MétaCan
Menu
Back to cohort
Record W4393079709 · doi:10.1021/acsami.4c00579

Unraveling Water-Based Lubrication with Carbon Dots of Asphaltene Origin

2024· article· en· W4393079709 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Applied Materials & Interfaces · 2024
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsUniversity of Calgary
FundersAlberta InnovatesUniversity of Calgary
KeywordsMaterials scienceZeta potentialAsphalteneGrapheneLubricationCarbon fibersChemical engineeringBiocompatibilityNanotechnologyNanomaterialsNanoparticleComposite materialComposite numberMetallurgy

Abstract

fetched live from OpenAlex

Despite the lower toxicity of water-based lubricants over nonrenewable petroleum-based analogues, they face challenges in achieving widespread adoption due to low stability and inadequate friction-reduction performance. To address this, a cost-effective nanoadditive is synthesized by expansive oxidation of asphaltenes to create biocompatible asphaltene-derived carbon dots [(ACDs); 5 nm]. These ACDs exhibit excellent water redispersibility, promoting long-term friction reduction and marking the first use of an asphaltene-based system for friction reduction in water or oil. Even at low loadings (0.2-4.0 wt %), ACDs significantly reduce friction on steel surfaces (>54%) with tribofilm stability surpassing pristine carbon dots, typical carbon-based graphene quantum dots, and inorganic nanomaterials (commercial 5 and 20 nm silica). The ACDs' attributes include high negative zeta potential, considerable water uptake, varied functional groups, biocompatibility, and a nanodisc shape conducive to stable tribofilm formation through effective particle stacking. The scalable synthesis, high yield, and impressive water redispersibility of ACDs position them favorably for commercial water-based lubrication.

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.

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 score0.005
Threshold uncertainty score0.517

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 head0.008
GPT teacher head0.207
Teacher spread0.198 · 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