Graphene: epoxy composites for anti-corrosion coatings
Bibliographic record
Abstract
The use of epoxy (EP) coatings for the protection of steel infrastructure from corrosion is a dominant technology in modern industrial settings. Improvement of this technology by compounding with graphene materials is explored. Composite coatings are produced on steel substrates using graphite nanoplatelets (GNP), more exfoliated graphene materials (MEG), and graphene oxide (GO). The anti-corrosion (AC) performance of the coatings is evaluated by salt-fog corrosion (SFC) testing and electrochemical (EC) methods. GO is found to be an excellent candidate as an AC barrier filler in EP coatings by both SFC and EC testing, clearly outperforming the neat EP. MEG also shows potential as an AC filler by the SFC tests, but performed poorly in the EC tests, possibly due to processing issues at the concentration investigated. GNP is found to show relatively less benefit as an AC filler in EP, compared with the more exfoliated GO and MEG fillers.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".