IN SITU MORPHOLOGICAL AND STRUCTURAL STUDY OF HIGH CAPACITY ANODE MATERIALS FOR LITHIUM-ION BATTERIES
Bibliographic record
Abstract
Lithium-ion batteries(LIBs) have dominated the energy storage market in the past two decades. The high specific energy, low self-discharge, relatively high power and low maintenance of LIBs enabled the revolution of electronic devices and electric vehicle industry, changed the communication and transportation styles of the modern world. Although the specific energy of LIBs has increased significantly since first commercialized in 1991, it has reached a bottleneck with current electrode materials. To meet the increasing market demand, it is necessary to develop high capacity electrode materials.<br>Current commercial anode material for LIB is graphite which has a specific capacity of 372 mAh g-1. Other group IV elements (silicon (Si), germanium (Ge), tin (Sn)) have much higher capacities. However, group IV elements have large volume change during lithiation/delithiation, leading to pulverization of active materials and disconnection between electrode particles and current collector, resulting in fast capacity fading. To address this issue, it is essential to understand the microstructural evolution of Si, Ge and Sn during cycling.<br><br>This dissertation is mainly focused on the morphological and structural evolution of Sn and Ge based materials. In this dissertation, anin situ focused ion beam-scanning electron microscopy (FIB-SEM) method is developed to investigate the microstructuralevolution of a single electrode particle and correlate with its electrochemical performance. This method is applied toall projects. The first project is to investigate the microstructural evolution of a Sn particle during cycling. Surface structures of Sn particles are monitored and correlated with different states of charge. The second project is to investigate the morphological evolution of Ge particles at different conditions. Different structures (nanopores, cracks, intact surface) appear at different cycling rates. The third project is to study selenium doped Ge (GeSe) anodes. GeSe and Ge particles are tested at the same condition. Se doping forms Li-Ge-Se network, provides fast Li transport and buffers volume change. The fourth project is to study the reaction front of Ge particle during lithiation. Micron-sized Ge particles have two reaction fronts and a wedge shape reaction interface, which is different from the well-known core-shell mode. The fifth project is to investigate antimony (Sb)-coated porous Ge particles. The Sb coating suppresses electrolyte decomposition and porous structure alleviates volume change. The results in this dissertation reveal fundamental information about the reaction mechanism of Sn and Ge anode. The results also show the effects of doping, porous structuring and surface coating of anode materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.038 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".