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Record W3084993489 · doi:10.1142/s1793292020501179

Graphene-Wrapped ZnMn<sub>2</sub>O<sub>4</sub> Nanoparticles with Enhanced Performance as Lithium-Ion Battery Anode Materials

2020· article· en· W3084993489 on OpenAlexaff
Meng Sun, Sijie Li, Jiajia Zou, Zhipeng Cui, Qingye Zhang, F. Schiettekatte, David Barba, Bing Liu, Yiqian Wang

Bibliographic record

VenueNANO · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité de MontréalRegroupement Québécois sur les Matériaux de Pointe
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsMaterials scienceGrapheneAnodeNanoparticleLithium (medication)ElectrochemistryChemical engineeringComposite numberLithium-ion batteryNanotechnologyOxideBattery (electricity)Composite materialMetallurgyElectrode

Abstract

fetched live from OpenAlex

ZnMn 2 O 4 nanoparticles (NPs) wrapped by reduced graphene oxide (rGO) were fabricated via a two-step solvothermal method and used as an anode material for lithium-ion batteries (LIBs). Compared to pure ZnMn 2 O 4 , the ZnMn 2 O 4 NPs/rGO composites deliver higher capacities of 1230 mAh g −1 and 578 mAh g −1 after 200 cycles at a current density of 100 mA g −1 and 500 mA g −1 , respectively. The enhanced electrochemical performance of ZnMn 2 O 4 NPs/rGO composites is mainly attributed to a distinctive structure (ZnMn 2 O 4 NPs surrounded by flexible rGO), which can promote the diffusion of Li + , accelerate the transport of electrons and buffer volume expansion during the Li + insertion/extraction process. Furthermore, the rGO sheets can effectively prevent the agglomeration of ZnMn 2 O 4 NPs, thus, improving structural stability of the composites. The excellent electrochemical performance indicates that such ZnMn 2 O 4 NPs/rGO composite structure has a great potential for high-performance LIBs.

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), Insufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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