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Record W2972838554 · doi:10.1115/1.4042552

Structural Evolution and Formation Mechanism of LiNiO2 During High-Temperature Solid-State Synthesis

2019· article· en· W2972838554 on OpenAlexaff
Shiyi Deng, Longlong Xue, Yunjiao Li, Zehua Lin, Wei Li, Yongxiang Chen, Tongxing Lei, Jie Zhu, Jinping Zhang

Bibliographic record

VenueJournal of Electrochemical Energy Conversion and Storage · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Toronto
FundersScience and Technology Department of Guangxi Zhuang Autonomous
KeywordsLithium (medication)Scanning electron microscopeThermal analysisOxideRaw materialSolid-stateChemistryInorganic chemistryComplex oxideChemical engineeringMaterials scienceThermalPhysical chemistryOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

The processes and mechanisms of LiNiO2 synthesis during the high-temperature solid state method, using Ni(OH)2 precursor and different lithium salts (Li2CO3 and LiOH), were revealed by the thermal (TG–DTA) and structural (X-ray diffraction (XRD)) analyses. Morphology characterization (scanning electron microscopy (SEM)) and the soluble lithium titration are carried out to support the findings. The results show that the synthetic processes of LiNiO2 generally include raw materials' dehydration, oxidation, and combination; also, the existence of lithium salts makes the oxidation of Ni(OH)2 relatively easier. Comparing the two lithium salts involved in the reactions, LiOH will bring about a transition oxide (Ni8O10) and lower the initial reaction temperature for LiNiO2 generation. In addition, a decent temperature under 800 °C, a preheat treatment in 500–600 °C, and a properly longer heating time are suggested to be significant for obtaining the ideal LiNiO2 materials.

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 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 score0.003
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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.

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

Citations18
Published2019
Admission routes1
Has abstractyes

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