Microwave Assisted Reduction for Screening Banned Aromatic Amines in Azo Dyes
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
The study proposes a simple, novel and green alternative for the efficient reduction of azo dyes by the standard method, EN 14362-1:2012 (Annex. F) for detection of harmful aromatic amines in colorants, by incorporating microwave heating in place of convective heating. Basic dye response to reduction methods was explored by UV-visible spectroscopy and the results were confirmed through GC-MS and HPLC-DAD. Four azo dyes namely Acid red 1 (AR-1), Direct blue 15 (DB-15), Direct red 28 (DR-28) and Direct red 7 (DR-7) were reduced with sodium dithionite at 70 °C for 30 min in a buffered solution at pH 6.0, serving as a reference method. The decline in dye absorbance after their reduction was explored by UV-visible spectroscopy with carefully chosen bands of maximum absorbance from 300 to 700 nm. The alternative method exposed dye solutions to short microwave heating (10 s) and immediate cooling, in cycles till the desired duration of microwave heating was achieved. Results obtained from reference method were used for comparison with MAR (experimental method 1). Most prominent results of MAR were observed in the case of DR-28 dye. Hence DR-28 was further subjected to the conditions of experimental method 2, which was simply EN 14362-1:2012 (F) method modified with MAR. For standard method and experimental method 2, amines were analysed by GC-MS and HPLC-DAD. MAR methods were compared with reference and standard reduction methods for efficiencies. The total saving with MAR in terms of time and energy was ~70% and ~92% respectively.
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 | 0.000 |
| 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