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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Corrosion Behavior of Hydrophobic Coatings in Aqueous CO2 Environments

Internal corrosion is caused by gas impurities such as CO2, moisture, and H2S, leading to material degradation. To combat this, the National Energy Technology Laboratory (NETL) developed a novel hydrophobic coating to reduce surface hydrophobicity and enhance the corrosion resistance of steel. NETL’s approach uses multi-layer hydrophobic coatings, a novel and promising coating that could potentially revolutionize the industry's approach to internal corrosion mitigation. This work aims to investigate the corrosion performance of the hydrophobic coating and determine the water uptake. Electrochemical corrosion experiments were carried out on bare X65 carbon steel without and with coating in 3.5 wt.% NaCl saturated with CO2 at 20 °C to follow the water uptake as a function of exposure time. Linear polarization resistance (LPR) was used to determine the corrosion rate for carbon steel immersed in a NaCl electrolyte saturated with CO2. Electrochemical impedance spectroscopy (EIS) of uncoated and coated bare carbon steel was investigated. The analyses of impedance models and water uptake behaviors of hydrophobic coatings were studied for 200 hours during the corrosion process. The water uptake was estimated using the Brasher and Kingsbury relation. The results showed that the superhydrophobic coating that was developed used innovative nano-based materials to act as protection layers on the surface of metallic parts against mechanical aggressors, corrosion, and fouling agents.

corrosion behavior↗
DOE OSTI2023

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗
DOE OSTI2020

Measurement and modeling of the radio frequency sheath impedance in a large magnetized plasma

The DC and RF properties of radio frequency (RF) driven sheaths were studied in the Large Plasma Device (LAPD) at the University of California, Los Angeles. The experiments diagnosed RF sheaths on field lines connected to a grounded plate at one end and an ion cyclotron range of frequencies (ICRF) antenna at the other end. The experimental setup permitted measurement of the RF sheath impedance at the plate as a function of DC sheath voltage, with the latter controlled by varying the RF current applied to the antenna. Here, the DC current-voltage characteristics of these sheaths and the RF sheath impedance measurements were compared with modeling. Hot electrons, present in the LAPD plasma, were inferred to contribute significantly to both the DC and RF currents and hence the RF impedance. It was postulated that at very low power hot electrons could not access the region of the plasma subject to RF waves, resulting in an increased RF impedance. Within some experimental limitations and significant assumptions, an RF sheath impedance model was verified by the experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

3D Multiphysics Model for Large Scale Planar Cell: Inductance Investigation in Impedance Analysis

Developed a comprehensive 3D multiphysics model to analyze impedance behavior in large-scale planar Solid Oxide Fuel Cells (SOFCs). The model investigates how impedance varies across operating conditions and cell components, with a particular focus on inductive loops or negative capacitance at the air electrode. It was found that the Inductive loop disappears in the low-frequency zone when the activation overpotential or faradic current is not temperature-dependent. These findings offer new insights into SOFC impedance behavior.

impedence analysis↗
DOE OSTI2020

Real Time Effective Impedance Estimation for Power System State Estimation

Here, we introduce two tools-the Effective Impedance State Estimator (EISE), and the Real Time Effective Impedance Estimator (RTEIE). The EISE is novel in that it is an entirely data-driven state estimator, and does not require a network model. Thus, the EISE is well suited for applications in which an accurate network model is not available. Instead of using a network impedance model, the EISE uses an effective impedance network model that is learned online by the RTEIE. The RTEIE recursively estimates the effective impedance network model using phasor measurement unit (PMU) measurements. The mathematical reasoning for using an effective impedance model, rather than a full network impedance model, is given. The recursive estimation framework allows the RTEIE to take the entire history of phasor measurements into account to produce a model estimate, while still adjusting to changes in the network impedance due to external factors such as topology changes and temperature. The merits of the RTEIE and EISE are demonstrated by comparing the accuracy of the EISE with a conventional state estimator on a toy network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

The Effect of Proton Conductivity of Fe–N–C–Based Cathode on PEM Fuel cell Performance

A model–based impedance spectroscopy is used to determine proton conductivity, oxygen transport parameter, double layer capacitance and oxygen reduction reaction (ORR) Tafel slope in the Fe–N–C cathode catalyst layer (CCL) of a PEM fuel cell. Experimental spectra of two cells differing by the membrane thickness only are processed using a physics–based model for PEMFC impedance. The spectra have been measured in the range of current densities from 25 to 800 mA cm -2 . The ORR Tafel slope of both the cells shows almost linear growth with the current density. In one of the cells, the CCL proton conductivity σp strongly decays at the current density of 100 mA cm -2 ; this decay is accompanied by the step growth of the double layer capacitance. Other minor variations of proton conductivity and double layer capacitance with the cell current occur also in a counterphase; presumed origin of this effect is discussed. The oxygen diffusion coefficient in the cathode exhibits explosive growth with the cell current. We attribute this effect to formation of temperature and pressure gradients in the CCL due to strongly non–uniform distribution of ORR rate in the electrode.

25 ENERGY STORAGE↗
DOE OSTI2022

Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling

Here, this article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time. For example, how will a system transit from one steady-state operation point to another?

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Modeling Multi-View Impedance-Based Cross-Geometry SOH Estimator for Li-ion Batteries

Abstract: Accurately estimating battery’s State of Health (SOH) remains challenging when models must generalize across cell designs and operating conditions. Most Electrochemical Impedance Spectroscopy (EIS)-based approaches either (i) hand-engineer a few Nyquist-plot features for shallow models—fast but does not generalize across geometries—or (ii) learn directly from Nyquist plots with deep networks, which removes manual feature extraction, yet still limited to a single plot type. As a result, cross-geometry robustness and deployability on constrained Internet of Things (IoT) devices remain open problems. We propose a compact Convolutional Neural Network (CNN) (∼ 10k parameters) that takes multi-representation EIS inputs—Nyquist (real/imaginary) and phase–magnitude (|Z|/ϕ) stacked as four channels, so the model can learn complementary degradation signatures while remaining small enough for fast inference. We build a dataset from cyclic aging of two geometries (LG INR18650MJ1 cylindrical cells and LIR2032 coin cells), acquire EIS every ten cycles from 10 kHz to 10 mHz (10 points/decade), and evaluate with leave-one-cell-out testing strategy. We further study fusion vs. single-representation inputs and assess feasibility for on-device deployment (e.g., NVIDIA Jetson device). The results show that training on multiple EIS representations improves SOH estimation accuracy and cross-geometry generalization compared to single-representation models, which uses only Nyquist or phase–magnitude plots. This design targets accurate, generalizable SOH prediction without manual feature engineering while enabling practical real-time use.

Bakr, Ahmed [The University of Alabama (UA)]↗
DOE OSTI2020

Vulnerability Assessments for Power-Electronics-Based Smart Grids

Here, in this paper, a novel method is proposed to evaluate the cyber security of the power-electronics-based smart grids (PESG). The proposed method considers the performance and stability of both the individual inverter and the grid. To our knowledge, this is a first attempt to evaluate the performance and stability of PESG due to cyber attacks. We first develop impedance-based modeling and cyber-attack modeling for PESG. Then we propose innovative two security criteria to evaluate the security of PESG, including stability-based and metrics-based. For metrics-based criteria, we propose to use both total harmonic distortion (THD) and space phasor model (SPM) to evaluate the inverter performance. The simulation results with a two-inverter-based power grid verify the validity and accuracy of the proposed security evaluation method. Results have shown that the performance and stability of PESG are significantly affected by cyber attacks, and thus there is indeed a need to further study cyber security issues of PESG.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Convergence study of wakefield simulations with GdfidL and ECHO3D

The interaction of charged particle beams with vacuum chamber components gives rise to electromagnetic wakefields, whose frequency-domain representation is known as beam coupling impedance. Geometric impedance arising from discontinuities and transitions in the vacuum chamber is the focus of this study. Minimizing this impedance is essential to mitigate adverse collective effects in modern storage rings operating with high-intensity particle beams. Accurate and reliable impedance simulations is a key factor of the vacuum chamber design. This paper presents the results of a convergence study of two widely used electromagnetic solvers, GdfidL and ECHO3D, applied to key vacuum-chamber components of the National Synchrotron Light Source II (NSLS-II) storage ring. Detailed comparisons are performed for several geometries, including flange absorbers, RF bellows, button-type beam position monitors, and an in-vacuum undulator (IVU). The results show notable differences in convergence and computational efficiency between the two codes. While GdfidL provides highly resolved results and serves as a common benchmark tool, ECHO3D yields consistent results with coarser meshes, significantly reducing simulation time and memory demands. Simulations with a full-geometry IVU model demonstrate that simplified taper-transition models can miss important impedance contributions. In conclusion, these findings provide practical guidelines for efficient and accurate impedance modeling to optimize design of vacuum chamber components for accelerators.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Interpreting Ionic Conductivity for Polymer Electrolyte Fuel Cell Catalyst Layers with Electrochemical Impedance Spectroscopy and Transmission Line Modeling

A cathode catalyst layer containing optimally distributed ionomer is critical to reduce the platinum loading and increase its utilization in polymer electrolyte fuel cells. Here, electrochemical impedance spectroscopy (EIS) was used to measure effective ionic conductivity of pseudo catalyst layers (PCLs) at a relative humidity (RH) range of 50%-120%. These results are compared to previous work using the hydrogen pump (HP) method. EIS effective ionic conductivity results reported here are higher than those from the HP because in the HP set-up ionic pathways must be effectively connected through the PCL to be counted, whereas in the EIS measurement, ionomer segments that are in contact with the membrane but are not effectively connected all the way through the PCL can be detected. Double layer capacitances and effective ionic conductivities of Pt/C catalyst layers with various supports and ionomer to carbon (I/C) ratios were studied. High surface area carbon support resulted in a lower effective ionic conductivity compared to the graphitized carbon support due to worse ionomer dispersion. Effective ionic conductivities of Pt/C layers were compared to that of PCLs. On average, effective ionic conductivities of Pt/C layers were higher than PCLs because of possible carbon agglomeratio n within the PCLs.

25 ENERGY STORAGE↗
DOE OSTI2024

Extracting and Interpreting Electrochemical Impedance Spectra (EIS) from Physics-Based Models of Lithium-Ion Batteries

This paper implements a highly efficient algorithm to extract electrochemical impedance spectra (EIS) from physics-based battery models (e.g., a P2D model). The mathematical approach is different from how EIS is practiced experimentally. Experimentally, the voltage (current) is harmonically perturbed over a wide range of frequencies and the amplitude and phase shift of the corresponding current (voltage) is measured. The experimental approach can be implemented in simulation software, but is computationally expensive. The approach here is to determine locally linear state-space models from the full physical model. The four Jacobian matrices that are the basis of the state-space models can be derived by numerical differentiation of the physical model. The EIS is then extracted from the state-space model using computationally efficient matrix-manipulation techniques. The algorithm can evaluate the full EIS at an instant in time during a transient, independent of whether the battery is in a stationary state. The approach is also able to separate the full-cell impedance to evaluate partial EIS, such as for a battery anode alone. Although such partial EIS is difficult to measure experimentally, the partial EIS provides valuable insights in interpreting the full-cell EIS.

25 ENERGY STORAGE↗
DOE OSTI2024

The MUSIC Critical Benchmark and Nuclear Data

The Measurement of Uranium Subcritical and Critical (MUSIC) experiment was a series of measurements of critical and subcritical configurations of bare highly enriched uranium. The goal was to compare measurement methods, analysis techniques, and simulation methods across regimes of criticality and to provide high-quality validation of 235 U nuclear data. A benchmark evaluation of the two critical configurations of the MUSIC experiments will soon be published in the release of the International Criticality Safety Benchmark Evaluation Project Handbook. The recent execution of the experiment aids in proper quantification of model simplifications and all uncertainties associated with the experiment. Historical benchmark evaluations are heavily relied on for uranium nuclear data validation despite the fact that the same level of documentation and comparable uncertainty analysis may not be present. The MUSIC evaluation is less likely to include “unknown unknowns” that could impede accurately modeling the system. Presented are both highly detailed and very simplified models, which represent the experimental configurations accurately, aiding the users of the benchmark for nuclear data or transport code validation. The sensitivities of k eff to nuclear data and nuclear data–related uncertainties are very similar between this experiment and previous bare uranium sphere experiments. In addition, the nuclear data uncertainties to any nuclides other than 235 U are small. For all these reasons, the recently evaluated MUSIC benchmark critical configurations could prove very useful for 235 U nuclear data validation. Currently, major libraries have good agreement with the experimental results, within 200 pcm for all nuclear data libraries, and within one standard deviation of the experimental result for most. Suggested nuclear data adjustments based on MUSIC and Lady Godiva are also presented, with posterior improvements to both the agreement in k eff and the uncertainty associated with the nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

High Impedance Fault Detection Through Quasi-Static State Estimation: A Parameter Error Modeling Approach

This paper presents a model for detecting high impedance faults using parameter error modeling and a two step per-phase weighted-least squares state estimation process. The proposed scheme leverages the use of Phasor Measurement Units and synthetic measurements to identify per-phase power flow and injection measurements which indicate a parameter error through ?2 Hypothesis Testing applied to the composed measurement error. Although current and voltage waveforms are commonly analyzed for high-impedance fault detection, wide area power flow and injection measurements, which are already inherent to the state estimation process, also show promise for real-world high-impedance fault detection applications. The error distributions after detection share the measurement function error spread observed in proven parameter error diagnostics and can be applied to high-impedance fault identification. Further, this error spread across measurement functions related to the fault will be clearly discerned from measurement error. Case studies are performed on the IEEE 33-Bus Distribution System along with the proposed model in Simulink.

Cooper, Austin↗
DOE OSTI2022

Chapter 8: Life-Cycle Testing and Analysis

Prior to a spacecraft launch, program mission assurance standards dictate that the flight battery power system should comply with mission requirements under the intended operating conditions. Ground life cycle testing (LCT) combined with an analysis on the electrical power system (EPS) battery is an empirical method used to demonstrate compliance to satellite service life requirements. The LCT compliance method adopted by the aerospace industry is based on demonstrating a space battery's life expectancy as a part of battery qualification. Real-time cell and lithium-ion battery (LIB) LCT data are commonly used for model inputs to EPS power and energy balance analyses, in LIB reliability analysis estimates, and to support on-orbit spacecraft mission life extension opportunities. This chapter describes the LCT planning steps, process approach, and analysis techniques commonly used to qualify space LIB power systems.

accelerated aging↗
DOE OSTI2022

Heat and mass transfer in hygroscopic hydrogels

Sorption and desorption with hygroscopic hydrogels hold significant promise for thermal management, passive cooling, thermal energy storage, and atmospheric water harvesting. However, a comprehensive understanding of the energy and mass transport mechanisms in hygroscopic hydrogels remains missing, impeding accurate modeling and optimization. In this paper, we develop a model for the simultaneous vapor, water, and heat transfer in hygroscopic hydrogels during sorption and desorption processes. We show that by considering vapor diffusion in the hydrogel micropores, water diffusion in the polymer mesh, and heat transfer in the porous hydrogel, we can accurately capture experimentally observed thermally-driven desorption rates in these hydrogels. Furthermore, we consider three typical operating configurations of hydrogels and elucidate the differences in the transport mechanisms depending on the configuration. Finally, for each of these configurations, we identify key design parameters, including hydrogel thickness, hydrogel shear modulus, heat transfer coefficient, and thermal conductivity, and we parametrically show that by varying these parameters, a hygroscopic hydrogel can desorb up to 128.5%, 14.9%, 69.7%, and 9.6% more water, respectively, relative to the initial water content. This work provides a generic framework to model sorption and desorption processes in hygroscopic hydrogels which can guide the design and optimization in applications of thermal management, passive cooling, thermal energy storage, and atmospheric water harvesting with hydrogels.

36 MATERIALS SCIENCE↗