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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Linking Perfluorosulfonic Acid Ionomer Chemistry and High-Current Density Performance in Fuel-Cell Electrodes

Transport phenomena are key in controlling the performance of electrochemical energy-conversion technologies and can be highly complex, involving multiple length scales and materials/phases. Material designs optimized for one reactant species transport however may inhibit other transport processes. We explore such trade-offs in the context of polymer-electrolyte fuel-cell electrodes, where ionomer thin films provide the necessary proton conductivity but retard oxygen transport to the Pt reaction site and cause interfacial resistance due to sulfonate/Pt interactions. We examine the electrode overall gas-transport resistance and its components as a function of ionomer content and chemistry. Low-equivalent-weight ionomers allow better dissolved-gas and proton transport due to greater water uptake and low crystallinity but also cause significant interfacial resistance due to the high density of sulfonic acid groups. These effects of equivalent weight are also observed via in situ ionic conductivity and CO displacement measurements. Of critical importance, the results are supported by ex situ ellipsometry and X-ray scattering of model thin-film systems, thereby providing direct linkages and applicability of model studies to probe complex heterogeneous structures. Structural and resultant performance changes in the electrode are shown to occur above a threshold sulfonic-group loading, highlighting the significance of ink-based interactions. Furthermore, our findings and methodologies are applicable to a variety of solid-state energy-conversion devices and material designs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Tailoring the Weight of Surface and Intralayer Edge States to Control LUMO Energies

Abstract The energies of the frontier molecular orbitals determine the optoelectronic properties in organic films, which are crucial for their application, and strongly depend on the morphology and supramolecular structure. The impact of the latter two properties on the electronic energy levels relies primarily on nearest‐neighbor interactions, which are difficult to study due to their nanoscale nature and heterogeneity. Here, an automated method is presented for fabricating thin films with a tailored ratio of surface to bulk sites and a controlled extension of domain edges, both of which are used to control nearest‐neighbor interactions. This method uses a Langmuir–Schaefer‐type rolling transfer of Langmuir layers (rtLL) to minimize flow during the deposition of rigid Langmuir layers composed of π‐conjugated molecules. Using UV–vis absorption spectroscopy, atomic force microscopy, and transmission electron microscopy, it is shown that the rtLL method advances the deposition of multi‐Langmuir layers and enables the production of films with defined morphology. The variation in nearest‐neighbor interactions is thus achieved and the resulting systematically tuned lowest unoccupied molecular orbital (LUMO) energies (determined via square‐wave voltammetry) enable the establishment of a model that functionally relates the LUMO energies to a morphological descriptor, allowing for the prediction of the range of accessible LUMO energies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge

Background: Humans are primary drivers of environmental–contaminant exposures worldwide, including in drinking-water (DW). In the United States, point-of-use DW (POU–DW) is supplied via private tapwater (TW), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly–intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision–making. Objectives: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU–DW contaminant–mixture exposures and corresponding potential human–health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical–health–benchmark–weighted and bioactivity–weighted effects predictions across previous studies by this research group. Discussion: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supplies. Differences in contaminant or contaminant–class exposures, with important implications for DW–quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. Conclusion: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW–supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low–level inorganic–/organic–contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased public engagement in source-water protection and drinking–water treatment is necessary to reduce risks associated with long-term DW–contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Using Nanofiller Assemblies to Control the Crystallization Kinetics of High-Density Polyethylene

Polyethylene-grafted nanoparticles (NPs) are organized into a variety of assemblies in a polydisperse polyethylene melt by tailoring the graft density and molecular weights of the graft chains. Under these conditions we systematically vary NP assemble state and study is consequences on crystal nucleation and growth rates. We find that the nucleation rate is suppressed below that of the unfilled polymer for good NP spatial dispersion. However, poorer dispersion, which leads to the formation of NP assemblies, can accelerate nucleation likely by providing multiple heterogenous sites due to topographical features. We find that a key parameter, the chain overcrowding in the brush, can predict these nucleation trends – in this language, the most enhanced nucleation rate is found when the grafts are the most overcrowded, and hence the least interpenetrated with the matrix chains. This result is consistent with one other literature result which utilized short crystallizable polyethylene glycol grafts in short PEO matrices. The growth kinetics were retarded for all nanocomposites, their temperature dependences were essentially equal to that for the pure polymer (in the absence of NPs) – the NPs thus do not affect secondary nucleation, indicating that the transport of the matrix to the growth front is the rate determining step. Thus, evidently the increase in matrix viscosity, or reduction in growth rates, is directly determined by the agglomeration state of the NPs. These results are consistent with past works with bare silica NPs in PEO, and with silica NPs grafted with amorphous chains in a PEO matrix, suggesting that growth kinetics in these systems apparently follow “universal” behavior. Additionally, there are initial hints that the ratio of the effective surface area of the NP clusters per unit matrix volume provides a unified description of the NP induced confinement that slows growth kinetics. Furthermore, our work thus shows that there is an evolving understanding of the role of NPs on crystallization kinetics, in particular crystal growth where trends appear to be independent of the grafts ability to crystallize.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Dominant heterocyclic composition of dissolved organic nitrogen in the ocean: A new paradigm for cycling and persistence

Marine dissolved organic nitrogen (DON) is one of the planet’s largest reservoirs of fixed N, which persists even in the N-limited oligotrophic surface ocean. The vast majority of the ocean’s total DON reservoir is refractory (RDON), primarily composed of low molecular weight (LMW) compounds in the subsurface and deep sea. However, the composition of this major N pool, as well as the reasons for its accumulation and persistence, are not understood. Past characterization of the analytically more tractable, but quantitatively minor, high molecular weight (HMW) DON fraction revealed a functionally simple amide-dominated composition. While extensive work in the past two decades has revealed enormous complexity and structural diversity in LMW dissolved organic carbon, no efforts have specifically targeted LMW nitrogenous molecules. Here, we report the first coupled isotopic and solid-state NMR structural analysis of LMW DON isolated throughout the water column in two ocean basins. Together these results provide a first view into the composition, potential sources, and cycling of this dominant portion of marine DON. Our data indicate that RDON is dominated by 15N-depleted heterocyclic-N structures, entirely distinct from previously characterized HMW material. This fundamentally new view of marine DON composition suggests an important structural control for RDON accumulation and persistence in the ocean. The mechanisms of production, cycling, and removal of these heterocyclic-N-containing compounds now represents a central challenge in our understanding of the ocean’s DON reservoir.

58 GEOSCIENCES↗
DOE OSTI2021

Role of tunable polymer flexibility in controlling wetting behavior and thermal properties of poly(1,3-cyclohexadiene)-silica nanocomposites

We present how altering the chain flexibility affects the nanoscale organization of polymer-grafted nanoparticles (PGNPs) and its ultimate impact on macroscale thermal properties. To isolate the role of chain flexibility on wetting behavior in athermal polymer nanocomposites (PNC), the graft and matrix chemistry is kept identical by utilizing 1,3-cyclohexadiene-based polymer materials. Increasing the rigidity and molecular weight of both the graft and matrix is found to favor mixing of poly(1,3-cyclohexadiene) PCHD-grafted silica NPs with the matrix, supported by a concomitant increase in glass transition temperatures of the PNCs. Further, the associated entropic factors that drive wetting behavior and dispersion of PGNPs are discussed, emphasizing the dominant role-played by chain flexibility. Alterations in graft flexibility had the strongest impact on dispersion and Tg values of the PNC, while molecular weight (MW) plays a secondary role. This investigation is a unique demonstration of how chain flexibility alteration in athermal semiflexible systems can be used to alter NP organization by altering filler-matrix wettability which also impacts thermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrated Ion-Exchange Membrane Resin Wafer Assemblies for Aromatic Organic Acid Separations Using Electrodeionization

Aromatic acids, such as p-coumaric acid, are valuable chemical intermediates that are used in the specialty chemical industries because they are precursors to phenylpropanoid compounds. The separation of p-coumaric acid from fermentation broths is a critical step in the biochemical production process and more broadly the circular carbon economy. Electrodeionization (EDI) has been applied toward separations of low-carbon chain acids, but purifying p-coumaric acid has been challenging due to fouling and irreversible binding with ion-exchange membranes and resins. Here, we report a new membrane wafer assembly (MWA) consisting of laminated ion exchange membranes to porous ionomer-binder resin wafers for EDI. The MWAs in an EDI stack showed a 7-fold increase in p-coumaric acid capture while also using 70% less specific energy consumption when benchmarked against state-of-the-art resin wafer EDI modules. The more efficient p-coumaric acid recovery was ascribed to (i) the 38% reduction in interfacial transport resistance between the membrane and resin wafer and (ii) using imidazolium anion exchange membranes and ionomer binders in the MWA. MD simulations revealed enhanced transport rates for p-coumarate in imidazolium ionomers through π–π interactions. As a result, adopting the new MWA significantly reduced the amount of ion-exchange membranes in EDI and may lead to drastic capital cost savings.

42 ENGINEERING↗
DOE OSTI2022

Population balance models for polymer upcycling: signatures of the mechanism in the molecular weight evolution

Chemical and catalytic upcycling processes could help realize a circular plastics economy, but current models for testing mechanistic hypotheses and designing catalysts remain primitive. This work shows how proposed catalytic mechanisms can be incorporated into population balance models to predict the time evolution of molecular weight distributions. We develop models for homogeneous and heterogeneous catalysts, including catalysts that cut at chain ends and catalysts that cut at random locations. For heterogeneous catalysts, we illustrate the effect of adsorption constants that depend on polymer chain length. Here, we discuss ongoing efforts and challenges in measuring and modeling the time evolving molecular weight distributions in polymer upcycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Model-based real-time surface heat flux and temperature estimation for the DIII-D tokamak

A control-oriented model for monitoring of wall power flux densities on the DIII-D tokamak has been successfully implemented and validated experimentally. Future reactors will have to withstand severe steady state high heat flux loads on plasma-facing components (PFCs). Due to the difficulty of directly-measuring local heat fluxes on these components, monitoring and protection of PFCs during the plasma discharge can benefit from simplified physics-based real-time (RT) functional models to estimate and guide heat load control. As a first step into the development, a control-oriented model for monitoring of wall power flux densities and temperatures on DIII-D tokamak has been successfully implemented. The paper discusses the experimental demonstration and comparison of the 2-D model-based wall heat flux algorithm on the DIII-Dinner wall limiter (IWL) against infra-red camera heat flux measurements for limited plasma configurations. The paper also reports on the benchmarking of the field line tracing environment, SMITER, developed at ITER organization on DIII-D tokamak against experimental IR diagnostic data and the derivation of the component shaping weighting factors for the 2-D model-based approach. Here, the extension of the model-based approach for surface temperature estimation on the DIII-D IWL is also presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Spatially Averaged Ice Contents of Ice-Wedge Polygon Cross-Sections to 3-m Depth, July 2013, Utqiagvik, Alaska

This dataset contains spatially averaged estimates of ice content (volume percent) for two-dimensional cross-sectional profiles (from trough center to trough center to a depth of 3 meters) of low- and flat-centered ice-wedge polygons (three of each type) located near Utqiagvik, Alaska. A combination of soil pits, trenches, and cores were used to describe, sample, and map the cross-section stratigraphy of soil horizons and ice wedges for each polygon at 6 depth intervals. Observed soil horizons were assigned to four types with increasing amounts of organic components (mineral, mineral/organic, organic/mineral, and organic). The average ice contents of each soil horizon type below the permafrost boundary and wedge ice were weighted by their cross-sectional area fractions to calculate spatially averaged estimates of ice content for each polygon. In the active layer, spatially averaged estimates of volumetric water contents were similarly determined and reported here as “ice” content to enable estimates of the soil’s structurally competent porosity and excess ice in permafrost layers. In this dataset, the file AK13_ice_contents.csv includes cross-sectional area fractions and spatially averaged ice contents for soil layers and horizon types at the six depth intervals. The file AK13_permafrost_ice_fractions.csv contains the calculated partitioning of ice contents into pore ice and excess ice fractions for the three permafrost-dominated depth intervals. In addition, there is a data dictionary file for each of these data files and a file-level metadata file. These data were generated by the Department of Energy’s Soil Carbon Response to Environmental Change Scientific Focus Area and were used as inputs to model simulations examining the consequences of thaw-affected subsidence and microtopography change on active layer thickness of low-relief polygonal tundra landscapes in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Semiconducting Small Molecules as Active Materials for p-Type Accumulation Mode Organic Electrochemical Transistors

A series of semiconducting small molecules with bithiophene or bis-3,4-ethylenedioxythiophene cores are designed and synthesized. The molecules display stable reversible oxidation in solution and can be reversibly oxidized in the solid state with aqueous electrolyte when functionalized with polar triethylene glycol side chains. Evidence of promising ion injection properties observed with cyclic voltammetry is complemented by strong electrochromism probed by spectroelectrochemistry. Blending these molecules with high molecular weight polyethylene oxide (PEO) is found to improve both ion injection and thin film stability. The molecules and their corresponding PEO blends are investigated as active layers in organic electrochemical transistors (OECTs). For the most promising molecule:polymer blend (P4E4:PEO), p-type accumulation mode OECTs with µA drain currents, μS peak transconductances, and a µC* figure-of-merit value of 0.81 F V -1 cm -1 s -1 are obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluating solvothermal and mechanochemical routes towards the metal–organic framework Mg 2 ( m -dobdc)

Metal–organic frameworks bearing coordinatively unsaturated Mg(II) sites are promising materials for gas storage, chemical separations, and drug delivery due to their low molecular weights and lack of toxicity. Furthermore, there remains a limited number of such MOFs reported in the literature. Herein, we investigate the gas sorption properties of the understudied framework Mg 2 (m-dobdc) (dobdc 4– = 4,6-dioxido-1,3-benzenedicarboxylate) synthesized under both solvothermal and mechanochemical conditions. Both materials are found to be permanently porous, as confirmed by 77 K N 2 adsorption measurements. In particular, Mg 2 (m-dobdc) synthesized under mechanochemical conditions using exogenous organic base displays one of the highest capacities reported to date (6.14 mmol g –1 ) for CO 2 capture in a porous solid under simulated coal flue gas conditions (150 mbar, 40 °C). As such, mechanochemically synthesized Mg 2 (m-dobdc) represents a promising new framework for applications requiring high gas adsorption capacities in a porous solid.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing the Morphology and Mobility of Amines in Porous Silica CO 2 Sorbents by 1 H T 1 – T 2 Relaxation Correlation NMR

Molecular and oligomeric amines supported in porous oxide supports are a promising class of CO 2 sorbent materials studied for CO 2 removal from diverse streams such as flue gas and ambient air. Among the various amines investigated, low molecular weight, hyperbranched poly(ethyleneimine) (PEI), and tetraethylenepentamine (TEPA) are among the most extensively studied. While macroscopic structure–performance relationships relating the support structure, amine loading, and other factors affecting CO 2 sorption capacities and kinetics have been developed, structural and dynamic information about the organic amine phase in the porous support is less plentiful. The structure and mobility of amines impregnated in the pores of porous supports directly impact gas sorption, as the accessibility of amine sites in the pores directly relates to amine distribution in the pores and overall pore filling as well as the dynamics of the amine chains. Here, we prepare a family of mesoporous silica SBA-15 materials containing varying loadings of oligomeric (PEI) and molecular (TEPA) amines. 1 H T 1 –T 2 relaxation correlation solid-state NMR experiments are used to characterize the structural and dynamic properties of the confined amines. Both TEPA and PEI are shown to form multiple different domains in the pores, each with distinguishable dynamic properties. TEPA and PEI form more rigid layers around the silica support walls at lower organic loading fractions, characterized by lower mobilities, followed by the formation of more mobile domains less engaged in pore wall interactions at higher loadings. TEPA shows faster mobilities than PEI because of its lower molecular weight. TEPA also appears to more easily transfer between domains within the pores, leading to generally faster CO 2 uptake rates with higher sorption capacities, while PEI located closer to the pore walls remained much less mobile and is thus less engaged in CO 2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Microstructural, Corrosion and Mechanical Characterization of Friction-Stir Welded Joints Between Aluminum and Magnesium Alloys

Friction Stir Welding (FSW) of Aluminum-Magnesium (Al-Mg) alloys has garnered increasing attention due to its wide-ranging applications in the automotive and aerospace industries. The microstructural, corrosion, and mechanical properties of FSW Al-Mg welds under selected conditions are critical factors that must be well-investigated to ensure their durability and performance. In this study, electrochemical tests, including Open Circuit Potential (OCP), Linear Polarization Resistance (LPR), Potentiodynamic Polarization Scan (PD), and Electrochemical Impedance Spectroscopy (EIS), have been used to analyze the corrosion resistance of these welds, along with weight loss measurements through cyclic corrosion testing (CCT) and surface evolution via SEM over an 8-week period. Mechanical properties are evaluated through microindentation, nanoindentation, fatigue, and lap-shear tests. The results of the electrochemical tests reveal that the corrosion properties of the center weld zone differ from those of the two base alloys. Indentation tests indicate that the weld zone behaves differently from the base alloys. Surprisingly, the lap shear strength did not decrease significantly even after 8 weeks of cyclic corrosion testing, indicating that the joint prevented any ingress of the electrolyte. Fatigue testing showed that applying an adhesive between the Al and Mg joint improved the fatigue life to some extent, although the corrosion resistance reduced due to the discontinuous bonding of the adhesive layer. Overall, these findings highlight the importance of investigating the corrosion and mechanical properties of FSW Al-Mg welds and provide valuable insights for future modeling works.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗