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Record W7117508674 · doi:10.11159/ijmmme.2025.001

The Effects of Dispersant on Slurry Properties and Electrochemical Behavior of LiMn <sub>0.6</sub> Fe <sub>0.4</sub> PO <sub>4</sub> /Graphite Batteries

2025· article· W7117508674 on OpenAlexvenueno aff
Chanmonirath Chak, Vadim Shipitsyn, Lin Ma, Joseph E. Remias

Bibliographic record

VenueInternational Journal of Mining Materials and Metallurgical Engineering · 2025
Typearticle
Language
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
Fundersnot available
KeywordsDispersantElectrochemistrySlurryElectrodeDispersion (optics)

Abstract

fetched live from OpenAlex

Phase separation during the slurry preparation process significantly shortens the slurry's usable lifetime, negatively impacting coating uniformity on the current collector and degrading electrochemical performance.This study investigates the effect of a small amount of proprietary dispersant on the slurry stability and electrochemical behavior of LiMn0.6Fe0.4PO4(LMFP) cathode.Three dispersant concentrations were tested and compared with a pristine sample containing no dispersant.A combination of digital microscopy, slurry storage evaluation, scanning electron microscopy, electrochemical impedance spectroscopy, and longterm cycling were used to assess the influence of dispersant on both slurry behavior and electrode performance.Results demonstrate that even a small amount, 0.01 wt%, of proprietary dispersant effectively suppresses phase separation, enabling better slurry handling and coating consistency, while preserving the electrode's morphology and electrochemical performance.These findings support the use of optimized dispersant strategies in the scalable production of LMFP electrodes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.216
Teacher spread0.208 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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