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Record W4323658109 · doi:10.1002/cplu.202300044

Effects of Various Valence Ions on an Aqueous Rechargeable Zn//Polyaniline‐coated ZnMn<sub>2</sub>O<sub>4</sub> Battery

2023· article· en· W4323658109 on OpenAlexaff
Yu Liu, Yu Xia Liu, Rongguan Lv, Mei Han, Yingna Chang, Zhiyuan Zhao, Yuzhen Sun, Tuan K.A. Hoang, Rong Xing

Bibliographic record

VenueChemPlusChem · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Waterloo
FundersJiangsu Key Laboratory for Bioresources of Saline SoilsJiangsu Agricultural Science and Technology Innovation FundNatural Science Foundation of Jiangsu ProvinceGovernment of Jiangsu ProvinceJiangsu Provincial Key Laboratory of New Environmental ProtectionJiangsu Provincial Department of Education
KeywordsElectrolyteZincPolyanilineValence (chemistry)ElectrochemistryInorganic chemistryDendrite (mathematics)IonAqueous solutionMaterials scienceBattery (electricity)CorrosionAdsorptionCathodeChemistryChemical engineeringMetallurgyPolymerComposite materialPhysical chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Zinc corrosion and dendrite formation are the main issues which impede the performance of aqueous zinc ion batteries (ZIBs) after certain times. In this work, we systematically investigated the effects of three different valence ions (e. g., Na + , Mg 2+ , Al 3+ ) as electrolyte additives on the suppression of zinc corrosion and the inhibition of dendrite growth. By combining experiments and theoretical calculations, it has been found that the existence of Na + ions effectively suppressing the zinc dendrite growth because Na + possessess high adsorption energy approximately −0.39 eV. Moreover, Na + ions could lengthen the zinc dendrite formation duration up to 500 h. On the other hand, the PANI/ZMO cathode materials showed the small band gap approximately 0.097 eV, signifying that the PANI/ZMO possessed the semiconductor characteristics. Furthermore, an assembled Zn//PANI/ZMO/GNP full battery using Na + ions as electrolyte additive displayed capacity retention of 90.2 % after 500 cycles at 0.2 A g −1 , whereas the capacity retention of the control battery using pure ZnSO 4 electrolyte was only 58.2 %. This work could provide a reference for the selection of electrolyte additives in future 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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.

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

Citations5
Published2023
Admission routes1
Has abstractyes

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