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Neurofilament protein is differentially distributed in subpopulations of corticocortical projection neurons in the macaque monkey visual pathways

Previous studies of the primate cerebral cortex have shown that neurofilament protein is present in pyramidal neuron subpopulations displaying specific regional and laminar distribution patterns. In order to characterize further the neurochemical phenotype of the neurons furnishing feedforward and feedback pathways in the visual cortex of the macaque monkey, we performed an analysis of the distribution of neurofilament protein in corticocortical projection neurons in areas V1, V2, V3, V3A, V4, and MT. Injections of the retrogradely transported dyes Fast Blue and Diamidino Yellow were placed within areas V4 and MT, or in areas V1 and V2, in 14 adult rhesus monkeys, and the brains of these animals were processed for immunohistochemistry with an antibody to nonphosphorylated epitopes of the medium and heavy molecular weight subunits of the neurofilament protein. Overall, there was a higher proportion of neurons projecting from areas V1, V2, V3, and V3A to area MT that were neurofilament protein-immunoreactive (57-100%), than to area V4 (25-36%). In contrast, feedback projections from areas MT, V4, and V3 exhibited a more consistent proportion of neurofilament protein-containing neurons (70-80%), regardless of their target areas (V1 or V2). In addition, the vast majority of feedback neurons projecting to areas V1 and V2 were located in layers V and VI in areas V4 and MT, while they were observed in both supragranular and infragranular layers in area V3. The laminar distribution of feedforward projecting neurons was heterogeneous. In area V1, Meynert and layer IVB cells were found to project to area MT, while neurons projecting to area V4 were particularly dense in layer III within the foveal representation. In area V2, almost all neurons projecting to areas MT or V4 were located in layer III, whereas they were found in both layers II-III and V-VI in areas V3 and V3A. These results suggest that neurofilament protein identifies particular subpopulations of corticocortically projecting neurons with distinct regional and laminar distribution in the monkey visual system. It is possible that the preferential distribution of neurofilament protein within feedforward connections to area MT and all feedback projections is related to other distinctive properties of these corticocortical projection neurons.

Non-NASA Center↗

The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates (CRADA Final Report)

Catalytic fast pyrolysis (CFP) is a versatile technology platform to convert biomass into fungible hydrocarbon transportation fuels and chemical co-products. Key technical barriers to reaching this goal include increasing the product yields and achieving the desired fuel properties for gasoline, diesel, and jet range fuels or blendstocks that would be suitable for introduction into existing refinery unit operations. Overcoming these barriers will require durable catalysts that are effective at upgrading and stabilizing biomass pyrolysis vapors. Towards these goals, this CRADA leveraged NREL experience as a leader in biomass pyrolysis research and Johnson Matthey's (JM) experience as a leader in the production of advanced catalytic materials. The scope spanned CFP catalyst development, characterization, multi-scale reaction testing, and computational modeling. CRADA benefits to DOE, Participant, and U.S. Taxpayer: Assists laboratory in achieving programmatic scope, Uses the laboratory’s core competencies. The purpose of this CRADA was to develop and deploy catalysts for biomass CFP to help achieve cost-competitive biofuels and bio-based products. This was accomplished through a close collaboration between biomass conversion researchers at NREL and catalyst development researchers at JM. Summary of Research Results: Focus Area 1. Foundational research on catalytic conversion and deactivation: Key interactions between pyrolysis vapors and heterogeneous catalysts were probed through catalyst characterization, model compound reaction testing, and atomistic-scale computational modeling. Catalyst development focused on multifunctional materials, which include zeolites, oxides, carbides, and nitrides. Computational modeling identified reaction mechanisms and elucidated surface chemistry to test hypotheses regarding mechanisms of deoxygenation, coupling, cracking, dehydration, coke formation, hydrogen transfer, and aromatic ring reactions. This information was used to design multifunctional catalysts to increase product yields, control product selectivity, and reduce deactivation during CFP and downstream processing steps. The results served to increase fundamental understanding of key catalyst attributes and durability features for the upgrading of biomass pyrolysis vapors. Model compound experiments confirmed the importance of metal-acid bifunctionality for the deoxygenation of lignin-derived phenolic species under hydrodeoxygenation conditions. This insight led to the development of catalysts such as Pt/TiO2 and Mo2C, which were confirmed as high-performing materials during subsequent bench-scale experiments using biomass-derived pyrolysis vapors. This focus area also led to the identification of important catalyst deactivation mechanisms associated with the deposition of inorganic contaminants such as potassium. The molecular-level insight from model compound experiments and computational modeling, shown in Figure 1, informed the development of regeneration procedures that have been shown to be effective for restoration of > 90% of initial catalyst activity. This understanding has subsequently been translated to other catalyst systems, including zeolite materials that can be operated without requirements for co-fed hydrogen.

09 BIOMASS FUELS↗

Portable, heterogeneous ensemble workflows at scale using libEnsemble

libEnsemble is a Python-based toolkit for running dynamic ensembles, developed as part of the DOE Exascale Computing Project. The toolkit utilizes a unique generator–simulator–allocator paradigm, where generators produce input for simulators, simulators evaluate those inputs, and allocators decide whether and when a simulator or generator should be called. The generator steers the ensemble based on simulation results. Generators may, for example, apply methods for numerical optimization, machine learning, or statistical calibration. libEnsemble communicates between a manager and workers. Flexibility is provided through multiple manager–worker communication substrates each of which has different benefits. These include Python’s multiprocessing, mpi4py, and TCP. Multisite ensembles are supported using Balsam or Globus Compute. We overview the unique characteristics of libEnsemble as well as current and potential interoperability with other packages in the workflow ecosystem. We highlight libEnsemble’s dynamic resource features: libEnsemble can detect system resources, such as available nodes, cores, and GPUs, and assign these in a portable way. These features allow users to specify the number of processors and GPUs required for each simulation; and resources will be automatically assigned on a wide range of systems, including Frontier, Aurora, and Perlmutter. Such ensembles can include multiple simulation types, some using GPUs and others using only CPUs, sharing nodes for maximum efficiency. We also describe the benefits of libEnsemble’s generator–simulator coupling, which easily exposes to the user the ability to cancel, and portably kill, running simulations based on models that are updated with intermediate simulation output. We demonstrate libEnsemble’s capabilities, scalability, and scientific impact via a Gaussian process surrogate training problem for the longitudinal density profile at the exit of a plasma accelerator stage. In conclusion, the study uses gpCAM for the surrogate model and employs either Wake-T or WarpX simulations, highlighting efficient use of resources that can easily extend to exascale.

Dynamic ensembles↗

Chlorine Isotopic Compositions of Apatite in Apollo 14 Rocks: Evidence for Widespread Vapor-Phase Metasomatism on the Lunar Nearside ~4 Billion Years Ago

Compared to most other planetary materials in the Solar System, some lunar rocks display high delta (sup 37) Cl signatures. Loss of Cl in a H<<Cl environment has been invoked to explain the heavy signatures observed in lunar samples, either during volcanic eruptions onto the lunar surface or during large scale degassing of the lunar magma ocean. To explore the conditions under which Cl isotope fractionation occurred in lunar basaltic melts, five Apollo 14 crystalline samples were selected (14053,19, 14072,13, 14073,9, 14310,171 along with basaltic clast 14321,1482) for in situ analysis of Cl isotopes using secondary ion mass spectrometry. Cl isotopes were measured within the mineral apatite, with delta (sup 37) Cl values ranging from +14.6 ± 1.6 per mille to +40.0 ± 2.9 per mille. These values expand the range previously reported for apatite in lunar rocks, and include some of the heaviest Cl isotope compositions measured in lunar samples to date. The data here do not display a trend between increasing rare earth elements contents and delta (sup 37) Cl values, reported in previous studies. Other processes that can explain the wide inter- and intra-sample variability of delta (sup 37) Cl values are explored. Magmatic degassing is suggested to have potentially played a role in fractionating Cl isotope in these samples. Degassing alone, however, could not create the wide variability in isotopic signatures. Our favored hypothesis, to explain small scale heterogeneity, is late-stage interaction with a volatile-rich gas phase, originating from devolatilization of lunar surface regolith rocks ~4 billion years ago. This period coincides with vapor-induced metasomastism recorded in other lunar samples collected at the Apollo 16 and 17 landing sites, pointing to the possibility of widespread volatile-induced metasomatism on the lunar nearside at that time, potentially attributed to the Imbrium formation event.

apatit↗

Developing Information Power Grid Based Algorithms and Software

This was an exploratory study to enhance our understanding of problems involved in developing large scale applications in a heterogeneous distributed environment. It is likely that the large scale applications of the future will be built by coupling specialized computational modules together. For example, efforts now exist to couple ocean and atmospheric prediction codes to simulate a more complete climate system. These two applications differ in many respects. They have different grids, the data is in different unit systems and the algorithms for inte,-rating in time are different. In addition the code for each application is likely to have been developed on different architectures and tend to have poor performance when run on an architecture for which the code was not designed, if it runs at all. Architectural differences may also induce differences in data representation which effect precision and convergence criteria as well as data transfer issues. In order to couple such dissimilar codes some form of translation must be present. This translation should be able to handle interpolation from one grid to another as well as construction of the correct data field in the correct units from available data. Even if a code is to be developed from scratch, a modular approach will likely be followed in that standard scientific packages will be used to do the more mundane tasks such as linear algebra or Fourier transform operations. This approach allows the developers to concentrate on their science rather than becoming experts in linear algebra or signal processing. Problems associated with this development approach include difficulties associated with data extraction and translation from one module to another, module performance on different nodal architectures, and others. In addition to these data and software issues there exists operational issues such as platform stability and resource management.

Dongarra, Jack↗

Structure–property relations of binary ferrite melts

Molten ferrite systems are used in the smelting and refining processes in steelmaking, to reduce the loss of metals in slags and to accelerate reaction rates. Here, high-energy x-ray diffraction experiments have been performed on aerodynamically levitated molten spheres of 43BaO–57FeO X and 43SrO–57FeO X at 1873 K using laser beam heating. The composition was varied within the range of x = 1–1.5 by changing the oxygen partial pressure of the levitation gas. The corresponding x-ray pair distribution functions have been interpreted using empirical potential structure refinement (EPSR) modeling. In oxygen-rich melts (x = 1.5), our EPSR models indicate very similar structures for the different alkaline-earth liquids, with both the Ba–O and Sr–O coordination numbers to be ∼8.4 and the total Fe–O coordination numbers ∼5.7. However, our models show that in reducing environments, the Fe 3+ and Fe 2+ ions exhibit very different behaviors in the Ba- and Sr-ferrite liquids. In the Ba-ferrite melt, the Fe 3+ –O coordination number decreases from 5.7 (at x = 1.5) to 5.2 (at x = 1.07), whereas Fe 2+ –O remains constant at ∼5.0 across the same compositional range. In the Sr melts, both the Fe 2+ –O and Fe 3+ –O coordination numbers rise from ∼5.7 (at x = 1.5) to 6.3 (at x = 1.07). All models show the structures to be heterogeneous with intertwined nanometer sized clusters or channels of Ba/Sr–O and Fe–O polyhedra that grow as oxygen content is reduced. Changes in the viscosity and electrical properties are interpreted in terms of the number of bridging and non-bridging oxygens associated with FeO 4 tetrahedra and concentration of charge carriers, respectively.

Benmore, Chris J. [Argonne National Laboratory (AN↗

Systematic Relationships Between Lidar Observables and Sizes And Mineral Composition Of Dust Aerosols

The physical and chemical properties of soil dust aerosol particles fundamentally affect their interaction with climate, including shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, heterogeneous formation of sulfates and nitrates on the surface of dust particles, and atmospheric processing of iron into bioavailable forms that increase the productivity of marine phytoplankton. Lidar measurements, such as extinction-to-backscatter, color and depolarization ratios, are frequently used to distinguish between aerosol types with different physical and chemical properties. The chemical composition of aerosol particles determines their complex refractive index, hence affecting their backscattering properties. Here we present a study on how dust aerosol backscattering and depolarization properties at wavelengths of 355, 532 and 1064 nm are related to size and complex refractive index, which varies with the mineral composition of the dust. Dust aerosols are represented by collections of spheroids with a range of prolate and oblate aspect ratios and their optical properties are obtained using T-matrix calculations. We find simple, systematic relationships between lidar observables and the dust size and complex refractive index that may aid the use of space-based or airborne lidars for direct retrieval of dust properties or for the evaluation of chemical transport models using forward simulated lidar variables. In addition, we present first results on the spatial variation of forward-simulated lidar variables based on a dust model that accounts for the atmospheric cycle of eight different mineral types plus internal mixtures of seven mineral types with iron oxides, which was recently implemented in the NASA GISS Earth System ModelE2.

Dust↗

Chemical Reactivity of In-Situ Lunar Dust for Biotoxicity Assessment

Introduction: How does the chemical reactivity of in-situ lunar dust compare to Apollo samples currently stored in curation facilities here on Earth? Essential investigations of this question will help us to further mitigate exploration risks for future human explorers on the Moon and will also provide critical information for astrobiologists and space biologists using the Moon for scientific inquiry. Discussion: Apollo 14 dust biotoxicity studies, carried out by the NASA Lunar Airborne Dust Toxici-ty Assessment Group (LADTAG), included numerous physiochemical studies[1] and cellular and animal ex-periments. Intratracheal instillation [2] and inhalation studies [3] in rats both showed Apollo 14 dust to be intermediate in toxicity compared to low-tox titanium dusts and high-tox quartz dusts of similar particle siz-es. The collective results were used in models [4] to establish a safe exposure limit for astronauts [5]. Alt-hough LADTAG took extensive steps to preserve what chemical reactivity may still have existed in the sam-ples, it is simply unknown if they possessed true in-situ chemical reactivity or if that reactivity has de-cayed. Initial gas loss on collection and other altera-tions, and even intermittent exposure to Earth-normal conditions during subsequent decades of handling, obscure a forensic reconstruction of the initial state. Because a mineral dust’s chemical reactivity influ-ences its biotoxicity [6], researchers have developed methods to “activate” lunar dust and simulants [7][8]. Past studies that modeled impact processes and radia-tion [9] in the lunar environment suggest that in-situ lunar dust is likely to be more chemically reactive than Earth-exposed samples. Because of these results, in-situ measurements are warranted [10]. Other studies have examined the hydroxyl generating capability of iron bearing mineral phases [11][12] and further em-phasize the role iron plays in chemical reactivity of lunar material, as well as decay of chemical reactivity in mineral dusts [12]. Recent observations of the lunar surface reveal the presence of hematite [13], a finding that further supports the hypothesis that in-situ lunar dust is reactive. Since the lunar surface is heterogene-ous, dust biotoxicity is expected to vary from site to site [14] due to particle size, mineralogy, physical characteristics, degree of space weathering, and chemi-cal reactivity (Figure 1). This circumstance dictates dust assessments at a suite of lunar sites enabled by upcoming NASA and commercial lunar payload ser-vices (CLPS) opportunities. Dose, location, and dura-tion of particle exposure will also affect biological responses. In-situ chemical reactivity measurements can inform cross-cutting collaborative research cam-paigns such as astrobiology studies examining regolith interactions with organisms and its ability to preserve chemical and structural biomarkers, as well as space biology investigations that examine regolith-microbe interactions relating to life support systems, plant growth, biomining, and development of regolith bio-composites. Figure 1: Environment conditions on the lunar surface that may alter regolith reactivity. Summary A series of in-situ measurements of lu-nar dust free radical chemistry at future Artemis and CLPS landing sites, combined with LADTAG-like studies of freshly collected lunar dust specimens, will reveal the true chemical reactivity of in-situ lunar dust and generate scientific data that can be compared to the chemical reactivity and biotoxicity of samples from Apollo landing sites. Furthermore, results from in situ measurements and biotoxicity studies of freshly col-lected specimens can also be used to validate, or re-quire revision of, the current astronaut permissible exposure limit [15]. References: [1] McKay D et al (2015), Acta As-tronaut 107:163–176. [2] Rask J et al (2013), LPSC, p 3062. [3] Lam CW et al (2013), Inhal Toxicol 25:661–678. [4] James JT, et. al. (2013) , Inhal Toxicol 25:243–256. [5] Scully RR, et.al. (2013), Inhal Toxi-col 25:785–793. [6] Porter, D. W., et.al., (2002), Tox-icology 175, 63–71. [7] Wallace WT, et.al., (2009), Meteorit Planet Sci 44:961–970. [8] Wallace WT, et.al., (2010), Earth Planet Sci Lett 295:571–577. [9] Loftus D, Rask J, et.al., (2010), Earth Moon Planet 107:95–105. [10] Rask J, et.al., (2009) LEAG p 57. [11] Turci F, et.a., (2015), Astrobiology. 2015;15(5):371-380. [12] Hendrix DA, et.al., (2019), Geohealth. 2019;3(1):28-42. [13] Li, S., et.al., (2020), Science advances, 6(36), p.eaba1940. [14] Rask J. (2018), In: Cudnik B. (eds) Encyclopedia of Lunar Science. Springer, Cham. [15] Rask, J, (2020), LPI, Artemis III Sci. def. paper 2120.

chemical reactivity↗

Verification and Validation of Elastodynamic Simulation Software for Aerospace Research

Physics-based simulation of nondestructive evaluation (NDE) inspection can help to advance the inspectability and reliability of mechanical systems. However, NDE simulations applicable to non-idealized mechanical components often require large compute domains and long run times. This has prompted development of custom NDE simulation software tailored to high performance computing (HPC) hardware. Verification and validation (V&V) is an integral part of developing this software to ensure implementations are robust and applicable to inspection problems, producing tools and simulations suitable for computational NDE research. This presentation addresses factors common to V&V of several elastodynamic simulation codes applicable to ultrasonic NDE. Examples are drawn from in-house simulation software at NASA Langley Research Center, ranging from ensuring reliability in a 1D heterogeneous media wave equation solver to the V&V needs of 3D cluster-parallel elastodynamic software. Factors specific to a research environment are addressed, where individual simulation results can be as relevant as the software product itself. Distinct facets of V&V are discussed including testing to establish software reliability, employing systematic approaches for consistency with fundamental conservation laws, establishing the numerical stability of algorithms, and demonstrating concurrence with empirical data. This talk also addresses V&V practices for small groups of researchers. This includes establishing resources (e.g. time and personnel) for V&V during project planning to mitigate and control the risk of setbacks. Similarly, we identify ways for individual researchers to use V&V during simulation software development itself to both speed up the development process and reduce incurred technical debt.

NDE↗

Tussock tundra surface temperatures, ambient air and incoming photosynthetically active radiation measured at the NGEE Arctic Council site, 2021 - 2023

This dataset contains temperature measurements carried out along two fiber optics cables/lines (150 m each) laid out along the ground at the Next Generation Ecosystem Experiment (NGEE) Arctic site near Council, Alaska. The lines traverse an heterogeneous part of the tussock tundra site including thermokarst features and lichen dominated sections of the tundra. Measurements were done using a Sensornet Oryx DTS, a Distributed Temperature sensor that was installed in September 2021 and taken down in August 2023. The sensor was powered by solar power with data being collected every 30 minutes at 1 m resolution. In addition to these measurements air temperature and incoming photosynthetically active radiation (PAR) are provided. These measurements are co-located with the NGEE Arctic Council eddy flux and meteorological station (AmeriFlux ID US-NGC). Included are six *.csv files (four data files and two reporting format files) and two *.kml files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Air temperature↗

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗

Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds

Abstract Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km 2 ) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

54 ENVIRONMENTAL SCIENCES↗

Correction to "Asian chemical Outflow to the Pacific in Spring: Origins, Pathways, and Budgets" by Isabelle Bey et al.

We analyze the Asian outflow of CO, ozone, and nitrogen oxides (NOx) to the Pacific in spring by using the GEOS-CHEM global three-dimensional model of tropospheric chemistry and simulating the Pacific Exploratory Mission-West (PEM-West B) aircraft mission in February-March 1994. The GEOS-CHEM model uses assimilated meteorological fields from the NASA Goddard Earth Observing System (GEOS). It reproduces relatively well the main features of tropospheric ozone, CO, and reactive nitrogen species observed in PEM-West B, including latitudinal and vertical gradients of the Asian pollution outflow over the western Pacific although simulated concentrations of CO tend to be too low (possibly because biogenic sources are underestimated). We use CO as a long-lived tracer to diagnose the processes contributing to the outflow. The highest concentrations in the outflow are in the boundary layer (0-2 km), but the strongest outflow fluxes are in the lower free troposphere (2-5 km) and reflect episodic lifting of pollution over central and eastern China ahead of eastward moving cold fronts. This frontal lifting, followed by westerly transport in the lower free troposphere, is the principal process responsible for export of both anthropogenic and biomass burning pollution from Asia. Anthropogenic emissions from Europe and biomass burning emissions from Africa make also major contributions to the Asian outflow over the western Pacific; European sources dominate in the lower troposphere north of 40 degrees N, while African sources are important in the upper troposphere at low latitudes. For the period of PEM-West B (February-March) we estimate that fossil fuel combustion and biomass burning make comparable contributions to the budgets of CO, ozone, and NO, in the Asian outflow. We find that 13% of NO, emitted in Asia is exported as NO, or PAN, a smaller fraction than for the United States because of higher aerosol concentrations that promote heterogeneous conversion of NOx to HNO3. Production and export of ozone from Asia in spring is much greater than from the United States because of the higher photochemical activity.

Bey, Isabelle↗

Fine particulate concentrations over East Asia derived from aerosols measured by the Advanced Himawari Imager using machine learning

Fine particulate matter with a diameter below 2.5 μm (PM 2.5 ) is deleterious to the cardiovascular and respiratory systems. It is often difficult to assess the effects of PM 2.5 on human health over regions with limited ground monitoring sites, especially in East Asia. As an alternative, we estimated near-surface PM 2.5 concentrations by analyzing Advanced Himawari Imager (AHI) Yonsei Aerosol Retrieval (YAER) products. This study incorporates daytime data for East Asia covering the Korean Peninsula, China, Japan, Southeast Asia, and southern Mongolia. We collocated AHI YAER product pixels with meteorological, land-cover, and other ancillary data for the period from March 2018 to February 2019. To estimate PM 2.5 concentrations over wide areas spanning many countries displaying various relationships between aerosol optical depth and PM 2.5 , monthly models were developed by considering both the spatial and temporal characteristics of ground-based PM 2.5 measurements. Random forest machine learning model estimated ground-level mass concentrations of PM 2.5 ; subsequent 10-fold cross validation (CV) yielded a CV R 2 value of 0.81 and a CV root mean squared error (RMSE) of 12.3 μg m -3 . We investigated the spatial pattern of PM 2.5 concentrations over multiple countries and seasonal variation in PM 2.5 concentrations. Diurnal variation of a severe PM 2.5 event in the Korean Peninsula was investigated as a case study. The model captured the extremely heterogeneous spatial distribution of PM 2.5 concentrations peaked around local noon. To measure the capability of the developed model to estimate PM 2.5 concentrations in areas with few in-situ data, its predictive performance was evaluated using a dataset independent of the training process with an R 2 of 0.60 and RMSE of 8.18 μg m −3 . This study demonstrates the potential for satellite-based PM 2.5 estimation for areas with insufficient measuring stations.

Pm2.5↗

Monolithic AlScN/SiC phononic waveguides for scalable acoustoelectric and quantum devices

Unlike conventional surface acoustic wave devices, phononic waveguide systems enable higher circuit density and stronger strain and piezoelectric fields, making them promising for advanced acoustoelectric and quantum applications. One such material system for generating and guiding phonons at gigahertz frequencies is AlScN on SiC, which can be synthesized by sputter depositing AlScN directly onto SiC wafers. The AlScN on the SiC platform allows for tightly vertically-confined acoustic modes with high electromechanical coupling, high speed of sound, and simple fabrication of strip and rib waveguides. Until now, this system has only been studied as a slab waveguide platform, i.e., without any lateral waveguiding. Here, we demonstrate a two-dimensionally confined phononic architecture in AlScN on SiC that supports guided modes at 2.95 and 4.05 GHz. These modes exhibit strong electromechanical coupling coefficients (k 2 = 4.27%) and propagation losses on the order of 10 dB/mm. Furthermore, this architecture is well-suited for phononic routing and power-efficient active or nonlinear devices such as amplifiers, mixers, and oscillators, and is compatible with the integration of quantum systems, including vacancy centers, charge carriers, photons, and spins, either embedded in SiC or heterogeneously integrated on the surface.

Electrical components↗

Oxidation of the Mantle Wedge by H+ in Aqueous Fluids: A New Interdisciplinary Approach

The observation that arc magmas are the most oxidized on Earth have led petrologists to question whether the subduction process might cause oxidation of the sub-arc mantle source. A strong correlation between the input of slab-derived aqueous fluid and Fe3(+)/ΣFe in arc magmas has led to the hypothesis that slab fluids may facilitiate the transfer of redox potential from oxidized slab material to mantle wedge and subsequently to primary arc melts. Despite this intuitive link, identifying an efficient and ubiquitous chemical process to transfer oxidation state in slab fluids has been challenging. Pure H2O alone is an inefficient oxidizer in the mantle, necessitating another oxidant within the fluid. Commonly invoked components include S or C, which are likely heterogeneously distributed within subducting slabs, and direct transfer of Fe3(+), which is only possible in very solute-rich fluids. Here we present a new mechanism to explain the oxidation of the sub-arc mantle by slab-derived aqueous fluid, wherein dissolved H(+)(aq) is reduced to H2(aq). Redox equilibrium is satisfied by electron transfer from Fe2(+)(s), which is oxidized in the rock to Fe3(+)(s) in the reaction: 2Fe2(+)(s) + 2H(+)(aq) = 2Fe3(+)(s) + H2(aq). This simple reaction was previously overlooked due to the assumption that all H must be bound by H2O molecules (i.e., no dissolved H), applicable to a pure H2O fluid, but not one with a solute load as addressed here. The application of thermodynamic modeling tools from aqueous geochemistry (DEW, EQ3/6) to mantle petrology predicts this reaction between mantle rock and slab fluid with our own experimentally constrained chemistry and fO2 (QFM+2). Mass transfer model results show an increase in Fe3(+)/ΣFe in mantle rock from MORB- like (0.15) to arc-like (0.2–0.3) values at reasonable fluid fluxes, co-incident with increasing H2 activity in the fluid. This can explain the stark correlation between slab fluid input into the mantle wedge and the observed fO2 of arc magmas. Moreover, it does not require diffusion of hydrogen out of the system. Instead, H2 remains dissolved in fluid in equilibrium with oxidized mantle rock.

Iacovino, Kayla↗

Origins of GEMS Grains

Interplanetary dust particles (IDPs) collected in the Earth s stratosphere contain high abundances of submicrometer amorphous silicates known as GEMS grains. From their birth as condensates in the outflows of oxygen-rich evolved stars, processing in interstellar space, and incorporation into disks around new stars, amorphous silicates predominate in most astrophysical environments. Amorphous silicates were a major building block of our Solar System and are prominent in infrared spectra of comets. Anhydrous interplanetary dust particles (IDPs) thought to derive from comets contain abundant amorphous silicates known as GEMS (glass with embedded metal and sulfides) grains. GEMS grains have been proposed to be isotopically and chemically homogenized interstellar amorphous silicate dust. We evaluated this hypothesis through coordinated chemical and isotopic analyses of GEMS grains in a suite of IDPs to constrain their origins. GEMS grains show order of magnitude variations in Mg, Fe, Ca, and S abundances. GEMS grains do not match the average element abundances inferred for ISM dust containing on average, too little Mg, Fe, and Ca, and too much S. GEMS grains have complementary compositions to the crystalline components in IDPs suggesting that they formed from the same reservoir. We did not observe any unequivocal microstructural or chemical evidence that GEMS grains experienced prolonged exposure to radiation. We identified four GEMS grains having O isotopic compositions that point to origins in red giant branch or asymptotic giant branch stars and supernovae. Based on their O isotopic compositions, we estimate that 1-6% of GEMS grains are surviving circumstellar grains. The remaining 94-99% of GEMS grains have O isotopic compositions that are indistinguishable from terrestrial materials and carbonaceous chondrites. These isotopically solar GEMS grains either formed in the Solar System or were completely homogenized in the interstellar medium (ISM). However, the chemical compositions of GEMS grains are extremely heterogeneous and seem to rule out this possibility. Based on their solar isotopic compositions and their non-solar elemental compositions we propose that most GEMS grains formed in the nebula as late-stage non-equilibrium condensates.

Messenger, S.↗