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At least 91 records · Page 5

Pathways Toward High-energy Li-sulfur Batteries, Identified via Multi-reaction Chemical Modeling

Here we present a 1D model of a Li-Sulfur battery with physically derived geometric parameters and thermodynamically consistent electrochemical kinetics. The approach enables straightforward comparison of proposed Li-S mechanisms and provides insights into the influence of polysulfide intermediates on battery discharge. Comparing predictions from multiple mechanisms demonstrates the need for both lithiated and non-lithiated polysulfide species, and highlights the challenge of developing parameter estimates for complex electrochemical mechanisms. The model is also used to explore cathode design strategies. Discharge performance and polysulfide concentrations for electrolyte/sulfur ratios in the range 2–4 μ L mg −1 identifies trade-offs that limit battery energy and power density, and highlights the risk of polysulfide precipitation. New cathode and electrolyte approaches must limit polysulfide concentrations in the electrolyte, both to unlock better rate capabilities in Li-S technology and to prevent capacity fade due to polysulfide precipitation.

25 ENERGY STORAGE↗

Multi-fidelity electrochemical modeling of thermally activated battery cells

Thermally activated batteries undergo a series of coupled physical changes during activation that influence battery performance. These processes include energetic material burning, heat transfer, electrolyte phase change, capillary-driven two-phase porous flow, ion transport, electrochemical reactions, and electrical transport. Several of these processes are strongly coupled and have a significant effect on battery performance, but others have minimal impact or may be suitably represented by reduced-order models. Additionally, assessing the relative importance of these phenomena must be based on comparisons to a high-fidelity model including all known processes. In this work, we first present and demonstrate a high-fidelity, multi-physics model of electrochemical performance. This novel multi-physics model enables predictions of how competing physical processes affect battery performance and provides unique insights into the difficult-to-measure processes that happen during battery activation. We introduce four categories of model fidelity that include different physical simplifications, assumptions, and reduced-order models to decouple or remove costly elements of the simulation. Using this approach, we show an order-of-magnitude reduction in computational cost while preserving all design-relevant quantities of interest within 5 percent. The validity of this approach and these model reductions is demonstrated by comparison between results from the full fidelity model and the different reduced models.

25 ENERGY STORAGE↗

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries and electrocatalysts. Experimental characterizations of such materials by operando microscopy produce rich image datasets, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Learning heterogeneous reaction kinetics from X-ray movies pixel-by-pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Chueh, William↗

Operando structural and chemical evolutions of TiS 2 in Na-ion batteries

Titanium disulfide (TiS 2 ) with high electric conductivity, fast rate capability, and good cycling performance is a promising candidate for electrode material in sodium (Na)-ion batteries. Despite the well-studied electrochemical behaviors of TiS 2 in Li-ion batteries, the detailed reaction mechanism of TiS 2 in Na-ion batteries is not yet fully understood due to a more complex multi-phase conversion process. In this work, reactions of TiS 2 in Na-ion batteries are investigated via a multi-modal synchrotron approach: operando X-ray Absorption Spectroscopy (XAS) – including X-ray Absorption Near-Edge Structure (XANES) and Extended X-ray Absorption Fine Structure (EXAFS) – and ex situ X-ray Powder Diffraction (XPD), coupled with computational modeling. Operando XANES spectra indicate that the redox reactions occur in both Ti and S during the electrochemically driven phase transformation. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) analysis of XAS suggests that different numbers of components are involved in the lithiation and sodiation of TiS 2 , with the sodiation including at least one intermediate phase in addition to the starting material and the final sodiation product. Ex situ XPD and Rietveld refinement further determined and quantified the unknown phases, showing that three phases, TiS 2 , Na 0.55 TiS 2 , and NaTiS 2 , participate in the sodiation of TiS 2 . Operando EXAFS results show the changes in the Ti–Ti coordination number and interatomic distance. This explains the coulombic efficiency decay due to the incomplete recovery of the coordination number of Ti after cycling. Overall, this work reveals the reaction mechanism occurring in Na–TiS 2 batteries with a greater quantitative understanding of the structural evolution. By combining the multi-modal synchrotron approach and computational work, this study provides a framework for studying a broader range of electrochemically driven phase-transformation systems towards advanced energy storage and conversion applications.

25 ENERGY STORAGE↗

Optimized Tandem Catalyst Patterning for CO 2 Reduction Flow Reactors

Tandem catalysis involves two or more catalysts arranged in proximity within a single reaction vessel, with the aim of synergistically aligning the catalysts’ reaction pathways to maximize overall system performance. This study presents a proof of concept showing the integration of continuum transport modeling with design optimization in a simplified two-dimensional flow reactor setup for electrochemical CO 2 reduction. Ag catalysts provide the CO 2 ⟶ CO reaction capability, and Cu catalysts provide the CO ⟶ high-value products reaction capability. Given a set of input parameters, the optimization algorithm uses adjoint methods to modify the Ag/Cu surface patterning in order to maximize the current density toward high-value products, such as ethylene. The optimized designs yield significant performance enhancement especially at more negative applied voltages (i.e., stronger surface reactions) and for larger numbers of patterning sections. For an applied voltage of −1.7 V vs. SHE, the 12-section optimized design increases the current density toward ethylene by up to 65% compared to the unoptimized 2-section design. For the optimized cases, observed differences in the production and consumption of CO (the key intermediate species) and minimized zones of low CO reactant surface concentration on Cu sections explain the improved reactor performance.

CO2 reduction↗

Predicting the chemical reactivity of organic materials using a machine-learning approach

Stability and compatibility between chemical components are essential parameters that need to be considered in the selection of functional materials in configuring a system. In configuring devices such as batteries or solar cells, not only the functionality of individual constituting materials such as electrodes or electrolyte but also an appropriate combination of materials which do not undergo unwanted side reactions is critical in ensuring their reliable performance in long-term operation. While the universal theory that can predict the general chemical reactivity between materials is long awaited and has been the subject of studies with a rich history, traditional ways proposed to date have been mostly based on simple electronic properties of materials such as electronegativity, ionization energy, electron affinity and hardness/softness, and could be applied to only a small group of materials. Moreover, prediction has often been far from accurate and has failed to offer general implications; thus it was practically inadequate as a selection criterion from a large material database, i.e. data-driven material discovery. Herein, we propose a new model for predicting the general reactivity and chemical compatibility among a large number of organic materials, realized by a machine-learning approach. As a showcase, we demonstrate that our new implemented model successfully reproduces previous experimental results reported on side-reactions occurring in lithium–oxygen electrochemical cells. Furthermore, the mapping of chemical stability among more than 90 available electrolyte solvents and the representative redox mediators is realized by this approach, presenting an important guideline in the development of stable electrolyte/redox mediator couples for lithium–oxygen batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Fluid Dynamics Modeling of Nickel Hydrogen Batteries

An electrochemical Ni-H2 battery model has been expanded to include thermal effects. A thermal energy conservation equation was derived from first principles. An electrochemical and thermal coupled model was created by the addition of this equation to an existing multiphase, electrochemical model. Charging at various rates was investigated and the results validated against experimental data. Reaction currents, pressure changes, temperature profiles, and concentration variations within the cell are predicted numerically and compared with available data and theory.

Cullion, R.↗

Voltage-Based Strategies for Preventing Battery Degradation under Diverse Fast-Charging Conditions

Maintaining safe operating conditions is a key challenge for high-performance lithium-ion battery applications. The lithium-plating reaction remains a risk during charging, but limited studies consider the highly variable charging conditions possible in commercial cells. Here we combine pseudo-2D electrochemical modeling with data visualization methods to reveal important relationships between the measurable cell voltage and difficult-to-predict Li-plating onset criteria. An extensively validated model is used to compute Li plating for thousands of multistep charging conditions spanning diverse rates, temperatures, states-of-charge, and cell aging. Here we observe an empirical cell operating voltage limit below which plating does not occur across all conditions, and this limit varies with the battery state-of-charge and aging. A model sensitivity analysis also indicates that, when comparing two charging voltage profiles, the capacity difference at 4.0 V correlates well with the difference in the plating onset capacity. These results encourage simple strategies for Li-plating prevention that are complementary to existing battery controls.

25 ENERGY STORAGE↗

New Secondary Batteries Utilizing Electronically Conductive Polypyrrole Cathode

To gain a better understanding of the dynamic behavior in electronically conducting polypyrroles and to provide guidance toward designs of new secondary batteries based on these polymers, two mathematical models are developed; one for the potentiostatically controlled switching behavior of polypyrrole film, and one for the galvanostatically controlled charge/discharge behavior of lithium/polypyrrole secondary battery cell. The first model is used to predict the profiles of electrolyte concentrations, charge states, and electrochemical potentials within the thin polypyrrole film during switching process as functions of applied potential and position. Thus, the detailed mechanisms of charge transport and electrochemical reaction can be understood. Sensitivity analysis is performed for independent parameters, describing the physical and electrochemical characteristic of polypyrrole film, to verify their influences on the model performance. The values of independent parameters are estimated by comparing model predictions with experimental data obtained from identical conditions. The second model is used to predict the profiles of electrolyte concentrations, charge state, and electrochemical potentials within the battery system during charge and discharge processes as functions of time and position. Energy and power densities are estimated from model predictions and compared with existing battery systems. The independent design criteria on the charge and discharge performance of the cell are provided by studying the effects of design parameters.

Yeu, Taewhan↗

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↗

Interplay of intercalation dynamics and lithium plating in monolithic and architectured graphite anodes during fast charging

Fast charging of high-capacity anodes is challenging due to lithium plating reactions, which lead to poor cycling performance and safety concerns. Thus, accurate predictions of plating onset and an understanding of this electrochemical process are crucial for robust battery design. However, the most commonly used models, based on porous electrode theory (e.g., the pseudo-2D model), are notoriously difficult to calibrate due to their complexity, limiting their predictive power. This work studies the process of lithium plating during fast charging of (small-particle) graphite half-cells by measuring local reaction progression and plating behavior using optical operando techniques. These experiments employ a realistic 1D graphite electrode geometry with commercially-relevant mass loading charged at fast charge rates. It is demonstrated that the local reaction progression and plating onset can not only be predicted accurately with a p2D numerical model, but that these processes follow a simple scaling law. Remarkably, the entire reaction histories of different electrodes charged at different rates (e.g., 160 μm thickness at 0.5C, 111 μm at 1C or 66 μm at 4C) were observed to have self-similar intercalation profiles. It is demonstrated that plating onset is in turn governed by the reaction profile which explains why both processes exhibit the same scaling behavior. Finally, operando measurements of local reaction dynamics are conducted for the first time in electrodes with channeled architectures, quantitatively determining how channels affect reaction uniformity and plating onset. Together, these results reveal underlying simplicity in the complex electrochemical environment of fast charging and lithium plating, improving understanding of this process. These fundamental insights are broadly applicable for design processes, modeling and experimental evaluation of lithium ion batteries.

25 ENERGY STORAGE↗

Mathematical modeling of novel porous transport layer architectures for proton exchange membrane electrolysis cells

Thin foil based porous transport layers (PTLs) that contain highly structured pore arrays have shown promise as anode PTLs in proton exchange membrane electrolysis cells. These novel PTLs, fabricated with advanced manufacturing techniques, produce thin, tunable, multifunctional layers with reduced flow and interfacial resistances and high thermal and electric conductivities. To further optimize their design, it is important to understand their fundamental impact on the transport of protons, electrons, and liquid/vapor mixtures in the electrode. In this work, we develop a two-dimensional multiphysics model to simulate the coupled electrochemistry and multiphase transport in an electrolysis cell operated with the novel PTL architecture. The results show that larger pores improve access of water to the anode catalyst layer, which is beneficial for both the oxygen evolution reaction and membrane hydration. Larger pore sizes also improve oxygen gas transport from the catalyst layer, because generated oxygen gas is forced to travel in-plane through the anode catalyst layer until it reaches a pore opening that is connected to a channel. The discussed results confirm that the proposed thin foil based PTLs are fundamentally different from conventional PTLs, such as felts or layered meshes. The model developed in this work also provides generalizable insight into fundamental PEMEC phenomena, such as the competition between liquid and gas phase transport, membrane hydration and water management, and nonuniform electrochemical reactions, which are processes relevant to all PEMEC designs.

25 ENERGY STORAGE↗

Modular Solar-to-Fuel Electrolysis at Low Cell Potentials Enabled by Glycerol Electrooxidation and a Bipolar Membrane Separator

Solar fuel generation through water electrolysis or electrochemical CO 2 reduction is thermodynamically limited when paired with the oxygen evolution reaction (OER). The glycerol electrooxidation reaction (GEOR) is an alternative anodic reaction with lower anodic electrochemical potential that utilizes a renewable coproduct produced during biodiesel synthesis. We show that GEOR on a Au-Pt-Bi ternary metal electrocatalyst in a model alkaline crude glycerol solution can provide significant cell potential reductions even when paired to reduction reactions in seawater and acidic catholytes via a bipolar membrane (BPM). We showed that the combination of GEOR electrooxidation and a BPM separator lowers the total cell potential by 1 V at an electrolysis current of 10.0 mA cm -2 versus to an anode performing OER when paired with hydrogen evolution and CO 2 reduction cathodes. The observed voltage reduction was steady for periods of up to 80 hours, with minimal glycerol crossover observed through the membrane. Furthermore, these results motivate new, high-performance cell designs for photoelectrochemical solar fuels integrated systems based on glycerol electrooxidation.

25 ENERGY STORAGE↗

An Efficient Electrochemical Tanks-in-Series Model for Lithium Sulfur Batteries

This article applies and efficiently implements the Tanks-in-Series methodology ( J. Electrochem. Soc. , 167 , 013534 (2020)) to generate a computationally efficient electrochemical model for Lithium-Sulfur batteries. The original Tank model approach for Lithium-ion batteries is modified to account for porosity changes with time. In addition, an exponential scaling method is introduced that enables efficient simulation of the model equations to address the wide range of time constants present for different reactions in the Lithium-Sulfur system. The Tank Model achieves acceptable voltage error even for transport-limited discharged conditions. Predictions of internal electrochemical variables are examined, and electrochemical implications of the approximations discussed. This suggests significant potential for real-time applications such as optimal charging, cell-balancing, and estimation, and represents a step forward in efforts to incorporate detailed electrochemical models in advanced Battery Management Systems for Lithium-Sulfur batteries.

Parke, Caitlin D. (ORCID:0000000177324044)↗

Intermediate Temperature Proton‐Conducting Solid Oxide Electrolysis Cells with Improved Performance and Durability

Technical understanding: A high-performance and stable intermediate temperature proton-conducting solid oxide electrolysis cell (PCEC) will add significantly to the hydrogen roadmap of EERE. However, the low electrocatalytic activity of the air electrode and the instability of the electrolyte are technical barriers. In this research, we utilized computational fluid dynamic modeling and materials/microstructure engineering to investigate the complex reaction chain and to improve the performance and reliability of the protonic ceramic electrochemical cells. An active and stable Pr 1.8 Ba 0.2 NiO 4+δ -BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ (BZCYYb) scaffold conformal coating electrode was rationally designed where the robust Pr 1.8 Ba 0.2 NiO 4+δ functions both as a catalytic active and a protective layer. The PCECs with porosity-optimized scaffold conformal coating electrodes demonstrate 1.46 Acm -2 under 1.3 V at 600°C, which is among the highest in recent years. The final optimization by computational fluid dynamic modeling and conformal coating technique was applied to evolve the PCEC air electrode from Pr 2 NiO 4+δ to Pr 1.8 Ba 0.2 NiO 4+δ -BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ scaffold conformal coating. The electrolysis current was boosted from 0.445A/cm 2 to 1.46A/cm 2 at 600°C and 1.3V. A superior low degradation rate of 1mV/kh was achieved in a 5000-hour of operation. Technical effectiveness and economic feasibility: The effectiveness of this TCO conformal coating on electrolyte backbone as air electrode has been proven by long-term demonstration. Based on the highly conductive BZCYYb electrolyte and the TCO steam electrode PNO, this project rationally took advantage of the existent materials to structure a PCEC device with high TRL and low risk. The solution infiltration method used to structure the conformal coating is a standard method used by the solid oxide cell community. Very minimal adoption is needed in the current SOC fabrication process. It is a cost-effective, scalable method for manufacturing, and brings up remarkable impact on the current technical status of PCEC. Benefit to the public: The findings in the research showed the industry that the severe challenge in PCEC can be overcome in a practical way. A various energy-hydrogen ecosystem is not beyond reach. The success of this technology provides sustainable and affordable H 2 to society. It will stimulate investment from the governmental and private sectors in response to the device manufacture and deployment, and the related infrastructure construction. It will generate high-pay domestic jobs and environmental benefits to the general public in the United States.

08 HYDROGEN↗

Kinetic study of hydrogen transport in graphite under molten fluoride salt environment

Here, in this work, a kinetic model, which describes the reactions occurring during the hydrogen charging process on a graphite surface, was optimized on Electrochemical Impedance Spectroscopic (EIS) to study the entry of hydrogen into graphite in high temperature molten FLiNaK salt. The results show that the rate constants of k 1 increases with decreasing applied potential (becoming more negative), and k 2 and k 3 are independent of the applied potential. At the same charging potential, all the three rate constants are independent of the water concentration in the FLiNaK salt. The surface coverage of absorbed hydrogen increases with decreasing the charging potential and increasing the moisture content in the salt. The adsorption efficiency of hydrogen increases with increasingly charging potential and decreases with increasing moisture content of the FLiNaK salt. These results demonstrate that EIS is a promising technique for measuring the kinetic parameters for hydrogen transport in graphite under molten fluoride salt environment.

EIS↗

Microstructure-based modeling of inner oxygen pressure in solid oxide electrolysis cells: Analysis of electrode delamination and mitigation

One major degradation mechanism during long-term operation of solid oxide electrolysis cells (SOECs) is delamination of oxygen electrodes (OEs). The driving force for the electrode delamination could be the generated high inner oxygen pressure near the electrode-electrolyte interface during operation. However, the effects of transport properties and electrode thickness on the inner oxygen partial pressure are not well understood. Here a microstructure-based electrochemical model, which includes the conduction of electrons and oxygen ions coupled with Butler-Volmer-type chemical reactions at triple-phase-boundaries (TPBs), is employed to investigate the oxygen pressure in lanthanum strontium manganate (LSM)-based SOECs. The model is applied to both two-dimensional (2D) prototype microstructures and three-dimensional (3D) realistic microstructures, and the oxygen pressure is analyzed as a function of transport properties and electrode thickness under both potentiostatic and galvanostatic operations. The simulation results suggest strategies to suppress electrode delamination. The simulation results are compared to an analytical solution, and the discrepancies are attributed to the Butler-Volmer-type kinetics included in the microstructure-based model.

25 ENERGY STORAGE↗