Interplay of Hydrophobic Thiol and Polar Epoxy Silicate Groups on Microstructural Development in Low-Alcohol, Crosslinked Sol–Gel Coatings for Corrosion Prevention
Bibliographic record
Abstract
We have demonstrated that our patented, crosslinked, sol–gel, epoxy–thiol silicates made from the combination of (a) tetraethoxysilane (TEOS, T), 3-glycidoxypropyltrimethoxysilane (GPTMS, G), and the (b) sulfur-containing 3-mercaptopropyltrimethoxysilane (MPTMS, S) with TEOS in a 1:1 stoichiometric ratio form the 1:1 TGST (crosslinked epoxy and thiol silicates) coating, which can be successfully utilized for the corrosion protection of low-carbon steel. Alcohols that are a by-product of sol–gel reactions influence the network formation, crosslinking density, and formulation stability, are volatile organic contents, and are regulated in the coatings industry. To improve environmental sustainability, a series of low-alcohol (LA) formulations with TG:ST ratios of 3:1 to 1:3 was prepared to investigate the microstructural development and crosslinking reactions emerging from the interplay of the hydrophobic thiol and polar epoxy silicates induced by the low-alcohol environment. The impact on crosslinking density was characterized by Fourier Transform Infrared (FTIR), Raman, XPS, viscosity, and pot-life measurements. Low-alcohol TGST (LA(TGST)) formulations were compared, using the example of 1:1 TGST, to corresponding TGST formulations where alcohols were retained. The reduced impact of LA(TGST) formulations on global warming was quantified. The glossy and scratch-resistant LA(TGST) coatings showed 71% enhanced corrosion protection compared to the non-crosslinked hybrids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 0.000 |
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.
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 teacher head, 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".