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Record W3034294738 · doi:10.11575/prism/37732

Microstructured Materials for Lithium-ion Batteries

2020· dissertation· en· W3034294738 on OpenAlexfundno aff
Umer Farooq

Bibliographic record

VenuePRISM (University of Calgary) · 2020
Typedissertation
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFord Motor Company
KeywordsLithium (medication)Materials scienceIonNanotechnologyChemistryMedicineInternal medicineOrganic chemistry

Abstract

fetched live from OpenAlex

Energy storage technology plays a vital role in a renewable energy harvesting system by providing the capability to remain functional during the intermittence periods. The long developmental and research phase which lithium-ion batteries (LIBs) batteries have undergone has made them one of the most prominent and promising energy storage technologies. Their high energy and power density, low cost, environmental benignity and excellent cyclic stability make them more attractive than competing energy storage technologies. Extensive efforts have been deployed on the synthesis of electrode and electrolyte materials for LIBs to increase their charge storage capacity and safety without affecting the cyclic stability. Among various electrode materials for LIBs, nanostructured metal-oxides have gained substantial attention as anodes due to their stable battery cycling. The high C-rate capacities of these electrode materials are attributed to the interesting conversion reactions of lithium ions (Li). Titanium dioxide (TiO2), among all the metal oxides, has shown great potential as a negative electrode material for LIBs in particular. Over the years, numerous methods have been adopted to enhance the electrochemical performance by bringing innovation TiO2 design; however, the low electronic conductivity remains a major challenge in achieving the best performance. In the first part of this PhD work, novel electrode architectures for TiO2 have been developed by preparing TiO2-graphene nanocomposite. The as-prepared material has exploited the unique electronic and mechanical characteristics of nanostructures to develop robust electrodes that improved electronic conductivity, electrochemical charge transfer and the storage capacity at high current densities. The TiO2-rGO nanocomposite delivered a capacity of ~ 250 mAh g1 at 0.2 C and exhibited superior rate capability performance with remarkably stable cycle life at high C-rates up to 20 C during the Li+ insertion/extraction process. To explore the further opportunities along the electrode side, silicon (Si) was investigated as an anode material for LIBs. Si can deliver a high theoretical capacity as an anode material; however, volume change during the alloying/dealloying reaction with Li limits its utilization in a practical battery. In this work, a unique structure comprised of Si cross-linked with hierarchical porous carbon spheres was demonstrated as a stable Li+ host to address the challenge of swelling and mechanical fracture in Si electrode. The high surface area with well-defined pore size distribution and fully exposed active sites not only defied the limitation of low Li+ storage but also facilitated the mobility of Li+ during alloying/dealloying, resulting in stable redox activity during battery cycling. Upon electrochemical response investigation, the as-prepared composite material delivered a stable and high discharge capacity (ca. 1200 mAh g1) even after 400 cycles with a relatively high columbic efficiency (> 99%) when tested with an alginate-assisted binder. This highly stable performance could be attributed to the lower volume change and enhanced conductivity of composite material. In contrast to the electrode section, safety of the LIBs has been identified as one of the major concerns in field of battery research that mainly arises from electrolytes. Unprecedented interest in solid-state Li-ion batteries (SSLIBs) for automotive applications has stimulated extensive research on solid-state electrolytes (SSE). A part of this dissertation was dedicated to the development of flexible ceramic-polymer composite electrolyte. In order to characterize the desired SSE, lithium stuffed garnet material, Li6.5La2.5Ba0.5TaZrO12 (LLBTZO) was synthesized via a solid-state method. To analyze the effect of sintering temperature on the microstructure and transport properties of as-prepared SSE, various physical and electrochemical studies were carried out to confirm the crystal structure, explore the morphological properties and electrochemical performance of the SSE material. Increasing the sintering temperature of this compound from 1100 to 1200 °C led to a more than a 60-fold increase in the ionic conductivity (at 26 °C) from 1.07 x 10-6 to 6.62 x 10-5 S cm-1, which can be attributed to the evolution of the microstructures of the SSE. Since these garnet-type materials are brittle and prone to cracking, it is not viable to use them in a practical battery directly. To obtain the mechanical properties desirable in a practical battery, ceramic-polymer based composites were developed using a track-etched polycarbonate (TEPC) to provide some form of flexibility. The LLBTZO particles were infiltrated in a TEPC membrane to make a composite. During the sintering process, the TEPC was decomposed to grow free-standing pillars having an approximate length and diameter of ~ 25 µm and 10 µm respectively. Further research is needed to select favorable polymers which could be adopted to fill the voids between the pillars to provide integrity and flexibility subsequently for its final integration in a working battery.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.005

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 head0.204
Teacher spread0.196 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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