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Record W2744316279 · doi:10.1149/ma2017-02/4/340

Subeutectic Growth of Carbon-Coated Silicon Nanowires on Carbon Fabric As Self-Supported Electrodes for Flexible Lithium-Ion Batteries

2017· article· en· W2744316279 on OpenAlexaff
Xiaolei Wang, Ge Li, Xingcheng Xiao, Zhongwei Chen

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsConcordia UniversityUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceAnodeElectrolyteLithium (medication)NanowireSiliconElectrodeNanotechnologyChemical vapor depositionCarbon fibersChemical engineeringOptoelectronicsComposite materialChemistry

Abstract

fetched live from OpenAlex

Developing rechargeable lithium-ion batteries (LIBs) with high energy density, which is of critical importance in energy storage applications such as portable electronics, hybrid electric vehicles (HEVs), and electric vehicles (EVs), requires the development of electrode materials with high capacity. Among the many candidates, silicon (Si) holds great promise and has been extensively studied as anode material owing to its natural abundance and theoretical specific capacity higher than that of graphite (4200 vs 372 mA h g–1) with similar working potential, giving a significantly higher energy density of LIBs. However, Si suffers from a dramatic volume and structure variation during the Li alloying/dealloying process, resulting in the severe pulverization and delamination from current collectors. Moreover, the dynamic formation and decomposition of the solid electrolyte interphase (SEI) layer caused by the side reaction between electrolyte and newly exposed Si surface leads to large irreversible capacities and further causes the rapid performance degradation of the Si-based electrodes. To conquer these critical obstacles, nanostructured Si materials have been widely investigated because they are capable of tolerating extreme changes in volume. Particularly, Si nanowire (NWs) has been considered as the most compelling candidate, since the one-dimensional structure provides not only the shorter lithium-ion diffusion distance due to the narrow diameter combined with long continuous paths for electron transport down their length but also a highly porous architecture, allowing volume variation. The most common approach for the growth of Si NWs involves the medium- or high-pressure chemical vapor deposition (CVD) through the vapor–liquid–solid mechanism, where expensive catalysts (e.g., Au, Ag, and Ga) and hazardous materials (e.g., silane) are often applied. Therefore, advanced technology is highly demanded in the synthesis of high-quality Si NWs for scalable production at low cost. On the other hand, conventional electrode fabrication technology requires significant fractions of binder and conductive agent, which inevitably sacrifice overall energy. Direct deposition of active materials on highly conductive current collectors avoids the use of inert components, resulting in a higher total capacity and a better active material utilization. Moreover, the intimate contact facilitates the electron transport and efficiently improves the electrode integrity as well. Furthermore, the utilization of flexible current collectors enables flexible electrodes, which have been attracting tremendous interest in applications such as wearable electronics and health care devices. So far, there are only a few reports on the fabrication of Si NW-based binder-free and flexible electrodes; however, these flexible electrodes either involve complex synthesis, which is hard for scale-up, or are composed of Si NWs with unsatisfactory quality or nonuniform size. In this context, it is of great importance and challenge as well for effective design and scalable fabrication of high-performance flexible Si NW-based electrodes for practical LIB applications. Herein, we demonstrate self-supported, binder-free, flexible electrodes with long cycling life and controllable high mass loading based on carbon-coated Si NWs grown in situ on highly conductive carbon fabric substrates (c-Si NWs/CF). The carbon-coated Si NWs are synthesized through a nickel catalyzed, bottom-up growth process via a one-pot atmospheric pressure CVD. Ni nanoparticles are first electrodeposited onto a piece of precleaned CF before the Si NWs are grown on the Ni catalyst using SiCl4 as the precursor through a vapor–solid–solid mechanism at a subeutectic temperature of 900 °C (below the eutectic temperature of 993 °C for Ni–Si system in the VLS growth mechanism). A thin carbon layer is coated on the Si NWs using toluene as the carbon source, forming a core–shell structure. Such novel electrodes with a unique three-dimensional architecture possess several characteristics needed for high-performance Si-based electrodes. First, the 1D Si NWs and the porous electrode architecture accommodate the volume change well, while the thin-layer carbon coating effectively confines the Si NWs during cycling. Second, the in-situ growth not only ensures intimate contact of the Si NWs with highly conductive CF, enabling a fast electron transport, but also improves the electrode integrity. Third, high mass loading of carbon-coated Si NWs can be achieved, which holds great potential for next-generation LIBs with high areal capacity and energy density. The high-quality carbon-coated Si nanowires resulted in high reversible specific capacity (∼3500 mA h g–1 at 100 mA g–1), while an exceptionally long cyclability with a capacity retention of ∼66% over 500 cycles at 1.0 A g–1 was achieved. The controllable high mass loading enables an electrode with extremely high areal capacity of ~5.0 mA h cm–2. Such a scalable electrode fabrication technology and the high-performance electrodes hold great promise in future practical applications in high energy density LIBs. Figure 1

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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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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
Published2017
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