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Record W2044635770 · doi:10.1080/10402000601105532

Effects of Mo-Containing Dispersants on the Function of ZDDP: Chemistry and Tribology

2007· article· en· W2044635770 on OpenAlexafffund
Z. Zhang, E. S. Yamaguchi, Lei Yu, M. Kasrai, G.M. Bancroft

Bibliographic record

VenueTribology Transactions · 2007
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsWestern University
FundersNational Research Council CanadaNational Science Foundation
KeywordsTribologyDispersantFunction (biology)ChemistryChemical engineeringOrganic chemistryNanotechnologyMaterials scienceMetallurgyEngineeringDispersion (optics)Physics

Abstract

fetched live from OpenAlex

The interactions of zinc dialkyldithiophosphate (ZDDP) with three different Mo-containing dispersants has been investigated both on thermally and tribologically generated films. X-ray absorption near-edge structure (XANES) spectroscopy, at the P and S L-edge and K-edge and the Mo L-edge, has been used to identify the chemical species in the surface and bulk of the films. XPS has also been used to complement the XANES data. Wear scar widths and friction coefficients have been measured. The data indicate a much enhanced improvement in antiwear and friction reduction properties of the blends containing the Mo dispersants/ZDDP over blends containing ZDDP alone. XANES spectroscopy shows clearly the presence of MoS 2 species in the rubbing films containing Mo/ZDDP along with long chain polyphosphate. However, the Mo dispersants alone have no antiwear and friction reducing characteristics. The thermally generated films did not show the formation of MoS 2 , and it is concluded that rubbing is required for the molybdenum disulfide species to form.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.005
GPT teacher head0.197
Teacher spread0.191 · 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

Citations10
Published2007
Admission routes2
Has abstractyes

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