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Record W4391662883 · doi:10.1149/ma2023-023478mtgabs

Approaches to Control Air Stability, Capacity Retention, Gas Generation, and Impedance Growth of Layered Oxide Positive Electrode Materials for Sodium-Ion Batteries

2023· article· en· W4391662883 on OpenAlexaff
Libin Zhang, Hussein Hijazi, Ziwei Ye, Ethan D. Alter, Jay Deshmukh, J. R. Dahn, Michael Metzger

Bibliographic record

VenueECS Meeting Abstracts · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrodeMaterials scienceElectrical impedanceOxideIonChemical engineeringSodiumChemistryElectrical engineeringMetallurgyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Sodium-ion batteries made of earth-abundant elements could potentially become affordable, scalable, and sustainable energy storage solutions. Among different sodium-ion positive electrode chemistries, layered transition metal oxides are of special interest due to their promising energy densities. Specific energy densities close to LiFePO4-based lithium-ion batteries have been demonstrated. [1] Promising capacity retention has been demonstrated as well, with >4,000 cycles to 80% at 30°C. [1] However, the poor air-stability of layered sodium-ion positive electrode materials poses challenges in materials storage and processing in both laboratory and industry scales. Moreover, sodium layered oxides can go through complex phase transitions during electrochemical sodium intercalation, which can result in poor capacity retention unless mitigated by effective materials design. Other challenges are gas generation, impedance growth and sodium plating during cycling, which must all be addressed to make viable layered oxide-based sodium-ion batteries for large-scale storage of renewable energy from wind and solar. In this contribution, we first explore compositional modification as an approach to mitigate structural degradation in sodium layered oxides during air exposure and sodium intercalation. A combination of substituent elements is utilized to dramatically improve air stability as evidenced by X-ray diffraction (XRD) and scanning electron microscopy (SEM) experiments. X-ray photoelectron spectroscopy (XPS) and energy-dispersive X-ray spectroscopy (EDS) are employed to understand the underlying mechanism that leads to improved air stability. Furthermore, coin cell results suggest that compositional modification enhances the capacity retention without sacrificing reversible capacity. [2] Secondly, we explore the performance of layered oxide positive electrodes in machine-made 250 mAh pouch cells with hard carbon negative electrodes. The capacity retention and impedance growth are studied in 40°C cycling tests with various electrolyte additives. High cycling stability with >99% capacity retention after 200 cycles can be attained with simple electrolyte additives. However, specialized additives need to be selected to suppress gas generation and impedance growth. Symmetric cell impedance spectroscopy is used to reveal whether impedance growth stems from the positive or negative electrode. [3] Gas generation is assessed by in-situ volume measurements using the Archimedes principle. [4] Interestingly, sodium-ion cells show distinct differences to lithium-ion batteries in terms of their gas generation during the formation cycle. Moreover, sodium plating can have a surprising effect on the gas generation during charge/discharge cycling. Using ultra-high precision coulometry, the critical conditions for sodium plating and its effect on cell performance are determined. In-situ volume measurements reveal a surprising mechanism that explains the interesting relationship between gas generation and cell voltage in sodium-ion batteries. [5] References [1] J. Barker, 242nd ECS Meeting, Atlanta (2022). [2] L. Zhang et al., manuscript in preparation. [3] H. Hijazi, Z. Ye, et al., manuscript in preparation. [4] C. Aiken et al., J. Electrochem. Soc. 161, A1548–A1554 (2014). [5] E. Alter et al., manuscript in preparation. Figure 1. Discharge capacity (a), discharge capacity normalized to cycle 5 (b), and voltage polarization vs cycle number (c) for Na-ion pouch cells cycling at C/5 and 40°C with various electrolyte additives in 1M NaPF6 EC:DEC (1:1 w/w). 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 score0.000
Threshold uncertainty score0.002

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.235
Teacher spread0.182 · 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
Published2023
Admission routes1
Has abstractyes

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