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Optimizing electrolyte systems for stable and low-temperature zinc-ion batteries via efficient coordinator

2024· article· en· W4393210121 on OpenAlexaff
Han Huang, Ziwei Zhao, Pengcheng Li, Hao Zhang, Ge Li

Bibliographic record

VenueJournal of Power Sources · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsElectrolyteZincMaterials scienceIonInorganic chemistryChemistryChemical engineeringMetallurgyEngineeringElectrodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Aqueous zinc-ion battery suffers poor cycling stability due to uneven Zn2+ deposition and serious dendrite growth. To effectively protect the Zn metal anode, diglyme (G2) is added as the co-solvent. Adding G2 can reconstruct the Zn2+ solvation structure and reduce the water molecule content of [Zn(H2O)6]2+ sheath. Theoretical calculations confirm that by adding G2, the triflate group OTF− ion shows greater interaction with Zn, and the water molecules from the [Zn(H2O)6]2+ solvation structure are replaced by OTF− ions. Benefitted from this, an organic-inorganic SEI layer is formed on the Zn anode, which isolates the Zn anode from the bulk electrolyte, and allows/suppresses Zn2+ diffusion. As well, Zn corrosion and side reactions are inhibited in this system. This co-solvent electrolyte system has a high Coulombic efficiency of 99.7%. A long cycling life of 1000 cycles with capacity retention of 80% is demonstrated by Zn//iodine (I2) - Activated Carbon (AC) full cell at room temperature. Even under a low-temperature condition (−18 °C), Zn//I2 - AC full cell shows a long lifespan of 1000 cycles with capacity retention of 65%. This work demonstrates a new direction and unparalleled insight into electrolyte engineering with solvation structure regeneration and SEI player formation for aqueous zinc-ion batteries.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.514

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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