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Record W2275577830 · doi:10.1021/acsnano.5b06538

Heterogeneous WS<sub><i>x</i></sub>/WO<sub>3</sub> Thorn-Bush Nanofiber Electrodes for Sodium-Ion Batteries

2016· article· en· W2275577830 on OpenAlexfundno aff
Won‐Hee Ryu, Hope Wilson, Sungwoo Sohn, Jinyang Li, Xiao Tong, Evyatar Shaulsky, Jan Schroers, Menachem Elimelech, André D. Taylor

Bibliographic record

VenueACS Nano · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsDivision of Materials ResearchBrookhaven National LaboratoryNature Conservancy of CanadaBasic Energy SciencesMaterials Research Science and Engineering Center, Harvard UniversityNational Science FoundationYale UniversityU.S. Department of Energy
KeywordsNanofiberElectrodeSodiumMaterials scienceIonNanotechnologyChemical engineeringInorganic chemistryChemistryMetallurgyPhysical chemistryEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Heterogeneous electrode materials with hierarchical architectures promise to enable considerable improvement in future energy storage devices. In this study, we report on a tailored synthetic strategy used to create heterogeneous tungsten sulfide/oxide core-shell nanofiber materials with vertically and randomly aligned thorn-bush features, and we evaluate them as potential anode materials for high-performance Na-ion batteries. The WSx (2 ≤ x ≤ 3, amorphous WS3 and crystalline WS2) nanofiber is successfully prepared by electrospinning and subsequent calcination in a reducing atmosphere. To prevent capacity degradation of the WSx anodes originating from sulfur dissolution, a facile post-thermal treatment in air is applied to form an oxide passivation surface. Interestingly, WO3 thorn bundles are randomly grown on the nanofiber stem, resulting from the surface conversion. We elucidate the evolving morphological and structural features of the nanofibers during post-thermal treatment. The heterogeneous thorn-bush nanofiber electrodes deliver a high second discharge capacity of 791 mAh g(-1) and improved cycle performance for 100 cycles compared to the pristine WSx nanofiber. We show that this hierarchical design is effective in reducing sulfur dissolution, as shown by cycling analysis with counter Na electrodes.

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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.219
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.

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

Citations130
Published2016
Admission routes1
Has abstractyes

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