Debonding Performance of Various Cationic Surfactants on Networks Made of Bleached Kraft Fibers
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.
Bibliographic record
Abstract
Debonding agents are applied in the paper industry for various purposes, for example, to increase the softness of tissue paper. In this work, the debonding capacities of three cationic aliphatic ammonium surfactants and one alkoxylated amine surfactant on kraft fibers were determined. The results showed that the adsorption of the alkoxylated amine surfactant (AAS) was higher than that of others on the fibers, but a cationic cetyltrimethyl ammonium surfactant (cetyltrimethyl ammonium bromide, CAB) was the most effective debonding agent, probably because of its relatively long hydrophobic chain. By applying CAB at levels of up to 20 mg/g, the tensile and burst indices were reduced by 37% and 41%, respectively. By applying AAS at levels of up to 20 mg/g, the tensile and burst indices of the networks were reduced by 18.6%, and 14.2%, respectively. The tear index of the fiber networks negligibly changed upon application of AAS, but increased by 19% upon application of CAB. The strain of the fiber networks prior to rupturing increased upon application of AAS, whereas it decreased upon application of CAB, which implies that the surfactants have different debonding mechanisms. The debonding efficiency of CAB was independent of both the refining revolutions and basis weights of the fiber networks.
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 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 | 0.001 | 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 | 0.001 |
| 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 it