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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 307 records · Page 17
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DOE OSTI2023

Crack Growth Rate at Oxygen Electrode/Electrolyte Interface in Solid Oxide Electrolysis Cells Predicted by Experiment Coupled Multiphysics Modeling

Solid oxide electrolysis cell (SOEC) is a very efficient hydrogen production technology, but the cell degradation is a serious limiting factor for its long-term implementation. Oxygen electrode (OE) delamination is reported to be the critical degradation mechanism. In this study, we present a methodology to understand the delamination failure of the OE due to chemical stress in a better perspective. Several OE configurations were tested: baseline strontium-doped lanthanum cobalt iron oxide (LSCF) single layer design and tantalum-doped strontium cobalt oxide (SCT) - LSCF bilayer designs with different SCT loadings. An electro-chemo-mechanical model is developed to associate the electrochemical behavior of the cell with solid mechanics for calculating crack growth of the cell during long term test. The bilayer configuration with SCT 20 wt% has better performance as it survived in the long-term life test with the least crack length. This study implies that an additional nano-coating of SCT over the OE have improved the species transport and oxygen evolution with reduced chemical stress. As the operating current density decreases, it takes longer time for the cell to reach the delamination with the same critical crack length of 6.5 μ m (∼93% of the electrode/electrolyte interface length). Finally, it was concluded that chemical stress plays a significant role in interface delamination failure, however it may not be the only source of stresses at the interface.

08 HYDROGEN↗
DOE OSTI2023

Predictive Engineering of Interfaces and Cathodes for High-Performance All Solid-State Lithium-Sulfur Batteries

The primary goal of this project is to leverage data-driven methods and machine learning strategies to develop accurate multi-physics models for all-solid-state Li-S battery (ASLSB) materials that can capture electrochemical and transport phenomena over atomic to mesoscopic length/timescales. These models will be rigorously validated by synthesis and advanced characterization experiments. The team will leverage the predictive power of these models, alongside synthesis/characterization experiments and battery fabrication to address longstanding issues at the electrode/electrolyte interfaces in ASLSBs. The project’s proposed technology involves the following: (1) halide-doped solid sulfide electrolytes that can concurrently provide high Li + ion conductivity and suppress dendrite growth; (2) novel mesoporous cathode composed of super-P and carbon nanotubes co-infiltrated with sulfur and sulfide electrolyte, which hold potential to allow high sulfur loading and optimal ion/electron pathways; and (3) functionalization of sulfide electrolyte with ionic liquids to improve physical contact and minimize impedance at the cathode/electrolyte interface. Successful development of proposed predictive models (at multiple scales) will bridge this knowledge gap and will advance fundamental understanding of reaction chemistry, kinetics, charge transfer, and dendrite growth at electrified SSIs. This will enable predictive design of effective strategies to mitigate interfacial problems in ASSLSBs, including poor interfacial contact, interfacial impedance to Li + ion transport, and poor electron/ion conduction within cathodes. Ultimately, the fundamental knowledge gained will lead to development of high-performance ASSLSBs.

25 ENERGY STORAGE↗
DOE OSTI2019

The Poisson–Boltzmann model for implicit solvation of electrolyte solutions: Quantum chemical implementation and assessment via Sechenov coefficients

Here, we present the theory and implementation of a Poisson-Boltzmann implicit solvation model for electrolyte solutions. This model can be combined with arbitrary electronic structure methods that provide an accurate charge density of the solute. A hierarchy of approximations for this model includes a linear approximation for weak electrostatic potentials, finite size of the mobile electrolyte ions, and a Stern-layer correction. Recasting the Poisson-Boltzmann equations into Euler-Lagrange equations then significantly simplifies the derivation of the free energy of solvation for these approximate models. The parameters of the model are either fit directly to experimental observables-e.g., the finite ion size-or optimized for agreement with experimental results. Experimental data for this optimization are available in the form of Sechenov coefficients that describe the linear dependence of the salting-out effect of solutes with respect to the electrolyte concentration. In the final part, we rationalize the qualitative disagreement of the finite ion size modification to the Poisson-Boltzmann model with experimental observations by taking into account the electrolyte concentration dependence of the Stern layer. A route toward a revised model that captures the experimental observations while including the finite ion size effects is then outlined. This implementation paves the way for the study of electrochemical and electrocatalytic processes of molecules and cluster models with accurate electronic structure methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effect of Electrolytes on the Cathode-Electrolyte Interfacial Stability of Fe-Based Layered Cathodes for Sodium-Ion Batteries

Iron (Fe)-based layered oxide cathodes that employ Fe 3+ /Fe 4+ redox reaction present a family of attractive cathode materials for sodium-ion batteries as iron is abundant, low-cost, and environmentally benign. However, their electrochemical performance is not yet satisfactory and requires further improvement. In this study, we investigate the effect of electrolytes on the electrochemical performance of α -NaFeO 2 , a prototypical model of Fe-based layered cathodes. First, we established the critical impact of the poor cathode-electrolyte interfacial stability on cell performances. Systematic electrochemical tests and material characterizations further revealed the degradation mechanism in which the highly reactive Fe 4+ state in the charged Na 1−x FeO 2 electrodes promotes severe electrolyte decomposition and subsequent growth of a thick interface layer that leads to impedance rise and performance degradation. In addition, the superior performance of NaPF 6 over NaClO 4 and the beneficial effect of the FEC additive are reported.

25 ENERGY STORAGE↗
DOE OSTI2025

Modeling Pb(II) Adsorption on Mineral Surfaces: Bridging Density Functional Theory and Experiment with Thermodynamic Insights

Despite decades of work on aqueous lead (Pb) adsorption on a-Fe2O3 (hematite) and a-Al2O3 (alumina), gaps between measurements and modeling obscure molecular-level understanding. Achieving well-matched geometries between theory and experimental for mineral-water interfaces is a hurdle, as surface functional group type and distribution must be accounted for in determining mechanisms. Additionally, computational methods that can describe the substrate are often not appropriate to capture aqueous effects. Progress requires focusing on well-studied and relevant systems, such as key facets (001),(012), and (110) of hematite and alumina, and ubiquitous contaminants such as aqueous Pb. In the past, bulk-parametrized bond-valence principles were used to rationalize Pb(II) adsorption trends. These approaches can break down at surfaces, where flexible bonding environments and adsorption-induced surface relaxations play a critical role. Here, we adapt and apply a density functional theory (DFT) and thermodynamics framework, integrating DFT-calculated energies with experimental data and electrochemical principles, to predict Pb(II) adsorption. Our model results capture trends across the full set of surfaces and predict that inner-sphere Pb(II) sorption on (001) alumina varies from unfavorable to weakly favorable across a range of pH conditions. This aligns with experiment insights that Pb(II) interacts at that surface through outer-sphere interactions. Extending to Fe(II) adsorption, we demonstrate a coverage-dependent site preference, potentially explaining disorder in overlayers grown by the oxidative adsorption of Fe(II) on hematite (001).

lead contamination↗
DOE OSTI2025

An unwanted guest in the electrochemical oxidation of high-voltage Li-ion battery electrolytes: the life of highly reactive protons

Lithium-ion batteries (LIBs) are central to the urgent societal need to decarbonize both transportation and energy storage on the grid. Unfortunately, despite their attractive energy/power density, as well as high coulombic and energy efficiencies, further improvement of this technology – especially their durability – is desperately needed. To support these efforts, our study focuses on fundamental understanding of the decomposition pathways for LIB electrolytes at the cathode–electrolyte interface (CEI), as the nature of these reactions directly controls the extent to which cell capacity and voltage decays in these systems. In this study, we employ electrochemical methods, coupled with product analysis using NMR spectroscopy and mass spectrometry, to determine the decomposition mechanisms in both model and technologically relevant electrolytes. Remarkably, we discovered the electrochemical formation of protons with high chemical activity, comparable to known superacids, at potentials relevant to practical Li-ion batteries. Their reactivity toward every individual component of the CEI provides a unified thermochemical origin for a myriad of side reactions that are commonly associated with the electrochemical reaction. In particular, electrochemically generated protons react with intact EC molecules to form CO 2 and other short and long chain ethers. They also undergo an acid–base reaction with LiPF 6 , to form the weaker acid HF, and with the cathode active material, leaching transition metals into the electrolyte. Collectively, the results of this study all point to the urgent need to either mitigate this proton formation or introduce benign harvesting additives via new electrolyte design strategies.

Ilic, Stefan [Argonne National Laboratory (ANL), A↗
DOE OSTI2026

Particle‐Size‐Dependent Lithium‐Ion Transport in PEO/LLZO Composite Electrolytes

Lithium-metal batteries with solid electrolytes can deliver higher energy density and improved safety than conventional Li-ion batteries. Among solid electrolyte candidates, polymer/ceramic composite electrolytes are attractive because they combine polymer flexibility with the high ionic conductivity of ceramics. However, whether ceramic fillers synergistically reduce polarization losses in the polymer matrix remains unclear. A central unknown is the critical polymer/ceramic interfacial resistance (Rint,crit), below which adding ceramics lowers electrolyte overpotential. Here, we present the first macroscale model framework to quantify R int,crit for composite electrolytes based on polyethylene oxide (PEO) and Ta-doped Li 7 La 3 Zr 2 O 12 (LLZO). A 1D model for DC-polarization of tri-layer cells (PEO-LiTFSI/LLZO/PEO-LiTFSI) shows that LLZO surface functionalization reduces the PEO/LLZO interfacial resistance, consistent with electrochemical impedance measurements. Extending to a 2D composite model, we show notably that Rint,crit scales linearly with LLZO particle diameter and shifts toward experimentally accessible values (e.g., 28.8 Ωcm 2 ) as particle size increases. At fixed ceramic volume fraction, larger LLZO particles reduce the number of interfacial crossings, driving more current through the ceramic phase and lowering concentration polarization. In contrast, R int,crit is largely independent of ceramic volume fraction. These results demonstrate that ceramic filler-size engineering can enable synergistic, energy-efficient transport in polymer/ceramic composite electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2025

Interfacial Properties of Gold and Cobalt Oxyhydroxide in Plasmon-Mediated Oxygen Evolution Reaction

Water electrolysis is one green approach of storing electrical energy within chemical bonds of the high-energy hydrogen gas (H2). The anodic reaction involved in the oxygen evolution reaction (OER) requires high kinetic overpotential on the overall rate of the process. Recently, plasmonic gold nanoparticles (Au NPs) have been added to enhance the charge transfer at the interface of the OER electrocatalysts and electrolyte under light illumination. However, mechanistic understanding of how Au NPs on the photo-assisted electrochemical process is still lacking. We applied a model system of plasmonic Au electrode and a cobalt (Co)-based OER electrocatalyst in alkaline electrolytes to investigate the plasmon-mediated OER process with (photo)electrochemical and spectroscopic studies. Our results demonstrated that the electrodeposited and surfactant-free plasmonic Au electrode could enhance the electrocatalytic performances of the Co-based electrocatalysts in the OER process with continuous visible and near infrared light illumination. Both the photothermal and energetic charge carriers were found to contribute to the enhanced OER performance based on the transient photocurrent studies, and the interfaces of Au and the Co-based electrocatalysts determined the enhancement mechanisms. The active phase of the cobalt based OER electrocatalyst at operating potentials was identified with electrochemical Raman measurements.

OER↗
DOE OSTI2020

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗
DOE OSTI2023

A Comparative Study of Electrical Double Layer Effects for CO Reduction Reaction Kinetics

Solvation models describe how the interactions between the solutes and solvents affect the reactivity and selectivity in electrochemical processes. In this study, we developed a framework for evaluating the effects of applied potential and electrical double layer on CO reduction (COR), comparing fully explicit, implicit, and hybrid solvation models at the standard hydrogen electrode (SHE) scale. We analyzed all crucial intermediates leading to the production of C 1 and C 2 products and found good agreement across these models. Some notable differences were observed in the implicit description of *C and *CO adsorption at higher overpotentials and overall trends in the adsorption energies within the hybrid model. Using this unified SHE framework, we built comparable microkinetic models for COR kinetics and rates. Despite small differences in thermodynamics, solvation-model-based microkinetic simulations showed good agreement for onset potentials against the benchmark experiment. Only qualitative difference was observed for C 1+ versus hydrogen evolution at high overpotentials for the implicit model. Finally, we constructed a generalized C 2 selectivity map in descriptor space (U SHE , ΔG electrolyte CO ), which highlights the limitations of a copper-based COR catalyst and guides the search for optimal descriptor parameters to maximize C 2 selectivity. In conclusion, these findings demonstrate the importance of considering electrical double layer effects in reduction reactions and offer a useful framework for comparing solvation models and predicting optimal electrochemical conditions for specific applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine learning-based surrogate models and transfer learning for derivative free optimization of HT-PEM fuel cells

Widespread adoption of high-temperature polymer electrolyte membrane electrochemical systems, such as fuel cells (HT-PEMFCs), requires models and computational tools for accurate optimization and guiding new materials for enhancing performance and durability. In this contribution, knowledge-based modelling and data-driven modelling are combined using Few-Shot Learning and implementing an Automated Machine Learning framework for the generation of Machine Learning-based surrogate models. Applicability of the resulting model for derivative-free optimization is demonstrated. Additionally, a way of considering extrapolation in the optimization task is presented. Results show that although extrapolation is needed to achieve better solutions during optimization, it can be monitored and managed. As a result, tuning the electrode ionomer binder's properties, such as ionic conductivity, in the fuel cell represents a promising pathway for improving HT-PEMFC performance.

08 HYDROGEN↗
DOE OSTI2023

Colocalized Raman spectroscopy – scanning electrochemical microscopy investigation of redox flow battery dialkoxybenzene redoxmer degradation pathways

Non-aqueous redox flow batteries offer high voltages for grid-level energy storage technologies. However, decomposition of the redoxmers - redox-active molecules that make up the anolyte and catholyte in the negative and positive cell compartments - is an important challenge to overcome for long-term storage. Here, we present a spectroelectrochemical study of the catholyte candidate 2,3-dimethyl-1,4-dialkoxybenzene (C7) and its decomposition mechanisms in the presence of a model nucleophilic base, pyridine. We utilize colocalized Raman microscopy and scanning electrochemical microscopy (Raman-SECM) to quantify the chemical rates of decom-position and qualitatively identify the reaction intermediates and products. A detailed study on how the Raman-SECM parameters (electrode distance, substrate electrode, and laser focal height) influence the Raman signal of the charged catholyte C7 ∙+ is presented. Using optimized conditions, we monitored the deprotonation of C7 ∙+ via Raman spectroscopy and the subsequent hydrogen abstraction from solvent molecules to regenerate C7 via electrochemistry. Finite element modeling was used to fit electrochemical and spectroscopic data, quantifying the deprotonation rates as k dep = 2000 and 700 L mol -1 s -1 and abstraction rates as k abs = 0.5 and 0.2 s - 1 in propylene carbonate and acetonitrile solvents, respectively. Our results show the value of spatiotemporal reso-lution in evaluating the chemical and electrochemical behavior of materials for redox flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Microelectrode Arrays for Electrochemical Cycling of Individual Battery Particles

The electrochemical characterization of battery materials is usually performed on porous electrodes containing conductive additives, binders, and ensembles of redox-active particles at densities as high as 10 15 cm –3 . These complex structures often obscure individual battery particles’ intrinsic properties, hindering insights into the fundamentals of battery electrochemistry. To address this challenge, we developed microelectrode arrays to enable the charge and discharge of individual battery particles in liquid electrolytes. In this Methods and Protocols paper, we describe the fabrication of the microelectrode array chips, the assembly of particles onto microelectrodes, and the different types of electrochemical techniques that can be used, including galvanostatic cycling, cyclic voltammetry, potentiostatic intermittent titration, and electrochemical impedance spectroscopy. We use micron-sized lithium cobalt oxide as a model system to showcase the reliability and versatility of single-particle electrochemical experiments enabled by our microelectrode array. In conclusion, we aim to provide a detailed description to promote future uses of microelectrode arrays in fundamental research of batteries and other electrochemical systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗
DOE OSTI2024

Mechanistic Insights into the Electrochemical Oxidation of 5-Hydroxymethylfurfural on a Thin-Film Ni Anode

The electrochemical oxidation of alcohols is being explored as a favorable substitute for the oxygen evolution reaction owing to its capability to generate high-value products and lower overpotentials. Herein, we present a systematic investigation into the electrochemical oxidation of 5-hydroxymethylfurfural (HMF), a model biomass platform chemical, on a thin-film nickel catalyst, aiming to investigate the underlying reaction mechanism and shed light on the role of the catalyst’s microenvironment and phase on activity and product selectivity. Utilizing a combined experimental and computational approach, we demonstrate that NiOOH is the active phase for HMF oxidation. Additionally, we find a substantial impact of the electrochemical environment, particularly the electrolyte pH, on the reaction. Under highly alkaline conditions (pH = 13), higher activity for HMF oxidation is observed, accompanied by an increased selectivity toward 2,5-furandicarboxylic acid (FDCA) production. Conversely, a less alkaline environment (pH = 11) results in diminished HMF oxidation activity and a higher preference for the partial oxidation product 2,5-diformylfuran (DFF). Mechanistic insights from DFT studies reveal that geminal diols that are present under highly alkaline conditions undergo hydride transfer via HMFCA, while a shift to an alkoxide route occurs at a lower pH, favoring the DFF pathway. Hydride transfer energetics are also strongly affected by the surface Ni oxidation state. Finally, this integrated approach, bridging experimental and computational insights, provides a general framework for investigating the electrochemical oxidation of aldehydes and alcohols, thereby advancing rational design strategies in electrocatalysts for alcohol electro-oxidation reactions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Electrochemically driven phase transformation for high-efficiency heat pumping

To reduce energy consumption and improve energy utilization in space conditioning, advanced heat pumping technologies are needed. The chemical looping heat pump (CLHP) is a promising thermodynamic cycle that has theoretically shown the potential to achieve a cooling coefficient of performance (COP c ) increase of over 20% relative to conventional vapor compression systems. In this paper, the key process of the CLHP is experimentally demonstrated, and the system performance and non-ideal behavior are predicted using the component-level models. The results show the feasibility of electrochemical phase change of a working fluid; the peak COP c was 7.64 with a cooling capacity of 3.6 mW (cooling density of 2.57 W m -2 ) at both sink and source temperature of 23°C based on laboratory experiments. The COP c can theoretically reach up to 13 at a temperature lift of 15°C as long as an electrochemical cell can achieve a greater degree of conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Robust Interpretation of Electrochemical Impedance Spectra Using Numerical Complex Analysis

Electrochemical Impedance Spectroscopy (EIS) is a noninvasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can suggest the presence of inductors and constant phase elements (nonideal capacitors) from impedance data and enable us to answer questions about the identifiability and nonuniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

charge transfer↗