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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Guidelines for Safe, High Performing Li-Ion Battery Designs for Manned Vehicles

New design features and test methods are in development at NASA to take advantage of the newest high power and energy dense commercial Li-ion cell designs and to achieve passively thermal runaway (TR) propagation resistant (PPR) designs for manned missions requiring high power/voltage. The goal is to minimize the parasitic mass and volume of the battery components; thus reaching a balance between high battery specific power (W/kg) and energy (Wh/kg) as well as power (W/L) and energy density (Wh/L). Current 18650 cell designs achieve greater than 275 Wh/kg, greater than 725 Wh/L, but present high risks of side wall breaching during TR which can defeat many other safety features resulting in nearly immediate TR propagation. This work seeks to better understand the phenomena of cell side wall breaches and to determine the effectiveness of promising battery design features for achieving safe, high performing battery designs for high voltage/power applications.

Darst, John J.↗
NASA NTRS2018

Li(+)-ligand Binding Energies and the Effect of Ligand Fluorination on the Binding Energies

The Li(+)-ligand binding energies are computed for seven ligands and their perfluoro analogs using Density Functional Theory. The bonding is mostly electrostatic in origin. Thus the size of the binding energy tends to correlate with the ligand dipole moment, however, the charge-induced dipole contribution can be sufficiently large to affect the dipole-binding energy correlation. The perfluoro species are significantly less strongly bound than their parents, because the electron withdrawing power of the fluorine reduces the ligand dipole moment.

Charles W Bauschlicher↗
NASA NTRS2019

Prognostics and Health Monitoring in Li-Ion Batteries and Capacitors Using Physics-Based Modeling Approach

In order to tackle and solve the prediction problem of the lifetime of Li-ion batteries, it is essential to have awareness of the current state and health of the battery pack. To be able to accurately predict the future state of any system, one must possess knowledge of its current and future operations. Using derived models of the current and future system behavior, a model-based prognostics approach can be implemented as a solution to the prediction problem. As more and more autonomous electric vehicles progressively emerge in our daily life, a very critical challenge lies in accurate prediction of remaining useful life of the systems/subsystems. Batteries, power electronics conditioning systems, and motors are integrated to form the powertrain in electric vehicles; one of the most critical systems. In the case of electric aircrafts, computing remaining flying time is critical for safety, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastropheThis presentation covers a physics-based modeling approach implemented for case studies in capacitor and battery prognostics which are an integral part of an electrical powertrain system. The general approach of model-based prognostics will be examined as a potential solution for safety critical problems related to battery state of charge and state of health.

Physics based modeling↗
NASA NTRSDate not supplied

Probing Sensitivity of Discharge Characteristics to Model Selection using Uncertainty Quantification in an aprotic Li-Oxygen Battery

Currently, there are several models in the literature, such as kinetic models, microstructural models, and mass transport models that describe a Li-air battery's discharge behavior. Many of these models are calibrated and tested at low current densities and cannot be easily transferred to high current densities. Even at low current densities, there is no quantitative method for a researcher to choose a reaction kinetic model such as classical Butler-Volmer and its derivatives, and modified Marcus-Hush-Chidsey, a resistance model for lithium peroxide such as electron transport via tunneling or linear resistivity, a surface coverage model (lithium peroxide growth) such as partial coverage or full coverage, and mass transport model (discussed in Ref. [1]). Also, it is time-consuming to test different models at high current density (1C) due to a lack of well-tested models and well-calibrated model parameters. For this presentation, we will develop an analytical model, which acts as a surrogate model for a sophisticated finite element model to predict discharge time and discharge voltage. Next, we use an uncertainty quantifying technique called reduced-order stochastic optimization [2, 3] to determine the uncertainty in model parameters for rate kinetics, lithium peroxide resistivity, and parasitic resistance. Finally, a finite element simulation is performed to determine the error introduced by the surrogate model and its influence on the uncertainty in the model parameters.

M Mehta↗
DOE OSTI2021

Rapid Laser Reactive Sintering of Garnet Li 6.1 La 3 Zr 2 Al 0.3 O 12 Solid-State Electrolyte

All solid-state lithium-ion batteries (ASSLIBs) have gained significant interest in recent years due to their wide range of applications, including mobile devices, electric vehicles, and grid storage. Garnet-type Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolyte (SSE) continues to be a significant player in the fabrication of ASSLIBs with excellent ionic conductivity on the order of 10 -3 S•cm -1 with the integration of dopants and sintering aids to assist conductivity and structural evolution during the sintering procedure. Traditional sintering techniques, such as solid-state sintering (SSS), have been proven to yield desirable crystal structures. However, the low ionic conductivity results from inferior microstructure, and lithium loss is a significant challenge. Recently, a relatively novel sintering process called rapid laser reactive sintering (RLRS) has shown great potential for achieving fully dense solid oxide electrolytes with less surface element loss, resulted in high ionic conductivity. Here, we applied the same RLRS method to fabricate LLZO dense electrolyte with different amounts of aluminum dopants. We hope the rapid high-temperature sintering can densify the electrolyte and avoid the lithium loss for achieving high lithium-ion conductivity. In this work, we optimized multiple combinations of laser parameters (speed, power, and defocus distance), initial precursor composition, and controlled atmospheres to discover the optimal conditions for reaching the efficacious crystal structure, microstructure, and ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2021

Metal fluoride passivation coatings prepared by atomic layer deposition for Li-ion batteries

The fabrication of robust interfaces between transition metal oxides and non-aqueous electrolytes is one of the great challenges of lithium ion batteries. Atomic layer deposition (ALD) of aluminum tungsten fluoride (AlWxFy) improves the electrochemical stability of LiCoO2. AlWxFy thin films were deposited by combining trimethylaluminum and tungsten hexafluoride. in-situ quartz crystal microbalance and transmission electron microscopy studies show that the films grow in a layer-by-layer fashion and are amorphous nature. Ultrathin AlWxFy coatings (<10 Å) on LiCoO2 significantly enhance stability relative to bare LiCoO2 when cycled to 4.4 V. The coated LiCoO2 exhibited superior rate capability (up to 400 mA/g) and discharge capacities at a current of 400 mA/g were 51% and 92% of the first cycle capacities for the bare and AlWxFy coated materials. These results open new possibilities for designing ultrathin and electrochemically robust coatings of metal fluorides via ALD to enhance the stability of Li-ion electrodes.

Mane, Anil U.↗
DOE OSTI2022

Physics-Informed Neural Network Modeling of Li-Ion Batteries: Preprint

Li-ion batteries (LIB) are a promising solution to enable storage of intermittent energy sources due to their high energy density. However, LIBs are known to significantly degrade after about 1000 charge-discharge cycles. LIBs degrade following different degradation modes and at a rate that depends on the operating conditions (external temperature, load). To plan the installation of batteries, appropriate understanding and prediction capabilities of their lifecycle is needed. High-fidelity numerical models of LIBs such as the pseudo-two-dimensional (P2D) model have been shown to accurately represent the charge-discharge-cycle of an LIB given ac- curate choice of the physical parameters. Given the large number of P2D parameters, adjusting them using forward runs is intractable. This work describes the development of a physics-informed neural network (PINN) as a surrogate substitute of the P2D model that captures parameter dependence. The PINN is advantageous as it needs little to no data, and can naturally encode the dependence of every model parameter. Here, a specific training procedure is adopted to efficiently cover parameter space, handle model stiffness and enforce boundary conditions. The trained PINN is validated against numerical solutions of the P2D model, and its applicability to battery degradation modeling is discussed.

battery degradation↗
DOE OSTI2023

Meshfree Multiphysics Damage Modeling of Li-ion Battery Materials

Through repeated charging and discharging cycles, the electrodes of a Li-ion battery experience significant swelling and contraction due to the movement of lithium, also known as intercalation. This research focuses specifically on the chemo-mechanical cracking in the cathode. Because cathode particles are comprised of many randomly-oriented grains, which have highly anisotropic material properties, the expansion and contraction is very non-uniform. As a result, stress concentrations tend to form between grains, which necessitates the modeling of crack propagation largely along grain boundaries and material interfaces. Chemo-mechanical damage models are generally simulated by one of two methods: the cohesive zone model (CZM) and the continuous damage model (CDM). The CZM is more accurate at capturing the sharp discontinuities of a crack but is very computationally expensive and intractable for large-scale models as a result. Conversely, the CDM is easily computed but not well-suited to easily allow for discontinuous field variables, which are inherent across a crack. This study aims to improve the CDM's ability to capture discontinuous cracks. Current versions of the CDM use the finite element method (FEM), which is one of the most widely used approaches for spatial discretization. This research investigates the use of the Reproducing Kernel Particle Method (RKPM), a meshfree method, for spatial discretization and aims to achieve a coupled chemo-mechanical crack propagation model that enhances accuracy while maintaining high computational efficiency. This model features a fully coupled, iterative electrochemistry solution, which informs the meshfree damage model of impending crack formation. To gain a better understanding of how the meshfree model compares to the current FEM model in capturing cathode crack propagation, further investigation is needed.

damage modeling↗
DOE OSTI2024

Image-Based Digital Twin for Assessing the Coupled Electro-Chemo-Mechanical Behavior of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The discrete nature of the images' pixel points is employed throughout the model and approximation construction. The mechanical model is verified using an image-based microstructure under tensile loading. A transient electro-chemo-mechanical coupled simulation is performed to evaluate the potential micro-cracking induced degradation of the battery cathode material subjected to charge/discharge cycling.

battery degradation↗
DOE OSTI2022

Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are widely adopted in many industrial applications. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Therefore, it can eventually help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. However, these images often suffer from low image contrast between multiple material constituents , making it difficult for humans to distinguish and characterize these constituents through visualization. A minor error in detecting distributions among the material constituents can lead to a high error in the calculated parameters of material properties.We present a novel hierarchical curriculum learning framework to address the complex task of estimating material constituent distribution in battery electrodes. To provide spatially smooth prediction, our framework comprises three modules: (i) an uncertainty-aware model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a technique to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator to appropriately fuse the local and global effects towards obtaining the final distribution.

Tabassum, Anika↗
DOE OSTI2024

Metal fluoride passivation coatings prepared by atomic layer deposition for Li-ion batteries

The fabrication of robust interfaces between transition metal oxides and non-aqueous electrolytes is one of the great challenges of lithium ion batteries. Atomic layer deposition (ALD) of aluminum tungsten fluoride (AlWxFy) improves the electrochemical stability of LiCoO 2 . AlWxFy thin films were deposited by combining trimethylaluminum and tungsten hexafluoride. in-situ quartz crystal microbalance and transmission electron microscopy studies show that the films grow in a layer-by-layer fashion and are amorphous nature. Ultrathin AlWxFy coatings (<10 Å) on LiCoO 2 significantly enhance stability relative to bare LiCoO 2 when cycled to 4.4 V. The coated LiCoO 2 exhibited superior rate capability (up to 400 mA/g) and discharge capacities at a current of 400 mA/g were 51% and 92% of the first cycle capacities for the bare and AlWxFy coated materials. These results open new possibilities for designing ultrathin and electrochemically robust coatings of metal fluorides via ALD to enhance the stability of Li-ion electrodes.

Mane, Anil U.↗
DOE OSTI2022

Constructing O2/O3 homogeneous hybrid stabilizes Li-rich layered cathodes

With the advantages of high energy density and low manufacture cost, lithium-rich layered oxides (LLOs), typically with a layered O3-type structure, are regarded as promising cathodes for lithium-ion batteries (LIBs), but their broad usages are hindered by severe voltage decay over cycling. Although recent progress in O2-type LLOs has aroused interest for their less voltage decay, the critical barrier of unsatisfactory capacity retention has not been overcome yet. In this work, to tackle these handicaps, we design a new type of LLO (O2/O3-type LLO) with a homogeneous hybrid structure, where the O2 and O3 lattice stacking sequences are arranged alternatively. Benefitting from this novel O2/O3 hybrid structure, the designed material shows greatly improved voltage and capacity stability than that of pure O2- and O3-type LLOs. Revealed by in-situ synchrotron X-ray diffraction and operando differential electrochemical mass spectra, the O2/O3-hybrid LLO cathode shows a more reversible structural evolution, smaller volume change and suppressed oxygen loss during the electrochemical processes. Our approach has initiated a new way to reduce the capacity and voltage decay of LLOs, which endows great promise to the development of high-energy-density LIBs.

25 ENERGY STORAGE↗