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Record W4285398585 · doi:10.1149/ma2022-014561mtgabs

Zinc-Ion Capacitors Working at Extreme Conditions

2022· article· en· W4285398585 on OpenAlexaff
Zhixiao Xu, Xiaolei Wang

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAnodeCapacitorElectrolyteSupercapacitorMaterials scienceCathodeEnergy storageCapacitanceCarbon fibersElectrodeEngineering physicsNanotechnologyChemical engineeringOptoelectronicsElectrical engineeringComposite materialChemistryVoltageEngineeringPower (physics)Physics

Abstract

fetched live from OpenAlex

Combing advantages of both Zn anode and carbon cathodes, zinc ion capacitors (ZICs) hold great potentials for electrical vehicles and grid storage. To meet practical applications, high-mass-loading electrodes and harsh environment need to be considered when designing energy storage devices. For one, high-loading electrodes bring simultaneously the dense packing of active materials in limited space and the reduction of inactive components, leading to lower production cost and higher energy densities at the cell level compared with thin electrodes. That is why active mass loadings must be no less than 10 mg cm −2 for practical applications and typical values for commercial energy storage devices are 10-20 mg cm -2 . However, this is not the case in most research papers with typical loadings of only 1-4 mg cm -2 . On the other hand, low and high temperature environment will be encountered in not only extreme regions like North Pole and outer space but also residential areas with ever-changing climate. As such, it is critical to develop cells working in a wide-temperature range of −30 °C–50 °C for most human habitats and a broader range from −50 °C to 70 °C for military uses . Strangely, those two important factors are often ignored in the development of ZICs. In this work, we demonstrate workable ZICs under extreme conditions through the incorporation of activated carbon, aqueous binder and concentrated electrolyte. First, with highly exposed surface area and enriched oxygen, nitrogen dopants, the activated carbon manifests large electrical double layer capacitance and Faradic pseudocapacitance. Second, sodium alginate-based aqueous binder shows better electrolyte wettability than the commonly used polymer binder, resulting in much improved capacitance. Third, highly concentrated electrolyte enables large zinc stripping/plating efficiency, long life cycles as well as low frozen temperature due to reduced hydrogen bonding interaction of water. Three keys combined unlock ZICs with a large capacitance of 436 F g −1 (capacity: 200 mAh g -1 ), ultrafast kinetics, ultralong cycles, ultrahigh loadings (10 mg cm -2 ), and wide-temperature cycling (-60 o C ~ 60 o C), resulting in a maximum energy density of 134.8 Wh kg −1 and power density of 118.4 kW kg −1 based on AC electrode, which lies among the best performance level for carbon-based ZICs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.039
GPT teacher head0.260
Teacher spread0.222 · 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.

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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