-duration event. Data from noble gas and aerosol samplers can be used simultaneously in the model. Application to a large synthetic data set using four isotopes shows the new algorithm generally gives more accurate location and time estimates than a comparable model using a single isotope.

54 ENVIRONMENTAL SCIENCES↗

Magnetic properties of (Mo 2/3 Dy 1/3 ) 2 AlC arc melted polycrystalline samples

Here, this study investigates the structural and magnetic properties of arc-melted (Mo 2/3 Dy 1/3 ) 2 AlC polycrystalline samples, a member of the i-MAX phase family. Temperature-dependent magnetization and specific heat measurements confirm the low-temperature antiferromagnetic transitions around 14 K and 17 K. Neutron diffraction data collected at 4 K reveal the emergence of magnetic Bragg peaks that are not allowed in the paramagnetic space group C2/c, further confirming the presence of antiferromagnetic ordering. The detection of a secondary phase, DyAl 2 , is complicated by overlapping Bragg peaks with the monoclinic phase of (Mo 2/3 Dy 1/3 ) 2 AlC in powder XRD patterns. However, magnetization and neutron diffraction data suggest the presence of DyAl 2 , evidenced by a ferromagnetic phase transition around 62 K.

36 MATERIALS SCIENCE↗

Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders

Calorimeters with dual readout measure both scintillation and Cherenkov light produced in their active media. They offer improvements in energy resolution and, therefore, have become increasingly interesting due to the need for precision jet measurements at Higgs factories. Furthermore, this paper presents GEANT4 simulations of single-particle responses in sampling and homogeneous calorimeters, and demonstrates the effect of inclusion of Cherenkov light in the reconstruction of energies.

Detector modeling and simulations↗

Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.

36 MATERIALS SCIENCE↗

Rapid analysis of 237 Np and Pu isotopes in unseparated sample matrices using ICP-MS/MS

Inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) is an emerging technique for measuring actinide isotopes when assessing pre- and post- detonation nuclear material. In this study, ICP-MS/MS was investigated for direct Np and Pu quantitation in unseparated, dissolved bulk soil matrices. To achieve this, purified nitric oxide (NO) was investigated for the reactivity of Th, Np, U, Pu, Am, and Cm. Purifying NO prior to the collision reaction cell (CRC) results in increased sensitivity and allows for higher gas flows to be utilized for the removal of interferences. Here, the interference from uranium hydrides was mitigated to less than 3.85 x 10 -11 . This method was demonstrated on standard reference materials which were measured for 237 Np and 238,239,240 Pu in dilute sample digestions. The 238 Pu measurement was validated by spiking into a standard reference material and was accurately measured with an excess of 85000 of 238 U.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Case Study in Assessing a Potential Severity Framework for Incidents from a Decadal Sample

In this study, the primary objective of this case study is to determine the applicability and feasibility of a framework that leverages occupational incident details to prospectively identify “potential Serious Injury or Fatality” (pSIF) cases. This study comprehensively reviewed a random sample of 1,081 injury and illness cases across 21 generalized incident types spanning over a decade at Lawrence Livermore National Laboratory (LLNL), a U.S. Department of Energy research and development facility with more than 9,000 employees. The review applied a general framework that classified each case on information suitability, potential severity, and future incident mitigation. The findings from the study indicate that 86.6% of the cases had sufficient information to make a high-confidence determination on potential severity, underscoring the feasibility of applying this general framework. Additionally, cases with a higher pSIF score had, on average, a higher level of institutional response. Implementing a simplified methodology for incident classification that emphasizes incidents that pose high potential severity, regardless of incident type, can help LLNL prioritize resources and tailor responses to such incidents using a graded approach. LLNL has recognized the value of this capability and is integrating the framework into their injury and illness process in the 2024 calendar year.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

FLAMES─Fast, Low-Storage, Accurate, and Memory-Efficient Adaptive Sampling─Approach to Resolve Spatially Dependent Dynamics of Molecular Liquids

Many critical phenomena in soft matter occur at large length scales, necessitating the resolution of their structure and dynamics at low wavenumbers. However, resolving wavenumber-dependent dynamics computationally via molecular dynamics simulations presents significant challenges, as these phenomena span several orders of magnitude in both time and length scales, resulting in high computational costs and memory demands. Here, this work highlights the computational and memory challenges associated with analyzing molecular trajectories in reciprocal space and demonstrates a method to address them. We introduce FLAMESFast, Low-storage, Accurate, and Memory-Efficient adaptive Sampling, which is a direct method for calculation of structure factors, allowing us to select only the required number of wavevectors for binning. We also use wavenumber-dependent time steps to extract dynamics. Our FLAMES approach effectively mitigates computational and memory/storage bottlenecks. We demonstrate the method using simulations of a model system, liquid octane, at various temperatures. Comparisons with experimental data and real space computation show that the FLAMES technique achieves high accuracy in resolving temperature- and spatially dependent dynamics while being significantly more computationally efficient and requiring less memory and storage than methods based on a uniform wavevector grid and fixed temporal spacing.

Chen, Guang [Argonne National Laboratory (ANL), Ar↗

Electrochemical Nutrient Recovery for the Food–Energy–Water Nexus at Municipal Wastewater Facilities: Multivariate Analyses of Seasonal Sampling and Reactor Performance

Digester-equipped municipal wastewater facilities generate recycle streams with high nutrient loads that increase energy consumption and can cause environmental pollution. The reduction of these loads through electrochemical nutrient recovery (ENR) could enhance the food–energy–water nexus by producing fertilizer (struvite). This study investigated the recovery process through a 1 year sampling of recycle streams and the implementation of nutrient recovery. Time series analyses showed that P (as orthophosphate) concentration was time-variant in digester effluent streams, while N (as ammonia) concentration was time-variant in only the aerobic system. Furthermore, these two nutrient concentrations did not correlate in any of the recycle streams. Subsequent multivariate screening analyses identified anode type, NH 4 + concentration, cathodic potential, P concentration, and temperature as most significant for ENR. Finally, the optimum conditions of cathodic potential, anode area-to-volume ratio, and temperature applied to a real recycle stream resulted in 95% P recovery with 0.03 kWh/kg P. This energy consumption is significantly lower than process energy for conventional P fertilizers (1.1 kWh/kg P) and chemical recovery processes at scale (1.7–12.9 kWh/kg P). Overall, this study recommended specific process controls for nutrient recovery, expanded the variables evaluated for ENR, and demonstrated the ability to significantly impact energy demand associated with P-based fertilizers.

36 MATERIALS SCIENCE↗

Rapid Generation of Tandem Mass Spectrometry Reference Libraries Using Immediate Drop-on-Demand Liquid Handling Coupled to an Open Port Sampling Interface

In metabolomics, tandem MS (MS2) fragmentation libraries are important for the identification of unknown features, but generating these libraries takes many valuable hours of instrument and operator time. Here, an immediate droplet-on-demand/open port sampling interface was used to rapidly acquire tandem MS of standards arrayed in a 96-well plate format. A workflow was developed for automated, high-throughput control of MS2 library generation. Pure standard mass spectral libraries were collected on Orbitrap and Q-TOF mass spectrometers for 192 compounds using 6 different collision energies with a throughput of 4 and 7.8 s/spectrum, respectively. Libraries were acquired using different solvent additives, precursor adducts, and ion polarities.

Cahill, John [ORNL] (ORCID:0000000298664010)↗

Integration of multiple coinflip devices for high-quality random sampling

Artificial intelligence, scientific computing, and probabilistic computing use random sampling to approximate solutions to various problems, with larger models requiring a substantial quantity of random numbers. To generate the required vast quantity of random numbers at high rates, we explore so-called “coinflip” devices, which are stochastic microelectronic devices ideally capable of independently generating random bits with a tunable weight at a high rate. However, coinflip devices are inherently analog and demonstrate nonidealities, like temperature dependence and drift, that can introduce determinism into the outputs. We present important considerations for building systems of multiple coinflip devices to produce high-quality bitstreams with low error and little dependency on previous bits. Using tunnel diodes as coinflip devices, we implement a control loop to adapt to temperature dependence and generate fair bitstreams with each device. While this can lead to dependencies between bits in a single bitstream, we demonstrate that combining results generated in parallel with individual tunnel diodes can produce fair and unpredictable bitstreams. The suitability of these bitstreams for use in probabilistic computing is then demonstrated through a Monte Carlo approximation of π.

Taylor, Brady Garland [Sandia National Laboratorie↗

Surface phase diagrams from nested sampling

From nested sampling, we compute the partition function and, from that, the phase diagram of gas adsorbates, including their anharmonic and configurational degrees of freedom, on flat and stepped surfaces of the Lennard-Jones solid.

Chemistry↗

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗

Interior soft x-ray tomography with sparse global sampling

To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.

3D imaging↗

Selecting samples of galaxies with fewer Fingers-of-God

The radial positions of galaxies inferred from their measured redshift appear distorted due to their peculiar velocities. We argue that the contribution from stochastic velocities — which gives rise to `Fingers-of-God' (FoG) anisotropy in the inferred maps — does not lend itself to perturbative modelling already on scales targeted by current experiments. To get around this limitation, we propose to remove FoG using data-driven indicators of their abundance that are local in nature and thus avoid selection biases. In particular, we show that the scale where the measured power spectrum quadrupole changes sign is tightly anti-correlated with both the satellite fraction and the velocity dispersion, and can thus be used to select galaxy samples with fewer FoG. In addition, we show that excluding galaxies in haloes more massive than a given mass threshold can help to discard many of the most problematic galaxies. Such selection could be achieved in practice using maps of the thermal Sunyaev-Zel'dovich distortion of the cosmic microwave background frequency spectrum. These techniques could potentially improve reconstructions of the large-scale velocity and displacement fields from the redshift-space positions of galaxies. They may also extend the reach of perturbative models for galaxy clustering, though in practice we find only marginal gains when fitting one-loop EFTofLSS models to simulations with mitigated FoG due to the relevance of other effects entering at two-loop order.

cosmological parameters from LSS↗

Multi-physics modeling of tungsten collector probe samples during the WEST C4 He campaign

Abstract We describe the results of a multi-scale, multi-physics modeling assessment of SOLPS-ITER, hPIC2, RustBCA and Xolotl, in which five single-crystal tungsten (W) samples were placed in a reciprocating collector probe and exposed to helium (He) plasma in the WEST fusion device. In our models, we considered a pure (100 %) He plasma, as well as one with oxygen (O) present (95% He 5% O) corresponding to the impurity concentration estimated during the C4 He campaign in WEST. Our SOLPS simulations approximately match experimental reciprocating Langmuir probe plasma measurements of plasma density and temperature. Using these plasma parameters as input, hPIC2 and RustBCA predict that the presence of oxygen impurities lead to a 15%–20% decrease in ion and heat fluxes to the surface, and an order of magnitude higher sputtering yields (compared with a pure He plasma). Xolotl predictions for the response of tungsten to plasma surface interactions (PSIs) agree with experimental LAMS analysis, and indicate large near-surface He concentrations, which quickly decay with depth. Our model also shows an increasing role of erosion—in removing the near-surface He—with time. Overall, slightly higher retention is predicted for tungsten exposed to a pure He plasma, with the largest differences in the near-surface gas content caused by the large oxygen-induced erosion. This highlights the important role that impurities play in PSI. Therefore, future work will focus on providing a fully self-consistent description of oxygen (and oxides, etc.) in our models, through multi-species implementation in GITR and inclusion of oxygen and tungsten oxide formation in Xolotl.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗