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Record W7039514156

Nanoscale X-ray Computed Tomography Based Modeling of Lithium-ion Battery Electrodes

2018· dissertation· en· W7039514156 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2018
Typedissertation
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsField (mathematics)Work (physics)Scale (ratio)Phase (matter)Noise (video)
DOInot available

Abstract

fetched live from OpenAlex

Because of their high energy/power density, long cycle life, and extremely low rate of self-discharge, lithium-ion batteries (LIBs) have dominated portable electronics, smart grid, and electric vehicles (EVs). Although they are the most developed and widely applied energy storage technology, there is still a strong desire to further enhance their energy/power density, cycle life, and safety. While all of these battery requirements are macroscopic and stated at cell/pack scale, they have to be addressed at particle or network of particles scale (mesoscale). At mesoscale, active material particles having different shape and morphologies are bound together with a carbon-doped polymer binder layer. This percolated network of particles serves as the electron conductive path from the reaction sites to the current collector. Even though significant research has been conducted to understand the physical and electrochemical behavior of material at the nanoscale, there have not been comprehensive studies to understand what is happening at the mesoscale. \nMathematical models have emerged as a promising way to shed light on complex physical and electrochemical phenomena happening at this scale. The idea of using mathematical model to study multiphysics behavior of LIBs is not new. Traditional models involved homogeneous spherical particles or computer generated electrode structures as the model geometry to simulate electrode/cell performance. While these models are successful to predict the cell performance, heterogeneous electrode’s structure at mesoscale questions the accuracy of their findings related to battery internal behavior and property distribution. \nThe new advances in the field of 3D imaging including X-ray computed tomography (XCT) and Focused-ion beam/Scanning electron microscopy (FIB-SEM), have enabled the 3D visualization of the electrode’s active particles and structures. In particular, XCT has offered nondestructive imaging and matter penetration capability in short period of time. Although it was commercialized in 70’s, with the recent development of high resolution (down to 20 nm) laboratory and synchrotron radiation tomography has been revolutionized. 3D reconstructed electrodes based on XCT data can provide quantitative structural information such as particle and pore size distribution, porosity, solid/electrolyte interfacial surface area, and transport properties. In addition, XCT reconstructed geometry can be easily adopted as the model geometry for simulation purposes. For this, similar to traditional models, a modeling framework based on conservation of mass/charge and electrochemistry needs to be developed. The model links the electrode performance to the real electrode’s structure geometry and allows for the detailed investigation of multiphysics phenomena. When combined with mechanical stress, such models can also be used for electrode’s failure and degradation studies. The work presented in this dissertation aims to adopt 3D reconstructed structures from nano-XCT as the geometry to study multiphysics behaviour of the LIBs electrodes. In addition, 3D reconstructed structure provides more realistic electrode’s morphological and transport properties. Such properties can benefit the homogeneous models by providing highly accurate input parameters. \nIn the first study, a multiscale platform has been developed to model LIB electrodes based on the reconstructed morphology. This multiscale framework consists of a microscale level where the electrode microstructure architecture is modeled and a macroscale level where discharge/charge is simulated. The coupling between two scales is performed in real time unlike using common surrogate based models for microscale. For microscale geometry 3D microstructure is reconstructed based on the nano-XCT data replacing typical computer generated microstructure. It is shown that this model can predict the experimental performance of LiFePO4 (LFP) cathodes at different discharge rates more accurately than the traditional/homogenous models. The approach employed in this study provides valuable insight into the spatial distribution of lithium within the microstructure of LIB electrodes. \nIn the second study, a new model that keeps all major advantages of the single-particle model of LIB and includes three-dimensional structure of the electrode was developed. Unlike the single spherical particle, this model considers a small volume element of an electrode, called the Representative Volume Element (RVE), which represent the real electrode structure. The advantages of using RVE as the model geometry was demonstrated for a typical LIB electrode consisting of nano-particle LFP active material. The model was employed to predict the voltage curve in a half-cell during galvanostatic operations and validated against experimental data. The simulation results showed that the distribution of lithium inside the electrode microstructure is very different from the results obtained based on the single-particle model. \nIn the third study, synchrotron X-ray computed tomography has been utilized using two different imaging modes, absorption and Zernike phase contrast, to reconstruct the real 3D morphology of nanostructured Li4Ti5O12 (LTO) electrodes. The morphology of the high atomic number active material has been obtained using the absorption contrast mode, whereas the percolated solid network composed of active material and carbon-doped polymer binder domain (CBD) has been obtained using the Zernike phase contrast mode. The 3D absorption contrast image revealed that some LTO nano-particles tend to agglomerate and form secondary micro-sized particles with varying degrees of sphericity. The tortuosity of the pore and solid phases were found to have directional dependence, different from Bruggeman’s tortuosity commonly used in homogeneous models. The electrode’s heterogeneous structure behaviour was also investigated by developing a numerical model to simulate a galvanostatic discharge process using the Zernike phase contrast mode. \nIn the last study, synchrotron X-ray nano-computed tomography has been employed to reconstruct real 3D active particle morphology of a LiMn2O4 (LMO) electrode. For the first time, CBD has been included in the electrode structure as a 108 nm thick uniform layer using image processing technique. With this unique model, stress generated inside four LMO particles with a uniform layer of CBD has been simulated, demonstrating its strong dependence on local morphology (surface concavity and convexity), and the mechanical properties of CBD such as Young’s modulus. Specifically, high levels of stress have been found in vicinity of particle’s center or near surface concave regions, however much lower than the material failure limits even after discharging rate as high as 5C. On the other hand, the stress inside CBD has reached its mechanical limits when discharged at 5C, suggesting that it can potentially lead to failure by plastic deformation. The findings in this study highlight the importance of modeling LIB active particles with CBD and its appropriate compositional design and development to prevent the loss of electrical connectivity of the active particles from the percolated solid network and power losses due to CBD failure. \nThere are still plenty of opportunities to further develop the methods and models applied in this thesis work to better understand the multiscale multiphysics phenomena happening in the electrode of LIBs. For example, in the multiscale model, microscale solid phase charge transfer and electrolyte mass/charge transfer can be included. In this way, heterogeneous distribution of current density in microscale would be achieved. Also, in both multiscale and RVE models, the exact location of CBD can be incorporated in the electrode structure to specify lithium diffusional path inside the group of particles in the solid matrix. Finally, in the fourth study, the vehicle battery driving cycle can be applied instead of galvanostatic operating condition, to mimic the stress generated inside the electrodes in real practical condition. \n

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.193
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueUWSpace (University of Waterloo)→Same topicAdvancements in Battery Materials→French-language works237,207→