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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 OSTI2024

Influence of high-strain-rate compression and subsequent heat treatment on (TiNbZr) 89 (AlTa) 11 refractory high-entropy alloys: Dynamic-mechanical behavior and microstructural changes

This study explored the dynamic-mechanical behavior of a novel low-density (TiNbZr) 89 (AlTa) 11 refractory high-entropy alloy (RHEA) across strain rates ranging from 1.0×10 3 to 3.5×10 3 s –1 . A significant increase in the yield and ultimate compressive strengths with rising strain rates up to 3.0×10 3 s –1 was observed and attributed to enhanced dislocation activities and stress-induced microstructural transformations. The formation of the B2 phase and Zr 5 Al 3 precipitates was found to be crucial in bolstering the alloy strength at high strain rates. Beyond strain rates of 3.0×10 3 s –1 , a decrease in strength occurred due to thermal softening and strain localization. Microstructural analyses at 3.5×10 3 s –1 revealed grain refinement, the development of micro shear bands, and dislocation tangles, which were indicative of dynamic recrystallization. Besides, the findings also revealed that the post-dynamic compression heat treatment further enhanced the hardness and microstructural stability of the alloy. These results highlight the potential of the (TiNbZr) 89 (AlTa) 11 RHEA for applications requiring materials with high strength-to-weight ratios, particularly in dynamically loaded environments. It is expected that the results of this study will further advance our fundamental understanding of the behavior of RHEAs under extreme conditions, thereby opening new avenues for material innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Radiation-induced segregation in dilute Fe–Cr: A rate-theory framework for the Cr enrichment–depletion transition at the grain boundary

Radiation-induced segregation (RIS) poses a significant challenge for ferritic Fe–Cr alloys under irradiation, as it can compromise mechanical integrity and increase susceptibility to intergranular corrosion. Yet, the mechanisms governing Cr segregation remain incompletely understood. Here, in this study, we present a physics-based rate-theory model parameterized using self-consistent mean field theory-based Onsager transport coefficients to investigate RIS at the grain boundary in dilute Fe-(0.1 at. %) Cr. Under equal production rates of vacancies and self-interstitial atoms (SIA), and their equal absorption rates by bulk dislocations, the model simulates the experimentally observed transition from Cr enrichment at low temperatures to depletion at higher temperatures. Under these unbiased conditions, systematic investigation reveals that while temperature-dependent transport properties dictate the segregation direction, dose rate, grain size, and dislocation density only influence the magnitude and spatial extent of Cr segregation. However, under more realistic conditions of preferential vacancy production within damage cascade and/or preferential SIA absorption by bulk dislocations, the enrichment-to-depletion transition shifts to lower temperatures. Our findings demonstrate that RIS predictions based solely on transport coefficients are valid only under symmetric point defect flux conditions, and that biases in defect production and absorption must be considered for accurate predictions. This work provides a mechanistic framework for understanding RIS in ferritic alloys and informs alloy design for advanced nuclear systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Analysis of Second Target Station Target Removal Dose Rates

The Second Target Station (STS) project at Oak Ridge National Laboratory’s spallation neutron source is a crucial initiative for maintaining U.S. leadership in neutron sciences. The STS aims to create the world’s brightest pulsed cold neutron source, enabling cutting-edge research across various scientific disciplines. To ensure safe and efficient maintenance operations, understanding the effects of shutdown dose rates from activated components within the STS target systems is essential. This study establishes a computational framework for calculating decay gamma sources and subsequent shutdown dose rates utilizing advanced methods to account for all activation channels, including high-energy interactions down to thermal neutron capture. This study describes a novel integration of multiple tools and provides an effective means of analyzing activation and shutdown dose rates at spallation neutron facilities. A custom-developed script automates the decay gamma source generation process, ensuring proper sampling during the variance reduction phase, which is critical for accurate predictions of shutdown dose rates.

Transmutation↗
DOE OSTI2026

Data-based filtered dissipation rate modelling for multi-modal turbulent combustion: evaluating a priori model generalizability

Manifold-based models offer a computationally efficient alternative to directly transporting the thermochemical state in computational simulations of turbulent reacting flows, projecting the high-dimensional thermochemical state-space onto a low-dimensional manifold. Recent efforts have yielded a manifold-based model applicable to multi-modal combustion, enabling reconstruction of the thermochemical state from solutions to two-dimensional manifold equations in mixture fraction and generalized progress variable that are parameterised by three scalar dissipation rates. In coarse-grained simulations such as Large Eddy Simulation (LES), closure of the multi-modal manifold equations and subfilter variances/covariance requires closure of three filtered scalar dissipation rates. Here, the present work adopts a data-based approach, providing closure for the three filtered scalar dissipation rates via deep neural networks (DNNs). High-fidelity datasets corresponding to an autoigniting n-dodecane jet flame and a bluff body swirl-stabilized confined lifted spray flame of two aviation fuels (Jet-A and C1) with different ignition propensities are leveraged to generate training data that spans a diverse range of thermodynamic conditions and combustion modes, including low- and high-temperature ignition regimes in addition to premixed and nonpremixed behaviour. A final DNN model is trained to enforce inherent physical constraints by learning nonlinear functional transformations of the three filtered scalar dissipation rates. The generalizability of this constrained DNN model is demonstrated a priori via conditional statistics evaluated on the lifted spray flame with C1–a configuration that had not been included in the training data. Excellent DNN agreement with conditional DNS statistics is observed, and integrated gradients are computed to identify the most sensitive input variables. The similarity of the marginal PDFs of the most informative input variables and outputs across configurations are quantified via the Wasserstein metric, demonstrating that data-based models may successfully generalize to unseen parametric conditions so long as the most informative input variables share similar distributions across training and testing datasets.

Data-based modelling↗
DOE OSTI2025

Rooftop Solar Deployment, Potential Electricity Rate Impacts, and the Timing of Revisions to State Net Metering Policy

Most U.S. states require utilities to credit residential solar photovoltaic (PV) output at the retail electricity rate, a structure known as net metering. However, 12 states have replaced net metering with alternative rate structures that reduce PV adopter bill savings. The share of households living in states that require net metering fell from around 84% in 2014 to around 57% by the end of 2023. Proponents of net metering revisions have argued that net metering can affect the electricity rates of customers without PV. This report analyzes the relationships between state PV deployment levels, potential electricity rate impacts on PV nonadopters, and the timing of revisions to net metering policy.

14 SOLAR ENERGY↗
DOE OSTI2025

Spent Nuclear Fuel Receipt Rate Analysis within an Integrated Waste Manage-ment System Architecture that Includes Consolidated Interim Storage

A key parameter in analyzing the performance of an integrated waste management system (IWMS) architecture for the disposition of spent nuclear fuel (SNF) is the SNF receipt rate from reactor and other custodian sites. The introduction of one or more federal consolidated interim storage facilities (CISFs) into the IWMS architecture can enable the receipt rate profile as a function of time to be accelerated relative to system architectures without a CISF. The question then arises as to what an optimal SNF receipt rate profile for an IWMS architecture might be in view of practical constraints and desired system performance attributes and associated metrics. This paper describes a sensitivity study on SNF receipt rates and the associated results for a selected set of IWMS scenarios aimed an in-forming near-term planning for interim storage capabilities and transportation assets. Two different strategies are compared, one that fills an initial CISF quickly and then idles the transportation system while a disposal system is prepared, and a second strategy that aims to provide a more continuous use of transportation assets and receipt capabilities at the IWMS while the disposal system is readied for SNF receipt. Cost considerations and other factors such as impact on timing of clearing reactor sites of SNF, efficient use of capital assets, and other metrics, including those which may be important to a CISF host community, are examined. Based on the analysis, an initial approach is presented targeting a continuous receipt strategy while having the flexibility to step up receipt capabilities to a reasonable degree when needed and beneficial within overall system constraints.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Monodomain Liquid‐Crystal Elastomer Lattices for Broad Strain‐Rate Mechanical Damping

Designing structures that effectively dissipate energy across a broad range of mechanical loading rates, including those from compression, shock, and vibration, poses a significant engineering challenge. In this study, liquid‐crystal elastomers (LCEs), which possess anisotropic properties due to the alignment of their polymer backbone, are explored. As a result, LCEs exhibit a soft elastic response under mechanical loading, making them ideal for energy dissipation. Advances in additive manufacturing (AM) enable simple fabrication of foamlike dissipative structures with complex lattice geometries. Herein, direct ink write 3D printing, an extrusion AM method, is used to fabricate aligned, monodomain LCE lattice structures for broad strain‐rate mechanical damping. In this work, it is shown that these structures can dissipate strain energy in quasi‐static environments, comparable to traditional elastomeric lattices, and provide improved damping under high strain‐rate drop testing due to LCE soft elasticity. Additionally, under dynamic mechanical vibration, monodomain LCE lattices enhance damping at structural natural frequencies and provide high‐frequency attenuation. Finally, in these findings, a promising method is presented for fabricating mechanical damping devices that effectively dissipate energy across a broad range of loading rates.

3D printings↗
DOE OSTI2025

Measurement of the $\textrm{t}\overline{\textrm{t}}\textrm{H}$ and tH production rates in the H → $\textrm{b}\overline{\textrm{b}}$ decay channel using proton-proton collision data at $\sqrt{s}$ = 13 TeV

An analysis of the production of a Higgs boson (H) in association with a top quark-antiquark pair ($\textrm{t}\overline{\textrm{t}}\textrm{H}$) or a single top quark (tH) is presented. The Higgs boson decay into a bottom quark-antiquark pair (H → $\textrm{b}\overline{\textrm{b}}$) is targeted, and three different final states of the top quark decays are considered, defined by the number of leptons (electrons or muons) in the event. The analysis utilises proton-proton collision data collected at the CERN LHC with the CMS experiment at $\sqrt{s}$ = 13 TeV in 2016–2018, which correspond to an integrated luminosity of 138 fb −1 . The observed $\sqrt{s}$ production rate relative to the standard model expectation is 0.33 ± 0.26 = 0.33 ± 0.17(stat) ± 0.21(syst). Additionally, the $\textrm{t}\overline{\textrm{t}}\textrm{H}$ production rate is determined in intervals of Higgs boson transverse momentum. An upper limit at 95% confidence level is set on the tH production rate of 14.6 times the standard model prediction, with an expectation of ${19.3}_{-6.0}^{+9.2}$. Finally, constraints are derived on the strength and structure of the coupling between the Higgs boson and the top quark from simultaneous extraction of the $\textrm{t}\overline{\textrm{t}}\textrm{H}$ and tH production rates, and the results are combined with those obtained in other Higgs boson decay channels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Local practically safe extremum seeking with assignable rate of attractivity to the safe set

We present Assignably Safe Extremum Seeking (ASfES), an algorithm designed to minimize a measured, static objective function while maintaining a measured, static metric of safety (a control barrier function or CBF) to be positive in a practical sense. We ensure that for trajectories with safe initial conditions, the violation of safety can be made arbitrarily small through appropriately chosen design constants. We also guarantee an assignable “attractivity” rate: from unsafe initial conditions, the trajectories approach the safe set, in the sense of the measured CBF, at a rate no slower than a user-assigned rate. Similarly, from safe initial conditions, the trajectories approach the unsafe set, in the sense of the CBF, no faster than the assigned attractivity rate. The feature of assignable attractivity is not present in the semiglobal version of safe extremum seeking, where the semiglobality of convergence is achieved by slowing the adaptation. We also demonstrate local convergence of the parameter to a neighborhood of the minimum of a quadratic objective function constrained to the safe set with a linear CBF. The ASfES algorithm and analysis are multivariable, but we also extend the algorithm to a Newton-Based ASfES scheme which we show is only useful in the scalar case. The proven properties of the designs are illustrated through simulation examples.

42 ENGINEERING↗
DOE OSTI2025

Recrystallization driven softening and heating rate dependencies of FeCrAl nuclear fuel cladding during accident transients

A refined understanding of FeCrAl cladding behavior during rapid transients is critical for its potential deployment in light-water reactors. Current assessments focus on transient burst testing metrics such as balloon geometry, burst temperature, and hoop stress, often used as proxies for simpler conventional tensile properties. However, directly correlating isothermal tensile and creep data with accident transient scenarios remains a challenge, although it is essential for high fidelity model development. Recent modeling based on tensile tests up to 800 °C, conducted with both immediate loading and a 10-minute soak, showed that immediate loading better predicts experimental burst temperatures, indicating a thermal softening effect. Building upon this observation, the current study connects transient performance, microstructural evolution, and high-temperature tensile properties by leveraging results from C26M claddings burst tests performed at heating rates of 1–50 °C/s and hoop stresses from 25 to 100 MPa. At 25 MPa, rupture temperatures varied by only 6 °C, but at 100 MPa, the difference reached 116 °C, with faster heating yielding higher burst temperatures. Microstructural analysis identified recrystallization as the primary cause of heating rate-dependent softening, eliminating prior cold-working. In-situ thermomechanical data linked ballooning onset to localized instabilities, similar to ultimate tensile strength behavior in conventional tensile tests. High heating rates correlated with immediate loading tensile data, while lower rates matched soaked data. Furthermore, by linking burst performance to microstructural evolution and tensile properties, this work provides a foundation for more accurate modeling of FeCrAl claddings and potentially other Fe-based materials under accident conditions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Effects of growth rate and dynamic substrate tilt on properties of Au-Ta alloy films deposited by high-power impulse magnetron sputtering

Gold-tantalum (Au—Ta) alloys are promising for next-generation hohlraums for magnetically-assisted indirect-drive inertial confinement fusion. Hohlraum fabrication involves sputter deposition of ultrathick coatings on sphero-cylindrical substrates. The control of physical properties of such coatings remains a challenge. Here, in this work, we systematically study effects of the growth rate and dynamic substrate tilt on properties of AuTa 4 films deposited onto rotating planar substrates mounted at different tilt angles to mimic different regions of the sphero-cylindrical surface of a hohlraum. We use high-power impulse magnetron sputtering (HiPIMS) in the constant charge per pulse mode with a pulse duration of 100 μs, a charge per pulse of 190 μC, a peak target current of about 3 A, and the pulse frequency varied in the range of 400–1400 Hz. The Langmuir probe, mass-resolved ion energy spectrometry, and optical emission spectroscopy are used to monitor plasma discharge characteristics in order to isolate and study effects of the growth rate. The deposition rate and the ballistics and energetics of depositing species are estimated by Monte Carlo simulations. Results show that the film microstructure, crystallographic phase, residual stress, and electrical resistivity strongly depend on both the deposition rate and substrate tilt, highlighting their critical role in tailoring properties of Au—Ta films during hohlraum fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring strain rate effects upon 3D materials using high speed in situ X-ray tomoscopy

Cellular materials are ubiquitous in our modern society. They may be stochastic gas-blown foams (e.g., polyurethane), foamed starches (e.g., cereals), or, in this case, 3D printed microlattices. Failure in these materials is often driven by surface or sub-surface defects, which may be nucleated at a surface roughness, an interior void, or inclusion interfaces that may not be typically observable. Obfuscating our understanding further, bulk materials are known to exhibit strain-rate-dependent mechanical response, making a subsurface understanding of damage even more critical. For the first time, an in situ uniaxial mechanical loading stage that simultaneously rotates specimens up to 18 Hz was fielded at a synchrotron for 3D tomographic imaging. This capability opens a plethora of materials science opportunities to explore strain rate effects in materials and examining deformation, fracture, and delamination’s (in composites) for a complete 3D picture (movie) of material response. We demonstrate the deformation of 3D printed polymer lattice structures, of three different material types, at 0.25, 1.1, and 2.2 s −1 strain rates. We successfully imaged the 3D deformation of these materials and can directly compare the same printed structure to the three material types at three strain rates, all in 3D. Material point method simulations were applied to one of the materials to better understand the role of voids on the 3D printed structure’s performance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Rate constants and third-body collision efficiencies for recombination of Na with OH and O2: Implications for flame inhibition by alkali salts

Flame inhibition by alkali metals has implications for solid fuel combustion, fire safety, and a number of industrial processes. While the mechanism of inhibition is fairly well understood, details related to thermodynamic properties and rate constants are still in question. In the present work, the recombination of Na with OH (R5) and O2 (R7), respectively, was characterized theoretically, and the implications for modeling laminar premixed hydrogen flames doped with sodium species were examined. Third-body collision efficiencies and low-pressure-limit rate constants were obtained using newly fitted ab initio-based potential energy surfaces, classical trajectories, and one-dimensional master equation calculations. The results are consistent with available experimental results and aid in the present modeling study by providing rate information for bath gases and conditions that remain unexplored experimentally. Chemical kinetic modeling of relative Na and absolute H and OH profiles in H2-fueled laminar, premixed flames doped with a sodium salt shows that the most important radical removal cycle is the sequence Na + OH (+M) → NaOH (+M) (R5), NaOH + H → Na + H2O (R12), even under oxidizing conditions. A secondary cycle, Na + O2 (+M) ⇄ NaO2 (+M) (R7), NaO2 + OH → NaOH + O2 (R14), is less important due to the low thermal stability of NaO2. In most flames, reaction R7 is partially equilibrated, and reaction R14 becomes rate-limiting for the second cycle. The flame analysis supports a lower value of k14 than indicated by recent work on KO2 + OH, but more work is required to confirm this.

Jasper, Ahren W.↗
DOE OSTI2025

How are Heterogeneous Nucleation Rate Observations Influenced by Instrument Resolution?

Experimental measurements of the heterogeneous nucleation rate rely on counting the number of nuclei with time. However, the size of a thermodynamically stable nucleus is often a few nanometers in diameter and is below the resolution of most (in situ) measurement techniques that provide a statistically valid sample. Due to the finite resolution of the instruments and analysis methods, it is challenging to capture the incipient nuclei and the subsequent evolution of nuclei density over time. In this work, we demonstrate the impact of instrument resolution on observed nuclei densities by comparing numerical modeling with experimental results. Further, to achieve this, we implemented heterogeneous nucleation within the pore-scale reactive transport modeling framework using classical nucleation theory (CNT). We compared the modeling results with nucleation rates measured using X-ray nanotomography (XnT) and evaluated how these impact the apparent values of the prefactor and interfacial energy based on CNT and the crystal growth rate. Specifically, we applied a resolution threshold (artificial resolution limit) in the model during nuclei counting to resemble an experimental resolution, ranging from 15 to 500 nm. The findings reveal that the instrument resolution significantly impacts the apparent prefactor and interfacial energy. Both apparent prefactor and interfacial energy decrease with a decrease in the instrument resolution. While deviation in the prefactor due to resolution is anticipated, those in the interfacial energy are unexpected. The approach described here allows one to correct apparent nucleation rates that depend on the instrument’s resolution to derive “intrinsic” CNT parameters for the prefactor and interfacial energy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Impact of Site Identity, Location, and Accessibility on Polyethylene Conversion Rates and Product Selectivities over Metal-Free MFI Zeolites

Brønsted (BAS), Lewis (LAS), and surface Brønsted (SBAS) acid sites have been investigated for polyethylene (PE) upcycling by zeolite catalysts, but there is no clear consensus regarding their catalytic roles, partly due to the complexity of the catalysts used and varying reaction conditions across studies. This work systematically determined how these sites impact PE conversion rates and product distributions by utilizing a suite of microporous MFI catalysts with varying Si/Al ratios, acid site densities, and inherent mesoporosities. PE conversion rates did not trend with total BAS or LAS densities due to a combination of internal mass transfer limitation and the apparent inability of LAS alone to cleave C–C bonds, but a strong, statistically significant correlation was present with respect to SBAS density and mesopore surface area, jointly, owing to accelerated polymer activation on external surfaces to smaller diffusion-limited chains. However, ingress of these SBAS-derived fragments ultimately remained rate limiting, as demonstrated by solid conversion rates that increased with mesopore surface area at similar SBAS density and likewise increased with SBAS density at similar mesopore surface area. In batch PE cracking reactions, light gaseous product selectivities were most sensitive to total BAS, with higher densities generally exhibiting higher selectivity to C 3 and linear C 4 –C 7 products and higher alkane/alkene product ratios, consistent with increased β-scission turnovers. Insights from this work help systematically clarify the roles of BAS, LAS, SBAS, and mesopores in PE cracking reactions and inform the development of tailored zeolite catalysts for efficient polyolefin upcycling.

accessibility↗
DOE OSTI2026

A Mesopore-Confined and Graphene Oxide-Localized Ruthenium Catalyst Increases Rates of Mid-Chain Polyolefin Hydrogenolysis

A catalyst architecture with mesoporous silica coating Ru nanoparticles on reduced graphene oxide (mSiO 2 /Ru/rGO) localizes the 2 nm Ru solely at the closed bottoms of 2.9 nm diameter mesopores. mSiO 2 /Ru/rGO catalyzes the rapid, selective hydrogenolysis of polyolefins at wax formation rates (ν wax ) up to 1700 g wax ·g Ru –1 ·h –1 and a turnover frequency (TOF) for C–C bond cleavage of 130 ± 8 min –1 . The ν wax and TOF for mSiO 2 /Ru/rGO are 23× and 16× those of nonporous Ru/rGO, respectively, indicating that faster chain cleavage is also more selective inside mesopores. The methane yield from mSiO 2 /Ru/rGO is ca. 30% of the value obtained from Ru/rGO. Methane decreases, and wax selectivity improves with narrow-pore (2.3 nm) mSiO 2 /Ru/rGO. The reaction rate decreases at lower and higher H 2 pressures from its maximum at 37 bar. Log(TOF)-log(P H2 ) plots reveal rates ∝ [P H2 ] 2.8 or [P H2 ] −2.0 in the lower or higher pressure ranges, respectively. Corresponding plots for Ru/C give rates ∝ [P H2 ] 1 or [P H2 ] −2.4 . Ru is hydrocarbon-covered at low pressure; thus, the higher H 2 order for mSiO 2 /Ru/rGO indicates that mesopores increase the density of cleavable unsaturated moieties on the Ru surface. The lower H 2 order on Ru/C implies a lower density of cleavable groups because saturated segments occupy a larger fraction of the Ru surface. Higher surface occupancy by the hydrocarbon reactant correlates with more methane formation. Therefore, pore confinement, narrower pore diameter in mSiO 2 /Ru/rGO, or higher H 2 pressure leads to lower methane yields. Ru nanoparticles in mSiO 2 /Ru/rGO maintain equivalent activity and selectivity over five recycling tests.

Catalysts↗
DOE OSTI2025

Can Biogeochemical Tracer Observations Constrain Southern Ocean Diapycnal Mixing Rates?

Abstract Direct observations of background diapycnal mixing rates in the Southern Ocean (SO) are limited spatially and temporally, making the choice of an appropriate value to parameterize this mixing in Earth system models a challenge. However, the deployment of Argo floats throughout the SO has provided an extensive range of observations of both physical and biogeochemical parameters. We use an ocean state estimate run with various background diapycnal mixing coefficients to assess if biogeochemical tracer observations can be used to better constrain SO diapycnal mixing rates. We find that vertical tracer distributions in the SO are highly sensitive to the rate of background diapycnal mixing and can provide an upper limit on background mixing rates. This demonstrates the importance of biogeochemical tracer observations throughout the full depth of the water column to validate ocean models.

Ellison, Elizabeth [The Australian National Univer↗
DOE OSTI2024

Prediction of Distributed River Sediment Respiration Rates Using Community-Generated Data and Machine Learning

River sediment microbial respiration is a key indicator of ecosystem functioning and the biogeochemical fluxes across this critical zone link surface and subsurface waters. As such, there is tremendous interest in measuring and mapping these respiration rates. Respiration observations are expensive and labor intensive; there is limited data available to the community. An open science, collaborative initiative is collecting samples for respiration rate analysis and multi-scale metadata; this evolving data set is being used for making machine learning (ML) predictions at unsampled sites to help inform continued community engagement. However, it is a challenge to find an optimum configuration for ML models to work with this feature-rich (i.e., 100+ possible input variables) data set. Here, we present results from a two-tiered approach to managing the analysis of this complex data set: (a) a stacked ensemble of models that automatically optimizes hyperparameters and manages the training of many models and (b) feature permutation importance to detect the most important features in the models. The major elements of this workflow are modular, portable, open, and cloud-based thus making this implementation a potential template for other applications. The models developed here predict that sediment organic matter chemistry is one of the most important features for predicting sediment respiration rate. Other larger-scale, important features fall into the categories of climatic, ecological, geological, and fluvial settings. Leveraging these larger-scale features to generate data-driven estimates of river sediment respiration rates reveals spatially consistent but heterogeneous patterns across the river network of the Columbia River Basin.

54 ENVIRONMENTAL SCIENCES↗