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At least 1,135 records · Page 63

Nanoscale Magnetic Ordering Dynamics in a High Curie Temperature Ferromagnet

Thermally driven transitions between ferromagnetic and paramagnetic phases are characterized by critical behavior with divergent susceptibilities, long-range correlations, and spin dynamics that can span kHz to GHz scales as the material approaches the critical temperature T c , but it has proven technically challenging to probe the relevant length and time scales with most conventional measurement techniques. In this study, we employ scanning nitrogen-vacancy center based magnetometry and relaxometry to reveal the critical behavior of a high-T c ferromagnetic oxide near its Curie temperature. Cluster analysis of the measured temperature-dependent nanoscale magnetic textures points to a 3D universality class with a correlation length that diverges near T c . Meanwhile, the temperature-dependent spin dynamics, measured through all optical relaxometry suggest that the phase transition is in the XY universality class. In conclusion, our results capture both static and dynamic aspects of critical behavior, providing insights into universal properties that govern phase transitions in magnetic materials.

36 MATERIALS SCIENCE↗

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗

Characterization of Glass Fiber Separator Material for Lithium Batteries

Characterization studies were carried out on a glass fiber paper that is currently employed as a separator material for some LiSOCl2 primary cells. The material is of the non-woven type made from microfilaments of E-type glass and contains an ethyl acrylate binder. Results from extraction studies and tensile testing revealed that the binder content and tensile strength of the paper were significantly less than values specified by the manufacturer. Scanning electron micrographs revealed the presence of clusters of impurities many of which were high in iron content. Results of emission spectroscopy revealed high overall levels of iron and leaching, followed by atomic absorption measurements, revealed that essentially all of this iron is soluble in SOCl2.

Subbarao, S.↗

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $\$$868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $\$$4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As we expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

33 ADVANCED PROPULSION SYSTEMS↗

Confocal Raman Microscopy as a Probe of Material Deconstruction in Processed Low-Density Polyethylene Particles

Confocal Raman microscopy was applied to detect structural change within individual particles of low-density polyethylene (LDPE) following chemical and electrochemical processing steps that aimed to facilitate material decomposition. A high numerical aperture (NA) oil-immersion objective enabled depth-profiling through the near surface region (20 μm–40 μm) of irregularly shaped particles with an axial spatial resolution < 2 μm estimated from measurements of instrument detection efficiency profiles. Changes in vibrational bands sensitive to polyethylene crystallinity were evident following treatments and linked to the release of low molecular weight compounds present as additives and products of processing. Effects of processing were probed by monitoring the rise of Raman scattering intensity in vibrational modes associated with polyethylene chains in a zig-zag (trans) conformation near 1128 cm –1 , 1294 cm –1 , and 1418 cm –1 , signaling chain clustering and development of organized, crystalline-like assemblies. Pristine LDPE particles displayed a uniform structure across the near surface region, while particles treated initially with chemical extractant and then further processed displayed increasingly enhanced crystallinity up to the maximum depth probed (40 μm). As a step toward measurements on ensembles of particles, least squares modeling was adapted to derive pure component spectra reflecting crystallinity change within spectral datasets. The work demonstrates high spatial resolution Raman depth-profiling for the characterization of processed polymers using a high NA immersion objective to overcome the limitations of air-objectives often used for confocal Raman microscopy.

Wahiduzzaman, Md. [Department of Chemistry and Bio↗

White dwarfs and mass segregation in the core of 47 Tucanae

The core of the galactic globular cluster (GC) 47 Tucanae was observed by the Faint Object Camera (FOC) on the refurbished Hubble Space Telescope (HST) for the first time through medium-band F253M and F346M filters centered at 255 and 348 nm. A total of 442 stars down to the detection limit at m(sub 346) approximately equal to 24 in the 7 sec x 7 sec field were accurately placed on a m(sub 346) versus m(sub 253) - M(sub 346) magnitude diagram to characterize the stellar populations in the core. Approximately 100 objects above and to the right of the main-sequence (MS) turnoff (TO) are the same as those classified earlier with the aberrated HST, but the rest below it are new objects seen now for the first time thanks to the substantial improvement in sensitivity. The new objects form a well-defined main sequence whose luminosity function (LF) turns over dramatically at m(sub 346) approximately equal to 19 well before the completeness limit and well before the end of the slowly increasing luminosity function for the outer fields measured from the ground by Hesser et al. We interpret this premature drop in the number of stars below approximately 0.8 solar masses in the core as the effect of mass segregation due to two-body relaxation. The position of nine objects in the range 20 less than m(sub 346) less than 24 and -1.5 less than m(sub 253) - m(sub 346) less than 0 is consistent with the expected location of a approx. a half solar mass white dwarf cooling sequence and luminosity function.

Paresce, Francesco↗

Numerical Propulsion System Simulation: An Overview

The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive and time consuming. One of the main contributors to the high cost and lengthy time is the need to perform many large-scale hardware tests and the inability to integrate all appropriate subsystems early in the design process. The NASA Glenn Research Center is developing the technologies required to enable simulations of full aerospace propulsion systems in sufficient detail to resolve critical design issues early in the design process before hardware is built. This concept, called the Numerical Propulsion System Simulation (NPSS), is focused on the integration of multiple disciplines such as aerodynamics, structures and heat transfer with computing and communication technologies to capture complex physical processes in a timely and cost-effective manner. The vision for NPSS, as illustrated, is to be a "numerical test cell" that enables full engine simulation overnight on cost-effective computing platforms. There are several key elements within NPSS that are required to achieve this capability: 1) clear data interfaces through the development and/or use of data exchange standards, 2) modular and flexible program construction through the use of object-oriented programming, 3) integrated multiple fidelity analysis (zooming) techniques that capture the appropriate physics at the appropriate fidelity for the engine systems, 4) multidisciplinary coupling techniques and finally 5) high performance parallel and distributed computing. The current state of development in these five area focuses on air breathing gas turbine engines and is reported in this paper. However, many of the technologies are generic and can be readily applied to rocket based systems and combined cycles currently being considered for low-cost access-to-space applications. Recent accomplishments include: (1) the development of an industry-standard engine cycle analysis program and plug 'n play architecture, called NPSS Version 1, (2) A full engine simulation that combines a 3D low-pressure subsystem with a 0D high pressure core simulation. This demonstrates the ability to integrate analyses at different levels of detail and to aerodynamically couple components, the fan/booster and low-pressure turbine, through a 3D computational fluid dynamics simulation. (3) Simulation of all of the turbomachinery in a modern turbofan engine on parallel computing platform for rapid and cost-effective execution. This capability can also be used to generate full compressor map, requiring both design and off-design simulation. (4) Three levels of coupling characterize the multidisciplinary analysis under NPSS: loosely coupled, process coupled and tightly coupled. The loosely coupled and process coupled approaches require a common geometry definition to link CAD to analysis tools. The tightly coupled approach is currently validating the use of arbitrary Lagrangian/Eulerian formulation for rotating turbomachinery. The validation includes both centrifugal and axial compression systems. The results of the validation will be reported in the paper. (5) The demonstration of significant computing cost/performance reduction for turbine engine applications using PC clusters. The NPSS Project is supported under the NASA High Performance Computing and Communications Program.

Lytle, John K.↗

GNN-based end-to-end reconstruction in the CMS Phase 2 High-Granularity Calorimeter

We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Neural Networks (GNNs) and directly analyzes the hits in each HGCAL endcap. The ML algorithm is trained to predict clusters of hits originating from the same incident particle by labeling the hits with the same cluster index. We impose simple criteria to assess whether the hits associated as a cluster by the prediction are matched to those hits resulting from any particular individual incident particles. The algorithm is studied by simulating two tau leptons in each of the two HGCAL endcaps, where each tau may decay according to its measured standard model branching probabilities. The simulation includes the material interaction of the tau decay products which may create additional particles incident upon the calorimeter. Using this varied multiparticle environment we can investigate the application of this reconstruction technique and begin to characterize energy containment and performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The crystal structure of Vibrio cholerae (6-4) photolyase reveals interactions with cofactors and a DNA-binding region

Photolyases (PLs) reverse UV-induced DNA damage using blue light as an energy source. Of these PLs, (6-4) PLs repair (6-4)-lesioned photoproducts. We recently identified a gene from Vibrio cholerae (Vc) encoding a (6-4) PL, but structural characterization is needed to elucidate specific interactions with the chromophore cofactors. Here, we determined the crystal structure of Vc (6-4) PL at 2.5 Å resolution. Our high-resolution structure revealed that the two well-known cofactors, flavin adenine dinucleotide and the photoantenna 6,7-dimethyl 8-ribityl-lumazin (DMRL), stably interact with an α-helical and an α/β domain, respectively. Additionally, the structure has a third cofactor with distinct electron clouds corresponding to a [4Fe-4S] cluster. Moreover, we identified that Asp106 makes a hydrogen bond with water and DMRL, which indicates further stabilization of the photoantenna DMRL within Vc (6-4) PL. Further analysis of the Vc (6-4) PL structure revealed a possible region responsible for DNA binding. The region located between residues 478 to 484 may bind the lesioned DNA, with Arg483 potentially forming a salt bridge with DNA to stabilize further the interaction of Vc (6-4) PL with its substrate. Our comparative analysis revealed that the DNA lesion could not bind to the Vc (6-4) PL in a similar fashion to the Drosophila melanogaster (Dm, (6-4)) PL without a significant conformational change of the protein. The 23rd helix of the bacterial (6-4) PLs seems to have remarkable plasticity, and conformational changes facilitate DNA binding. In conclusion, our structure provides further insight into DNA repair by a (6-4) PL containing three cofactors.

(6-4) lesioned photoproduct↗

Secondary Ion Mass Spectroscopy

Secondary Ion mass Spectroscopy (SIMS), as the name suggests, involves characterizing metallic and other materials trough the spectroscopic analysis of secondary ions emanating from the surface of the material to be characterized by the impact of the high energy primary ions. The primary ion source including the choice of its gun, voltage and current can be selected and used depending on the purpose of the analysis. In most instruments more than one primary ion gun is lined up to the sample stage and can be activated with selected accelerating parameters (voltage and beam intensity). The impingement of primary ions on to the sample surface generates positive, negative or neutral ions, electrons, atoms and atomic clusters. Majority of these sample fragments being neutral, could not be utilized as such fragments cannot be manipulated through the use of electromagnetic or electrostatic lenses. Secondary ions that are positively or negatively charged possess large variation in velocity, charge, and mass. These ionic fragments eventually travel through a system of several lenses in very high vacuum to reach detector/counter. Relative amounts of alloying elements or impurities in an alloy can be calculated from the counts of related ions accumulated in the detector/counter.

Panda, Binayak↗

Computational Inference of Vibratory System with Incomplete Modal Information Using Parallel, Interactive and Adaptive Markov Chains

Inverse analysis of vibratory system is an important subject in fault identification, model updating, and robust design and control. It is challenging subject because 1) the problem is oftentimes underdetermined while the measurements are limited and/or incomplete; 2) many combinations of parameters may yield results that are similar with respect to actual response measurements; and 3) uncertainties inevitably exist. The aim of this research is to leverage upon computational intelligence through statistical inference to facilitate an enhanced, probabilistic framework using incomplete modal response measurement. This new framework is built upon efficient inverse identification through optimization, whereas Bayesian inference is employed to account for the effect of uncertainties. To overcome the computational cost barrier, we adopt Markov chain Monte Carlo (MCMC) to characterize the target function/distribution. Instead of using single Markov chain in conventional Bayesian approach, we develop a new sampling theory with multiple parallel, interactive and adaptive Markov chains and incorporate it into Bayesian inference. This can harness the collective power of these Markov chains to realize the concurrent search of multiple local optima. The number of required Markov chains and their respective initial model parameters are automatically determined via Monte Carlo simulation-based sample pre-screening followed by K-means clustering analysis. These enhancements can effectively address the aforementioned challenges in finite element inverse analysis. The validity of this framework is systematically demonstrated through case studies.

K Zhou↗

Surface heterogeneity propagation and homogenization for pouch cell-scale Li metal anodes

Li metal anode is a promising candidate for next-generation energy storage systems and is widely explored in Li-ion and solid-state batteries. Despite its potential, Li metal anodes face instabilities during long-term cycling, especially when paired with NMC or sulfur-based cathodes, where Li is cycled at high capacities of 6-8 mAh/cm2, equivalent to a thickness of 30-40 µm. During such extensive utilization, degradation mechanisms such as excessive solid electrolyte interphase (SEI), dendrites, and dead Li emerge, and ultimately lead to sudden failure and reduced cycle life. The origin of the degradation mechanisms stem from surface heterogeneities introduced during Li foil manufacturing and storage [1, 2]. As cycling progresses, the local heterogeneities propagate, resulting in uneven Li utilization and degradation-prone regions across the electrode [3], which consequently induce performance variations at the cell level. This heterogeneity propagation is particularly pronounced in large-format pouch cells in practical applications, where the surface effects are magnified. Without a clear understanding of the multi-scale heterogeneities and the development of surface homogenization methods, the performance consistency will be compromised, hindering the commercialization of Li metal batteries. In this presentation, we investigate the evolution of surface heterogeneity propagation on commercially available Li foils. We discover that inhomogeneous Li utilization appears as early as the first half-cycle of formation, manifesting as localized clusters and pits. In pouch cell configurations, these features exhibit areal density variations across the electrode on a scale of millimeters. To improve Li utilization homogeneity, a scalable mechanical brushing method is introduced to remove the chemically heterogeneous surface passivation layer. Furtherore, the influence of utilization homogeneity on cell-to-cell consistency is evaluated using 32 Li-NMC811 pouch cells divided into as-received and brushed Li groups. On the brushed Li, clusters and pits are no longer observable, and the cells exhibit significantly improved consistency in discharge capacity trajectories and cycle lifetime. Overall, this study highlights the role of Li surface utilization homogeneity on long-term cycling performance. Our research provides a pathway for improving large-area electrode uniformity and establishing evaluation methods for cell-to-cell consistency, both are key steps toward the commercialization of Li metal batteries and beyond. [1] Otto, Svenja-K., et al. "In-depth characterization of lithium-metal surfaces with XPS and ToF-SIMS: toward better understanding of the passivation layer." Chemistry of Materials 33.3 (2021): 859-867. [2] Hatzell, Kelsey, et al. "Aligning lithium metal battery research and development across academia and industry." Joule (2024). [3] Kim, Sangwook, et al. "Calendar life of lithium metal batteries: Accelerated aging and failure analysis." Energy Storage Materials 65 (2024): 103147.

25 - ENERGY STORAGE↗

Understanding drivers of oil and gas well integrity issues in the greater wattenberg area of Colorado

Well integrity is critically important to maintain to minimize the environmental impacts of oil and gas development and other subsurface energy operations. The Wattenberg Field of Colorado—a top producing field with >40,000 wells—has one of the most robust publicly reported well integrity programs in the country. Here, in this study, we analyzed annular pressure and annular-fluid geochemical test results collected from Wattenberg wells through the end of 2019 to characterize the frequency and spatial variability of integrity issues in the field and understand their drivers. Estimated frequencies of integrity issues among tested wells were 8.2-17.1% between 1955 and 2019 and 6.1-11.4% in 2019 alone. The frequency of integrity issues was nearly four times greater in wells located above the Longmont Wrench Fault Zone. Potential drivers of integrity issues were identified using ensemble decision tree models trained with a broad set of relevant information. Models show that well integrity issues are spatially clustered on regional and sub-regional scales and suggest the relatively high frequency of integrity issues observed is likely attributed to geologic factors. These findings are valuable for regulatory agencies and operators seeking to inform well integrity monitoring, plugging, and emissions reduction efforts and design future subsurface energy projects.

03 NATURAL GAS↗

Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach

Understanding the genetic relationships between human disorders could lead to better treatment and prevention strategies, especially for individuals with multiple comorbidities. A common resource for studying genetic-disease relationships is the GWAS Catalog, a large and well curated repository of SNP-trait associations from various studies and populations. Some of these populations are contained within mega-biobanks such as the Million Veteran Program (MVP), which has enabled the genetic classification of several diseases in a large well-characterized and heterogeneous population. Here we aim to provide a network of the genetic relationships among diseases and to demonstrate the utility of quantifying the extent to which a given resource such as MVP has contributed to the discovery of such relations. We use a network-based approach to evaluate shared variants among thousands of traits in the GWAS Catalog repository. Our results indicate many more novel disease relationships that did not exist in early studies and demonstrate that the network can reveal clusters of diseases mechanistically related. Finally, we show novel disease connections that emerge when MVP data is included, highlighting methodology that can be used to indicate the contributions of a given biobank.

59 BASIC BIOLOGICAL SCIENCES↗

Precise relative magnitude measurement improves fracture characterization during hydraulic fracturing

SUMMARY Microseismic monitoring is an important technique to obtain detailed knowledge of in-situ fracture size and orientation during stimulation to maximize fluid flow throughout the rock volume and optimize production. Furthermore, considering that the frequency of earthquake magnitudes empirically follows a power law (i.e. Gutenberg–Richter), the accuracy of microseismic event magnitude distributions is potentially crucial for seismic risk management. In this study, we analyse microseismicity observed during four hydraulic fracture treatments of the legacy Cotton Valley experiment in 1997 at the Carthage gas field of East Texas, where fractures were activated at the base of the sand-shale Upper Cotton Valley formation. We perform waveform cross-correlation to detect similar event clusters, measure relative amplitude from aligned waveform pairs with a principal component analysis, then measure precise relative magnitudes. The new magnitudes significantly reduce the deviations between magnitude differences and relative amplitudes of event pairs. This subsequently reduces the magnitude differences between clusters located at different depths. Reduction in magnitude differences between clusters suggests that some attenuation-related biases could be effectively mitigated with relative magnitude measurements. The maximum likelihood method is applied to understand the magnitude frequency distributions and quantify the seismogenic index of the clusters. Statistical analyses with new magnitudes suggest that fractures that are more favourably oriented for shear failure have lower b-value and higher seismogenic index, suggesting higher potential for relatively larger earthquakes, rather than fractures subparallel to maximum horizontal principal stress orientation.

58 GEOSCIENCES↗

Utilization of lasso peptides for biodegradation of polycyclic aromatic hydrocarbons

Abstract Many microbial genes involved in degrading recalcitrant environmental contaminants such as polycyclic aromatic hydrocarbons (PAHs) have been identified and characterized. However, all molecular mechanisms required for PAH utilization have not yet been elucidated. In this work, we demonstrate the proposed involvement of lasso peptides in the utilization of the PAH phenanthrene in Sphingomonas BPH. Transpositional mutagenesis of Sphingomonas BPH with the miniTn5 transposon yielded 3 phenanthrene utilization deficient mutants, #257, #1778, and #1782. In mutant #1782, Tn5 had inserted into the large subunit of the naph/bph dioxygenase gene. In mutant #1778, Tn5 had inserted into the B2 protease gene of a lasso peptide cluster. This finding is the first report on the role of lasso peptides in PAH utilization. Our studies also demonstrate that interruption of the lasso peptide cluster resulted in a significant increase in the amount of biosurfactant produced in the presence of glucose when compared to the wild‐type strain. Collectively, these results suggest that the mechanisms Sphingomonas BPH utilizes to degrade phenanthrene are far more complex than previously understood and that the #1778 mutant may be a good candidate for bioremediation when glucose is applied as an amendment due to its higher biosurfactant production.

59 BASIC BIOLOGICAL SCIENCES↗