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At least 55 records · Page 3

Studies of optical and chemical properties of aged and fresh biomass burning absorbing aerosols for climate models

Particulate emissions from burning fuels from sub-Saharan Africa is currently poorly characterized. With increasing population and industrialization, emissions are expected to grow. Optical methods for measuring light absorption in the ultraviolet (UV) and visible (vis) regions of the spectrum are crucial for understanding the optical properties of BB aerosols (Bond and Bergstrom, 2006; Lack and Cappa, 2010; Moschos et al., 2021). One such instrument is the dual-spot AE33 model aethalometer is a common filter-based instrument that can be used to measure aerosol absorption properties (Hansen et al., 1984). This instrument has many figures of merit; however, the method's limitations include potential biases from scattering within the filter material, multiple scattering effects of the particles, filter loading (i.e. particle shadowing), and the need for wavelength-specific correction factors (Cλ), which depend on accurate intercomparison with other in situ techniques (Bond et al., 1999; Collaud Coen et al., 2010). This work aims to: 1. Optically characterize BB aerosol generated from African fuel 2. Correct the aethalometer at multiple wavelengths 3. Parametrize these correction factors. 4. Combusting the same fuels with two difference tube furnace systems assess the general applicability of this flexible means of producing BB aerosol. This was accomplished by conducting laboratory studies at Los Alamos National Laboratory (LANL) and North Carolina A&T State University (NCA&T), where aethalometer measurements were compared to in situ optical measurements. Mass cross sections of BB aerosol from these under-studied fuels will be determined along with their wavelength dependence.

09 BIOMASS FUELS

Optimizing Charge-coupled Device Readout Enabled by the Floating-gate Amplifier

Multiple-Amplifier Sensing (MAS) charge-coupled devices (CCDs) have recently been shown to be promising silicon detectors that meet noise sensitivity requirements for next generation Stage-5 spectroscopic surveys and potentially, future space-based imaging of extremely faint objects on missions such as the Habitable Worlds Observatory. Building upon the capability of the Skipper CCD to achieve deeply sub-electron noise floors, MAS CCDs utilize multiple floating-gate amplifiers along the serial register to increase the readout speed by a factor of the number of output nodes compared to a Skipper CCD. We introduce and experimentally demonstrate on a 16-channel prototype device new readout techniques that exploit the MAS CCD’s floating-gate amplifiers to optimize the correlated double sampling by resetting once per line instead of once per pixel. With this new mode, we find an optimal filter to subtract the noise from the signal during read out. We also take advantage of the MAS CCD’s structure to tune the read time by independently changing integration times for the signal and reference level. Together with optimal weighted averaging of the 16 outputs, these approaches enable us to reach a sub-electron noise of 0.9 e − rms pix −1 at 19 μs pix −1 for a single charge measurement per pixel—simultaneously giving a 30% faster readout time and 10% lower read noise compared to performance previously evaluated without these techniques.

Lin, Kenneth W. (ORCID:0000000189672281)

Wind turbine power phase control with DC collection bus for onshore/offshore windfarms

A DC bus collection system for a wind farm reduces the overall required number of converters and minimizes the energy storage system requirements. The DC bus collection system implements a power phasing control method between wind turbines that filters the variations and improves power quality. The phasing control method takes advantage of a novel power packet network concept with nonlinear power flow control design techniques that guarantees both stable and enhanced dynamic performance.

Weaver, Wayne W.

An Integrated Framework for Memory-Centric Analysis: From Trace Collection to Co-Design

The memory wall phenomenon—where advances in processor performance significantly outpace those in memory subsystems—poses a fundamental challenge for contemporary computing systems. In memory-bound applications, memory subsystem behavior dominates performance, yet existing analysis approaches present significant limitations: detailed microarchitectural simulators require days to weeks to simulate modest workloads; hardware performance counters provide only aggregate statistics that obscure temporal and spatial access patterns; and scaled simulation approaches face challenges in capturing certain behaviors that emerge at larger scales. These limitations reflect a processor-centric design philosophy increasingly misaligned with memory-bound workloads where detailed understanding of memory access patterns, cache hierarchy interactions, and contention is critical for effective optimization. This paper presents an integrated framework for memory-centric analysis that enables effective hardware-software co-design. We describe practical trace collection techniques, including hardware-assisted processor tracing with minimal overhead and portable software-based instrumentation with statistical sampling. We present multi-perspective analysis methods that examine memory behavior from temporal, sequential, spatial, and relational viewpoints, revealing distinct optimization opportunities invisible in aggregate metrics. We detail an architectural modeling framework that uses sampled traces with temporal interpolation and confidence-based filtering to evaluate cache and memory configurations. Evaluation on representative benchmarks demonstrates that this framework achieves practical accuracy (L2 cache errors of 2.64\%, confidence-filtered L3 errors of 9.92\%, bandwidth errors of 7.33\%) while providing substantial speedup (26.8×) over cycle-accurate simulation, enabling rapid design space exploration. We demonstrate how this integrated framework enables systematic identification of both hardware optimizations (memory controller tuning, bank partitioning, NUMA configuration) and software optimizations (data layout restructuring, prefetching strategies, memory-aware scheduling). Through this comprehensive treatment of the memory-centric analysis pipeline—from trace collection through architectural modeling to co-design application—we provide researchers and practitioners with practical techniques for addressing memory bottlenecks in contemporary computing systems.

Gajaria, Dhruv Mayur

Towards gradient multimaterial toolpath generation for direct ink writing with connected fermat spirals

This work describes advances towards a reproducible, parametrically defined algorithm for generating graded multimaterial toolpaths for direct ink writing. Expanding on the existing Fermat space-filling algorithm and coupling with image-driven processing techniques, we demonstrate the fabrication of multimaterial structures. Here, material composition is encoded within toolpaths by parsing hue values from a multi-colored image. By performing dynamic velocity compensation based on local curvature and Euclidean distance filtering, internal voids are mitigated while optimizing print fidelity. Here, the work opens new avenues for designing complex toolpaths with locally programmable composition.

3D Printing

Robustness of the Ensemble Score Filter to the Type of Assimilated Observation Networks

Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods depends on the observation network characteristics. In this study, we present initial experiments with the surface quasi‐geostrophic model, in which we compare a recently developed ensemble filter using score‐based diffusion models with the standard Local Ensemble Transform Kalman Filter (LETKF). Our results show that the analysis solutions respond differently to the number, spatial distribution, and nonlinear fraction of assimilated observations. We also find notable changes in the multiscale characteristics of the analysis errors. Given that standard DA techniques will eventually be replaced by more advanced methods, we hope this study sets the ground for future efforts to reassess the value of Earth observing systems in the context of newly emerging algorithms.

97 MATHEMATICS AND COMPUTING

Density of molten oxides measured in an aero-acoustic levitator

Knowing the thermophysical properties of high-temperature melts can aid the design of melt processes and validate atomic structural models, such as those used in studying glass formation. Property measurements on such melts are challenging, however, due to container-related contamination and heterogeneous nucleation. Containerless processing techniques that employ levitation can be used to avoid these obstacles. In that context, we demonstrate here the application of silhouette imaging to measure the density of molten oxides in an aero-acoustic levitation instrument (AAL). The AAL combines gas jet levitation with actively controlled acoustic positioning to enable full optical access to samples ca. 2–4 mm in diameter, which are laser beam heated and melted. The cross sections of molten drops are imaged using a monochromatic light source and narrowband-filtered camera. Melt volume is calculated from the cross sections and used to find density at several temperatures ranging 1530–1920 K, including up to 350 K of supercooling. We report densities for CaAl 2 O 4 , Ca 12 Al 14 O 33 , CaSiO 3 , their Fe 2 O 3 -bearing analogs, and 83TiO 2 -17RE 2 O 3 (RE = La or Nd). These provide important benchmarks of the capabilities, measurement uncertainties, and future outlook for this technique.

36 MATERIALS SCIENCE

Multicarrier Spread Spectrum Communications With Noncontiguous Subcarrier Bands for HF Skywave Links

Existing high-frequency (HF) radio platforms offer robust performance against the volatile HF propagation channel. However, the growing traffic across the band contests the reliability of these systems. While techniques to mitigate the effects of narrowband interference have been thoroughly explored, they are insufficient against wideband interference or when the transmission band is occupied by numerous scattered users. To improve reliability in these congested channel conditions, we propose a filter-bank based multicarrier spread-spectrum waveform with noncontiguous subcarrier bands. Using noncontiguous subcarrier bands enables the system to at once leverage the robustness of a wideband system while retaining the frequency agility of a narrowband system. In this study, we modify a filter-bank transmitter structure to accommodate noncontiguous subcarrier bands and consider several immediate impacts of this change, such as elevated peak-to-average-power ratios (PAPRs). A receiver architecture to process the noncontiguous spread-spectrum signal is also introduced, along with details regarding wideband channel estimation. Finally, we develop efficient transmitter and receiver structures to support practical system implementations. We conclude by comparing the performance of contiguous and noncontiguous systems through both simulation and over-the-air testing. The results show that the noncontiguous system remains robust in typical HF channels while significantly outperforming the contiguous system in congested spectral conditions.

(PAPR

Broadband Infrared Carbon Nanotube Linear Photodetector Arrays

Carbon nanotubes (CNTs) possess exceptional optoelectronic properties, including broadband absorption and high absorption coefficients, making them promising candidates for photodetector applications. However, conventional designs often rely on single or aligned nanotubes, which restrict device scalability and require complex fabrication techniques. Here, in this work, we address these limitations by utilizing CNT-suspended solutions to fabricate large-area photodetectors based on CNT networks via vacuum filtration and direct laser scribing. CNT networks are uniformly formed onto low-thermal-conductance polymeric filter papers that serve as substrates and mitigate the need for suspended structures, reducing the fabrication complexity and cost. The CNT films are patterned into single devices and 49-pixel linear arrays by using a laser-cutting process, enabling scalable and cost-effective production. The resulting devices operate as bolometers and exhibit broad spectral sensitivity extending from visible to midwave infrared, showing stable operation at room temperature. We further demonstrate proof-of-concept IR imaging using linear arrays.

IR imaging

Migration of 60 Co, 133 Ba, 137 Cs, and 152 Eu from cementitious wasteforms in field lysimeter experiments

Safe and effective storage of radioactive waste is essential to protect environmental health. Due to the potential for accidental releases and the severity of the associated risks, it is imperative to further understand radionuclide transport should an accident occur. This work analyzed the vadose zone migration of radionuclides from cementitious wasteforms at the Savannah River Site after ten years. The observed radionuclides are prominent constituents of radioactive waste or analogs for other groups or series of radionuclides. Lysimeters were first analyzed in 2016 using a collimated high-purity germanium gamma-ray spectrometer to non-destructively measure the concentration of each radionuclide in the sediment column as a function of depth. Following these measurements, the lysimeters were redeployed in the field for another 4 years. All radionuclides in all lysimeters were observed to transport further during the redeployment period; however, the extent of migration varied with the material used for introduction. Except for 137 Cs, migration through the sediment control system increased with decreasing ionic potential (ionic charge/radius); migration order: 152 Eu< 137 Cs< 60 Co< 133 Ba. Overall, the cementitious wasteforms were observed to decrease radionuclide migration extent relative to the filter paper. In both cementitious wasteforms, the migration extent increased in the order 152 Eu< 133 Ba< 60 Co< 137 Cs. However, less migration was measured when the radionuclides were incorporated into a reducing grout wasteform. The novelty of this paper is the demonstration of a technique capable of creating non-destructive measurements over decade time scales. Ultimately, this work provides insight into the long-term migration of alkali, alkali earth, divalent transition metal, and trivalent actinide element isotopes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Nano Filters for Selective Metal Capture (CRADA Final Report)

As part of the Cyclotron Road program, Sunchem investigated novel nanoporous materials and their metal extraction performance in both batch and dynamic continuous flow operations. The proposed project developed novel nanoporous materials for selective metal extraction from complex industrial mixtures. The technical objectives were to synthesize and characterize the nanoporous materials, structure the nanoporous materials with binders along with structuring techniques and evaluate its performance in both a batch and dynamic continuous flow operation. The nanoporous material was structured through a disc granulation method to obtain particles in the size range of 250 to 500 micron diameter. This structured material was packed into a continuous flow column which achieved up to 48 wt% of gold capture. This work aimed to address the key technical risk of the materials’ capability to be employed in an industrial operation with competitive performance compared to other adsorbents.

36 MATERIALS SCIENCE

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to enable and understanding of their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transfected with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produce. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of novel DB positions and enzymatic specificity.

mass spectrometry, deep learning, Lipidomics, doub

Fast superconducting qubit control with subharmonic drives

Increasing the fidelity of single-qubit gates requires a combination of faster pulses and increased qubit coherence. However, these requirements can be contradictory. Additionally, increasing the drive power can heat the qubit’s environment and degrade coherence. In this work, we circumvent this issue and achieve rapid gates by pumping a transmon’s native Kerr at approximately one third of the qubit’s resonant frequency. The subharmonic Rabi rate of the process is proportional to applied drive amplitude cubed, allowing for rapid gates. In addition, we demonstrate that filtering can be used to protect the qubit’s coherence while performing rapid gates. Single qubit gates as short as 37.4 ns are demonstrated with fidelity of 99.91%. We present theoretical calculations indicating that drive induced multi-photon decay will not limit qubit lifetime; calculated power absorption also indicates that this technique could reduce cryostat heating for fast gates, a vital requirement for large-scale quantum computers.

Xia, Mingkang [Univ. of Pittsburgh, PA (United Sta

Reconstruction of 2D line-integrated electron density using angular filter refractometry and a fast marching Eikonal solver

Refraction of an optical probe beam by a plasma can be measured with angular filter refractometry (AFR), which produces an image of the beam’s 2D spatial profile that contains intensity contours corresponding to curves of constant refraction angle. Further analysis is required to reconstruct the underlying line-integrated electron density. Most prior efforts to calculate density from AFR data have been limited to 1D analysis or forward-fitting techniques. Here, in this paper, we detail the use of a fast-marching Eikonal solver to directly invert AFR data and obtain the full 2D line-integrated electron density. The analysis method is first verified with synthetic data and then applied to experimental measurements of single and colliding plasma plumes collected at the OMEGA EP Laser Facility. The calculated densities agree with 1D results and are shown to be consistent with the original AFR measurements via forward modeling. We also discuss ways to improve the precision of this technique.

McCluskey, B. [Princeton Univ., NJ (United States)

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew

Advancing Aerosol Chemical Characterization and Vertical Profiling over the Southern Great Plains Using Uncrewed Aerial Sampling and Offline Aerosol Mass Spectrometry

Recent advancements in uncrewed aerial systems (UASs) and particulate matter (PM) analytical techniques have provided opportunities for atmospheric research. In this study, we deployed the Department of Energy’s fixed-wing ArcticShark UAS to examine PM 2.5 composition at varying altitudes─within and above the planetary boundary layer (PBL)─over the Southern Great Plains atmospheric observatory (SGP). A total of 22 flights were conducted across March, June, and August 2023. Composite filter samples were collected during each flight and analyzed with offline aerosol mass spectrometry (AMS), complemented by on-board real-time sensors and ground-based instrumentation, to provide a comprehensive view of regional aerosol characteristics. Results show clear vertical and seasonal differences in the aerosol composition. Relative to ground-level measurements, aloft samples exhibited shifts in the distribution of organic and inorganic PM, with the organic composition varying distinctly across seasons. Particulate organic nitrogen (ON) was elevated, with bulk compositions similar in March and June but strongly altered in August, likely driven by biomass burning and enhanced photochemical activity. Combined AMS and chemical ionization mass spectrometry analyses detected amines, amides, and amino acids. PM above the planetary boundary layer was enriched in oxidized organic aerosols, while ground-level PM contained higher nitrate and sulfate. Seasonal differences in aqueous-phase processing were also observed, which were strongest in March during persistent cloud cover and weaker in the drier August period, suggesting a shift from aqueous- to gas-phase SOA formation. In conclusion, these findings highlight the value of UAS in advancing PM measurements and vertical profiling of aerosol composition.

54 ENVIRONMENTAL SCIENCES

Fractionation of Filamentous Algae from Mixed Biofilms

Filamentous algae, which grow in long, hair-like filaments within biofilms, play a crucial role in wastewater treatment due to their ability to produce significant biomass and their resistance to predation compared to traditional microalgal treatments. These algae can effectively uptake and utilize pollutants, particularly excessive nitrogen (ammonia, nitrate, nitrite) and phosphorus (phosphate), making filamentous algae valuable for wastewater treatment, as well as bioethanol and biodiesel production due to high lipid productions. However, each algal species possesses different capacities, necessitating a thorough genetic identification and understanding of each community. A major challenge in accurately assessing these communities is the lack of coverage in large sequencing databases which can lead to misrepresentation of the true composition and abundance of organisms and overall sequencing bias. To address this, I evaluated chemical and physical techniques for separating filamentous algae from mixed biofilms to achieve clean genetic sequencing results. I employed pH washing (0.001M HCl, 0.001M HCl, DiH2O, 0.0001M HCl, 0.001M HCl) for chemical treatment, followed by physical separation through centrifugation (5000rpm, 6500rpm) or filtration (2mm, 250um, 75um). The most successful method was deionized water washing, which yielded clear differences across stacked filters; the 2mm filtrate showed high levels of filamentous algae, with microalgae eluting in the 75um filtrate or remaining within agglutinations of algae larger filters. Base washing eluted the highest concentrations of microalgae, with larger filter sizes retaining more filamentous algae, indicating the breakdown of extracellular polymeric substances (EPS). Our downstream plans include sending the high-throughput next-generation sequencing to confirm the purity and ratios of filamentous and non-filamentous algae, as well as bacteria present, thereby validating the success of our treatments. Potential applications include creating community-based fractions for analysis, refining current sequencing data with clearer isolations, and generating designer biofilms to enhance our understanding of community interactions.

59 BASIC BIOLOGICAL SCIENCES

Graph neural network for neutrino physics event reconstruction

Liquid argon time projection chamber (LArTPC) detector technology offers a wealth of high-resolution information on particle interactions, and leveraging that information to its full potential requires sophisticated automated reconstruction techniques. Here, this article describes NUGRAPH 2, a graph neural network for low-level reconstruction of simulated neutrino interactions in a LArTPC detector. Simulated neutrino interactions in the MicroBooNE detector geometry are described as heterogeneous graphs, with energy depositions on each detector plane forming nodes on planar subgraphs. The network utilizes a multihead attention message-passing mechanism to perform background filtering and semantic labeling on these graph nodes, identifying those associated with the primary physics interaction with 98.0% efficiency and labeling them according to particle type with 94.9% efficiency. The network operates directly on detector observables across multiple two-dimensional representations but utilizes a three-dimensional-context-aware mechanism to encourage consistency between these representations. Model inference takes 0.12 s / event on a CPU and 0.005 s / event batched on a GPU. This architecture is designed to be a general-purpose solution for particle reconstruction in neutrino physics, with the potential for deployment across a broad range of detector technologies, and offers a core convolution engine that can be leveraged for a variety of tasks beyond the two described in this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS