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Record W3182190414 · doi:10.1002/cssc.202101270

Recent Progress in Amorphous Carbon‐Based Materials for Anodes of Sodium‐Ion Batteries: Synthesis Strategies, Mechanisms, and Performance

2021· review· en· W3182190414 on OpenAlex

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.

Bibliographic record

VenueChemSusChem · 2021
Typereview
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche Scientifique
FundersState Key Laboratory of Advanced Chemical Power SourcesNational Natural Science Foundation of China
KeywordsAnodeFaraday efficiencyMaterials scienceLithium (medication)NanotechnologyElectrolyteCarbon fibersAmorphous solidAmorphous carbonElectrochemistryCathodeChemistryElectrodeComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Sodium-ion batteries (SIBs) are gaining renewed interest as a promising alternative to the already commercialized lithium-ion batteries. The large abundance, low cost, and similar electrochemistry of sodium (compared with lithium) is attracting the attention of the research community for their deployment in energy storage devices. Despite the fact that there are adequate cathode materials, the choice of suitable anodes for SIBs is limited. Graphite, the most versatile anode for LIBs, exhibits poor performance in case of SIBs. Amorphous or disordered carbons (hard and soft carbon) have been the most promising and cost-effective anode materials for SIBs. This Review discusses the recent advances of various forms of amorphous or disordered carbons used in SIBs with emphasis on their synthesis processes and relationship between microstructure, morphology, and performance. A profound understanding of the charge storage mechanisms of sodium in these carbon materials has been deliberated. The performance of these anode materials also depends upon electrolyte optimization, which has been aptly conferred. However, these anodes are often plagued with large voltage loss, low initial coulombic efficiency, and formation of solid electrolyte interphase. In order to overcome these challenges, several mitigation strategies have been put forward in a concise way to offer visions for the deployment of these amorphous carbon materials for the progress and commercial success of 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.756
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.283
Teacher spread0.248 · 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