Stimulus-Responsive Biopolymeric Surface: Molecular Switches for Oil/Water Separation
Bibliographic record
Abstract
In this work, we fabricated a stimulus-responsive biopolymeric material and demonstrated the reversible character of a hydrophilic/hydrophobic interface upon exposure to UV light. Importantly, this stimulus-responsive material exhibited excellent features in an oil/water separation system. Cellulose was functionalized on both sides of the surface with a dopamine polymer and further modified with an azobenzene-fluorosilane material. Azobenzene can alter the properties of a material via an isomerization effect ( trans–cis ) upon exposure to UV light. Initially, the azobenzene-fluorosilane material was in a hydrophobic state; the contact angle was over 130°; and absorption performance with various organic solvents showed there to be high levels of extractive activity and outstanding reusability. When we exposed the material to UV light, the surface changed to that of a hydrophilic nature, and this phenomenon was influenced by the azobenzene chemistry of folding and unfolding of an azobenzene-fluorosilane molecule. Significantly, this phenomenon is a reversible, reusable, and eco-friendly material. Furthermore, dopamine polymers could block organic material, bacteria, and fungi, and this surface can be used for wastewater purification. Therefore, we foresee that the stimulus-responsive surface of biopolymeric material could result in a different direction in the oil/water purification fields.
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) | 0.000 | 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) | 0.002 | 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 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".