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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Atomistic learning in the electronically grand-canonical ensemble

Abstract A strategy is presented for the machine-learning emulation of electronic structure calculations carried out in the electronically grand-canonical ensemble. The approach relies upon a dual-learning scheme, where both the system charge and the system energy are predicted for each image. The scheme is shown to be capable of emulating basic electrochemical reactions at a range of potentials, and coupling it with a bootstrap-ensemble approach gives reasonable estimates of the prediction uncertainty. The method is also demonstrated to accelerate saddle-point searches, and to extrapolate to systems with one to five water layers. We anticipate that this method will allow for larger length- and time-scale simulations necessary for electrochemical simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Time-Resolved X-ray Operando Observations of Lithiation Gradients across the Cathode Matrix and Individual Oxide Particles during Fast Cycling of a Li-Ion Cell

Lithiated transition metal oxides serve as active materials in the positive electrode (cathode) of lithium-ion cells. During electrochemical cycling, lithium ions intercalate and deintercalate into these oxide particles. This behavior causes two types of lithiation gradients to emerge: (i) a bulk gradient across the depth of the cathode matrix (averaged over individual oxide particles) and (ii) a microscopic gradient across the particles themselves, which also depends on their location in the electrode. Here we show how both gradients can be studied using operando X-ray diffraction during 4C charge and 4C discharge. The oxide (de)lithiation is estimated from the unit cell parameters by indexing the X-ray diffraction spectra. By fitting the lithiation profiles with orthogonal polynomials, the bulk gradients across the electrode thickness are quantified. These gradients develop as the current flows through the cell and dissipate during open-circuit and potentiostatic-hold periods. Further details of lithiation dynamics can be obtained through shape analysis of the Bragg peaks. In particular, from electrochemical model simulations, we show that the width and skewness of the (003) peak track (de)lithiation fronts moving across the individual oxide particles.

(003) peak↗
DOE OSTI2022

Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer

Proton-coupled electron transfer (PCET) plays an essential role in a wide range of electrocatalytic processes. Here, a vast array of theoretical and computational methods have been developed to study electrochemical PCET. These methods can be used to calculate redox potentials and pKa values for molecular electrocatalysts, proton-coupled redox potentials and bond dissociation free energies for PCET at metal and semiconductor interfaces, and reorganization energies associated with electrochemical PCET. Periodic density functional theory can also be used to compute PCET activation energies and perform molecular dynamics simulations of electrochemical interfaces. Various approaches for maintaining a constant electrode potential in electronic structure calculations and modeling complex interactions in the electric double layer (EDL) have been developed. Theoretical formulations for both homogeneous and heterogeneous electrochemical PCET spanning the adiabatic, nonadiabatic, and solvent-controlled regimes have been developed and provide analytical expressions for the rate constants and current densities as functions of applied potential. The quantum mechanical treatment of the proton and inclusion of excited vibronic states have been shown to be critical for describing experimental data, such as Tafel slopes and potential dependent kinetic isotope effects. The calculated rate constants can be used as input to microkinetic models and voltammogram simulations to elucidate complex electrocatalytic processes.

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

Modulating Cu electrode microenvironments with MOF coatings: insights from molecular dynamics and electrochemical experiments of CO reduction

Metal-organic frameworks (MOFs) present a compelling strategy for tuning electrochemical interfaces by reshaping interfacial solvent structure. In this study, we examine how MOF coatings influence the microenvironment at copper electrodes during the CO electroreduction reaction (CORR) using a combined approach of molecular dynamics (MD) simulations and electrochemical experiments. Two MOFs, NU-901 and ZIF-8, are selected to explore the impact of pore size and channel hydrophobicity on electrochemical activity and interfacial concentration in acetonitrile (ACN) and dimethyl sulfoxide (DMSO) electrolytes. Electrochemical measurements reveal that MOF@Cu electrodes exhibit lower Faradaic efficiencies for CO hydrogenation products (ethylene and methane) compared to bare copper but have dramatic impacts on the interfacial microenvironment. NU-901, with its larger pores and strong interactions with DMSO, traps DMSO molecules and enhances CO coordination in DMSO but suppresses CORR selectivity in favor of the hydrogen evolution reaction (HER). ZIF-8, with smaller pores and hydrophobic channels, limits the interfacial water concentration, and, in ACN, promotes CO coordination. The simulations provide insights into how MOFs can act as physical modulators of reactant delivery and interfacial structure to control electrochemical microenvironments. This work highlights the value of molecular dynamics in uncovering how structural features of MOFs influence interfacial phenomena, even when catalytic performance is not directly improved.

Copper electrode microenvironments↗
DOE OSTI2023

Optimizing the Composite Cathode Microstructure in All‐Solid‐State Batteries by Structure‐Resolved Simulations

Abstract All‐solid‐state batteries are considered as an enabler for applications requiring high energy and power density. However, they still fall short of their theoretical potential due to various limitations. One issue is poor charge transport kinetics resulting from both material inherit limitations and non‐optimized design. Therefore, a better understanding of the relevant properties of the cathode microstructure is necessary to improve cell performance. In this article, we identify optimization potentials of the composite cathode by structure‐resolved electrochemical 3D‐simulations. In our simulation study, we investigate the influence of cathode active material fraction, density, particle size, and active material properties on cell performance. Special focus is set on the impact of grain boundaries on the cathode design. Based on our simulation results, we can predict target values for cell manufacturing and reveal promising optimization strategies for an improved cathode design.

25 ENERGY STORAGE↗
DOE OSTI2020

Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse

The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.

25 ENERGY STORAGE↗
DOE OSTI2020

Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials

Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple phase boundary density, being highly similar to those of the original microstructure. These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. Finally, the ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.

36 MATERIALS SCIENCE↗
DOE OSTI2020

(Photo)Electrocatalytic CO 2 Reduction at the Defective Anatase TiO 2 (101) Surface

Excessive carbon dioxide (CO 2 ) emissions by combustion of fossil fuels are linked to global warming and rapid climate change. One promising route to lowering the concentration of CO 2 in the atmosphere is to reduce it to useful small molecules via photoelectrocatalytic hydrogenation, which would enable solar energy storage with a zero-carbon emission cycle and perform a more efficient separation of the photogenerated electron and hole pair than pure photocatalysis. Indeed, photoelectrocatalytic CO 2 reduction has been an intense focus of research. Using the density functional theory (DFT), we studied the CO 2 reduction reaction on the defective anatase TiO 2 (101) surface, at both the solvent/catalyst and the electrolyte/catalyst interfaces. The analysis of the electronic structure of the surface shows a contrast between the solvent/catalyst and the electrolyte/catalyst interfaces, which results in the two corresponding catalytic cycles being distinct. Furthermore, our study explains at the electronic and mechanistic levels why methanol is the main product in the presence of the electrolyte and why the overpotential is not only controlled by the reaction process but also by the diffusion process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ion-specific phenomena limit energy recovery in forward-biased bipolar membranes

The ability for bipolar membranes (BPMs) to interconvert voltage and pH makes them attractive materials for use in energy conversion and storage. Reverse-biased BPMs, which use electrical voltage to dissociate water into acid and base, have become increasingly well studied. However, forward-biased BPMs (FB-BPMs), in which voltage is extracted from pH gradients through recombination, require further study. Here physics-based modeling elucidates how the complex coupling of transport and kinetics dictates the performance of FB-BPMs in electrochemical devices. Simulations reveal that the open-circuit potential of FB-BPMs is dictated by the balance of ion recombination and crossover, where recombination of buffering counter-ions attenuates the open-circuit potential. Counter-ion mass-transport limitations and uptake of ionic impurities limit achievable current densities by reducing the applied pH gradient or the available fixed-charge sites that mediate recombination. Further, the model highlights the importance of selective ion management in mitigating energy losses and provides insight into the rational material design of FB-BPMs for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluation of the Generation-2 Dechlorination Apparatus for Treating Salt Wastes

This document satisfies the requirements for two milestones, i.e., M2FT-21PN030103021 and M3FT-21PN030103026, which are described in detail below. Also, details for the work package at the Pacific Northwest National Laboratory (PNNL) are provided below. The goal of this milestone was to demonstrate the generation-2 dechlorination apparatus (G2DA) for removing Cl from chloride-based electrochemical salt simulants. The two salts chosen for this initial study were KCl to simulate a component from the eutectic salt (LiCl is harder to detect with analytical instruments) and CsCl to simulate a fission product chloride that might be present in these types of waste streams. The overall scope of this work included receiving, installing, and testing the G2DA. This new system was designed to address several shortcomings identified with the generation-1 apparatus (G1DA), which are described in detail within this document. The G2DA was designed to address all of these shortcomings. The studies presented in here show that the G2DA worked as intended and will help provide scaled-up batches for additional testing at Argonne National Laboratory.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Electrochemical grand potential-based phase-field simulation of electric field-assisted sintering

Here, an electrochemical grand potential functional was proposed to describe the sintering of an ionic ceramic green body. The resultant phase-field description enables simulation of the consolidation of an arbitrary number of granular particles and their interactions with the surrounding void phase. The model includes the effects of charged vacancies and the associated interactions between internal and applied electric fields. Defect segregation to grain boundaries is also accounted for, as well as enhanced interfacial defect mobilities. The model was parameterized for Y 2 O 3 . Simulations of two-particle systems showed that the applied electric field had an increasingly important impact on neck growth as particle size increased. A sudden rapid increase in temperature occurred for larger field strengths, which has been reported to be correlated to the onset of a flash event in flash sintering. Simulations of many particles showed that internal heat generation by Joule heating was localized at particle–particle contacts (grain boundaries), even though their conductivities were lower than nearby internal particle-void interfaces. A percolative path for ionic charge across the green body and the ceramic sintered solid was thus defined, accelerating the Joule heating process as the porosity of the green body is removed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Localised instability of titanium during its erosion-corrosion in simulated acidic hydrometallurgical slurries

Electrochemical techniques were used to investigate the erosion-corrosion of titanium in simulated acidic mineral leaching slurries. Erosion-corrosion of titanium was caused by solid particle impingement. Electrochemical noise revealed that solid particle impacts resulted in localised fracture of the passive film, and erosion-corrosion of titanium proceeded in the form of current transients. As conditions become more abrasive, erosion-corrosion is an increasing threat to titanium equipment exposed to acidic slurries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory

Renewably driven, electrochemical conversion of carbon dioxide into value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2 to CO reaction intermediate energies at -0.3, -0.7, and -1.2 VSHE catalyzed by MNCs each doped with 1 of the 10 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (-0.7 to -1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate-determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT-computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that the formation of the adsorbed *CO2- anion is critical to CO2R activation. This work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.

CO2 reduction↗
DOE OSTI2022

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗
DOE OSTI2020

Development and Validation of a Simulation Tool to Predict the Combined Structural, Electrical, Electrochemical and Thermal Responses of Automotive Batteries

Battery safety is one of the most important design factors of electrified vehicles (EVs) since battery failure may lead to a catastrophic consequence. To improve the safety of battery systems in EVs, battery behaviors under various abuse conditions should be well understood. One way to examine battery response under extreme conditions is to conduct abuse tests in different scenarios. They can provide first-hand pass/fail information on battery safety, but they are usually expensive and time-consuming, which is inconvenient during design iterations and optimization. On the other hand, computational modeling can predict the battery behaviors in a more efficient and cost-effective way, which becomes an important tool to evaluate battery safety. Modeling battery responses and failure is challenging since it involves multiple coupled physical processes, needs to consider complex material properties and is computationally intensive. This project aims to develop a practical simulation tool to predict the combined structural, electrical, electrochemical, and thermal responses of automotive batteries to crash-induced crush and short circuit and validate it for conditions relevant to automotive crash. Advanced material constitutive models will be utilized to capture the mechanical response of cell components. Moreover, methods will be developed to reduce computational complexity of the model and allow battery safety simulations to extend from cell-level to module/pack level with affordable computational resources.

25 ENERGY STORAGE↗