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Record W2787429895 · doi:10.14447/jnmes.v20i4.451

Can the Calcined Weathered Stones be Employed as Anode Materials for Lithium Ion Batteries?

2017· article· en· W2787429895 on OpenAlexvenueno aff
Keqiang Ding, Binjuan Wei, Yan Zhang, Chenxue Li, Xiaomi Shi, Junqing Pan

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
Fundersnot available
KeywordsCalcinationAnodeLithium (medication)Materials scienceElectrochemistryChemical engineeringCurrent densityIonMineralogyElectrodeChemistryCatalysis

Abstract

fetched live from OpenAlex

A novel finding, that the calcined weathered stones (denoted as CWS) can be employed as the anode materials for lithium ion batteries (LIBs), is reported for the first time in this work. Under the air conditions, the weathered stones were respectively calcined at 400ºC (sample a), 600ºC (sample b) and 800ºC (sample c) for 2 h, with an intention to examine the influence of the calcination temperature on the physicochemical properties of the resultant materials. XRD results indicated that the main components of all the final products were SiO2. And the SEM images demonstrated that all the as-prepared samples were irregular and larger particles with no evident crystal structure. The results of the electrochemical measurements revealed that the initial discharge capacity of sample b was about 104 mAh g-1 at the current density of 100 mA g-1, which was remarkably larger than that of the employed pure SiO2 (50 mAh g-1). Interestingly, after 20 cycles, the discharge capacity of sample b was still maintained as high as 70 mAh g-1, along with a capacity retention rate of about 70%. Although the discharge capacity reported here was lower as compared to the currently reported anode materials, this novel finding was very meaningful to the large scale production of anode materials, mainly due to the rather lower cost and abundant resources as well as the simple preparation process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.288
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2017
Admission routes1
Has abstractyes

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