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Record W4221038484 · doi:10.1002/smll.202200550

Eutectic Electrolytes Chemistry for Rechargeable Zn Batteries

2022· review· en· W4221038484 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSmall · 2022
Typereview
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsEutectic systemElectrolyteMaterials scienceBattery (electricity)NanotechnologyEnergy storageFast ion conductorElectrodeComputer scienceProcess engineeringAlloyMetallurgyChemistryEngineeringPower (physics)Thermodynamics

Abstract

fetched live from OpenAlex

Rechargeable zinc batteries (RZBs) have proved to be promising candidates as an alternative to lithium-ion batteries due to their low cost, inherent safety, and environmentally benign features. While designing cost-effective electrolyte systems with excellent compatibility with electrode materials, high energy/power density as well as long life-span challenge their further application as grid-scale energy storage devices. Eutectic electrolytes as a novel class of electrolytes have been extensively reported and explored taking advantage of their feasible preparation and high tunability. Recently, some perspectives have summarized the development and application of eutectic electrolytes in metal-based batteries, but their infancy requires further attention and discussion. This review systematically presents the fundamentals and definitions of eutectic electrolytes. Besides, a specific classification of eutectic electrolytes and their recent progress and performance on RZB fields are introduced as well. Significantly, the impacts of various composing eutectic systems are disserted for critical RZB chemistries including attractive features at electrolyte/electrode interfaces and ions/charges transport kinetics. The remaining challenges and proposed perspectives are ultimately induced, which deliver opportunities and offer practical guidance for the novel design of advanced eutectic electrolytes for superior RZB scenarios.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.315
Teacher spread0.235 · 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