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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Addressing Spacer Channel Resistances in MCDI Using Porous and Pliable Ionic Conductors

Membrane capacitive deionization (MCDI) is a unique electrochemical separations platform that allows for energy recovery during electrode regeneration. Similar to other electrochemical separation technologies producing deionized water (e.g. electrodialysis), ohmic resistances in the spacer channel significantly hampers the performance and energy efficiency of the process. This work devised a series of ionomer coated nylon mesh nets to address spacer channel resistances in MCDI. Under constant current operation, the ionomer coated nylon meshes displayed a 300 mV lower cell voltage rise during deionization while sustaining the same deionization rate. Furthermore, energy recovery was improved by 1.4x to 5.5x depending on the saline feed concentration. The lower cell voltage rise during deionization combined with the greater energy recovery with ionomer coated meshes resulted in energy normalized adsorbed salt (ENAS) values that were 2x to 3x greater. Addressing the spacer channel resistances in MCDI allowed for 8% to 19% increase in current density without the cell voltage exceeding 1.6 V—the upper bound set for mitigating parasitic reactions. Operating at higher current density leads to smaller MCDI units for a given deionization requirement and has implications for reducing the capital costs of the MCDI unit.

Palakkal, Varada Menon (ORCID:0000000317038323)↗
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 OSTI2021

Decoupling Conductivity and Solubility in Electrolytes Using Microemulsions

Redox flow batteries have recently received considerable attention as possible large-scale energy storage devices, but their low energy density has inhibited widespread application. In this work, a novel strategy of decoupling conductivity and solubility of electrolytes using microemulsion is put forward to enhance ionic conduction of non-aqueous electrolytes, increase the selectivity of active species, improve the battery voltage, and eventually achieve the possibility of high energy density. We report a study of the electrochemistry of ferrocene in single phase Tween® 20/1-butanol/H 2 O/toluene microemulsion system at 20 °C. At low and intermediate surfactant to water weight ratios (<0.5/0.5), the voltammogram exhibits reversible electrochemical behavior, while at high surfactant levels the curves show lower levels of reversibility. The latter voltammograms have a form typically associated with high resistance in solution, consistent with a gradual transition in microstructure as surfactant levels increase. This change in structure is supported by correlations with conductivity results based on the literature. The voltammograms show little evidence of anomalies in double layer capacitance or electrode "blocking" by droplets, suggesting that the electron transfer is indeed occurring in a facile manner between the electrode and the ferrocene inside the oil phase.

25 ENERGY STORAGE↗
DOE OSTI2022

Tuning the Porous Structure in PMMA-Templated Mesoporous MoO 2 for Pseudocapacitive Li-Ion Electrodes

MoO 2 is an exciting candidate for next-generation energy storage. It can be used for fast-charging applications in nanoscale form, but its kinetic performance is often limited by insulating MoO 3 surface oxide layers. Here, we developed methods to produce polymer-templated porous MoO 2 powders where electrical conductivity was well-maintained throughout the structure, even in the presence of some surface oxidation. Porosity, pore size, and crystallite size were controlled by varying the amount and size of the colloidal templates and through calcination temperature. The electrochemical performance was correlated with nanoscale structure: samples with high porosity, medium pore sizes, and good crystallinity display optimal rate capabilities, with over 100 mAh g −1 delivered in 3 min and 93% capacity retention after 1000 cycles. Kinetic studies were performed on samples with the largest and smallest crystallite sizes to understand the charge storage mechanism. In the sample with the smallest crystallite size, 85% of the total stored charge was capacitive, compared to 60% for the largest crystallite size. Sloping voltage profiles in materials with smaller domain sizes further suggest suppression of intercalation-induced phase transitions. This work thus provides insights into the mechanisms of charge storage in nanoscale MoO 2 and design parameters for the production of fast charging materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Impedance Modeling for Mixed Conductors with Simultaneous Insertion & Electrocatalytic Reactions: A Case Study of Transition-Metal Hydroxides in Aqueous Electrolyte

Electrochemical impedance spectroscopy (EIS) is commonly used to investigate the kinetics of mixed ionic–electronic conductor (MIEC) electrodes. Across various applications, MIECs exhibit ionic (e.g., insertion) and/or electronic (e.g., electrocatalytic) charge transfer reactions at the electrode/electrolyte interface. Bulk storage and transport of charge carriers also couple with these interfacial reactions. Here, we build a generalized, physics-based impedance model for MIECs with an ion-blocking current collector and explore how bulk and interfacial resistance, chemical capacitance, and DC polarization affect the impedance response. Using transition metal hydroxides as a case study, we provide guidance on extracting reaction kinetics or bulk resistance from the Nyquist plots in interface- or bulk-controlled conditions, respectively. Generalizing our EIS analysis enables a robust analysis of MIEC kinetics for a diverse set of systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electrolyzer Performance Loss from Accelerated Stress Tests and Corresponding Changes to Catalyst Layers and Interfaces

Stress tests are developed for proton exchange membrane electrolyzers that utilize low catalyst loading, elevated potential, and frequent cycling with square- and triangle-waves to accelerate anode catalyst layer degradation during intermittent operation. Kinetics drive performance losses (ohmic/transport secondary) and are accompanied by decreasing exchange current density, decreasing cyclic voltammetric capacitance, and increasing polarization resistance. Decreased kinetics are likely due to a combination of iridium (Ir) migration into electrochemically inaccessible locations in the anode or membrane, Ir particle growth (supported by X-ray scattering), changes in the extent of the Ir oxidation state (supported by X-ray absorption spectroscopy), and anode catalyst layer reordering. Decreasing catalyst/transport layer contact and catalyst/membrane interfacial tearing may add contact resistances and account for increasing ohmic losses. Performance losses for low and moderate catalyst loading, as well as from accelerated and model wind/solar cycling protocols, were likewise dominated by kinetics but vary in severity. Additionally, accelerated cycling (1 cycle per minute) appears to reasonably accelerate relevant loss mechanisms and can be used to project electrolyzer lifetime from anode deterioration. Ongoing accelerated stress test development and studies into performance loss mechanisms will continue to be critical as electrolysis shifts to intermittent power and low-cost applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Anolyte Enhances Catalyst Utilization and Ion Transport Inside a CO 2 Electrolyzer Cathode

Electrochemical CO 2 reduction is a promising technology to capture and convert CO 2 to valuable chemicals. High Faradaic efficiencies of CO 2 reduction products are achieved with zero-gap alkaline CO 2 electrolyzers with a supporting electrolyte at the anode (anolyte). Herein, we investigate the effect of anolyte on the electrode properties such as catalyst utilization, ionic accessibility etc. of a CO 2 reduction cathode using electrochemical techniques and cell configurations that avoid the complexities related to co-electrolysis. Using 1M KOH as the anolyte and a Cu gas-diffusion-electrode with low Nafion content as the model CO 2 reduction electrode, we find that electrode capacitance (proxy for electrochemically active surface area) and ionic conductivity inside the cathode increase approximately 4 and 447 times, respectively, in presence of KOH. Liquid anolyte wets the electrode’s pore structure more efficiently than capillary condensation of feed water vapor. The ionomer coverage is very low, and its distribution inside the electrode is highly fragmented. Surface ion conduction mechanisms inside the electrode are orders of magnitude lower than the bulk ion conduction in presence of anolyte. This study shows that when an anolyte (e.g., KOH) is used, catalyst utilization and ionic accessibility inside the electrode increase significantly.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Catalytic Activity and Stability of Non-Platinum Group Metal Oxides for the Oxygen Evolution Reaction in Anion Exchange Membrane Electrolyzers

The activities and stabilities of non-platinum group metals (PGMs) in the forms of monometallic (Mn 2 O 3 , Fe 2 O 3 , Co 3 O 4 , NiO) and bimetallic (NiFe 2 O 4 , CoNiO 2 ) oxides were assessed for the oxygen evolution reaction (OER) in alkaline media and compared with IrO 2 . Both half-cell, rotating disc electrode (RDE) apparatus and single-cell, membrane electrode assemblies (MEA) were used to study kinetic and device-level performance in parallel and to provide insights into the use of these materials in anion exchange membrane (AEM) electrolyzers. Normalization of RDE results by geometric and physical surface areas, double layer capacitance, and metal content probed differences in physically vs electrochemically accessible surface areas and ensured reported trends were independent of the normalization method. The results showed that: (i) Ni- and Co- containing materials met or exceeded IrO 2 performance in both RDE and MEA testing, (ii) Co 3 O 4 deactivated over time-on-stream (1.8 V for 13.5 h) due to oxide and, relatedly, particle growth, (iii) NiFe 2 O 4 increased in activity over time-on-stream due to dissolution of Fe and an increased Ni/Fe ratio, and (iv) reduction of catalyst layer resistance is an avenue to further increase device-level performance. These results demonstrated the clear viability for non-PGMs to be used as anode catalysts in AEM devices.

25 ENERGY STORAGE↗
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 OSTI2023

Simulation of Impedance Changes with Aging in Lithium Titanate-based Cells Using Physics-Based Dimensionless Modeling

Quantifying aging effects in lithium-ion cells with chemistries that have a flat open circuit potential is challenging. We implement a physics-based electrochemical model to track changes in the electrochemical impedance response of lithium titanate-based cells. Frequency domain equations of a pseudo two-dimensional model are made dimensionless, and the corresponding non-dimensional parameters are estimated using a Levenberg-Marquardt routine. The model weighs the relative contributions of changes in diffusion, ionic conduction within the electrolyte phase against solid phase electronic conduction towards cell aging. Solid-phase diffusion, charge transfer resistance and double layer capacitance at the solid-liquid interface are accounted for in the particle impedance. The estimation routine tracks dimensionless parameters using accelerated cycling data from full cells over 1000 cycles. The model can be deployed within a short time for state estimation using physics-based models without requiring prior knowledge of the battery chemistry, format, or capacity.

25 ENERGY STORAGE↗
DOE OSTI2019

Electrochemical Kinetics of SEI Growth on Carbon Black: Part I. Experiments

Growth of the solid electrolyte interphase (SEI) is a primary driver of capacity fade in lithium-ion batteries. Despite its importance to this device and intense research interest, the fundamental mechanisms underpinning SEI growth remain unclear. In Part I of this work, we present an electroanalytical method to measure the dependence of SEI growth on potential, current magnitude, and current direction during galvanostatic cycling of carbon black/Li half cells.We find that SEI growth strongly depends on all three parameters; most notably, we find SEI growth rates increase with nominal C rate and are significantly higher on lithiation than on delithiation. We observe this directional effect in both galvanostatic and potentiostatic experiments and discuss hypotheses that could explain this observation. This work identifies a strong coupling between SEI growth and charge storage (e.g., intercalation and capacitance) in carbon negative electrodes.

25 ENERGY STORAGE↗
DOE OSTI2019

Spontaneous multi-keV electron generation in a low-RF-power axisymmetric mirror machine

Title:Spontaneous multi-keV electron generation in a low-RF-power axisymmetric mirror machineAbstract:X-ray emission shows the existence of multi-keV electrons in low-temperature, low-power, capacitively-coupled RF-heated magnetic-mirror plasmas that also contain a warm (300 eV) minority electron population. Though these warm electrons are initially passing particles, we suggest that collisionless scattering -- mu non-conservation in the static vacuum field -- is responsible for a minority of them to persist in the mirror cell for thousands of transits during which time a fraction are energized to a characteristic temperature of 3 keV, with some electrons reaching energies above 30 keV. A heuristic model of the heating by a Fermi-acceleration-like mechanism is presented, with mu non-conservation in the static vacuum field as an essential feature.

Swanson, C↗
DOE OSTI2021

PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient

We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.

Yoon, Tae-Jun↗
DOE OSTI2022

Neural Networks for Supercapacitor Modeling

This software implements a one-dimensional model of a supercapacitor and calibrates it to experimental data. A system of coupled partial differential equation models the salt concentration and the ionic and electronic potentials. The term in the equation modeling the capacitance contains a neural network, whose parameters are optimized to fit the provided experimental data. The software is written in python using the open-source library JAX to calculate the gradients needed for the optimization.

Salazar de Troya, Miquel↗
DOE OSTI2026

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN↗
DOE OSTI2020

Benders Cut Classification via Support Vector Machines for Solving Two-Stage Stochastic Programs

In this work, we consider Benders decomposition for solving two-stage stochastic programs with complete recourse based on finite samples of the uncertain parameters. We define the Benders cuts binding at the final optimal solution or the ones significantly improving bounds over iterations as valuable cuts. We propose a learning-enhanced Benders decomposition (LearnBD) algorithm, which adds a cut classification step in each iteration to selectively generate cuts that are more likely to be valuable cuts. The LearnBD algorithm includes two phases: (i) sampling cuts and collecting information from training problems and (ii) solving testing problems with a support vector machine (SVM) cut classifier. We run the LearnBD algorithm on instances of capacitated facility location and multicommodity network design under uncertain demand. Our results show that SVM cut classifier works effectively for identifying valuable cuts, and the LearnBD algorithm reduces the total solving time of all instances for different problems with various sizes and complexities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Quantitative defect analysis in MOCVD GaN-on-GaN using cathodoluminescence

Cathodoluminescence (CL) is used as a quantitative characterization technique to probe impurities at the metal-organic chemical vapor deposition (MOCVD) grown GaN-on-GaN homoepitaxial interfaces. CL intensity contrast shows a strong correlation with the interfacial impurity concentrations. Based on the analysis of recombination mechanisms of electron beam induced non-equilibrium carriers, an analytical model is proposed to quantitatively determine the impurity concentrations from CL intensity. The extracted interfacial impurity concentrations from the analytical model show a good agreement with the compensation levels obtained from capacitance-voltage measurement, signifying the potential of CL for probing the quantitative impurity levels in GaN-on-GaN structures. This approach can also be extended to be applied in other material systems.

Chen, Zhaoying↗
DOE OSTI2020

High Dynamic Voltage Range Studies of Piezoelectric Multilayer Actuators at Low Temperatures

Piezo actuators are used for resonance control in superconducting linacs. In high accelerating gradients linacs, such as those operated in a pulsed mode, the piezos require a large operating voltage. This is due to the Lorentz forced detuning which causes a large frequency shift and is compensated with an active piezo-tuning system. In this high dynamic voltage range the piezo is expected to warm up drastically due to it being in an insulated vacuum. This study characterizes the dielectric properties (capacitance, dielectric losses), the piezo stroke (from geophone), and thermal properties such as heating. Results obtained in the temperature range of 20K to 300K will be presented and discussed.

43 PARTICLE ACCELERATORS↗