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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparative clumped isotope temperature relationships in freshwater carbonates

Lacustrine, riverine and spring carbonates represent archives of terrestrial climates and their geochemistry has been used to study palaeoenvironments. Clumped isotope thermometry is an emerging tool that has been applied to freshwater carbonates. Limited work has been done to evaluate comparative relationships between clumped isotopes and temperature in different types of modern freshwater carbonates. This study assembles an extensive calibration data set with 135 samples of modern freshwater carbonates from 96 sites and constrains the relationship between independent observations of water temperature and the clumped isotopic composition of carbonates (denoted by Δ 47 ), including new measurements, and recalculates published data in accordance with current community-defined standard values. For temperature reconstruction, the study reports a composite freshwater calibration and material-specific calibrations for biogenic carbonates (freshwater gastropods and bivalves), fine-grained carbonate (e.g. micrites), biologically mediated carbonates (microbialites and tufas) and travertines. Material-specific calibration trends show a convergence of slopes that are in agreement with recently published syntheses, but statistically significant differences in intercepts occur between some materials (e.g. some biogenics, fine-grained carbonates). These differences may arise due to unresolved seasonal biases, kinetic isotope effects and/or varying degrees of biological influence. The impact of different calibrations is shown through application to new data for glacial and deglacial age travertines from Austria and published data sets. While material-specific calibrations may yield more accurate results for biogenic and fine-grained carbonate samples, the use of material-specific and the composite freshwater calibrations generally produces values within 1.0–1.5°C of each other, and typically fall within calibration uncertainty given limitations of precision.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets

This study examines the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach adopted in the U.S. National Weather Service Hydrometeorological Reports No. 51 and No. 52. Although widely used for infrastructure design and risk regulation, fundamental aspects of PMP estimation—such as storm sample size, transposition domain, maximization procedures, and storm rotation—remain poorly constrained and lack formal guidance. Using the Red Rock watershed in Iowa as a case study, and leveraging the 2002–2023 NOAA Analysis of Record for Calibration (AORC) precipitation dataset, we systematically evaluate how each methodological choice, individually and in combination, influences PMP estimates. Our findings demonstrate that PMP is not a fixed physical upper bound but rather a modeling construct shaped heavily by user-defined assumptions. Notably, PMP values derived from modern gridded rainfall datasets can be substantially higher than the legacy estimate used in the original spillway design for Red Rock Dam. Decisions regarding storm sample size, domain extent, climatological window, and particularly storm rotation all contributed to higher PMP estimates. Storm rotation alone—a loosely constrained element in the current PMP practice—can amplify PMP by more than 25%. These results reveal the lack of standardized bounds in current PMP workflows and the need for systematic sensitivity and uncertainty analysis. As PMP estimation shifts toward probabilistic approaches, incorporating physically meaningful storm attributes will be key to developing more transparent, defensible methods for dam safety and climate-resilient infrastructure.

Probable maximum precipitation↗
DOE OSTI2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Here, we analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We present sub-percent measurements of the galaxy auto-correlation and galaxy-dark matter cross correlations in Fourier space and configuration space for a magnitude-limited galaxy sample. At these levels of precision, the statistical errors of the measurement are comparable to the systematic effects present in the simulation and measurement procedure; nevertheless, using a hybrid-PT model, we are able to model non-linear galaxy bias with 0.5% precision up to scales of k max = 0.5 h/Mpc and r min = 4 Mpc/h. While the linear bias parameter is measured with 0.01% precision, other bias parameters are determined with considerably weaker constraints and sometimes bimodal posterior distributions. We compare our fiducial model with lower dimensional models where the higher-order bias parameters are fixed at their co-evolution values and find that leaving these parameters free provides significant improvements in our ability to model small scale information. We also compare bias parameters for galaxy samples defined using different magnitude bands and find agreement between samples containing equal numbers of galaxies. Finally, we compare bias parameters between Fourier space and configuration space and find moderate to significant tension between the two approaches. Although our model is often unable to fit the CosmoDC2 galaxy samples within the 0.1% precision of our measurements, our results suggest that the hybrid-PT model used in this analysis is capable of modeling non-linear galaxy bias within the percent level precision needed for upcoming galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Uncovering hidden bias in neutron diffraction residual strain measurements

When calculating residual strain via neutron or X-ray diffraction, uncertainties propagated from the peak fit are often inadequate to describe the true scatter of measurements about a singular strain state, such as one that should describe a macroscopic continuum. Because diffraction is inherently a selective process, orientation-dependent scatter arises from the sub-sampling of strong microstructure and strain gradients. This paper investigates the appropriateness of propagated uncertainties with reference to their original intention, i.e. noise about a mean value. Thirty-six unique orientations of strain measurements are taken at multiple locations within an additive friction-stir deposition component with fine-scale gradients (∼200 µm) of plastic strain, texture and residual elastic strain. Multiple strain and stress calculation pathways are compared: direct substitution of three measurements into Hooke's law, direct inversion of any six unique orientations into the strain state tensor and thirty-six measurement least-squares estimation. For the last two cases, the appropriateness of the uncertainty interval is statistically evaluated on the basis of a physical constraint: common agreement under the strain transformation law. For this sample, the direct inversion of six measurements retains a conservative estimate of the uncertainty. However, propagated uncertainties in the least-squares solution greatly underestimate the true experimental scatter. A simple pathway to estimate appropriate uncertainty intervals is suggested. These results demonstrate that the interpretation of uncertainty in residual strain is strongly dependent on intrinsic sample-dependent effects, and that oversampling orientations and statistical analysis can give more accurate results with realistic uncertainties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A round bobbin critical current measurement and thermal runaway simulation of REBCO coated conductors

A round bobbin test has been widely used to measure critical current Ic of practical superconductors including Nb–Ti, Nb3Sn, and Bi-2212 round strands at 4.2 K and in high magnetic fields but rarely used for rare earth-barium-copper-oxide (REBCO) coated conductor tapes. Here, we applies this method to REBCO tapes and test their Ic at 77 K, self-field, and 4.2 K with a magnetic field of 14 T applied parallel to the tape. The sample carries very high current densities; it is 1.3 m long and has a dense array of voltage taps that allows probing localized thermal runaways and correlation with Ic variations along the length. At 77 K, the Ic values of all sections were measured and found to be rather uniform. However, at 4.2 K, we found that a 3 cm section has 90% of the overall voltage drop and it went into thermal runaways upon further increasing current. Thus, at 4.2 K, we were prevented by localized thermal runaways and unable to determine Ic of most of the REBCO conductor sections; this behavior is different from Bi-2212 and Bi-2223 for which Ic of all turns of a round barrel sample can be determined. We simulate REBCO tapes during current ramping to a thermal runaway and analyze impacts of various factors including cooling, conductor n-values, and thickness of stabilizer on the thermal runaway current Iq. The combined experiments and simulations identify n-value as a crucial factor that leads to the observed differences between Bi-2212 and REBCO. Together with cooling and the standard deviation of Ic variations along the length, the n-value determines whether Iq is above or below the average Ic of a long piece of conductor and their ratio Iq/Ic,ave, greatly affecting quench detection and thermal runaway prevention strategies of Bi-2212 and REBCO magnets.

Mosat, Marek↗
DOE OSTI2020

Deformation of Néel-type skyrmions revealed by Lorentz transmission electron microscopy

Néel-type magnetic skyrmions in multilayers are promising candidates for ultra-low power spintronic devices. To image the Néel-type skyrmions using Lorentz transmission electron microscopy (L-TEM), the samples must be tilted. Thus, the external magnetic field consists of both in-plane and out-of-plane components. To date, it is still not well known on the effect of the in-plane magnetic field on the L-TEM images, leading to ambiguities in retrieving the structure of Néel-type skyrmions. Here, Néel-type skyrmions in three [Pt/Co/Ta]$_{20}$ multilayer samples, with the easy magnetization axis being tuned from the out-of-plane to the in-plane direction by increasing the Co thickness from 1.8 to 2.2 nm, are imaged. When using a smaller defocus value (-2 mm) and a higher magnification (×9100) of L-TEM, a surprising dark-bright-dark-bright double contrasted pattern, instead of the previously reported dark-bright contrasted pattern, is observed. The additional dark-bright contrasted pattern becomes more evident for thicker Co layer samples in which the magnetization axis tilts more toward the in-plane direction. Further analysis, via a combination of magnetic force microscopy experiments, micromagnetic simulations, and micromagnetic analysis to Lorentz TEM simulation, shows that the additional dark-bright features originate from the deformation of the Néel-type skyrmions within an in-plane magnetic field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

The Compilation and Validation of the Spectroscopic Redshift Catalogs for the DESI-COSMOS and DESI-XMM-LSS Fields

Over several dedicated programs that include targets beyond the main cosmological samples, the Dark Energy Spectroscopic Instrument collected spectra for 304,970 unique objects in two fields centered on the COSMOS and XMM-LSS fields. In this work, we develop spectroscopic redshift robustness criteria for those spectra, validate these criteria using visual inspection, and provide two custom value-added catalogs with our redshift characterizations. With these criteria, we reliably classify 212,935 galaxies below z < 1.6, 9713 quasars, and 35,222 stars. The resulting catalogs achieve a redshift purity exceeding 99.4% across all galaxy samples. As a critical element in characterizing the selection function, we provide the description of 70 different algorithms that were used to select these targets from imaging data. To facilitate joint imaging/spectroscopic analyses, we provide row-matched photometry from the Dark Energy Camera, Hyper-Suprime Cam, and public COSMOS2020 photometric catalogs. Finally, we demonstrate example applications of these large catalogs to photometric redshift estimation, cluster finding, and completeness studies.

Ratajczak, J. [Univ. of Utah, Salt Lake City, UT (↗
DOE OSTI2025

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.

Deep learning↗
DOE OSTI2023

The influence of chemical short-range order on the nanoindentation properties of high-entropy alloys prepared via laser powder bed fusion

Chemical short-range order (CSRO) plays an instrumental role in determining the mechanical properties of high-entropy alloys (HEAs). Current methods for controlling CSRO mainly focus on cast HEAs, which can not solve the problem of grain coarsening caused by homogenization treatments. Laser Powder Bed Fusion (LPBF), which has extremely high cooling rates, can suppress compositional segregation, refine grain structures, and achieve low CSRO. This offers a promising avenue for quantitatively controlling CSRO without the need for homogenization treatments. In this study, we investigate the CSRO of HEAs fabricated via LPBF and elucidate their influence on nanoindentation behavior. The results show that, at the low cooling rate, the average size of CSRO is 0.66 nm and they occupy 2.8% of the cross-sectional area, while at high cooling rate, the corresponding values are 0.92 nm and 9.9%, respectively, both of which are significantly smaller than those of cast HEAs. Furthermore, by analyzing samples with different CSROs, we observe that the hardness increases and then decreases with the increase of CSRO, primarily due to the preferential formation of dislocations in regions enriched with Cr-Mn-Ni. With the improvement of CSRO, both the size and quantity of Cr-Mn-Ni rich region gradually increased; subsequently, as multiple Cr-Mn-Ni rich regions tend to merge into one during the CSRO improvement, the size of the Cr-Mn-Ni rich region continued to increase while the quantity gradually decreased; when the size of the Cr-Mn-Ni rich region is moderate and widely dispersed, the dislocation density is higher with much more uniform distributions, which favorably improves nanoindentation hardness.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Boron-loaded organic glass scintillators

Herein we report the progress towards an organic glass scintillator with fast and thermal neutron sensitivity providing “triple” pulse shape discrimination (PSD) through the inclusion of a boron-incorporated aromatic molecule. Here, the commercially available molecule 2-(p-tolyl)-1,3,2-dioxaborinane (TDB) can be readily synthesized in one step using inexpensive materials and incorporated into the organic glass scintillator at 20% by weight or 0.25% 10 B by mass. In addition, we demonstrate that TDB can be easily scaled up and formulated into organic glass scintillator samples to produce a thermal neutron capture signal with a light yield equivalent to 120.4 ± 3.7 keVee, which is the highest value reported in the literature to date.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Influence of the Dielectric Constant on the Ionic Current Rectification of Bipolar Nanopores

In this paper, we investigate how the dielectric constant, ϵ, of an electrolyte solvent influences the current rectification characteristics of bipolar nanopores. It is well recognized that bipolar nanopores with two oppositely charged regions rectify current when exposed to an alternating electric potential difference. Here, we consider dilute electrolytes with NaCl only and with a mixture of NaCl and charged nanoparticles. These systems are studied using two levels of description, all-atom explicit water molecular dynamics (MD) simulations and coarse-grained implicit solvent MD simulations. The charge density and electric potential profiles and current-voltage relationship predicted by the implicit solvent simulations with ϵ = 11.3 show good agreement with the predictions from the explicit water simulations. Under nonequilibrium conditions, the predictions of the implicit solvent simulations with a dielectric constant closer to the one of bulk water are significantly different from the predictions obtained with the explicit water model. Further, these findings are closely aligned with experimental data on the dielectric constant of water when confined to nanometric spaces, which suggests that ϵ decreases significantly compared to its value in the bulk. Moreover, the largest electric current rectification is observed in systems containing nanoparticles when ϵ = 78.8. Using enhanced sampling, we have shown that this larger rectification arises from the presence of a significantly deeper minimum in the free energy of the system with a larger ϵ, and when a negative voltage bias is applied. Since implicit solvent models and mean-field continuum theories are often used to design Janus membranes based on bipolar nanopores, this work highlights the importance of properly accounting for the effects of confinement on the dielectric constant of the electrolyte solvent. The results presented here indicate that the dielectric constant in implicit solvent simulations may be used as an adjustable parameter to approximately account for the effects of nanometric confinement on aqueous electrolyte solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

SDSS IV MaNGA: visual morphological and statistical characterization of the DR15 sample

ABSTRACT We present a detailed visual morphological classification for the 4614 MaNGA galaxies in SDSS Data Release 15, using image mosaics generated from a combination of r band (SDSS and deeper DESI Legacy Surveys) images and their digital post-processing. We distinguish 13 Hubble types and identify the presence of bars and bright tidal debris. After correcting the MaNGA sample for volume completeness, we calculate the morphological fractions, the bi-variate distribution of type and stellar mass M* – where we recognize a morphological transition ‘valley’ around S0a-Sa types – and the variations of the g − i colour and luminosity-weighted age over this distribution. We identified bars in 46.8 per cent of galaxies, present in all Hubble types later than S0. This fraction amounts to a factor ∼2 larger when compared with other works for samples in common. We detected 14 per cent of galaxies with tidal features, with the fraction changing with M* and morphology. For 355 galaxies, the classification was uncertain; they are visually faint, mostly of low/intermediate masses, low concentrations, and discy in nature. Our morphological classification agrees well with other works for samples in common, though some particular differences emerge, showing that our image procedures allow us to identify a wealth of added value information as compared to SDSS-based previous estimates. Based on our classification, we also propose an alternative criteria for the E–S0 separation, in the structural semimajor to semiminor axis versus bulge to total light ratio (b/a − B/T) and concentration versus semimajor to semiminor axis (C − b/a) space.

Vázquez-Mata, J. A. (ORCID:0000000186941204)↗
DOE OSTI2025

The Milky Way and M31 orbital history: did the Local Group evolve in isolation?

ABSTRACT We use new measurements of the M31 proper motion to examine the Milky Way (MW) – M31 orbit and angular momentum. For Local Group (LG) mass consistent with measured values, and assuming the system evolves in isolation, we show a wide range of orbits is possible. We compare to a sample of LG-like systems in the Illustris simulation, and find that ∼13 per cent of these pairs have undergone a pericentric passage. Using the simulated sample, we examine how accurately an isolated, two-body model describes the MW–M31 orbit, and show that ∼10 per cent of the analogues in the simulation are well-modelled by such an orbit. Systems that evolve in isolation by this definition are found to have a lower rate of major mergers, and in particular have no major mergers since $z \approx 0.3$. For all systems, we find an increase in the orbital angular momentum which is fairly independent of the merger rate, and is possibly explained by the influence of tidal torques on the LG. Given the likely quiet recent major merger history of the MW, it is plausible that the isolated two-body model appropriately describes the orbit, though recent evidence for a major merger in M31 may complicate this interpretation.

Hartl, Odelia V. (ORCID:0000000202379726)↗
DOE OSTI2022

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Single crystal growth of iridates without platinum impurities

Iridates have attracted much interest in the last decade for their novel magnetism emerging in the limit of strong spin-orbit coupling and possible unconventional superconductivity. A standard for growing iridate single crystals has been the flux method using platinum crucibles. Here, in this work, we show that this widely used method compromises the sample quality by inclusion of platinum impurities. We find that Sr 2 ⁢IrO 4 single crystals grown in iridium crucibles show remarkable differences from those grown in platinum crucibles in their sample characterizations using Raman spectroscopy, resistivity, magnetization, optical third harmonic generation, resonant x-ray diffraction, and resonant inelastic x-ray scattering measurements. In particular, we show that several peaks of sizable intensities disappear in the Raman spectra of samples free of platinum impurities, and a significantly larger activation energy is extracted from the resistivity data compared to previously reported values. Furthermore, we find no evidence of the previously reported glide-symmetry-breaking structural distortions and confirm the I⁢ 4 1 / acd space group of the lattice symmetry. Although the platinum impurities are not apparent in the magnetic properties and thus went unnoticed in the stoichiometric insulating phase for a long time, their effects can be much more detrimental to transport properties in chemically doped compounds. Therefore, our result suggests using growth methods that avoid platinum impurities for an investigation of the intrinsic physical properties of iridates, and possible superconducting phases.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of Off-Stoichiometry on Electrical Conductivity in Ni-Fe and Mn-Co Spinel Systems

This study seeks to clarify the effects of off-stoichiometry on the electrical conductivity of spinels in the (Ni,Fe) 3 O 4 and (Mn,Co) 3 O 4 systems. Spinels with the compositions Ni x Fe 3–x O 4 (where x = 0.85, 0.875, 0.9, 1.0, 1.05, and 1.15) and Mn x Co 3–x O 4 (where x = 1.0, 1.2, 1.35, 1.5, 1.75, and 2.0) were prepared using conventional solid-state process. Electrical conductivity measurements were taken between 500 °C and 800 °C using the 4-point DC method. The conductivity in Ni-Fe spinels increased with increasing Fe content. Similarly, the conductivity of Mn-Co spinels increased drastically with increasing Co content. The coefficients of thermal expansion (CTEs) of these samples were also evaluated. All the (Ni,Fe) 3 O 4 spinels were found to exhibit excellent CTE matching with prospective stack components. However, thermal expansion characteristics were highly dependent on the composition in the (Mn,Co) 3 O 4 system, and only a narrow range of compositions was well-matched in CTE with prospective stack components. The significant effect of cation off-stoichiometry and sample preparation on the electrical behavior of spinels was discussed as a possible explanation for the large discrepancies in reported conductivity values for both systems.

08 HYDROGEN↗
DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, 2023

This dataset includes raw and corrected specific conductivity, temperature, and calculated salinity measurements collected at 10 cm depth in a Typha angustifolia-dominated tidal brackish wetland at the upper estuary of Plum Island Sound in Newbury, Massachusetts (MA) within the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site. Measurements were taken to evaluate temporal variation in porewater salinity (a proxy for porewater sulfate concentration) in high frequency to assess soil and plant responses to changes in salinity. Measurements were collected using an Onset HOBO U24-002 Saltwater Conductivity/Salinity data logger deployed in a well. Specific conductivity was corrected using non-linear temperature compensation, and salinity was calculated using the Practical Salinity Scale 1978 via Onset's HOBOware software. Reference conductivity measurements to correct for sensor drift were taken at the start and end of each deployment using a HACH HQ14D Portable Conductivity Meter. Data were then filtered in MATLAB to remove values logged while the sensor was out of the well or during post-deployment equilibration. Detailed metadata, including variable descriptions, sampling methods, QA/QC procedures, and site information, are provided in the files: Typha_ctd_salinity_dd.csv and Typha_MI_ctd_salinity_2023_flmd.csv.

54 ENVIRONMENTAL SCIENCES↗