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Record W6907781548 · doi:10.25394/pgs.13110593.v1

IN SITU MORPHOLOGICAL AND STRUCTURAL STUDY OF HIGH CAPACITY ANODE MATERIALS FOR LITHIUM-ION BATTERIES

2020· dissertation· en· W6907781548 on OpenAlexfundno aff

Bibliographic record

VenueFigshare · 2020
Typedissertation
Languageen
FieldMaterials Science
TopicChemical and Physical Properties of Materials
Canadian institutionsnot available
FundersArgonne National LaboratoryBasic Energy SciencesDivision of Chemical, Bioengineering, Environmental, and Transport SystemsFundamental Research Funds for the Central UniversitiesOffice of ScienceNational Natural Science Foundation of ChinaWuhan UniversityCanada Excellence Research Chairs, Government of CanadaU.S. Department of EnergyLarge-Scale Instrument and Equipment Sharing Foundation of Wuhan UniversityNational Science Foundation
KeywordsAnodeElectrodeParticle (ecology)TinElectrochemistryGraphiteEnergy storageNanoparticle

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0380.000

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 head0.050
GPT teacher head0.271
Teacher spread0.221 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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