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Record W4403839914 · doi:10.1002/cssc.202401681

Aqueous Supercapacitor with Wide‐Temperature Operability and over 100,000 Cycles Enabled by Water‐in‐Salt Electrolyte

2024· article· en· W4403839914 on OpenAlexaff
Zahid Ali Zafar, Radim Weisser, Ghulam Abbas, Martin Šilhavík, Prabhat Kumar, Jiří Červenka

Bibliographic record

VenueChemSusChem · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of Waterloo
FundersGrantová Agentura České RepublikyEuropean Commission
KeywordsSupercapacitorElectrolyteOperabilityMaterials scienceElectrochemistryAqueous solutionEnergy storageChemical engineeringChemistryElectrodeComputer sciencePower (physics)Engineering

Abstract

fetched live from OpenAlex

Abstract Supercapacitors are crucial in renewable energy integration, satellite power systems, and rapid power delivery applications for mitigating voltage fluctuations and storing excess energy. Aqueous electrolytes offer a promising solution for low‐cost and safe supercapacitors. However, they still face limitations in cycle life and wide‐temperature range performance. Here, we present a symmetric supercapacitor utilizing activated carbon electrodes and a “water‐in‐salt” electrolyte (WiSE) based on lithium perchlorate. The WiSE electrolyte exhibits an expanded electrochemical stability window, endowing the aqueous supercapacitor with remarkable stability and long cycle life of over 100,000 cycles at 500 mA g −1 with more than 91 % capacity retention. Moreover, the supercapacitor demonstrates good rate capability and wide temperature operability ranging from −20 to 80 °C. The use of high concentrations of salt in the aqueous electrolyte contributes not only to the enhancement of supercapacitor performance and cycle life but also to the temperature stability range, enabling all‐season operability.

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)0.001
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 score0.005
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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