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Record W2767152203 · doi:10.1039/c6cs00639f

Biomass-derived nanostructured carbons and their composites as anode materials for lithium ion batteries

2017· review· en· W2767152203 on OpenAlex
Wenyu Long, Baizeng Fang, Anna Ignaszak, Zhuangzhi Wu, Yan-Jie Wang, David P. Wilkinson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Society Reviews · 2017
Typereview
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of FrederictonUniversity of New BrunswickVancouver Biotech (Canada)University of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnodeRenewable energyBiomass (ecology)Materials scienceLithium (medication)DurabilityBattery (electricity)Composite numberEnergy storageNanotechnologyCarbon fibersTinComposite materialElectrodeChemistryMetallurgy

Abstract

fetched live from OpenAlex

Since ever-increasing energy demands stimulated intensive research activities on lithium-ion batteries (LIBs), biomass as an earth-abundant renewable energy source has played an intriguing and promising role in developing sustainable biomass-derived carbons and their composite materials for high-performance LIB anodes. Different from other materials (e.g., silicon, tin, metal oxides, etc.), biomass-derived carbons and their composite materials have been applied more and more to LIBs due to their advantages such as low cost, green and eco-friendly synthesis, easy accessibility, sustainable strategy, and improved battery performance, including capacity, cycling property, and stability/durability. This tutorial review focusing on biomass-derived carbons and their composites in the application of LIB anodes will act as a strategic guide to build a close connection between renewable materials and electrochemical energy storage devices. Also, this review provides a critical analysis and comparison of biomass-derived carbons and their composites for LIB anodes, coupled with an important insight into the remaining challenges and future directions in the field.

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.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.059
GPT teacher head0.324
Teacher spread0.266 · 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