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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 OSTI2023

An Ultra-Fast Inrush-Current-Free Startup Method for Grid-tie Inverter without Voltage Sensors

This paper proposes an ultra-fast inrush-currentfree startup method for grid-tie inverters without voltage sensors and phase-locked loop (PLL). Traditionally, the grid-tie inverter needs the voltage measured from points of common couplings (PCC) to generate the phase angle via PLL for inverter pulsewidth- modulation (PWM) signals. The startup procedure is slow and inrush current occurs if the initial PWM does not match the unknown grid voltage well. This paper proposes a startup method that only uses measured inverter ac currents to generate the initial PWM by controlling the current to zero. The generated PWM pattern can be used to reproduce the real grid voltage regardless of the grid impedance. The zero-crossing points of the grid voltage are detected and then used for grid synchronization. The proposed startup procedure only needs a few cycles (16.67 ms/cycle) to reliably synchronize the inverter to the grid without any inrush current. Simulation and experimental results are presented to verify the effectiveness of this control strategy.

He, Yuchen↗
DOE OSTI2019

Changes in Soil Carbon Dynamics in Response to Long-Term Soil Warming - Integration Across Scales from Cells to Ecosystems

This project produced a series of papers documenting the effects of soil warming on fluxes of carbon dioxide between soils and the atmosphere, and the temporal changes in structure and function of soil microbial community. A diversity of techniques was used in the study including: pyrolysis–GC/MS to analyze soil chemistry; isotopically–labeled organic compounds to estimate microbial carbon use efficiency; and Illumina sequencing of the 16S ribosomal RNA gene to study bacterial community composition. We found that soil warming resulted in a four–phase pattern of soil organic matter decay and carbon dioxide fluxes to the atmosphere, with phases of substantial soil carbon loss alternating with phases of no detectable loss. Several factors combined to affect the timing, magnitude, and thermal acclimation of soil carbon loss. These include depletion of microbially accessible carbon pools, reductions in microbial biomass, a shift in microbial carbon use efficiency, and changes in microbial community composition. Our results support projections of a long–term, self–reinforcing carbon feedback from mid–latitude forests to the climate system as the world warms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

What Is the Limit of Quantification for the Minor Phase in Time-of-Flight Neutron Diffraction? A Case Study on Fe and Ni Powder Mixtures at VULCAN

A phase present in small quantities within materials may not simply serve as a secondary component; it can play a crucial role in determining the integrity, properties, and performance of the material. These minor but important phases usually draw attention in material design and processing for fundamental understanding as well as material quality control. Accurately quantifying a minor phase amid a majority phase, especially at extremely low fractions, remains a challenging task. Time-of-flight neutron diffraction, coupled with advanced pattern analysis techniques like Rietveld refinement, is a powerful tool for crystal structure identification and phase quantification. The deep penetrating capability of neutrons enables the detection and quantification of trace phases within materials. In this study, the quantification limits of time-of-flight neutron diffraction were explored using the VULCAN diffractometer at the Spallation Neutron Source, using Fe–Ni powder mixtures as a sample system. By comparing the refinement results to the known weighed values, it was determined that the reliable quantification of a minor Ni phase is achievable down to about 0.1 wt% while a Ni fraction as low as 0.02 wt% is difficult to trace. Effective control of the refinement parameters, especially the profile function parameters, are found to significantly influence the convergence of fittings and the accuracy of phase quantification.

Rietveld refinement↗
DOE OSTI2015

Water masers in W43A: Early morphological changes of a future planetary nebula

We present the distribution patterns of H{sub 2}O maser features in the “water fountain” source (WF) W43A and show that they are closely related to the early morphological changes in a planetary nebula (PN). Using the Very Long Baseline Array, we have detected H{sub 2}O maser features in W43A in 13 epochs across >10 yr. W43A is the only WF that has been observed for over a decade. We introduce a new cavity model scenario—a halo with a bipolar evacuated volume that has a partially enhanced wall—and compare it with the “traditional” precessing jet model particularly in terms of explaining the bow-shaped distribution patterns of H{sub 2}O maser features in the most recent epochs and their temporal evolution. Long-term observations show that the distribution patterns require more than a single jet to form. Moreover, we have identified six groups of H{sub 2}O maser features at both the redshifted and blueshifted sides with point symmetry. The six groups are believed to correspond to periodic mass profiles in the envelope and have recorded the mass-loss history. Together with a geometric similarity to the mid-infrared morphology of W43A, the results suggest that H{sub 2}O masers can be used to trace the inner morphology and rapid temporal changes in evolved stars, especially where the PN shaping has just started.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Plasma constraints on the cosmological abundance of magnetic monopoles and the origin of cosmic magnetic fields

Existing theoretical and observational constraints on the abundance of magnetic monopoles are limited. Here we demonstrate that an ensemble of monopoles forms a plasma whose properties are well determined and whose collective effects place new tight constraints on the cosmological abundance of monopoles. In particular, the existence of micro-Gauss magnetic fields in galaxy clusters and radio relics implies that the scales of these structures are below the Debye screening length, thus setting an upper limit on the cosmological density parameter of monopoles, Ω {sub M} {sub ∼<} {sub 3} {sub ×} {sub 10}{sup −4}, which precludes them from being the dark matter. Future detection of Gpc-scale coherent magnetic fields could improve this limit by a few orders of magnitude. In addition, we predict the existence of magnetic Langmuir waves and turbulence which may appear on the sky as ''zebra patterns'' of an alternating magnetic field with k·B ≠ 0. We also show that magnetic monopole Langmuir turbulence excited near the accretion shock of galaxy clusters may be an efficient mechanism for generating the observed intracluster magnetic fields.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors

Purpose: In using flat panel detectors (FPD) for cone beam computed tomography (CBCT), pixel gain variations may lead to structured nonuniformities in projections and ring artifacts in CBCT images. Such gain variations can be caused by change in detector entrance exposure levels or beam hardening, and they are not accounted by conventional flat field correction methods. In this work, the authors presented a method to identify isolated pixel clusters that exhibit gain variations and proposed a pixel gain correction (PGC) method to suppress both beam hardening and exposure level dependent gain variations. Methods: To modulate both beam spectrum and entrance exposure, flood field FPD projections were acquired using beam filters with varying thicknesses. “Ideal” pixel values were estimated by performing polynomial fits in both raw and flat field corrected projections. Residuals were calculated by taking the difference between measured and ideal pixel values to identify clustered image and FPD artifacts in flat field corrected and raw images, respectively. To correct clustered image artifacts, the ratio of ideal to measured pixel values in filtered images were utilized as pixel-specific gain correction factors, referred as PGC method, and they were tabulated as a function of pixel value in a look-up table. Results: 0.035% of detector pixels lead to clustered image artifacts in flat field corrected projections, where 80% of these pixels were traced back and linked to artifacts in the FPD. The performance of PGC method was tested in variety of imaging conditions and phantoms. The PGC method reduced clustered image artifacts and fixed pattern noise in projections, and ring artifacts in CBCT images. Conclusions: Clustered projection image artifacts that lead to ring artifacts in CBCT can be better identified with our artifact detection approach. When compared to the conventional flat field correction method, the proposed PGC method enables characterization of nonlinear pixel gain variations as a function of change in x-ray spectrum and intensity. Hence, it can better suppress image artifacts due to beam hardening as well as artifacts that arise from detector entrance exposure variation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

EHR-BERT: A BERT-based model for effective anomaly detection in electronic health records

Objective: Physicians and clinicians rely on data contained in electronic health records (EHRs), as recorded by health information technology (HIT), to make informed decisions about their patients. The reliability of HIT systems in this regard is critical to patient safety. Consequently, better tools are needed to monitor the performance of HIT systems for potential hazards that could compromise the collected EHRs, which in turn could affect patient safety. In this paper, we propose a new framework for detecting anomalies in EHRs using sequence of clinical events. This new framework, EHR-Bidirectional Encoder Representations from Transformers (BERT), is motivated by the gaps in the existing deep-learning related methods, including high false negatives, sub-optimal accuracy, higher computational cost, and the risk of information loss. EHR-BERT is an innovative framework rooted in the BERT architecture, meticulously tailored to navigate the hurdles in the contemporary BERT method; thus, enhancing anomaly detection in EHRs for healthcare applications.Methods: The EHR-BERT framework was designed using the Sequential Masked Token Prediction (SMTP) method. This approach treats EHRs as natural language sentences and iteratively masks input tokens during both training and prediction stages. This method facilitates the learning of EHR sequence patterns in both directions for each event and identifies anomalies based on deviations from the normal execution models trained on EHR sequences.Results: Extensive experiments on large EHR datasets across various medical domains demonstrate that EHR-BERT markedly improves upon existing models. It significantly reduces the number of false positives and enhances the detection rate, thus bolstering the reliability of anomaly detection in electronic health records. This improvement is attributed to the model’s ability to minimize information loss and maximize data utilization effectively.Conclusion: EHR-BERT showcases immense potential in decreasing medical errors related to anomalous clinical events, positioning itself as an indispensable asset for enhancing patient safety and the overall standard of healthcare services. The framework effectively overcomes the drawbacks of earlier models, making it a promising solution for healthcare professionals to ensure the reliability and quality of health data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Detection of Isotopes in Urban Source Search Low-Count Gamma Spectra Using Hopfield Neural Networks

Source search campaigns involve measurements of background gamma-ray spectra with a mobile detector-spectrometer traveling along arbitrarily chosen trajectories over a wide screening area. Radiation counts are typically measured with a tellurium-doped sodium iodide [NaI(Tl)] scintillator detector-spectrometer in short acquisition intervals, usually 1 s. The objective is to detect orphan isotopes with half-lives shorter than those of the isotopes in the natural background. In principle, radioisotopes can be identified by their unique gamma emission spectrum. However, detecting orphan isotopes in search data is challenging because low counts measured in short acquisition intervals result in incomplete spectral lines. In this study, we investigate the performance of a Hopfield neural network (HNN) that implements an auto-associative memory for the detection of isotopes of interest in an urban search campaign. The HNN is trained on one example of gamma spectra with well-resolved spectral lines of each isotope of interest. During testing, the auto-associative memory implementation of the HNN processes low-count gamma spectra with partially complete isotopic lines by matching incoming measurements to the closest one of its memory-stored patterns. The testing database consisted of almost 10 000 1-s gamma spectra, including measurements of orphan isotopes 137 Cs, 241 Am, and 131 I, obtained during two urban search surveys with a NaI(Tl) detector. The performance of the HNN detection algorithm was evaluated using precision, recall, and F1 scores, and benchmarked with a multiple linear regression (MLR) identification algorithm. In conclusion, the test results demonstrate that HNN outperforms MLR in the detection of all the isotopes of interest.

Auto associative memory↗
DOE OSTI2014

Prediction of reinforcement corrosion using corrosion induced cracks width in corroded reinforced concrete beams

This paper studies the evolution of reinforcement corrosion in comparison to corrosion crack width in a highly corroded reinforced concrete beam. Cracking and corrosion maps of the beam were drawn and steel reinforcement was recovered from the beam to observe the corrosion pattern and to measure the loss of mass of steel reinforcement. Maximum steel cross-section loss of the main reinforcement and average steel cross-section loss between stirrups were plotted against the crack width. The experimental results were compared with existing models proposed by Rodriguez et al., Vidal et al. and Zhang et al. Time prediction models for a given opening threshold are also compared to experimental results. Steel cross-section loss for stirrups was also measured and was plotted against the crack width. It was observed that steel cross-section loss in the stirrups had no relationship with the crack width of longitudinal corrosion cracks. -- Highlights: •Relationship between crack and corrosion of reinforcement was investigated. •Corrosion results of natural process and then corresponds to in-situ conditions. •Comparison with time predicting model is provided. •Prediction of load-bearing capacity from crack pattern was studied.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multimodal Nondestructive Dry Cask Basket Structure and Spent Fuel Evaluation

This NEUP-IRP assembled a team from diverse institutions and a diverse set of expertise to examine the problem of assessing the structural health of dry nuclear fuel storage casks, specifically the TN-32 design. With no physical access designed into these storage casks and the high cost and risk associated with opening casks for direct inspection, the technical difficulty of structural assessment of the basket structure and fuel assemblies is high. In response to this challenge, this IRP brought together experts in both traditional and novel NDE methodologies: active acoustics (University of Mississippi), emissions tomography (University of Florida), muon tomography (Oregon State University), and passive-active ultrasonics (University of South Carolina). Further, our industry partners in the Electric Power Research Institute (EPRI) and AREVA provided invaluable insight into technical design details for the cask, practical knowledge of operating parameters at a storage facility, and key relationships that enabled activities unforeseen at the time of the proposed work but were critical in guiding the path of the research. The team decided early in the project that we had a collective goal of laying the technical ground work for practical solutions that could be implemented in the field with reasonable cost, time, and reliability. A fortunate opportunity arose early in this IRP project to obtain access to a new TN-32 cask at Columbiana High Tech. Both acoustics teams were given access for testing concepts in the first year of the project. This ended up providing critical guidance in the design of subsequent laboratory experiments. Specifically, it became clear that the only reliable acoustic pathways to the interior were through the trunnions, base plate, and top ring of the cask. Based on these field tests and discussions about what would be of practical interest, the team as a whole decided a realistic goal was to detect catastrophic failure of a single fuel assembly, or one that was missing. It is clear from this work that the active acoustics / resonance and muon tomography methodologies would be capable of detecting interior structural integrity problems at this level. The other two areas of investigation (emissions tomography and passive/active ultrasonics) would need more testing to determine a successful implementation, but each may also have other applications such as long term monitoring and monitoring during transportation. This IRP project resulted in technical advances with applications that extend beyond the problem at hand, supported the training of 10 graduate students + 1 post doc, 21 publications, and 13 conference presentations. The remainder of this summary highlights significant activities and achievements in each of the methodologies and a brief discussion on how they can be combined to leverage strengths. Active Acoustics The active acoustics team at UM used both linear and non-linear structural resonance methods to infer information about the internal structure of a cask. Significant activities were a set of four field test measurements on a full scale TN-32 cask at the Columbiana Hi Tech facility in Greensboro, NC and the design and fabrication of a 1/6th scale model TN-32 cask for laboratory measurements. A significant set of acoustic data has been acquired on both the full scale and laboratory scale casks. It was determined early in the project that mechanical resonance techniques were not going to be sensitive to small scale (centimeter) cracks and structural defects in the basket structure or fuel assemblies. We were able to ascertain that both the energy and complexity of the resonance spectra were sensitive to “bulk state” of the fuel assemblies – an intact assembly versus a severely degraded assembly. By developing a novel combination of metrics, we are able to measure a statistically significant shift due to one out of the 32 fuel assemblies being either missing or degraded to a point of complete loss of structural coherence (i.e. “rubble”). We believe this combination of resonance metrics is new to the field and will have applications beyond the fuel storage problem. Emissions Tomography The Emissions Tomography team at the University of Florida explored the concept of using scattering of radiation emissions from the stored fuel as method of evaluating the internal structural health of the cask. Due to the need for emissive fuel assemblies and the difficulties of gaining access to storage facilities, this team primarily relied on simulations to inform feasibility. A key question was the flux estimates of neutrons with a small enough number of scattering events to retain spatial information. Some key conclusions from the transmission component of this work are that the number of scattering events falls rapidly with energy – setting a 11MeV threshold, the average number of scattering events is 8∓4. Rough estimates of scanning times using an ideal detector array would be 1 week. The team also explored the case of significant structural failure resulting in a shift of the source material (fuel). The result is that a +/- 2% mass shift results in a detectable (5.13%) shift in the correlated 2 neutron emission counts and thus may be a candidate as an initial survey. Finally, simulations for predicting the azimuthal dependence of the flux based on specific loading patterns were conducted. Due to self-shielding effects of the assemblies, a periodic pattern results and could potentially be used to identify missing or severely degraded assemblies. This work forms a basis for proper detector placement with the goal of optimizing sensitivity. Muon Tomography Muon tomography (MT) is a relatively novel method of interrogating interior structure on a large scale. One of the advantages of this technique is that the exciting energy source (cosmic muons) is ubiquitous and relatively stable in time. Challenging aspects are relatively low flux rates and appropriate detector technologies. The efforts of the muon group at Oregon State University focused on two areas: (1) simulation of various combinations of muon scattering events and detection schemes to assess sensitivities and time scales for image construction and (2) building a prototype muon detection system applicable to the dry storage cask problem as well as many other similar systems. Significant accomplishments in this area are: (1) demonstration that MT is a viable method for detecting missing or severely degraded rod assemblies, (2) a scintillation based detector with 4 panels and 32 channels of position data each were constructed, tested, and calibrated. Testing of the panels using natural muon background and no scattering objects yielded largely expected results – a straight line path for the muon through the four panels. However some anomalies (paths deviating from a line) were also detected. A redesign of the board improved the signal which greatly improved the muon tracking through the panels. Testing with lead bricks as scattering bodies showed a reduction in the coincidence rate with increasing bricks indicating increased scattering events. A refinement of the scintillator detector design resulted in a spatial image resolution of around 2 cm based on lead brick spacing tests lasting 24 hours. Passive/Active Ultrasonics This team at the University of South Carolina investigated the feasibility of combining passive ultrasonics, in which an elastic pulse is generated by a degradation process (such as a crack extending), and active ultrasonics, in which a known excitation is introduced into the structure and detected by an array of transducers. Significant accomplishments in this area include the development of elastic wave propagation simulation in relevant materials, development of diagnostic algorithms, and laboratory testing and validation using laser doppler vibrometry. This group demonstrated the applicability of various non-contact vibration detection methodologies such as air-coupled ultrasonic transducers and scanning laser doppler vibrometry. While passive acoustic emissions monitoring will likely have a role during the transportation of a fuel storage cask, the level of detailed information about the defect generating the event which can be ascertained from the detections in a complex structure remains for future work. Thermography The EPRI team contributed early in the project a series of thermography measurements in which various levels of water pooled in a mock-up canister were analyzed using commercially available infrared imaging technologies. While large levels of water (100 L, ~10 cm deep) were observable in the thermograms, more realistic levels of pooled water (1 L) were not detectable whether localized or distributed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

The Surface Chemistry of Methanol on Cu 3 Pd(111): Effects of Metal Alloying and Reaction with Hydrogen

Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the adsorption and surface chemistry of methanol on a Cu 3 Pd(111) model surface. The composition and morphological properties of the pristine Cu 3 Pd(111) substrate were analyzed using a combination of low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and low-energy ion scattering (LEIS). The results of ion scattering showed segregation of Pd toward the surface, with a Pd/Cu ratio close to 0.5, a larger value than the ratio of 0.33 expected for a Cu 3 Pd bimetallic structure. The surface of the alloy exhibited a good LEED pattern with three-fold long-range periodicities. In STM, clusters of palladium with hexagonal arrays and Pd- Pd distances of 2.7-2.8 Å were detected. Bonding to copper perturbed the electronic properties of the atoms in the Pd clusters, shifting their 4d states toward higher binding energy with respect to the Fermi level. Further, the valence band spectrum of Cu 3 Pd(111) exhibited a line shape that was very different from those displayed by Cu(111) or Pd(111). At low pressures, the adsorption of methanol on Cu 3 Pd(111) at 300 K mainly produced CH 3 O, CO and CH x species. AP-XPS showed that most Pd atoms in the surface of the Cu 3 Pd(111) alloy interacted with the decomposition products of methanol. No significant changes were observed in the core levels of copper upon the adsorption and dissociation of methanol, suggesting that the molecule mainly interacted with Pd sites of the alloy. Reaction with hydrogen led to fast removal of CH x , C and PdC x species from Cu 3 Pd(111) at moderate (< 450 K) temperatures and prevented a CH x → C transformation. If the stability of adsorbed CH 3 O is used as a descriptor for the hydrogenation of CO 2 to methanol, Cu 3 Pd should be a much better catalyst than monometallic palladium. This may be a consequence of electronic and ensemble effects in the alloy that moderate the reactivity of Pd sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unsupervised Clustering of Microseismic Events and Focal Mechanism Analysis at the CO 2 Injection Site in Decatur, Illinois

Characterization of induced microseismicity at a carbon dioxide (CO 2 ) storage site is critical for preserving reservoir integrity and mitigating seismic hazards. We apply a multilevel machine learning (ML) approach that combines the nonnegative matrix factorization and hidden Markov model to extract spectral representations of microseismic events and cluster them to identify seismic patterns at the Illinois Basin-Decatur Project. Unlike traditional waveform correlation methods, this approach leverages spectral characteristics of first arrivals to improve event classification and detect previously undetected planes of weakness. By integrating ML-based clustering with focal mechanism analysis, we resolve small-scale fault structures that are below the detection limits of conventional seismic imaging. Our findings reveal temporal bursts of microseismicity associated with brittle failure, providing insights into the spatio-temporal evolution of fault reactivation during CO 2 injection. This approach enhances seismic monitoring capabilities at CO 2 injection sites by improving fault characterization beyond the resolution of standard geophysical surveys.

Willis, Rachel Marie [Sandia National Laboratories↗
DOE OSTI2020

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R 2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R 2 = 0.04–0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The ELISA Detectability and Potency of Pegfilgrastim Decrease in Physiological Conditions: Key Roles for Aggregation and Individual Variability

PEGylated recombinant human granulocyte colony stimulating factor (pegflgrastim) is used clinically to accelerate immune reconstitution following chemotherapy and is being pursued for biosimilar development. One challenge to overcome in pegflgrastim biosimilar development is establishing pharmacokinetic (PK) similarity, which is partly due to the degree of PK variability. We herein report that commercially available G-CSF and PEG ELISA detection kits have different capacities to detect pegflgrastim aggregates that rapidly form in vitro in physiological conditions. These aggregates can be observed using SDS-PAGE, size-exclusion chromatography, dynamic light scattering, and real-time NMR analysis and are associated with decreased bioactivity as reflected by reduced drug-induced cellular proliferation and STAT3 phosphorylation. Furthermore, individual variability in the stability and detectability of pegflgrastim in human sera is also observed. Pegflgrastim levels display marked subject variability in sera from healthy donors incubated at 37°C. The stability patterns of pegflgrastim closely match the stability patterns of flgrastim, consistent with a key role for pegflgrastim’s G-CSF moiety in driving formation of inactive aggregates. Taken together, our results indicate that individual variability and ELISA specificity for inactive aggregates are key factors to consider when designing and interpreting studies involving the measurement of serum pegflgrastim concentrations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The chemical composition of ρ puppis and the signs of accretion in the atmospheres of B–F-type stars

We investigated the chemical composition of ρ Pup using high-resolution spectral observations taken from the Very Large Telescope and the IUE archives and also spectra obtained at the 1.8 m telescope of the Bohyunsan observatory in Korea. The abundances of 56 chemical elements and the upper limits of Li and Be abundances were determined. The abundance pattern of ρ Pup was found to be similar to that of Am-type stars. The possibility of the influence of the accretion of interstellar gas and dust on the abundance patterns of B–F-type stars is discussed. The plots of the relative abundances of chemical elements in the atmospheres of ρ Pup and δ Sct versus the second ionization potentials of these elements show the correlations. The discontinuities at 13.6 and 24.6 eV—the ionization potentials of hydrogen and helium, respectively, are also exhibited in these plots. These discontinuities can be explained by interaction of the atoms of interstellar gas, mainly hydrogen and helium atoms, with the atoms of stellar photospheres (so-called charge-exchange reactions). Note that only the jumps near 13.6 and 24.6 eV were pointed out in previous investigations of relative abundances versus the second ionization potentials for Am-type stars. The dependencies of the relative abundances of chemical elements on the second ionization potentials of these elements were investigated using the published abundance patterns of B–F-type stars. The correlations of relative and absolute abundances of chemical elements, second ionization potentials, and projected rotational velocities are clearly detected for stars with effective temperatures between 7,000 and 12,000 K. If the correlation of relative abundances and second ionization potentials can be explained by the accretion of interstellar gas on the stellar surfaces, the investigation of these correlations can provide valuable information on the density and velocities of interstellar gas in different regions of the Galaxy and also on the influence of this phenomenon on stellar evolution. The dependencies of the relative abundances of chemical elements on the condensation temperatures of these elements were also found in the atmospheres of ρ Pup, δ Sct, and other B–F-type stars. Ten possible λ Boo-type stars were detected. The effective temperatures of these objects are between 10,900 and 14,000 K.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Host population dynamics influence Leptospira spp. transmission patterns among Rattus norvegicus in Boston, Massachusetts, US

Leptospirosis (caused by pathogenic bacteria in the genus Leptospira ) is prevalent worldwide but more common in tropical and subtropical regions. Transmission can occur following direct exposure to infected urine from reservoir hosts, or a urine-contaminated environment, which then can serve as an infection source for additional rats and other mammals, including humans. The brown rat, Rattus norvegicus , is an important reservoir of Leptospira spp. in urban settings. We investigated the presence of Leptospira spp. among brown rats in Boston, Massachusetts and hypothesized that rat population dynamics in this urban setting influence the transportation, persistence, and diversity of Leptospira spp. We analyzed DNA from 328 rat kidney samples collected from 17 sites in Boston over a seven-year period (2016–2022); 59 rats representing 12 of 17 sites were positive for Leptospira spp. We used 21 neutral microsatellite loci to genotype 311 rats and utilized the resulting data to investigate genetic connectivity among sampling sites. We generated whole genome sequences for 28 Leptospira spp. isolates obtained from frozen and fresh tissue from some of the 59 positive rat kidneys. When isolates were not obtained, we attempted genomic DNA capture and enrichment, which yielded 14 additional Leptospira spp. genomes from rats. We also generated an enriched Leptospira spp. genome from a 2018 human case in Boston. We found evidence of high genetic structure among rat populations that is likely influenced by major roads and/or other dispersal barriers, resulting in distinct rat population groups within the city; at certain sites these groups persisted for multiple years. We identified multiple distinct phylogenetic clades of L. interrogans among rats that were tightly linked to distinct rat populations. This pattern suggests L. interrogans persists in local rat populations and its transportation is influenced by rat population dynamics. Finally, our genomic analyses of the Leptospira spp. detected in the 2018 human leptospirosis case in Boston suggests a link to rats as the source. These findings will be useful for guiding rat control and human leptospirosis mitigation efforts in this and other similar urban settings.

Stone, Nathan E.↗
DOE OSTI2022

Robust Event Classification Using Imperfect Real-world PMU Data

Here, this paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

2D to 3D transition of polymeric carbon nitride nanosheets

The transition from a prevalent turbostratic arrangement with low planar interactions (2D) to an array of polymeric carbon nitride nanosheets with stronger interplanar interactions (3D), occurring for samples treated above 650 °C, was detected by terahertz-time domain spectroscopy (THz-TDS). The simulated 3D material made of stacks of shifted quasi planar sheets composed of zigzagged polymer ribbons, delivered a XRD simulated pattern in relatively good agreement with the experimental one. The 2D to 3D transition was also supported by the simulation of THz-TDS spectra obtained from quantum chemistry calculations, in which the same broad bands around 2 THz and 1.5 THz were found for 2D and 3D arrays, respectively. This transition was also in accordance with the tightening of the interplanar distance probably due to an interplanar π bond contribution, as evidenced also by a broad absorption around 2.6 eV in the UV–vis spectrum, which appeared in the sample treated at 650 °C, and increased in the sample treated at 700 °C. The band gap was calculated for 1D and 2D cases. The value of 3.374 eV for the 2D case is, within the model accuracy and precision, in a relative good agreement with the value of 3.055 eV obtained from the experimental results. - Graphical abstract: 2D lattice mode vibrations and structural changes correlated with the so called “2D to 3D transition”. - Highlights: • A 2D to 3D transition has been detected for polymeric carbon nitride. • THz-TDS allowed us to discover and detect the 2D to 3D transition of polymeric carbon nitride. • We propose a structure for polymeric carbon nitride confirming it with THz-TDS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗