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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Polarization-Controlled Structural Modulation in the Single Atomic Layer at the PbZr 0.2 Ti 0.8 O 3 /LaNiO 3 Interface

Conductivity modulation via ferroelectric polarization coupling with LaNiO 3 (LNO) is demonstrated at an epitaxial ferroelectric–LNO interface. Conductivity measurements, varying the thickness of the LNO channel, show that this phenomenon is confined to a few atomic layers at the interface. Combining in situ biasing and off-axis holography, we mapped out electrostatic potentials at the PbZr 0.2 Ti 0.8 O 3 (PZT)/LNO/SrTiO 3 (STO) heterostructure upon polarization switching. Using aberration-corrected STEM, the interfacial atomic structures were investigated for the two different PZT polarization states. Polarization in PZT induces a significant change in the in-plane O–Ni–O bond angles, with a 37° modulation in the topmost 1 or 2 LNO unit cells, driven by strain in the oxygen sublattice for the two opposite polarization directions in PZT. Both oxygen and cation sublattices exhibit strain responses exceeding 10% upon switching. This atomic-layer structural modulation highlights a mechanism for functional oxide heterostructure development, offering pathways for advancements in nonvolatile memory, sensors, and energy-efficient transistors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Dark Energy Survey Year 3 results: galaxy clustering and systematics treatment for lens galaxy samples

ABSTRACT In this work, we present the galaxy clustering measurements of the two DES lens galaxy samples: a magnitude-limited sample optimized for the measurement of cosmological parameters, maglim, and a sample of luminous red galaxies selected with the redmagic algorithm. maglim/redmagic sample contains over 10 million/2.5 million galaxies and is divided into six/five photometric redshift bins spanning the range z ∈ [0.20, 1.05]/z ∈ [0.15, 0.90]. Both samples cover 4143 $\deg ^2$ over which we perform our analysis blind, measuring the angular correlation function with an S/N ∼ 63 for both samples. In a companion paper, these measurements of galaxy clustering are combined with the correlation functions of cosmic shear and galaxy–galaxy lensing of each sample to place cosmological constraints with a 3 × 2pt analysis. We conduct a thorough study of the mitigation of systematic effects caused by the spatially varying survey properties and we correct the measurements to remove artificial clustering signals. We employ several decontamination methods with different configurations to ensure the robustness of our corrections and to determine the systematic uncertainty that needs to be considered for the final cosmology analyses. We validate our fiducial methodology using lognormal mocks, showing that our decontamination procedure induces biases no greater than 0.5σ in the (Ωm, b) plane, where b is the galaxy bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Estimating Subhourly Inverter Clipping Loss From Satellite-Derived Irradiance Data

Photovoltaic system production simulations are conventionally run using hourly weather datasets. Hourly simulations are sufficiently accurate to predict the majority of long-term system behavior but cannot resolve high-frequency effects like inverter clipping caused by short-duration irradiance variability. Direct modeling of this subhourly clipping error is only possible for the few locations with high-resolution irradiance datasets. This paper describes a method of predicting the magnitude of this error using a machine learning regressor ensemble model, comprised of a random forest and an XGBoost model, and 30-minute satellite irradiance data. The method predicts a correction for each 30-minute interval with the potential to roll up into 60-minute corrections to match an hourly energy model. The model is trained and validated at locations where the error can be directly simulated from 1-minute ground data. The validation shows low bias at most ground station locations. The model is also applied to gridded satellite irradiance to produce a heatmap of the estimated clipping error across the United States. Finally, the relative importance of each predictor satellite variable is retrieved from the model and discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

Comparing Outdoor to Indoor Performance for Bifacial Modules Affected by Polarization-Type Potential-Induced Degradation

Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m 2 , 500–600 W/m 2 , and 900–1000 W/m 2 . These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m 2 ) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance.

14 SOLAR ENERGY↗
DOE OSTI2020

Estimating Subhourly Inverter Clipping Loss From Satellite-Derived Irradiance Data: Preprint

Photovoltaic system production simulations are conventionally run using hourly weather datasets. Hourly simulations are sufficiently accurate to predict the majority of long-term system behavior but cannot resolve high-frequency effects like inverter clipping caused by short-duration irradiance variability. Direct modeling of this subhourly clipping error is only possible for the few locations with high-resolution irradiance datasets. This paper describes a method of predicting the magnitude of this error using a machine learning model and 30-minute satellite irradiance data. The method predicts a correction for each 30-minute interval with the potential to roll up into 60-minute corrections to match an hourly energy model. The model is trained and validated at locations where the error can be directly simulated from 1-minute ground data. The validation shows low bias at most ground station locations. The model is also applied to gridded satellite irradiance to produce a heatmap of the estimated clipping error across the United States. Finally, the relative importance of each predictor satellite variable is retrieved from the model and discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Comparative Density Functional Theory Study of Magnetic Exchange Couplings in Dinuclear Transition-Metal Complexes

Multicenter transition-metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information-processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular, the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory is the only practical electronic structure method for evaluating the J coupling. Here, we assess the accuracy of different density functional approximations for predicting the magnetic couplings of eight dinuclear transition-metal complexes, including five dimanganese, two dicopper, and one divanadium with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r 2 SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids tested in this work have a tendency to over-correct the error in magnetic coupling parameters from the Perdew–Burke–Ernzerhof (PBE) GGA as seen for manganese complexes. The performance of local hybrid density functionals shows no improvement in terms of bias and is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r 2 SCAN meta-GGAs are found to perform as well as benchmark global hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error or delocalization error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Systematic softening in universal machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have led to universal MLIPs (uMLIPs) that are pre-trained on diverse datasets, providing opportunities for universal force fields and foundational machine learning models. However, their performance in extrapolating to out-of-distribution complex atomic environments remains unclear. In this study, we highlight a consistent potential energy surface (PES) softening effect in three uMLIPs: M3GNet, CHGNet, and MACE-MP-0, which is characterized by energy and force underprediction in atomic-modeling benchmarks including surfaces, defects, solid-solution energetics, ion migration barriers, phonon vibration modes, and general high-energy states. The PES softening behavior originates primarily from the systematically underpredicted PES curvature, which derives from the biased sampling of near-equilibrium atomic arrangements in uMLIP pre-training datasets. Our findings suggest that a considerable fraction of uMLIP errors are highly systematic, and can therefore be efficiently corrected. We argue for the importance of a comprehensive materials dataset with improved PES sampling for next-generation foundational MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

WRF Modelling of Deep Convection and Hail for Wind Power Applications

Deep convection and the related occurrence of hail, intense precipitation and wind gusts represent a hazard to a range of energy infrastructure including wind turbine blades. Wind turbine blade leading edge erosion (LEE) is caused by the impact of falling hydrometeors onto rotating wind turbine blades. It is a major source of wind turbine maintenance costs and energy losses from wind farms. In the United States Southern Great Plains (SGP), where there is widespread wind energy development, deep convection and hail events are common, increasing the potential for precipitation-driven LEE. A 25-day Weather Research and Forecasting (WRF) model simulation conducted at convection-permitting resolution and using a detailed microphysics scheme is carried out for the SGP to evaluate the effectiveness in modelling the wind and precipitation conditions relevant to LEE potential. WRF output for these properties is evaluated using radar observations of precipitation (including hail) and reflectivity, in situ wind speed measurements and wind power generation. This research demonstrates some skill for the primary drivers of LEE. Wind speeds, rainfall rates and precipitation totals show good agreement with observations. Here, the occurrence of precipitation during power producing wind speeds is also shown to exhibit fidelity. Hail events frequently occur during periods when wind turbines are rotating and are especially important to LEE in the SGP. The presence of hail is modelled with a mean proportion correct of 0.77 and an odds ratio 4.55. Further research is needed to demonstrate sufficient model performance to be actionable for the wind energy industry and there is evidence for positive model bias in cloud reflectivity.

17 WIND ENERGY↗
DOE OSTI2021

Modernizing the active neutron collar poison rod correction using simulations to enhance PWR fresh fuel verification

The declared inventory of 235 U in fresh, low enriched uranium, nuclear fuel assemblies is routinely verified by nuclear safeguards inspectorates using the UNCL (Uranium Neutron Collar – Light Water Reactor Fuel) nondestructive assay instrument. The trend in modern fuels is towards higher initial enrichment, which in turn requires a larger number of burnable poison pins with higher Gadolinia concentration to hold down the initial reactivity. UNCL assay error for modern fuel assemblies typically exceeds 10%. The traditional algorithm used to correct the response for burnable poison content needs revision to achieve accuracy comparable to the $\sigma_\text{R}$ of 4.5% expected for poison-free assemblies. Here we review the problem and use a large set of 287 Monte Carlo simulations based on an experimentally benchmarked model corresponding to the 16×16 PWR array used in Brazilian Angra type II and III fuel. Simulated relative responses are used to evaluate the functional form of the poison correction and determine parameters optimal for 16×16 PWR assemblies. This update is conducted using between 4–24 Gadolinia pins ranging 2–11 wt% Gd 2 O 3 with assemblies having mean enrichments ranging 2.5%–5%. Experimental validation of the updated coefficients using seven measurements shows bias is reduced by an order of magnitude and $\sigma_\text{R}$R reduced from 10% to less than 2%. Two updated sets of coefficients are provided, the most accurate of which is directly useable in the existing analysis code (INCC) in use by inspectorate at fuel fabrication facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Measurement of space charge effects in the MicroBooNE LArTPC using cosmic muons

Large liquid argon time projection chambers (LArTPCs), especially those operating near the surface, are susceptible to space charge effects. In the context of LArTPCs, the space charge effect is the build-up of slow-moving positive ions in the detector primarily due to ionization from cosmic rays, leading to a distortion of the electric field within the detector. This effect leads to a displacement in the reconstructed position of signal ionization electrons in LArTPC detectors ("spatial distortions"), as well as to variations in the amount of electron-ion recombination experienced by ionization throughout the volume of the TPC. We present techniques that can be used to measure and correct for space charge effects in large LArTPCs by making use of cosmic muons, including the use of track pairs to unambiguously pin down spatial distortions in three dimensions. Finally, the performance of these calibration techniques are studied using both Monte Carlo simulation and MicroBooNE data, utilizing a UV laser system as a means to estimate the systematic bias associated with the calibration methodology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

TDCOSMO 2025: Cosmological constraints from strong lensing time delays

We present cosmological constraints from eight strongly lensed quasars (hereafter, the TDCOSMO-2025 sample). Building on previous work, our analysis incorporated new deflector stellar velocity dispersions measured from spectra obtained with the James Webb Space Telescope (JWST), the Keck Telescopes, and the Very Large Telescope (VLT), utilizing improved methods. We used integrated JWST stellar kinematics for five lenses, VLT-MUSE for 2, and resolved kinematics from Keck and JWST for RX J1131−1231. We also considered two samples of non-time-delay lenses: 11 from the Sloan Lens ACS (SLACS) sample with Keck-KCWI resolved kinematics; and four from the Strong Lenses in the Legacy Survey (SL2S) sample. We improved our analysis of line-of-sight effects, the surface brightness profile of the lens galaxies, and orbital anisotropy, and corrected for projection effects in the dynamics. Our uncertainties are maximally conservative by accounting for the mass-sheet degeneracy in the deflectors’ mass density profiles. The analysis was blinded to prevent experimenter bias. Our primary result is based on the TDCOSMO-2025 sample, in combination with Ωm constraints from the Pantheon+ Type Ia supernovae (SN) dataset. In the flat Λ cold dark matter (CDM), we find H0 = 71.6+3.9−3.3 km s−1 Mpc−1. The SLACS and SL2S samples are in excellent agreement with the TDCOSMO-2025 sample, improving the precision on H0 in flat ΛCDM to 4.6%. Using the Dark Energy Survey SN Year-5 dataset (DES-SN5YR) or DESI-DR2 baryonic acoustic oscillations (BAO) likelihoods instead of Pantheon+ yields very similar results. We also present constraints in the open ΛCDM, wCDM, w0waCDM, and wϕCDM cosmologies. The TDCOSMO H0 inference is robust and consistent across all presented cosmological models, and our cosmological constraints in them agree with those from the BAO and SN.Key words: cosmological parameters / cosmology: observations / dark energy / distance scale⋆⋆ Brinson Fellow.⋆⋆⋆ NHFP Einstein Fellow.

Birrer, Simon [SUNY, Stony Brook] (ORCID:000000033↗
DOE OSTI2021

Gravitational wave signatures from discrete flavor symmetries

Non-Abelian discrete symmetries have been widely used to explain the patterns of lepton masses and flavor mixing. In these models, a given symmetry is assumed at a high scale and then is spontaneously broken by scalars (the flavons), which acquire vacuum expectation values. Typically, the resulting leading order predictions for the oscillation parameters require corrections in order to comply with neutrino oscillation data. Here, we introduce such corrections through an explicit small breaking of the symmetry. This has the advantage of solving the cosmological problems of these models without resorting to inflation. The explicit breaking induces an energy difference or "bias" between different vacua and drives the evolution of the domain walls, unavoidably produced after the symmetry breaking, towards their annihilation. Importantly, the wall annihilation leads to gravitational waves which may be observed in current and/or future experiments. We show that a distinctive pattern of gravitational waves with multiple overlapped peaks is generated when walls annihilate, which is within the reach of future detectors. We also show that cosmic walls from discrete flavor symmetries can be cosmologically safe for any spontaneous breaking scale between 1 and 10 18 GeV, if the bias is chosen adequately, without the need to inflate the walls away. We use as an example a particular A 4 model in which an explicit breaking is included in right-handed neutrino mass terms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations

Abstract We investigate the atmospheric diurnal variability inside and above the Amazonian rainforest for a representative day during the dry season. To this end, we combine high‐resolution large‐eddy simulations that are constrained and evaluated against a comprehensive observation set, including CO 2 concentrations, gathered during GoAmazon2014/15. We design systematic numerical experiments to quantify whether a multilayer approach in solving the explicit canopy improves our canopy‐atmosphere representation. We particularly focus on the relationship between photosynthesis and plant transpiration, and their distribution at leaf and canopy scales. We found the variability of photosynthesis drivers like vapor pressure deficit and leaf temperature to be about 3 times larger for sunlit leaves compared to shaded leaves. This leads to a large spread on leaf stomatal conductance values with minimum and maximum values varying more than 100%. Regarding the turbulent structure, we find wind‐driven stripe‐like shapes at the canopy top and structures resembling convective cells at the canopy. Wind‐related variables provide the best spatiotemporal agreement between model and observations. The potential temperature and heat flux profiles agree with an observed decoupling near the canopy top interface, although with less variability and cold biases of up to 3 K. The increasing complexity on the biophysical processes leads to the largest disagreements for evaporation, CO 2 plant assimilation and soil efflux. The model is able to capture the correct dependences and trends with the magnitudes still differing. We finally discuss the need to revise leaf and soil models and to complete the observations at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Low Cost SIPM Evaluation and Control Prototyping System including accurate bias voltage generation, leakage current measurement, and temperature control using Peltier cooling

We describe an electronics system to operate SIPMs in the laboratory. The system is comprised of a single channel amplifier board (SIPM Amp) and a 4-channel control board to which up to 4 SIPM Amp boards can be connected. The control board supplies a common low voltage power for the amplifiers. All channels feature individually regulated bias and Peltier power voltages, along withPt10K RTD readout. A graphical user interface allows control of the bias voltages, amplifier voltage, Peltier voltages, and also provides for readback of leakage currents and other voltages. The GUI app has a feedback loop to measure the SIPM temperature (with the PT10K) and generate correction voltages to the Peltier to regulate the temperature. The temperatures, which can be achieved by Peltier cooling depend on the thermal design of the setup, the practical limit being about 50C below ambient. The SIPM Amp. board is a small (3x5cm) PCB that has a single SIPM readout channel. The SIPM scan be surface mounted on the pcb or connected to a 2-pin 0.100" socket. The area around the SIPM footprint is thermally isolated by perforations in the PCB. The RTD is located inside the thermal break. Onboard is BV and LV filtering. The 10X amplifier is based on MiniCircuits' GALI-S66+ integrated circuit, tweaked for a 6V power. The amplifier was selected for a combination of high bandwidth, low noise, and low power. An accoupled amplifier output is connected to an SMA connector. For best operation of this inverting amplifier the output signal should be in the range of 0 to -1V.The Amplifier board is connected to the Control board with a 10-conductor 0.025" pitch ribbon cable, carrying all the services. Peltier power for currents more than 1A should use a separate 2-contact connector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

PLATO hare-and-hounds exercise: asteroseismic model fitting of main-sequence solar-like pulsators

ABSTRACT Asteroseismology is a powerful tool to infer fundamental stellar properties. The use of these asteroseismic-inferred properties in a growing number of astrophysical contexts makes it vital to understand their accuracy. Consequently, we performed a hare-and-hounds exercise where the hares simulated data for six artificial main-sequence stars and the hounds inferred their properties based on different inference procedures. To mimic a pipeline such as that planned for the PLATO mission, all hounds used the same model grid. Some stars were simulated using the physics adopted in the grid, others a different one. The maximum relative differences found (in absolute value) between the inferred and true values of the mass, radius, and age were 4.32, 1.33, and 11.25 per cent, respectively. The largest systematic differences in radius and age were found for a star simulated assuming gravitational settling, not accounted for in the model grid, with biases of −0.88 per cent (radius) and 8.66 per cent (age). For the mass, the most significant bias (−3.16 per cent) was found for a star with a helium enrichment ratio outside the grid range. Moreover, an ∼7 per cent dispersion in age was found when adopting different prescriptions for the surface corrections or shifting the classical observations by ±1σ. The choice of the relative weight given to the classical and seismic constraints also impacted significantly the accuracy and precision of the results. Interestingly, only a few frequencies were required to achieve accurate results on the mass and radius. For the age the same was true when at least one l = 2 mode was considered.

Cunha, M. S. (ORCID:0000000182377343)↗
DOE OSTI2021

Interaction effects in graphene in a weak magnetic field

A weak perpendicular magnetic field, B, breaks the chiral symmetry of each valley in the electron spectrum of graphene, preserving the overall chiral symmetry in the Brillouin zone. Here we explore the consequences of this symmetry breaking for the interaction effects in graphene. In particular, we demonstrate that the electron-electron interaction lifetime acquires an anomalous B dependence. Also, the ballistic zero-bias anomaly, δv(ω), where ω is the energy measured from the Fermi level, emerges at a weak B and has the form δv(B) ~ B 2 /ω 2 . Temperature dependence of the magnetic-field corrections to the thermodynamic characteristics of graphene is also anomalous. We discuss experimental manifestations of the effects predicted. The microscopic origin of the B-field sensitivity is an extra phase acquired by the electron wave function resulting from the chirality-induced pseudospin precession.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations

Photosynthesis plays an important role in carbon, nitrogen, and water cycles. Ecosystem models for photosynthesis are characterized by many parameters that are obtained from limited in situ measurements and applied to the same plant types. Previous site-by-site calibration approaches could not leverage big data and faced issues like overfitting or parameter non-uniqueness. Here we developed an end-to-end programmatically differentiable (meaning gradients of outputs to variables used in the model can be obtained efficiently and accurately) version of the photosynthesis process representation within the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) model. As a genre of physics-informed machine learning (ML), differentiable models couple physics-based formulations to neural networks (NNs) that learn parameterizations (and potentially processes) from observations, here photosynthesis rates. We first demonstrated that the framework was able to correctly recover multiple assumed parameter values concurrently using synthetic training data. Then, using a real-world dataset consisting of many different plant functional types (PFTs), we learned parameters that performed substantially better and greatly reduced biases compared to literature values. Further, the framework allowed us to gain insights at a large scale. Our results showed that the carboxylation rate at 25 °C (V c,max25 ) was more impactful than a factor representing water limitation, although tuning both was helpful in addressing biases with the default values. This framework could potentially enable substantial improvement in our capability to learn parameters and reduce biases for ecosystem modeling at large scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Estimating dermal contact soil exposure for amphibians

Abstract Chemical exposure estimation through the dermal route is an underemphasized area of ecological risk assessment for terrestrial animals. Currently, there are efforts to create exposure models to estimate doses from this pathway for use in ecological risk assessment. One significant limitation has been insufficient published data to characterize exposure and to support the selection and parameterization of appropriate models, particularly for amphibians in terrestrial habitats. Recent publications measuring pesticide doses to terrestrial‐phase amphibians have begun to rectify this situation. We collated and summarized available measurements of terrestrial amphibian dermal exposure to pesticides from 11 studies in which researchers measured tissue concentrations associated with known pesticide experimental application rates. This data set included tissue concentrations in 11 amphibian species and 14 different pesticides. We then compared the results of two screening exposure models that differed based on surface area scaling approaches as a function of body weight (one based on birds as surrogates for amphibians and another amphibian‐specific) to the measured tissue residue concentrations. We define a false‐negative rate for each screening model as the proportion of amphibians for which the predicted concentration is less than the observed concentration (i.e., underestimate), contrary to the intent of screening models, which are intended to have a bias for higher exposure concentrations. The screening model that uses birds as surrogates did not have any instances where estimated expected avian doses were less than measured amphibian body burdens. When using the amphibian‐specific exposure model that corrected for differences between avian and amphibian surface area, measured concentrations were greater than model estimates for 11.3% of the 1158 comparisons. The database of measured pesticide concentrations in terrestrial amphibians is provided for use in calculating bioconcentration factors and for future amphibian dermal exposure model development. Integr Environ Assess Manag 2023;19:9–16. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Environmental Sciences & Ecology↗