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Record W4405495014 · doi:10.3390/batteries10120447

ZnSe⊂MoSe2/rGO Petal-like Assembly as Fast and Stable Sodium Ion Storage Anodes

2024· article· en· W4405495014 on OpenAlexafffund
Haoliang Xie, Shunxing Chen, Lianghao Yu, Guang Chen, Huile Jin, Jun Li, Shun Wang, Jichang Wang

Bibliographic record

VenueBatteries · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsAnodeFaraday efficiencyMaterials scienceGrapheneChemical engineeringOxideSodiumNanoparticleEnergy storageElectrochemistryNanotechnologyElectrodeChemistryMetallurgyPower (physics)

Abstract

fetched live from OpenAlex

The development of high energy and power density sodium-ion batteries (SIBs) has attracted increasing interest in the last two decades due to the abundance and cost-effectiveness of sodium resources. Herein, this study developed a self-templating synthetic method to construct MoSe2 nanosheets which were intercalated by ZnSe nanoparticles and were anchored on the in situ reduced graphene oxide layers. The thus-fabricated composites exhibited excellent Coulombic efficiency, a remarkable rate capability and an exceptionally long cycle life when being utilized as the anode in SIBs. Specifically, a reversible capacity of 265 mAh g−1 was achieved at 20 A g−1, which could be maintained for 6400 cycles. At an ultra-high rate of 30.0 A g−1, the anode retained a capacity of 235 mAh g−1 after 9500 cycles. Such a strong performance was attributed to its unique porous structure and synergistic interactions of multi-components. The underlying sodium storage mechanism was further investigated through various techniques such as in situ X-ray diffraction spectroscopy, the galvanostatic intermittent titration method, etc. Overall, this study illustrates the great potential of clad-structured multicomponent hybrids in developing high-performance SIBs.

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 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 score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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