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Record W2765611643 · doi:10.14447/jnmes.v19i1.345

Novel Synthesis of Plate-like LiFePO4 by Hydrothermal Method

2016· article· en· W2765611643 on OpenAlexvenueno aff
Yijie Gu, Chang-Jiao Li, Long Cheng, Penggong Lv, Fu-Jie Fu, Hongquan Liu, Jianxu Ding, Yanming Wang, Yunbo Chen, Haifeng Wang, Shun-Wei Fan

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
Fundersnot available
KeywordsHydrothermal circulationHydrothermal synthesisLithium iron phosphateMaterials scienceLithium (medication)Citric acidStoichiometryImpurityPhase (matter)Particle sizeFerrousParticle (ecology)Nuclear chemistryChemical engineeringChemistryMetallurgyElectrochemistryPhysical chemistryElectrodeGeology

Abstract

fetched live from OpenAlex

Lithium iron phosphate (LiFePO4) was prepared by hydrothermal synthesis method using FeSO4·7H2O and LiH2PO4 as resource of Li and Fe. The ratio of Li: Fe was maintained 1:1. The results suggested that pH value played a crucial role in the synthesis of LiFePO4, especially for the generation of impurities. We found that adding citric acid to the precursor was an effective way for chelating ferrous ions, thereby preventing the undesirable iron compounds during hydrothermal treatment. The particle morphology and the crystal orientation of the prepared LiFePO4 particles were investigated by the XRD and SEM results. The X-ray diffraction pattern of the samples indicated that single-phase LiFePO4 were successfully synthesized by hydrothermal method with a stoichiometric 1:1 ratio of Li :Fe.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.255
Teacher spread0.242 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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Same venueJournal of New Materials for Electrochemical Systems→Same topicAdvancements in Battery Materials→French-language works237,207→