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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 163 records · Page 9

Complexation of Tc(IV) with ${\text{SO}}_{4}^{2–}$ in NaCl Medium

We report on the experimental determination of the stability constant for the complexation of the Tc(IV) cation by ${\text{SO}}_{4}^{2–}$ at 1.0 mol kg -1 ionic strength (NaCl) and pcH 1.51 ± 0.05, using a solvent extraction method. This research represents a first step in determining unknown thermodynamic parameters for the complexation of Tc(IV) by simple polyatomic anions. Radiotracer studies were carried out with 99 Tc and 35 S, using both HDEHP and TOPO as extractants, to characterize the mechanism of the solvent extraction and to examine the extraction of the competing species, TcO(HSO 4 )+ and TcOSO 4 , into the organic phase. The apparent stability constant log 10 β app for the complexation of Tc(IV) by sulfate was found to be 1.13 ± 0.04.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Various Low-Symmetry Phases in High- χ and Conformationally Asymmetric PDMS- b -PTFEA Copolymers

Since the discovery of the Frank–Kasper (FK) phase a decade ago, single-component block copolymer systems have offered unique opportunities to explore the structural and phase-transition properties of topologically close-packed FK phases composed of point-particle motifs. Here, we present the formation of complex low-symmetry phases and their thermodynamic stability using high-χ and high-ε linear diblock copolymers, where χ and ε are the Flory–Huggins interaction parameter and conformational asymmetry between the two blocks, respectively. In this work, a series of polydimethylsiloxane-b-poly(2,2,2-trifluoroethyl acrylate) (PDMS-b-PTFEA) copolymers are prepared by tuning the volume fraction ($f_{\text{PTFEA}}$) of a minor PTFEA block. The packing structures of PDMS-b-PTFEAs are mapped in the space of temperature versus $f_{\text{PTFEA}}$ using X-ray scattering measurements. In addition to the packing structures reported earlier, we identify another A15 phase at higher $f_{\text{PTFEA}}$ close to a hexagonally packed cylinder (HEX) phase and establish the phase sequence of HEX–A15–σ–C14–BCC with decreasing $f_{\text{PTFEA}}$. Theoretical calculation of relative free-energy densities confirms the experimental phase sequence of the composition-dependent sphere-packing structures. Interestingly, the domain sizes of three-dimensional (3D) sphere-packing structures are nearly temperature-invariant compared to that of a two-dimensional HEX structure, and we attribute this dimensional stability to the strong enthalpic effects in the formation of 3D packing structures and the geometrical characteristics of spherical domains. Our results demonstrate that the interaction parameter χ, together with the known role of conformational asymmetry ε, serves as the primary thermodynamic parameter for selecting and stabilizing various low-symmetry packing structures in sphere-forming linear diblock copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Student-Friendly Guide to Molecular Integrals

Preceding even the Hartree–Fock method, molecular integrals are the very foundation upon which quantum chemical molecular modeling depends. Discussions of molecular integrals are normally found only in advanced and technical texts or articles. The objective of the present article is to provide less experienced readers, or students in a physical/computational chemistry course, a thorough understanding of molecular integrals. Through a series of detailed Handouts, the student/reader can participate in the derivation of molecular integrals, and in turn implement them in computer code. Hartree–Fock theory is discussed in enough detail to motivate the molecular integrals and address such topics as the atomic orbital basis. An introduction to the programming language of choice, Python3, is provided, tailored toward developing the essential skills necessary for implementing molecular integrals. In conclusion, the article is intended to be useful not only to instructors of physical/computational chemistry, but also to any reader who has independently sought a primer on this elusive subject.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Particle acceleration in relativistic magnetic flux-merging events

Using analytical and numerical methods (fluid and particle-in-cell simulations) we study a number of model problems involving merger of magnetic flux tubes in relativistic magnetically dominated plasma. Mergers of current-carrying flux tubes (exemplified by the two-dimensional ‘ABC’ structures) and zero-total-current magnetic flux tubes are considered. In all cases regimes of spontaneous and driven evolution are investigated. We identify two stages of particle acceleration during flux mergers: (i) fast explosive prompt X-point collapse and (ii) ensuing island merger. The fastest acceleration occurs during the initial catastrophic X-point collapse, with the reconnection electric field of the order of the magnetic field. During the X-point collapse, particles are accelerated by charge-starved electric fields, which can reach (and even exceed) values of the local magnetic field. The explosive stage of reconnection produces non-thermal power-law tails with slopes that depend on the average magnetization $\unicode[STIX]{x1D70E}$ . For plasma magnetization $\unicode[STIX]{x1D70E}\leqslant 10^{2}$ the spectrum power-law index is $p>2$ ; in this case the maximal energy depends linearly on the size of the reconnecting islands. For higher magnetization, $\unicode[STIX]{x1D70E}\geqslant 10^{2}$ , the spectra are hard, $p<2$ , yet the maximal energy $\unicode[STIX]{x1D6FE}_{\text{max}}$ can still exceed the average magnetic energy per particle, ${\sim}\unicode[STIX]{x1D70E}$ , by orders of magnitude (if $p$ is not too close to unity). The X-point collapse stage is followed by magnetic island merger that dissipates a large fraction of the initial magnetic energy in a regime of forced magnetic reconnection, further accelerating the particles, but proceeds at a slower reconnection rate.

Physics↗

Materials design of perovskite solid solutions for thermochemical applications

Perovskites are excellent candidate materials as oxygen carriers in thermochemical processes. Due to their versatile composition, it is possible to fine-tune the perovskite's properties. Here, we present a method for the rational design of AMO 3– δ perovskite solid solutions with two different species on the Msite in order to tune their redox behavior. To account for the different ionic radii of different transition metal species M, two distinct ions are used in a solid solution on the A site, allowing tolerance-factor adjusted materials design. Using this methodology, we can create stable perovskites over a large range of different compositions. Leveraging the infrastructure of Materials Project, we calculate redox enthalpies for the reduction of over 240 of these $(\text {A}^{\prime}_x\text {A}^{\prime\prime}_{1-x})(\text {M}^{\prime}_y\text {M}^{\prime\prime}_{1-y})$O 3 perovskites to their brownmillerite phases based on density functional theory (DFT). We compare this data to experimentally measured data on thermodynamics of 24 of these materials to verify our theoretical framework. An empirical model is formulated for predicting the enthalpy and entropy changes as a function of the perovskites non-stoichiometry δ , which can be used to simulate the equilibrium composition as a function of temperature and oxygen partial pressure and to create a perovskite search engine based on an energetic analysis of the redox cycles. The data has been added as a contribution to MPContribs, which now includes publicly available user-controlled interactive graphs based on our theoretical and experimental data.

36 MATERIALS SCIENCE↗

Joint galaxy–galaxy lensing and clustering constraints on galaxy formation

ABSTRACT We compare predictions for galaxy–galaxy lensing profiles and clustering from the Henriques et al. public version of the Munich semi-analytical model (SAM) of galaxy formation and the IllustrisTNG suite, primarily TNG300, with observations from KiDS + GAMA and SDSS-DR7 using four different selection functions for the lenses (stellar mass, stellar mass and group membership, stellar mass and isolation criteria, and stellar mass and colour). We find that this version of the SAM does not agree well with the current data for stellar mass-only lenses with $M_\ast \gt 10^{11}\, \mathrm{ M}_\odot$. By decreasing the merger time for satellite galaxies as well as reducing the radio-mode active galactic nucleus accretion efficiency in the SAM, we obtain better agreement, both for the lensing and the clustering, at the high-mass end. We show that the new model is consistent with the signals for central galaxies presented in Velliscig et al. Turning to the hydrodynamical simulation, TNG300 produces good lensing predictions, both for stellar mass-only (χ2 = 1.81 compared to χ2 = 7.79 for the SAM) and locally brightest galaxy samples (χ2 = 3.80 compared to χ2 = 5.01). With added dust corrections to the colours it matches the SDSS clustering signal well for red low-mass galaxies. We find that both the SAMs and TNG300 predict $\sim 50\, {{\ \rm per\ cent}}$ excessive lensing signals for intermediate-mass red galaxies with 10.2 < log10M*[M⊙] < 11.2 at $r \approx 0.6\, h^{-1}\, \text{Mpc}$, which require further theoretical development.

79 ASTRONOMY AND ASTROPHYSICS↗

Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.

2018 NEON and 2025 CHESS Campaigns↗

H2OI95: A Stand-Alone Fortran Code for Evaluating the IAPWS-95 Equation-of-State Model for Water

H2OI95 is a stand-alone Fortran code for evaluating the IAPWS-95 equation-of-state model (Wagner and Pruss, 2002) for the thermodynamic properties of water. It further evaluates the corresponding thermochemical properties of water consistent with the CODATA recommendations (Cox et al., 1989). The IAPWS-95 model is based on a model equation for the dimensionless Helmholtz energy for which the primary variables are the inverse reduced temperature (τ = T cr /T) and reduced density ( δ= ρ/ρ cr ). Here T is the absolute temperature (K), ρ is density (kg/m 3 ), and the subscript “cr” refers to the critical point of water (647.096 K and 22.064 MPa pressure in this model, for which ρ cr is 322 kg/m 3 ). The code solves four basic types of problems, distinguished by the specified inputs: 1, Temperature (K) and density (ρ kg/m 3 ) or reduced density (δ) 2. Temperature (K) and pressure (MPa). 3. Temperature (K) on the saturation (liquid-vapor equilibrium) curve 4. Pressure (MPa) on the saturation curve Each type of problem is run using a corresponding input (text) file. All but the first type of problem require iteration. For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network

Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. This work addresses several important tasks of visualizing and predicting short term text representation shift, i.e. the change in a word’s contextual semantics. We study the relationship between short-term concept drift and representation shift on a large social media corpus – VKontakte collected during the Russia-Ukraine crisis in 2014 – 2015. We visualize short-term representation shift for example keywords and build predictive models to forecast short-term shifts in meaning from previous meaning as well as from concept drift. We show that short-term representation shift can be accurately predicted up to several weeks in advance and that visualization provides insight into meaning change. Our approach can be used to explore and characterize specific aspects of the streaming corpus during crisis events and potentially improve other downstream classification tasks including real-time event forecasting in social media.

concept drift↗

Incorporation of rare earth elements $\text{Sc}$, $\text{Y}$ and $\text{La}$ into gibbsite

Rare earth elements (REE) are increasingly critical resources in technological applications, but the current understanding of their separation by uptake into minerals remains limited. We examined the adsorption and solubilization of scandium (Sc), yttrium (Y), and lanthanum (La) into aluminum hydroxide (gibbsite, Al(OH) 3 ). Based on spectroscopic investigations such as inductively coupled plasma-optical emission spectroscopy (ICP-OES) and time of flight-secondary ion mass spectrometry (ToF-SIMS), only Sc exhibited favorable incorporation and adsorption (0.66 and 0.06 atom%, respectively). Analysis of solid state 45 Sc magic angle spinning-nuclear magnetic resonance spectroscopy (MAS-NMR) indicated that Sc exhibits an octahedral coordination consistent with isolated substitutions for Al in the gibbsite structure, leading to a increase in lattice constants detectable by X-ray diffraction. Density functional theory (DFT) calculations reinforced this interpretation by reproducing the detected structural distortion as well as demonstrating the relatively favorable energetic basis for Sc incorporation into gibbsite by substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unveiling Highly Sensitive Active Site in Atomically Dispersed Gold Catalysts for Enhanced Ethanol Dehydrogenation

Developing a desirable ethanol dehydrogenation process necessitates a highly efficient and selective catalyst with low cost. Herein, we show that the “complex active site” consisting of atomically dispersed Au atoms with the neighboring oxygen vacancies (Vo) and undercoordinated cation on oxide supports can be prepared and display unique catalytic properties for ethanol dehydrogenation. The “complex active site” Au–Vo–Zr 3+ on Au 1 /ZrO 2 exhibits the highest H 2 production rate, with above 37,964 mol H 2 per mol Au per hour (385 g H 2 $\text{g}^{-1}_{\text{Au}} \text{h}^{–1}$) at 350 °C, which is 3.32, 2.94 and 15.0 times higher than Au 1 /CeO 2 , Au 1 /TiO 2 , and Au 1 /Al 2 O 3 , respectively. Combining experimental and theoretical studies, we demonstrate the structural sensitivity of these complex sites by assessing their selectivity and activity in ethanol dehydrogenation. Our study sheds new light on the design and development of cost-effective and highly efficient catalysts for ethanol dehydrogenation. Fundamentally, atomic-level catalyst design by colocalizing catalytically active metal atoms forming a structure-sensitive “complex site”, is a crucial way to advance from heterogeneous catalysis to molecular catalysis. Finally, our study advanced the understanding of the structure sensitivity of the active site in atomically dispersed catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Process Engineering to Increase the Layered Phase Concentration in the Immediate Products of Flame Spray Pyrolysis

Flame-spray-pyrolysis (FSP) is a robust and scalable process to synthesize particles at the commodity-scale. FSP has been used to produce the precursor powders which were converted to the layered structure $(R\bar{3m} \text { phase})$ by a postannealing step in making nickel-rich cathode materials (NCMs). Theoretically, the high flame temperature (normally >1500 K) in FSP can provide adequate energy for the phase conversion from rock-salt to layered structures and potentially enables one-step synthesis. However, the high flame temperature is a critical issue to cause lithium loss and structural degradation, preventing the formation of the layered phase. Here, guided by the gaseous nucleation theory, we implemented several FSP processes with different solution recipes. The layered phase concentration in the as-burned products can be increased with the solution enthalpies. By adding a rapid quench step to suppress the lithium loss and phase degradation, the layered phase can be further increased. This work contributes new ideas to innovating process regarding the process efficiency and throughput of manufacturing cathode materials at a large scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data Mining Scientific Literature Demonstrates Use of Biological and Medical Data Across Scientific Disciplines

The Protein Data Bank (PDB) was established as the 1st open access digital data resource in biology and medicine. Today, the PDB archive contains over 140,000 atomic‐level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. About 20 new structures are deposited daily. PDB data is used in basic and applied research, patent applications, discovery of lifesaving drugs, product innovation, and education. About 80% of all PDB structures deposited have a “primary citation,” which is the first paper to describe the molecule and its structure and function. In turn, these primary citations have contributed to more than 1 million publications. An initial study by Clarivate Analytics on the Nucleic Acids Research publication demonstrated that PDB data drive high‐impact research in diverse scientific fields. To build on this study, we used Python programming to perform several data mining studies to understand the impact of these structures in fundamental biology, biomedicine, and energy in the scientific literature. The scientific literature database, Web of Science, tracks scientific article metrics such as the number of times cited, subject category, year published, funding source, and keywords. Web of Science data for PDB primary citations was compiled as used as the data set. Two main investigations were performed. In the first, we examined the number of citations per article (data overall and by individual subject categories) to develop “top 10 cited structures” lists and analyzed for trends. In the second investigation, we extended our data mining analysis to consider for each main subject category, the papers with the most citations and the structures they cite, and the most frequently occuring keywords. We have observed different aspects of biological data utility in various subject areas, at times in ways unanticipated from the structures' primary citation. This research demonstrates the value of biological data from the PDB by showing the diverse ways in which the data are being used. Support or Funding Information RCSB PDB is funded by a grant (DBI‐1338415) from the National Science Foundation, the National Institutes of Health, and the US Department of Energy. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Verdiguel, Natalie↗

Group additivity values for the heat of formation of C 2 –C 8 alkanes, alkyl hydroperoxides, and their radicals

A set of 58 group additivity values (GAV) for the calculation of the heat of formation is derived from an extensive and accurate database of 192 ab initio heats of formation. The ab initio values are from companion calculations at the CCSD(T)–F12/cc-pVTZ-F12//B2PLYPD3/cc-pVTZ level of theory employing second order connectivity based hierarchy reference reactions with ANL energies for the reference species. This database of 192 species consists of alkanes (RH), alkyl radicals ($\dot{\text {R}}$), alkyl hydroperoxides (RO 2 H), alkyl-peroxy (R$\dot{\text {O}}$ 2 ) radicals, and hydroperoxy-alkyl ($\dot{\text {Q}}$OOH) radicals of all of the isomers of C 2 –C 5 alkane fuels and a select set of C 6 –C 8 isomers. The GAV and ab initio based enthalpies for this dataset show excellent agreement, with an estimated 2σ uncertainty of 0.9 kcal mol –1 . Among the 58 GAV terms, 40 are refinements of previously reported terms, while 18 are newly developed. These new GAV terms are mainly non-next-nearest neighbor interactions (NNI) and β-corrections. The inclusion of these new groups significantly improves the accuracy of the GAV estimates of the heats of formation. Finally, the updated GAVs can be used with increased confidence to estimate the heats of formation of combustion relevant hydrocarbons and oxygenated hydrocarbons and their corresponding radicals, which are important in predicting low-temperature chemistry and are critical in the development of accurate chemical kinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Oxidation potentials of phenols and anilines: correlation analysis of electrochemical and theoretical values

As described in the main text, we classified our voltammograms into four types. For phenols, most compounds were type I or type II, except four phenols that were type III (4-nitrophenol, 4-cyanophenol, DNOC, and 4-hydroxyacetphenone); and two phenols that were type IV (4-aminophenol and dopamine). Almost all of the compounds gave the same type by SCV and SWV, except for 2,4-dinitrophenol (whose current went up and down and therefore could be considered a type II or III), 4-cyanophenol (which fell into a type III for SCV, but whose current went up and down in SWV (type II or III)), and 4-hydroxyacetophenone (which was a type III in SCV, but a type II in SWV). The majority of the anilines were type I except for p-toluidine (type II) and 4-methyl-3-nitroaniline and 2-methoxy-5-nitroaniline (both were type I for SWV, but for SCV fell into type III and type II respectively).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Extracting Material Property Measurements from Scientific Literature with Limited Annotations

Extracting material property data from scientific text is pivotal for advancing data-driven research in chemistry and materials science; however, the extensive annotation effort required to produce training data for named entity recognition (NER) models for this task often makes it a barrier to extracting specialized data sets. Here, in this work, we present a comparative study of the conventional, supervised NER methodology to alternative few-shot learning architectures and large language model (LLM)-based approaches that mitigate the need to label large training data sets. We find that the best-performing LLM (GPT-4o) not only excels in directly extracting relevant material properties based on limited examples but also enhances supervised learning through data augmentation. We supplement our findings with error and data quality assessments to provide a nuanced understanding of factors that impact property measurement extraction.

36 MATERIALS SCIENCE↗

Denudation, solute export, landscape evolution modeling, and geographic information system data for the East River watershed, Colorado, USA (2020-2024)

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of lithologic controls on denudation, solute export, carbon-scaling relationships, and transient landscape evolution in the East River watershed near Crested Butte, Colorado, USA. The package includes GIS layers used to produce the Figure 2 map, including drainage, hillshade, lithology, sample locations, and basin polygons, together with comma-separated value (CSV) tables and matching CSV data dictionaries. One group of tables reports sample-level and catchment-level information for river-sediment samples analyzed for in situ-produced cosmogenic beryllium-10 (10Be), including sample names, outlet elevations, geographic coordinates, upstream drainage area, rock-type classes, production-rate scaling scheme, analyzed nuclide, catchment-averaged denudation rates, and associated lower and upper analytical uncertainties. Sample and catchment attributes provide the basis for comparing denudation rates across intrusive, shale, sedimentary, and mixed-lithology settings. A second group of tables reports supporting information for landscape-evolution modeling and the mapped geologic framework of the study area. Included files list parameter values and definitions for the two-phase landscape-evolution simulations, summarize full-domain model erosion fluxes and topographic metrics for different simulation configurations, provide a fixed-area carbon-model scaling table, and summarize mapped geologic units within the East River study domain, including geologic code, formation name, lithologic description, mapped area, and lithologic class grouping. Model outputs and geologic summaries support interpretation of transient landscape behavior and its relation to the mapped distribution of shale, intrusive, sedimentary, and surficial units. A third group of tables reports hydrologic and hydrochemical information used to quantify dissolved export from the watershed. Included files provide site-level values for drainage area, mean annual solute export, standard error of annual export, area-normalized solute yield, and equivalent weathering rate for five East River monitoring sites, along with metadata describing the number, sampling cadence, and date range of discharge records and partial and full total dissolved solids observations used in the solute-yield analyses. The package also contains a supplementary daily ion-load time series with daily mean discharge, discharge observation counts, dissolved concentrations, and daily loads for calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, fluoride, dissolved silica, charge-balance bicarbonate, and total dissolved solids. The package contains GIS files, comma-separated value files (.csv), CSV data dictionaries, a file-level metadata table, a package-tree text file, and a readme text file.

10Be↗