Sunscreen Performance of Lignin from Different Technical Resources and Their General Synergistic Effect with Synthetic Sunscreens
Bibliographic record
Abstract
Five types of industrial lignin are blended with a pure cream and a commercial sunscreen lotion. Lignin is found to significantly boost their sunscreen performance. Photostability of the lignin-modified lotions is analyzed. The results show that hydrophobic lignin has better sunscreen performance than hydrophilic counterpart. Sun protection factor (SPF) of the pure cream containing 10% organosolv lignin (OL) reaches 8.66. Small amount of hydrophobic lignin dramatically increases SPF value of the sunscreen lotions. Adding 1% lignin almost doubles the sun lotion’s SPF. Addition of 10% OL to the lotion boosts its SPF from 15 to 91.61. However, it is also found that hydrophilic lignin tends to demulsify the lotions due to an electrostatic disequilibrium. After 2 h of UV radiation, UV absorbance of all the five lignin-modified sunscreen lotions increases up to the limit of measuring instrument. All the lignin types studied in this work are found to have a general synergistic effect with sunscreen actives in the commercial lotion. An effort is also made to elucidate radical mechanisms of the synergy.
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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) | 0.001 | 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".