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At least 595 records · Page 33

Acoustic Rocket Signatures Collected by Smartphones

Rockets generate complex acoustic signatures that can be detected over a thousand kilometers from their source. While many far-field acoustic rocket signatures have been collected and released to the public, very few signatures collected at distances less than 100 km are available. This work presents a curated and annotated dataset of acoustic signatures of 243 rocket launches collected by a network of smartphones stationed at distances between 10 and 70 km from the launch sites, resulting in 1089 individual recordings. Due to the frequency dependence of atmospheric attenuation and the relatively short propagation distances, higher-frequency features not preserved in most publicly available data are observed. The signals are time-aligned to allow for different segments of the signal (ignition, launch, trajectory, chronology) to be more easily examined and compared. Initial analysis of the features of these rocket launch stages is performed, observed features are compared to those found in the existing literature, and comparisons between signals from launches of different rocket types are made. The dataset is annotated and made available to the public to aid future analysis of the characteristics and source mechanisms of rocket acoustics as well as applications such as rocket detection and classification models.

33 ADVANCED PROPULSION SYSTEMS↗

Effects of red imported fire ant ( Solenopsis invicta ) control on carrion use by vertebrate scavengers

Carrion is an important resource, and competition for carrion by microbial, invertebrate, and vertebrate scavenging communities is great. In particular, carrion is important to facultative and obligate vertebrate scavengers globally, and these species provide an irreplaceable ecological service by efficiently removing carcasses, which potentially harbor pathogens, from the environment. Although vertebrates efficiently acquire carcasses, they compete intensively with invertebrate and microbial communities, especially during warmer months when invertebrate and microbial activity peaks. The presence of invasive invertebrates may further exacerbate competition among scavenging groups; however, little is known about how invasive invertebrates can influence invertebrate scavenger dynamics and ultimately competition with vertebrate scavengers. The red imported fire ant (Solenopsis invicta; RIFA) is an invasive species of particular interest in North America, as it is a dominant predator and decomposer throughout much their range. We hypothesized that in areas where abundant, RIFA can outcompete vertebrates for carrion resources, altering nutrient cycling and food web dynamics. We tested this hypothesis by experimentally excluding RIFA from rabbit carcasses and found strong seasonal effects in our data; however, surprisingly, we found no effect of RIFA control on vertebrate scavenging efficiency, rates of carcass detection, carcass persistence, or the richness of local scavengers. Rather, we observed a highly efficient vertebrate scavenging community that assimilated 87.4% of carcasses during our study. Furthermore, this high rate of vertebrate scavenging efficiency was maintained in both control (93.0%) and RIFA treatment (81.8%) sites, suggesting presence of abundant RIFA populations did not limit vertebrate acquisition of carrion. Future research should focus on the interactions of RIFA with the remaining invertebrate scavenging community to further investigate whether RIFA impact the assimilation of carrion resources within invertebrate communities.

59 BASIC BIOLOGICAL SCIENCES↗

Effects of Supercritical CO 2 Injection on the Shale Pore Structures and Mass Transport Rates

Characterizing the pore structures and transport properties of low-permeability shales is critical for evaluating these formations as potential seals or storage sites for geological CO 2 sequestration. Here, we use low-pressure gas adsorption in conjunction with nuclear magnetic resonance (NMR) to characterize the pore-size distribution of shales before and after injection of supercritical CO 2 . Nitrogen gas was used as the detecting phase for the adsorption experiments and pentane liquid was used for the NMR experiments. We also performed time-resolved NMR and gravimetric microbalance measurements to observe mass transport during desaturation. We use these data to estimate the self-diffusion coefficient of pentane and changes in the saturation state of the pore network. We analyzed samples with a range of compositions from the Wolfcamp shale before and after exposure to supercritical CO 2 for 3 days. Integrating the gas adsorption and NMR data shows how supercritical CO 2 injection alters the pore-size distribution for pore sizes <1 nm to 1 mm. Finally, our results provide insights on how the pore structure and mass transport properties of different shale lithologies may evolve during storage of supercritical CO 2 .

58 GEOSCIENCES↗

Structurally Different Yet Functionally Similar: Aptamers Specific for the Ebola Virus Soluble Glycoprotein and GP1,2 and Their Application in Electrochemical Sensing

The Ebola virus glycoprotein (GP) gene templates several mRNAs that produce either the virion-associated transmembrane protein or one of two secreted glycoproteins. Soluble glycoprotein (sGP) is the predominant product. GP1 and sGP share an amino terminal sequence of 295 amino acids but differ in quaternary structure, with GP1 being a heterohexamer with GP2 and sGP a homodimer. Two structurally different DNA aptamers were selected against sGP that also bound GP1,2. These DNA aptamers were compared with a 2'FY-RNA aptamer for their interactions with the Ebola GP gene products. The three aptamers have almost identical binding isotherms for sGP and GP1,2 in solution and on the virion. They demonstrated high affinity and selectivity for sGP and GP1,2. Furthermore, one aptamer, used as a sensing element in an electrochemical format, detected GP1,2 on pseudotyped virions and sGP with high sensitivity in the presence of serum, including from an Ebola-virus-infected monkey. Our results suggest that the aptamers interact with sGP across the interface between the monomers, which is different from the sites on the protein bound by most antibodies. The remarkable similarity in functional features of three structurally distinct aptamers suggests that aptamers, like antibodies, have preferred binding sites on proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗

Carbon nanospike coated nanoelectrodes for measurements of neurotransmitters

Here, carbon nanoelectrodes enable the detection of neurotransmitters at the level of single cells, vesicles, synapses and small brain structures. Previously, the etching of carbon fibers and 3D printing based on direct laser writing have been used to fabricate carbon nanoelectrodes, but these methods lack the ability of mass manufacturing. In this paper, we mass fabricate carbon nanoelectrodes by growing carbon nanospikes (CNSs) on metal wires. CNSs have a short, dense and defect-rich surface that produces remarkable electrochemical properties, and they can be mass fabricated on almost any substrate without using catalysts. Tungsten wires and niobium wires were electrochemically etched in batch to form sub micrometer sized tips, and a layer of CNSs was grown on the metal wires using plasma-enhanced chemical vapor deposition (PE-CVD). The thickness of the CNS layer was controlled by the deposition time, and a thin layer of CNSs can effectively cover the entire metal surface while maintaining the tip size within the sub micrometer scale. The etched tungsten wires produced tapered conical nanotips, while the etched niobium wires were long and thin. Both showed excellent sensitivity for the detection of outer sphere ruthenium hexamine and the inner sphere test compound ferricyanide. The CNS nanosensors were used for the measurement of dopamine, serotonin, ascorbic acid and DOPAC with fast-scan cyclic voltammetry. The CNS nanoelectrodes had a large surface area and numerous defect sites, which improved the sensitivity, electron transfer kinetics and adsorption. Finally, the CNS nanoelectrodes were compared with other nanoelectrode fabrication methods, including flame etching, 3D printing, and nanopipettes, which are slower to make and more difficult for mass fabrication. Thus, CNS nanoelectrodes are a promising strategy for the mass fabrication of nanoelectrode sensors for neurotransmitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cluster Expansion Analysis of Atomic Order in Li-Ion Battery Cathode Material LiCo y Ni 1-y O 2

A modified cluster-expansion treatment was developed recently to analyze atomic order in LiCo y Ni 1-y O 2 , a model cathode material for Li-ion batteries. In this treatment, referred to as a “spin-atom” cluster expansion, the occupant of a lattice site is identified by its spin state as well as its atomic species. Further, Effective Cluster Interaction (ECI) coefficients are derived from a large training data set (i.e., the set of atomic arrangements for which DFT calculations are performed) which is filtered by an anomaly detection algorithm to eliminate poorly converged DFT calculations. The cluster expansion incorporates Li-Ni (LN) exchange as well as intralayer Co-Ni (CN) exchange. Monte Carlo simulations based on the cluster expansion were applied to the Ni-rich part of the phase diagram. The simulations predict a miscibility gap between y = 0.05 and y = 0.65.

25 ENERGY STORAGE↗

Assessment of Cold Spraying Mild-Steel Powder onto Mild-Steel Substrate for Development of Waste Tank Repair System - 20515

Infrastructure for nuclear waste storage and processing (e.g., waste tanks, transfer pipelines, evaporators) at the U.S. Department of Energy (DOE) Hanford Site has been in service well beyond its original design life. Past corrosion control methods at Hanford for waste tanks have not been fully successful, as evidenced by leaks forming in tank AY-102, the first double-shell tank (DST) constructed, and significant degradation detected in the primary tanks of AP-102 and AY-101. Failure of infrastructure components can pose a significant risk to the environment, worker safety, and project schedules. Therefore, remotely deployable methods for repairing and extending the service life of the existing tank waste infrastructure are needed. Cold spray has been identified as a potential technique for performing in situ repairs and material buildup for life extension of waste storage and processing infrastructure. Cold-spray repair methods and technology are well-established and are used extensively by industry and the military for making repairs using dissimilar materials. Pacific Northwest National Laboratory is evaluating the process of making repairs using mild-steel powder applied to a mild-steel substrate to minimize the galvanic corrosion potential. This paper presents the initial results for a feasibility ('go/no-go') assessment as to whether low-density deposits with sound metallurgic bonds, to build-back steel plate material, can be achieved using existing commercial cold-spray equipment. An assessment of steel-on-steel deposit is necessary to determine if cold spray is a viable candidate for DST carbon steel plate restoration/repair and thus DST service life extension. Powder properties and preparation requirements have been investigated and operating conditions and parameters for depositing a cold-spray buildup of mild steel on a mild-steel substrate have been determined. Soundness of metallurgic bonding as a function of the operating parameters exercised and results from applying cold spray to lay a deposit over simulated small-diameter flaws in 1/2-inch mild-steel plate are presented. Application of in situ cold-spray repair to the DOE complex has the potential to reduce cost and schedule impacts associated with component failures and the need to procure and construct replacement infrastructure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Preliminary report on applications of machine learning techniques to the Nevada play fairway analysis

We are applying machine learning (ML) techniques, including training set augmentation and artificial neural networks, to mitigate key challenges in the Nevada play fairway project. The study area includes ~85 active geothermal systems as potential training sites and >12 geologic, geophysical, and geochemical features. The main goal is to develop an algorithmic approach to identify new geothermal systems in the Great Basin region. Major objectives include: 1) integrate ML techniques into the geothermal community; 2) develop open community datasets, whereby all play fairway and ML datasets and algorithms are publicly released and available for modification by various user groups; 3) identify data acquisition targets with high value for future work; 4) identify new signatures to detect blind geothermal systems; and 5) foster new capabilities for characterizing subsurface temperature and permeability. Initially, ML techniques are being applied to the same play fairway datasets and workflow. ML will then be applied to both enhanced and additional datasets, with modification of the PFA workflow to incorporate the new datasets. Finally, ML will be applied to define new workflows using the enhanced and additional datasets. An algorithmic approach that empirically learns to estimate weights of influence for diverse parameters can potentially scale and perform better than the play fairway analysis. Initial work on this project has involved 1) evaluating potential positive and negative training sites, 2) transformation of datasets into formats suitable for ML, and 3) initial development and testing of ML techniques.

58 GEOSCIENCES↗

Allosterically coupled conformational dynamics in solution prepare the sterol transfer protein StarD4 to release its cargo upon interaction with target membranes

Complex mechanisms regulate the cellular distribution of cholesterol, a critical component of eukaryote membranes involved in regulation of membrane protein functions directly and through the physiochemical properties of membranes. StarD4, a member of the steroidogenic acute regulator-related lipid-transfer (StART) domain (StARD)-containing protein family, is a highly efficient sterol-specific transfer protein involved in cholesterol homeostasis. Its mechanism of cargo loading and release remains unknown despite recent insights into the key role of phosphatidylinositol phosphates in modulating its interactions with target membranes. We have used large-scale atomistic Molecular dynamics (MD) simulations to study how the dynamics of cholesterol bound to the StarD4 protein can affect interaction with target membranes, and cargo delivery. We identify the two major cholesterol (CHL) binding modes in the hydrophobic pocket of StarD4, one near S136&S147 (the Ser-mode), and another closer to the putative release gate located near W171, R92&Y117 (the Trp-mode). We show that conformational changes of StarD4 associated directly with the transition between these binding modes facilitate the opening of the gate. To understand the dynamics of this connection we apply a machine-learning algorithm for the detection of rare events in MD trajectories (RED), which reveals the structural motifs involved in the opening of a front gate and a back corridor in the StarD4 structure occurring together with the spontaneous transition of CHL from the Ser-mode of binding to the Trp-mode. Further analysis of MD trajectory data with the information-theory based NbIT method reveals the allosteric network connecting the CHL binding site to the functionally important structural components of the gate and corridor. Mutations of residues in the allosteric network are shown to affect the performance of the allosteric connection. These findings outline an allosteric mechanism which prepares the CHL-bound StarD4 to release and deliver the cargo when it is bound to the target membrane.

59 BASIC BIOLOGICAL SCIENCES↗

Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State

Spring phenology plays an essential role in climate change, terrestrial ecosystem, and public health. Field-based monitoring and understanding of changes in spring phenology for long periods and in large regions are challenging due to the limited in-site observations. Space-based remotely sensed observations offer great potentials for monitoring decadal spring phenology changes from regional to global scales. However, the coarse-scale remotely sensed observations are insufficient to capture fine-scale spring phenology dynamics, especially in urban areas, and this makes it challenging for understanding the combined effects of climate change and urbanization on spring phenology. We derived the start of phenology season (SOS) in New York State using 30 m Landsat observations from 1990 to 2015 to understand the impact of the environment and urbanization on SOS. The results show that SOS for different years reveals heterogeneous spatial distribution. Most regions of New York State have been experiencing significant spring phenology changes in form of earlier onset of vegetation greening, ranging from 0.2 to 0.6 day/year during 1990 to 2015, and this trend varies slightly with latitudes and urbanization levels. Further, spatial correlation analysis shows that the increase in temperature and urbanization could both promote the advancement of SOS. However, the effect of urbanization (partial correlation coefficient (R) ranges from −0.289 to −0.542) on SOS is greater than the effect of temperature (R ranges from 0.006 to −0.192). The study generates a high spatio-temporal resolution spring phenology dataset for ecological, environmental and public health studies, especially in urban areas, and reveals the importance of better accounting for the urbanization effects when quantifying the SOS dynamics in phenology models.

Landsat↗

Diaspora: Resilience-Enabling Services for Real-Time Distributed Workflows

The need for real-time processing to enable automated decision making and experimental steering has driven a shift from high-performance computing workflows on a centralized system to a distributed approach that integrates remote data sources, edge devices, and diverse compute facilities. Under this paradigm, data can be processed close to the source where it is generated, thus reducing latency and bandwidth usage. System resilience is thus a key challenge, requiring distributed workflows to survive component failures and to meet stringent quality-of-service requirements, which results in the need to mitigate anomalies such as congestion and low availability of resources. To address these challenges, we propose Diaspora, a unified resilience framework that is inspired by event-driven communication patterns used in public clouds. Specifically, we propose an event fabric that extends across sites, facilities, and computations to provide timely, reliable, and accurate information about data, application, and resource status. On top of the event fabric, we build resilience-enabling services that combine QoS-aware data streaming, resilient data views, resilient compute and data resources, and anomaly detection and prediction, all of which collectively enhance workflow resilience for these scientific cases.

Rao, Nageswara↗

The DUNE Far Detector Vertical Drift Technology. Technical Design Report

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals.

47 OTHER INSTRUMENTATION↗

Detectability of Varied Hybridization Scenarios Using Genome-Scale Hybrid Detection Methods

Hybridization events complicate the accurate reconstruction of phylogenies, as they lead to patterns of genetic heritability that are unexpected under traditional, bifurcating models of species trees. This phenomenon has led to the development of methods to infer these varied hybridization events, both methods that reconstruct networks directly, as well as summary methods that predict individual hybridization events from a subset of taxa. However, a lack of empirical comparisons between methods – especially those pertaining to large networks with varied hybridization scenarios – hinders their practical use. Here, we provide a comprehensive review of popular summary methods: TICR, MSCquartets, HyDe, Patterson’s D-Statistic (ABBA-BABA), D3, and Dp. TICR and MSCquartets are based on quartet concordance factors gathered from gene tree topologies and HyDe, Patterson’s D-Statistic, D3, and Dp use site pattern frequencies to identify hybridization events between sets of three taxa. We then use simulated data to address questions of method accuracy and ideal use scenarios by testing methods against complex networks which depict gene flow events that differ in depth (timing), quantity (single vs. multiple, overlapping hybridizations), and rate of gene flow (γ). We find that deeper or multiple hybridization events may introduce noise and weaken the signal of hybridization, leading to higher relative false negative rates across all methods. Despite some forms of hybridization eluding quartet-based detection methods, MSCquartets displays high precision in most scenarios. While HyDe results in high false negative rates when tested on hybridizations involving extinct or unsampled ghost lineages, HyDe is the only method able to identify the direction of hybridization, distinguishing the source parental lineages from recipient hybrid lineages. Lastly, we test the methods on a dataset of ultraconserved elements from the bee subfamily Nomiinae, finding possible hybridization events between clades which correspond to regions of poor support in the species tree estimated in a previous study.

Bjorner, Marianne B.↗

Micromechanical and fatigue in situ synchrotron characterization of an additively manufactured superalloy with porosity

Additive manufacturing (AM) has the potential to transform component production, but its widespread adoption is constrained by defects, such as pores, that compromise structural integrity. Here, this study investigates the influence of porosity on the micromechanical and fatigue response of AM Inconel 718 (IN718), a widely used aerospace superalloy. One baseline specimen with minimal stochastic porosity and another intentionally seeded with lack of fusion (LOF) pores were examined using high-energy X-ray diffraction microscopy (HEDM) and micro-computed tomography during cyclic loading. Fatigue cracks in the LOF specimen initiated more frequently and at lower cycle counts than in the baseline specimen. The number fraction of fatigue cracks that grew was comparatively higher in the LOF specimen. Grain-level metrics, including stress and diffraction spot widths, were quantified using far-field HEDM. Across the thousands of grains detected in both specimens, the pores in the LOF specimen increased the variability of stress and spot width evolution in the azimuthal direction, the latter serving as a surrogate measure of plastic deformation. However, no correlations emerged between these metrics and grain proximity to fatigue crack initiation sites or pores, underscoring the limitations of grain-averaged metrics for predicting fatigue. Nonetheless, the rich dataset reported here provides a foundation for future modeling efforts.

High-energy X-ray diffraction microscopy↗

Automated compatibility checking of prefabricated components using 3D as-built models and BIM

There have been recent efforts to use reality capture technologies to perform remote quality control in construction. However, there is a lack of research efforts in detecting construction incompatibilities in modular construction using reality capture technologies. The construction incompatibilities in modular construction often cause reworks and delays in the project schedule. To address this issue, this paper presents a general compatibility analysis method that propose scanning the modules in manufacturing plant and construction site, and check module-to-module compatibility remotely, prior to the shipment and installation. This study provides three sample module-to-module compatibility scenarios to validate the proposed compatibility analysis. The case study results show that the compatibility analysis method was able to identify the compatibility issues with high accuracy. Lastly, the compatibility analysis method was validated in terms of accuracy and time performance in six scenarios that was defined on the modules.

42 ENGINEERING↗

Visualizing the atomic-scale origin of metallic behavior in Kondo insulators

A Kondo lattice is often electrically insulating at low temperatures. However, several recent experiments have detected signatures of bulk metallicity within this Kondo insulating phase. In this study, we visualized the real-space charge landscape within a Kondo lattice with atomic resolution using a scanning tunneling microscope. We discovered nanometer-scale puddles of metallic conduction electrons centered around uranium-site substitutions in the heavy-fermion compound uranium ruthenium silicide (URu 2 Si 2 ) and around samarium-site defects in the topological Kondo insulator samarium hexaboride (SmB 6 ). These defects disturbed the Kondo screening cloud, leaving behind a fingerprint of the metallic parent state. Our results suggest that the three-dimensional quantum oscillations measured in SmB 6 arise from Kondo-lattice defects, although we cannot exclude other explanations. Finally, our imaging technique could enable the development of atomic-scale charge sensors using heavy-fermion probes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗