Mechanism of Acetyl Salicylic Acid (Aspirin) Degradation under Solar Light in Presence of a TiO2-Polymeric Film Photocatalyst
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
Application of titanium dioxide (TiO2) as a photocatalyst has presented a promising avenue for the safe photocatalytic degradation of pollutants. Increasing levels of the release of pharmaceuticals in the environment and formation of the intermediates during their degradation may impose health and environmental risks and therefore require more attention. Photocatalytic degradation of acetylsalicylic acid (aspirin) was carried out in the presence of the TiO2-filled polymeric film as a photocatalyst under solar light irradiation. The polymeric film incorporates TiO2 in the matrix, which acts as a photocatalyst under solar illumination and degrades the acetyl salicylic acid (ASA) into a range of organic compounds before complete demineralization (formation of carbon dioxide and water as final products). Among the intermediates, acetic acid was found to be present in a larger amount compared to other organic acids. The qualitative/quantitative analyses of the intermediates resulted in the determination of the most probable reaction’s mechanism in the degradation process. The mechanism of degradation of acetylsalicylic acid and its reaction pathway were developed from liquid chromatography/mass spectroscopy (LC/MS), Fourier Transform Infra Red (FTIR) and UV spectrophotometric analysis. It was found that hydroxyl groups were dominant in the degradation process compared to electrons and holes generated by TiO2. The total organic carbon (TOC) analysis was also carried out to analyze the organic carbon content of the intermediates formed during the course of degradation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it