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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of neutron spin-phase imaging for amorphous magnetic thin film investigation

Neutron spin-phase imaging (NSPI) capability was developed to study the magnetization distribution of an amorphous magnetic thin film. The local magnetization under different applied magnetic fields between 0.09 and 1.36 mT was investigated. The developed radio frequency flippers showed more than 95% flipping efficiency under these fields. A spatial resolution of ~0.4 mm and field of view of ~24 mm x 27 mm were achieved. In conclusion, the bulk property of the random distributions of the magnetization and magnetic field distribution ranging between ~1.1 and 1.4 T were observed showing that NSPI is a useful technique for investigating the spatial dependence of magnetic properties of amorphous magnetic thin films.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Protein Coatings Dictate the Dispersibility and Stability of Hydrophobic Zeolitic-Imidazolate Frameworks in Water

Metal–organic frameworks are promising materials for many biomedical technologies due to their ability to store and release large quantities of guest molecules in a predictable and tunable fashion. In biological fluids, proteins readily adsorb to the external surfaces of metal–organic framework particles through a combination of hydrophobic and electrostatic interactions. However, much remains to be understood about the nature of these protein coatings and how they influence the bulk properties of aqueous dispersions of metal–organic frameworks. Here, in this work, we show that a variety of proteins can be used to manipulate the properties of aqueous dispersions of zeolitic-imidazolate framework (ZIF) particles. Specifically, noncovalently associated protein coatings promote the formation of dispersions of hydrophobic ZIFs in water with high colloidal and hydrolytic stability, as long as the density of adsorbed proteins exceeds a critical, protein-dependent threshold. Further, these dispersions feature low viscosity and complete retention of gas carrying capacity. The wide range of properties accessible with protein coatings provides a highly modular approach to design hydrophobic metal–organic frameworks with properties tailored for specific biological applications.

adsorption↗
DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
DOE OSTI2025

Anode Potential Evolution During Zinc Metal Plating and Stripping in Dual-Solvent Battery Electrolytes

In the field of battery electrolyte research, the importance of the working cation solvation environment has become increasingly more apparent. To optimize bulk properties and, especially, interfacial reactions, multisolvent electrolytes (electrolytes containing two different solvents) have become more prevalent in battery research and development. In this work, we elucidate the relationship between cation solvation and interfacial electrochemistry, demonstrating that preferential solvation of Zn 2+ by a strong coordinating solvent such as 2-methoxyethylamine or ethylenediamine as opposed to a weaker solvent such as 3-methylsulfolane or acetonitrile leads to dynamic evolution in the interfacial energetics during Zn plating and stripping due to local changes in solvent composition and coordination. In some instances, interfacial solvation evolution can shift the reversible potential of Zn plating by as much as 1 V under relatively mild rate conditions. Through these investigations, we establish the generality of this phenomenon, highlight its importance as a consideration in dual-solvent battery electrolytes, and provide direction for tailoring electrochemistry through solvent design.

Hahn, Nathan T.↗
DOE OSTI2025

Unequal {110} Facets: The Potential Role of Intraparticle Heterogeneity and Facet Termination in Photoelectrochemical Activity of Single BiVO 4 Particles

BiVO 4 photoanodes are promising for solar water splitting, with photogenerated electrons and holes preferentially reacting at top {010} and lateral {110} facets, respectively. However, the mechanisms driving this facet-dependent reactivity remain unclear. Here, in this study, we investigate facet-dependent photocurrent and material heterogeneity using correlative scanning photoelectrochemical microscopy (SPCM), electron beam induced current (EBIC) mapping, and mid-IR scattering scanning near-field optical microscopy (s-SNOM). SPCM measurements of 62 BiVO 4 particles confirmed higher photocurrents at lateral {110} facets compared to top {010} facets, but unexpectedly revealed variations in photocurrent among lateral facets within the same particle. Variations in lateral facet surface termination could explain the intraparticle-level reactivity heterogeneity, consistent with theoretical predictions. Nano-FTIR spectroscopy and Raman microspectroscopy indicated significant materials chemistry heterogeneity within individual particles and facets that could be attributed to variations in lattice vibration distortions that enhance the overlap between Bi 6s and O 2p orbitals. The increased orbital overlap is significant as it potentially increases hole mobility in the valence band and potentially explains the lateral facet-dependent charge separation efficiency observed in photocurrent maps. Facet-dependent electrical and EBIC measurements showed no space charge regions at interfacet junctions or metal-BiVO 4 contacts under vacuum, suggesting that photogenerated holes beneath top {010} facets are unlikely to transport to lateral {110} facets to drive water/sulfite oxidation. These findings indicate the potential influence of distinct bulk properties and surface termination chemistries across different particles and facets, highlighting the importance of carefully controlling defects and surface chemistry during sample growth to optimize photocatalytic performance.

BiVO4↗
DOE OSTI2026

Revealing the Full Potential of Glycolated Mixed Ionic-Electronic Semiconductors – Symmetric Monomer Polymerization to Boost Electrochemical Transistor Performance

Organic electrochemical transistors (OECTs) enable the transduction of ionic signals into electronic outputs, positioning them as ideal candidates for next-generation sensing and (bio)signal processing applications. Recent years have witnessed the development of various OECT channel materials, affording insights into structural fine-tuning to achieve optimal performance and/or stability. However, homocouplings, commonly present in alternating conjugated polymers, have largely been overlooked. This study investigates the effect of homocoupling on OECT materials by employing two synthesis methods – standard Stille polymerization and an alternative symmetric approach – to create the p-type enhancement-mode benchmark polymer pgBTTT. The impact of homocoupling, and its absence, is studied by comparing the bulk properties of the two polymers and evaluating their respective OECT metrics. The new, homocoupling-free polymer exhibits a notably improved OECT performance ( μC *), mainly due to an average 3-fold increase in electronic mobility (μ).

defects↗
DOE OSTI2024

Quantifying the Diversity of an Atmospheric Aerosol Population in an Arctic Oil Field on a Single‐Particle Level

As the Arctic rapidly warms, sea ice extent is decreasing and oil and gas extraction activities are expanding. Local combustion emissions affect the Arctic atmospheric aerosol chemical mixing state (the distribution of chemical species across the aerosol population), which impacts climate-relevant properties. Bulk and single-particle measurements of submicron aerosols were conducted at Oliktok Point, Alaska within the North Slope of Alaska oil fields. In this work, we quantify aerosol diversity using online single-particle mass spectrometry data (32,880 individual particles), offline single-particle microscopy data (20,912 individual particles), and online bulk aerosol mass spectrometry and aethalometer data. This method was used to derive individual particle mass fractions for both refractory and non-refractory material within distinct particle types. Single-particle, average single-particle, and bulk population diversities (D i , D α , D γ , respectively) and mixing state indices (χ) were calculated for the data set. Calculated D i values were generally low (2.2 ± 0.6), as individual particle masses were dominated by a few chemical species of interest. Aged aerosol particles (those internally mixed with nitrate and/or sulfate) exhibited higher D i values (>3) compared to recently emitted (fresh) aerosol particles. During oil field plume periods, D α values approached three due to the abundance of diesel combustion particles, which were rich in sulfate, black carbon, and organic aerosol. Overall, the submicron aerosol population within the Arctic oil fields was found to be relatively externally mixed (χ < 50%), due to the constant local emissions within oil fields combining with background aerosol and locally emitted sea spray aerosol at the coastal site.

Wu, J.↗
DOE OSTI2026

Field-tailoring quantum materials via magneto-synthesis: metastable metallic and magnetically suppressed phases in a trimer iridate

We demonstrate that applying modest magnetic fields (< 0.1 T) during high-temperature crystal growth can profoundly alter the structure and ground state of a spin-orbit-coupled, antiferromagnetic trimer lattice. Using BaIrO₃ as a model system, whose ground state is intricately dictated by the trimer lattice, we show that magneto-synthesis , a field-assisted synthesis approach, stabilizes a structurally compressed, metastable metallic and magnetically suppressed phases inaccessible via conventional methods. These effects include a 0.85% reduction in unit cell, 4-order-of-magnitude decrease in resistivity, a 10-fold enhancement of the Sommerfeld coefficient, and the collapse of long-range magnetic order -- all intrinsic and bulk in origin. First-principles calculations confirm that the field-stabilized structure lies substantially above the ground state in energy, highlighting its metastable character. These large, coherent and correlated changes across multiple bulk properties, unlike those caused by dilute impurities, defects or off-stoichiometry, point to an intrinsic field-induced mechanism. The findings establish magneto-synthesis as a powerful new pathway for accessing non-equilibrium quantum phases in strongly correlated materials.

magneto-synthesis↗
DOE OSTI2025

Hybrid epoxy–acrylate resins for wavelength-selective multimaterial 3D printing

Structures in nature have evolved to combine hard and soft materials in precise 3D arrangements, which imbues bulk properties and functionality that remain elusive to mimic synthetically. However, the potential for biomimetic analogs to seamlessly interface hard materials with soft surfaces for applications ranging from robotics and sealants to medical devices (e.g., prosthetics and wearable health monitors) has driven the demand for innovative chemistries and manufacturing approaches. Herein, we unveil a liquid resin for rapid, high resolution digital light processing (DLP) 3D printing of multimaterial objects with an unprecedented combination of strength, elasticity, and resistance to aging. Two enabling discoveries are the use of a covalently bound (hybrid) epoxy-acrylate monomer that precludes plasticization of soft domains and a wavelength-selective photosensitizer that accelerates cationic curing for hard domains. Using dual projection for multicolor DLP 3D printing (UV and violet light), several bioinspired metamaterial structures are fabricated, including one with hard springs embedded in a soft cylinder to adjust compressive behavior and a detailed knee joint featuring “bones” and “ligaments” for smooth motion. Lastly, the application of this system to facilitate selective stretching for electronic devices is demonstrated with a proof-of-concept device.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Neutron spin echo spectroscopy

Neutron spin echo (NSE) spectroscopy is a powerful technique used to probe the internal dynamics and diffusion processes within matter, allowing researchers to quantify how materials respond to changes in external conditions. To fully understand the bulk properties of a material, it is often crucial to investigate dynamic processes occurring on nanometre length scales and nanosecond timescales. NSE spectroscopy provides an exceptional capability to measure such dynamics across a broad spectrum of condensed matter systems, ranging from proteins and quantum magnets to catalysts. In this Primer, we present an overview of NSE spectroscopy, highlighting the instruments used, methods of data collection and representative applications in both soft-matter and hard-matter sciences.

Czakkel, Orsolya [Institut Max von Laue-Paul Lange↗
DOE OSTI2026

Solution structures in alkali nitrates and nitrites at high concentrations

In highly concentrated electrolyte solutions, where classical models often fail, specific ion–solvent interactions dictate bulk properties. Here, in this study, we combine small-angle X-ray scattering (SAXS) and Raman spectroscopy to link molecular coordination to mesoscale structure across alkali nitrate and nitrite solutions. Our results reveal a structural hierarchy driven by cation identity in that smaller cations (Li + , Na + ) form discrete contact ion pairs, while larger cations (K + , Rb + ) promote increasingly disordered local coordination and extended solute–solvent networks. Using nitrite salts as a structural control, we confirm this organizing principle across different anion geometries. Cs + undergoes a concentration-induced transition to a uniquely ordered state, resulting in a highly structured solution. This work provides a direct, mechanistic explanation for how cation choice dictates the ‘rules’ of solution architecture, offering a predictive basis for understanding phase behavior in complex industrial and environmental systems.

Mergelsberg, Sebastian T. [Pacific Northwest Natio↗
DOE OSTI2025

Soft x-ray spectroscopy of ammonium sulfate aerosols at varied pH conditions

Aqueous aerosols are useful model systems for understanding the physical chemistry that takes place in the Earth’s atmosphere, as well as the chemistry of other solar system objects. Ammonium sulfate aerosols are impacted by anthropogenic sources such as farming and shipping and are understood to be important seeds of cloud nucleation in the atmosphere, affecting climate. X-ray photoelectron spectroscopy and near edge x-ray absorption fine structure spectroscopy were used in tandem to probe the surface and bulk properties of aqueous (NH 4 ) 2 SO 4 , respectively. Aerosolized solutions of (NH 4 ) 2 SO 4 , some altered with NaOH to modify pH, were introduced via an aerodynamic lens to a velocity map imaging instrument for detection. The results show that as pH and sodium cation concentration increase, sulfate anion and ammonia become more prevalent at the surface, and the aerosol surface appears to become drier. However, most of the aerosol remains aqueous, with ion concentrations insensitive to the addition of NaOH. Density functional theory calculations were also performed to probe the coordination environment at the aerosol surfaces to understand the underlying phenomena. Finally, the changes seen on the surface of the aerosol underscore the importance of pH in regulating the structure and chemical properties of atmospherically relevant aerosols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Neural simulation-based inference of the neutron star equation of state directly from telescope spectra

Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of matter inside neutron stars and their equation of state are not directly visible, but determine bulk properties, such as mass and radius, which affect the star's thermal X-ray emissions. However, the telescope spectra of these emissions are also affected by the stellar distance, hydrogen column, and effective surface temperature, which are not always well-constrained. Uncertainties on these nuisance parameters must be accounted for when making a robust estimation of the equation of state. In this study, we develop a novel methodology that, for the first time, can infer the full posterior distribution of both the equation of state and nuisance parameters directly from telescope observations. This method relies on the use of neural likelihood estimation, in which normalizing flows use samples of simulated telescope data to learn the likelihood of the neutron star spectra as a function of these parameters, coupled with Hamiltonian Monte Carlo methods to efficiently sample from the corresponding posterior distribution. Our approach surpasses the accuracy of previous methods, improves the interpretability of the results by providing access to the full posterior distribution, and naturally scales to a growing number of neutron star observations expected in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Identified charged hadron production in Au+Au collisions at $\sqrt{s_{NN}}$ = 54.4 GeV with the STAR detector

Here, we present results on the production of 𝜋±, 𝐾±, 𝑝, and $\bar{𝑝}$ in Au+Au collisions at $\sqrt{𝑠_{N⁢N}}$ = 54.4~GeV using the STAR detector at RHIC, at mid-rapidity (|𝑦|< 0.1). Invariant yields of these particles as a function of transverse momentum are shown. We determine bulk properties such as integrated particle yields (𝑑 ⁢𝑁 /𝑑 ⁢𝑦 ), mean transverse momentum (⟨𝑝 𝑇 ⟩), particle ratios, which provide insight into the particle production mechanisms. Additionally, the kinetic freeze-out parameters (𝑇 kin and ⟨𝛽 𝑇 ⟩), which provide information about the dynamics of the system at the time of freeze-out, are obtained. The Bjorken energy density (𝜖 𝐵⁢𝐽 ), which gives an estimate of the energy density in the central rapidity region of the collision zone at the formation time 𝜏, is calculated and presented as a function of multiplicity for various energies. The results are compared with those from the models such as A Multi-Phase Transport (AMPT) and Heavy Ion Jet INteraction Generator (HIJING) for further insights.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

From closed shells to open shells: Coupled-cluster calculations of atomic nuclei

Coupled-cluster theory is a powerful tool for first-principles calculations of atomic nuclei, enabling accurate predictions of nuclear observables across the Segrè chart. While coupled-cluster computations are especially efficient at shell closures, extensions have been developed to tackle open-shell nuclei, by exploiting the equation-of-motion method or by expanding the coupled-cluster wave function on top of a symmetry-breaking (either deformed or superfluid) reference state. In this study, we provide a comprehensive comparison of these different formulations applied to the calcium and nickel isotopes using nuclear two-and three-body interactions from chiral effective field theory. Here, based on ground-state energies, two-neutron separation energies, and two-neutron shell gaps, different coupled-cluster computations—based on symmetry-broken reference states and equationof-motion techniques— offer consistent descriptions of bulk properties across medium-mass isotopic chains.

Marino, Francesco [Johannes Gutenberg-Universität ↗
DOE OSTI2026

Excitation spectrum and low-temperature magnetism in the disordered defect-fluorite Ho2⁢Zr2⁢O7

In this work, we report on the thermomagnetic characterization and crystalline-electric field (CEF) energy scheme of the disordered defect-fluorite Ho2⁢Zr2⁢O7. This structural phase is distinguished by the coexistence of magnetic frustration and extensive disorder, with Ho3+ and Zr4+ sharing randomly the same 4⁢𝑎 site with even 50% occupancy, and an average 1/8 oxygen vacancy per unit cell. AC magnetic susceptibility measurements performed on powder samples down to 0.5 K revealed signs of slowing spin dynamics without glassy behavior, including a frequency dependent peak at ∼1K. Yet, no evidence for long-range magnetic order is found down to 200 mK in the specific heat. Inelastic neutron scattering measurements show a weak, low-lying CEF excitation around 2 meV, accompanied by a broad level centered at 60 meV. To fit our observations, we propose an approach to account for structural disorder in the crystal-field splitting of the non-Kramers Ho3+. Our model provides an explanation to the broadening of the high-energy, single-ion excitations and suggests that the zirconate ground-state wavefunction has zero magnetic moment. Through the breaking of local symmetry, structural disorder enables the magnetic response observed in Ho2⁢Zr2⁢O7, allowing the mixing of low-lying states at finite temperatures. Finally, we show that this scenario is in good agreement with the bulk properties reported in this work.

Gardner, Jason [ORNL] (ORCID:0000000278234072)↗
DOE OSTI2024

Revealing subterahertz atomic vibrations in quantum paraelectrics by surface-sensitive spintronic terahertz spectroscopy

Understanding surface collective dynamics in quantum materials is crucial for advancing quantum technologies. For example, surface phonon modes in quantum paraelectrics are thought to be essential in facilitating interfacial superconductivity. However, detecting these modes, especially below 1 terahertz, is challenging because of limited sampling volumes and the need for high spectroscopic resolution. Here, we report surface soft transverse optical (TO1) phonon dynamics in KTaO 3 and SrTiO 3 by surface-sensitive spintronic terahertz spectroscopy that can sense the collective modes only a few nanometers deep from the surface. In KTaO 3 , the TO1 mode softens and sharpens with decreasing temperature, leveling off at 0.7 terahertz. In contrast, this mode in SrTiO 3 broadens substantially below the quantum paraelectric crossover and coincides with the hardening of a sub–milli–electron volt phonon mode related to the antiferrodistortive transition. These observations that deviate from their bulk properties may have implications for interfacial superconductivity and ferroelectricity. The developed technique opens opportunities for sensing low-energy surface collective excitations.

Chu, Zhaodong↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. 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.

EARTH SCIENCE > LAND SURFACE > SOILS↗