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Record W1979285658 · doi:10.2174/1874088x01105010222

LiMnPO4 Olivine as a Cathode for Lithium Batteries

2011· article· en· W1979285658 on OpenAlexaff
Zhumabay Bakenov, Izumi Taniguchi

Bibliographic record

VenueThe Open Materials Science Journal · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceCathodeElectrochemistryLithium (medication)Lithium iron phosphateHydrothermal circulationChemical engineeringOlivinePyrolysisLithium vanadium phosphate batteryNanotechnologyMineralogyElectrodeChemistry

Abstract

fetched live from OpenAlex

The olivine structured mixed lithium-transition metal phosphates LiMPO4 (M = Fe, Mn, Co) have attracted tremendous attention of many research teams worldwide as a promising cathode materials for lithium batteries. Among them, lithium manganese phosphate LiMnPO4 is the most promising considering its high theoretical capacity and operating voltage, low cost and environmental safety. Various techniques were applied to prepare this perspective cathode for lithium batteries. The solution based synthetic routes such as spray pyrolysis, precipitation, sol-gel, hydrothermal and polyol synthesis allow preparing nanostructured powders of LiMnPO4 with enhanced electrochemical properties, which is mostly attributed to the higher chemical homogeneity and narrow particle size distribution of the material. Up-to-date, the LiMnPO4/C composites prepared by the spray pyrolysis route have the best electrochemical performance among the reported in the literature.

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 score0.004

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.059
GPT teacher head0.308
Teacher spread0.250 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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