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At least 631 records · Page 35

Bulk Glassy GeTe 2 : A Missing Member of the Tetrahedral GeX 2 Family and a Precursor for the Next Generation of Phase-Change Materials

Vitreous germanium disulfide GeS 2 and diselenide GeSe 2 belong to canonical chalcogenide glasses extensively studied over the past half century. Their high-temperature orthorhombic polymorphs are congruently melting compounds, and the tetrahedral crystal and glass structure is largely preserved in the melt. In contrast, the ditelluride counterpart is absent in the Ge-Te phase diagram, which shows only a single compound, monotelluride GeTe. Phase-change materials based on GeTe have become a technologically important class of solids, and their structure and properties are also widely studied. Surprisingly, very scarce information is available for alloys having GeTe 2 stoichiometry. Using a fast quenching procedure in silica capillaries, high-energy X-ray diffraction, and Raman spectroscopy supported by first-principles simulations, we show that bulk glassy GeTe 2 differs substantially from the lighter GeX 2 members, revealing 46% of trigonal germanium, 31% of three-fold coordinated tellurium, and only 20% of edge-sharing tetrahedra or pyramids. The fraction of homopolar Ge-Ge bonds is low; however, the population of dominant Te-Te dimers and Te n oligomers, n <= 10, appears to be significant. The complex structural and chemical topology of g-GeTe 2 is directly related to the thermodynamic metastability of germanium ditelluride, schematically represented by the following reaction: GeTe 2 $\rightleftarrows$ GeTe + Te. Disproportionation is complete above liquidus in the temperature range of semiconductor-metal transition, and the dense metallic GeTe 2 liquid, mostly consisting of five-fold coordinated Ge species, exhibits high fluidity, strong fragility (m = 99 ± 5), and presumably a fast structural transformation rate combined with low atomic mobility in the vicinity of the glass transition temperature, favorable for reliable long-term data retention in nonvolatile memories. The observed and predicted characteristic features make GeTe 2 a promising precursor for the next generation of phase-change materials, especially coupled with additional metal doping, depolymerizing the tetrahedral interconnected glass network and accelerating (sub)nanosecond crystallization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A general cratering-history model and its implications for the lunar highlands

Through analysis of a large number of Monte Carlo and Markov Chain simulations, a model for determining crater accumulation and crater obliteration histories has been derived. The model generally applies to populations of large craters. It predicts that the following relationships hold for subequilibrium-density crater populations: (1) the more negative the production function's exponent, alpha (N near D super alpha) the lower the crater density at which the population size-frequency distribution will significantly depart from its production function; (2) the more negative the production function's exponent, the less obliteration a crater population will sustain after a set number of impacts. Application of the model to the lunar highlands implies (1) the production function for the large craters is highly structured, resembling the observed size-frequency distribution and not the function N near D to the -2; (2) even the densely cratered highlands have not attained crater saturation or equilibrium. Direct simulations of the highlands' crater population supports the model's implications.

Woronow, A.↗

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology

Abstract The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum . The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

59 BASIC BIOLOGICAL SCIENCES↗

Monovalent ion–graphene oxide interactions are controlled by carboxylic acid groups: Sum frequency generation spectroscopy studies

Graphene oxide (GO) is a two-dimensional, mechanically strong, and chemically tunable material for separations. Elucidating GO–ion–water interactions at the molecular scale is highly important for predictive understanding of separation systems. However, direct observations of the nanometer region by GO surfaces under operando conditions are not trivial. Therefore, thin films of GO at the air/water interface can be used as model systems. With this approach, we study the effects of alkali metal ions on water organization near graphene oxide films at the air/water interface using vibrational sum frequency generation (SFG) spectroscopy. Here, we also use an arachidic acid Langmuir monolayer as a benchmark for a pure carboxylic acid surface. Theoretical modeling of the concentration-dependent sum frequency signal from graphene oxide and arachidic acid surfaces reveals that the adsorption of monovalent ions is mainly controlled by the carboxylic acid groups on graphene oxide. An in-depth analysis of sum frequency spectra reveals at least three distinct water populations with different hydrogen bonding strengths. The origin of each population can be identified from concentration dependent variations of their SFG signal. Interestingly, an interfacial water structure seemed mostly insensitive to the character of the alkali cation, in contrast to similar studies conducted at the silica/water interface. However, we observed an ion-specific effect with lithium, whose strong hydration prevented direct interactions with the graphene oxide film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optically induced changes in the band structure of the Weyl charge-density-wave compound (TaSe 4 ) 2 I

Collective modes are responsible for the emergence of novel quantum phases in topological materials. In the quasi-one dimensional (1D) Weyl semimetal (TaSe 4 ) 2 I , a charge density wave (CDW) opens band gaps at the Weyl points, thus turning the system into an axionic insulator. Melting the CDW would restore the Weyl phase, but 1D fluctuations extend the gapped regime far above the 3D transition temperature (T CDW = 263 K), thus preventing the investigation of this topological phase transition with conventional spectroscopic methods. Here we use a non-equilibrium approach: we perturb the CDW phase by photoexcitation, and we monitor the dynamical evolution of the band structure by time- and angle-resolved photoelectron spectroscopy. We find that, upon optical excitation, electrons populate the linearly dispersing states at the Fermi level (E F ), and fill the CDW gap. The dynamics of both the charge carrier population and the band gap renormalization (BGR) show a fast component with a characteristic time scale of a few hundreds femtoseconds. However, the BGR also exhibits a second slow component on the µs time scale. The combination of an ultrafast response and of persistent changes in the spectral weight at E$_\mathrm{F}$, and the resulting sensitivity of the linearly dispersing states to optical excitations, may explain the high performances of (TaSe 4 ) 2 I as a material for broadband infrared photodetectors.

36 MATERIALS SCIENCE↗

Spatiotemporal predictions of toxic urban plumes using deep learning

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic plumes by solving fluid dynamical equations. However, these models can be computationally expensive due to the need for many grid cells to simulate turbulent flow and resolve individual buildings and streets. In emergency response situations, alternative methods are needed that can run quickly and adequately capture important spatiotemporal features. Here, we present a novel deep learning model called ST-GasNet inspired by the mathematical equations that govern the behavior of plumes as they disperse through the atmosphere. ST-GasNet learns the spatiotemporal dependencies from a limited set of temporal sequences of ground-level toxic urban plumes generated by a high-resolution large eddy simulation model. On independent sequences, ST-GasNet accurately predicts the late-time spatiotemporal evolution, given the early-time behavior as an input, even when a building splits a large plume into smaller plumes. By incorporating large-scale wind boundary condition information, ST-GasNet achieves a prediction accuracy of at least 90% on test data for the entire prediction period.

Civil and Environmental Engineering↗

Scalable and Secure Power Outage Data Reporting: A Hexagonal Geospatial Approach

Power outages disrupt critical infrastructure and cause billions of dollars in economic losses annually in the United States. Accurate and granular outage reporting is vital for effective restoration and mitigation. This paper examines the integration of the Hexagonal Hierarchical Geospatial Indexing System (H3) to enhance power outage reporting, leveraging its uniform grid structure, scalable resolutions, and support for privacy-preserving analysis. Using high-resolution LandScan Global population data and K-anonymization techniques, this work achieves a balance between data granularity and privacy. Results show that lower privacy thresholds (e.g., K-anonymity = 2) enable higher resolution, while stricter thresholds (e.g., >15 people per hex) reduce granularity, potentially affecting localized responses. State-and county-level resolution case studies demonstrate H3’s adaptability and the trade-offs between precision and privacy. The proposed H3-based framework offers a scalable and efficient solution for geospatial data integration within the energy sector, such as outage data, aiding utilities and regulators in improving resilience and response efforts, particularly in disaster-prone regions.

Ahmad, Nasir [ORNL] (ORCID:0000000150677368)↗

Integrating Viral Metagenomics into an Ecological Framework

Viral metagenomics has expanded our knowledge of the ecology of uncultured viruses, within both environmental (e.g., terrestrial and aquatic) and host-associated (e.g., plants and animals, including humans) contexts. Here, we emphasize the implementation of an ecological framework in viral metagenomic studies to address questions in virology rarely considered ecological, which can change our perception of viruses and how they interact with their surroundings. Additionally, an ecological framework explicitly considers diverse variants of viruses in populations that make up communities of interacting viruses, with ecosystem-level effects. It provides a structure for the study of the diversity, distributions, dynamics, and interactions of viruses with one another, hosts, and the ecosystem, including interactions with abiotic factors. An ecological framework in viral metagenomics stands poised to broadly expand our knowledge in basic and applied virology. We highlight specific fundamental research needs to capitalize on its potential and advance the field.

59 BASIC BIOLOGICAL SCIENCES↗

Dwarf Galaxies at Cosmic Noon: New JWST Constraints on Satellite Models and Subhalo Tidal Evolution

The advent of JWST has revolutionized the study of faint satellite galaxies at z ≳ 1, enabling statistical constraints on galaxy evolution and the galaxy–halo connection in a previously unexplored mass and redshift regime. We compare satellite abundances at 1 < z < 3.5 from recent JWST observations with predictions from cosmological dark-matter-only zoom-in simulations. We identify and quantify several sources of biases that can impact theoretical satellite counts, finding that assumptions about subhalo tidal evolution introduce the largest uncertainty in predictions for the satellite mass function. Using a flexible galaxy disruption model, we explore a range of disruption scenarios, spanning hydrodynamically motivated and idealized prescriptions, to bracket plausible physical outcomes. We show that varying galaxy durability can change the predicted satellite mass functions by a factor of ∼3.5. The JWST data and our fiducial model are consistent within 1σ–2σ across the full redshift (1 < z < 3.5) and stellar mass (M⋆ > 10 7 M ⊙ ) range probed. We find evidence that subhalos are at least as long-lived as predicted by hydrodynamic simulations. Our framework will enable robust constraints on the tidal evolution of subhalos with future observations. This work presents the first direct comparison between cosmological models and observations of the high-redshift satellite population in this low-mass regime. These results showcase JWST’s emerging power to test structure formation in the first half of the Universe in a new domain and to constrain the physical processes driving the evolution of low-mass galaxies across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗

AlGaAs phased array laser for optical communications

Phased locked arrays of multiple AlGaAs diode laser emitters were investigated both in edge emitting and surface emitting configurations. CSP edge emitter structures, coupled by either evanescent waves or Y-guides, could not achieve the required powers (greater than or similar to 500 mW) while maintaining a diffraction limited, single lobed output beam. Indeed, although the diffraction limit was achieved in this type of device, it was at low powers and in the double lobed radiation pattern characteristic of out-of-phase coupling. Grating surface emitting (GSE) arrays were, therefore, investigated with more promising results. The incorporation of second order gratings in distribute Bragg reflector (DBR) structures allows surface emission, and can be configured to allow injection locking and lateral coupling to populate 2-D arrays that should be able to reach power levels commensurate with the needs of high performance, free space optical communications levels. Also, a new amplitude modulation scheme was developed for GSE array operation.

Carlson, N. W.↗

Far-infrared emission in the Rho Ophiuchi region - A comparison with molecular gas emission and visual extinction

The dust characteristics of a 40 arcmin x 40 arcmin section of the Rho Ophiuchi molecular clouds complex revealed by the IRAS satellite are compared with both molecular line and deep star count data for the region. The data reveal the cloud to be clearly visible at 12 and 25 microns, as well as at 60 and 100 microns. Modeling the infrared emission from the cloud as being due to two populations of dust grains, the short-wavelength emission is found not to reflect the internal structure of the molecular cloud. The 60 micron opacity determined using a single grain emission model correlates reasonably well with (C-13)O column density and visual extinction up to roughly 5 mag. The cloud edges appear to be heated by the interstellar radiation field. The far-infrared luminosity to mass ratio for the region is determined to be 0.9 solar luminosity/solar mass, a value much smaller than the average ratio for the inner Galaxy.

Jarrett, T. H.↗

Improved interpretation of satellite altimeter data using genetic algorithms

Genetic algorithms (GA) are optimization techniques that are based on the mechanics of evolution and natural selection. They take advantage of the power of cumulative selection, in which successive incremental improvements in a solution structure become the basis for continued development. A GA is an iterative procedure that maintains a 'population' of 'organisms' (candidate solutions). Through successive 'generations' (iterations) the population as a whole improves in simulation of Darwin's 'survival of the fittest'. GA's have been shown to be successful where noise significantly reduces the ability of other search techniques to work effectively. Satellite altimetry provides useful information about oceanographic phenomena. It provides rapid global coverage of the oceans and is not as severely hampered by cloud cover as infrared imagery. Despite these and other benefits, several factors lead to significant difficulty in interpretation. The GA approach to the improved interpretation of satellite data involves the representation of the ocean surface model as a string of parameters or coefficients from the model. The GA searches in parallel, a population of such representations (organisms) to obtain the individual that is best suited to 'survive', that is, the fittest as measured with respect to some 'fitness' function. The fittest organism is the one that best represents the ocean surface model with respect to the altimeter data.

Messa, Kenneth↗

The morphology of faint galaxies in Medium Deep Survey images using WFPC2

First results from Hubble Space Telescope (HST) Medium Deep Survey images taken with Wide Field/Planetary Camera-2 (WFPC2) demonstrate that galaxy classifications can be reliably performed to magnitudes I814 approximately less than 22.0 in the F815W band. Published spectroscopic surveys to this depth indicate a mean redshift of bar-z approximately 0.5. We have classified over 200 galaxies in nine WFPC2 fields according to a basic morphological scheme. The majority of these faint galaxies appear to be similar to regular Hubble-sequence examples observed at low redshift. To the precision of our classification scheme, the relative proportion of spheroidal and disk systems of normal appearance is as expected from nearby samples, indicating that the bulk of the local galaxy population was in place at half the Hubble time. However, the most intriguing result is the relatively high proportion (approximately 40%) of objects which are in some way anomalous, and which may be of relevance in understanding the origin of the familiar excess population of faint galaxies established by others. These diverse objects include apparently interacting pairs whose multiple structure is only revealed with HST's angular resolution, galaxies with superluminous star-forming regions, diffuse low surface brightness galaxies of various forms, and compact galaxies. These anomalous galaxies contribute a substantial fraction of the excess counts at our limiting magnitude, and may provide insights into the 'faint blue galaxy' problem.

Griffiths, R. E.↗

Automated spectral classification and the GAIA project

Two dimensional spectral types for each of the stars observed in the global astrometric interferometer for astrophysics (GAIA) mission would provide additional information for the galactic structure and stellar evolution studies, as well as helping in the identification of unusual objects and populations. The classification of the large quantity generated spectra requires that automated techniques are implemented. Approaches for the automatic classification are reviewed, and a metric-distance method is discussed. In tests, the metric-distance method produced spectral types with mean errors comparable to those of human classifiers working at similar resolution. Data and equipment requirements for an automated classification survey, are discussed. A program of auxiliary observations is proposed to yield spectral types and radial velocities for the GAIA-observed stars.

Lasala, Jerry↗

Developing a Business Intelligence Process for a Training Module in SharePoint 2010

Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.

Schmidtchen, Bryce↗