Spectroscopic determination of the synergistic effect of natural antioxidants in Bio-Transformer oils
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
Considering the eventual depletion of fossil fuels from which mineral oil transformer fluids are derived in addition to the environmental footprint associated with the use of the latter, vegetable oils are increasingly becoming formidable alternatives both as environmentally benign lubricants and as dielectric fluids. However, their lower oxidative stability and higher viscosity compared to traditional mineral oils are their main shortfalls. To address the lower oxidative stability problem, addition of synthetic antioxidants to vegetable oil transformer fluids has been found technically feasible, but given that these natural esters already have organo-soluble antioxidants, information about the concentrations of these phytochemicals is essential for a systematic approach to boosting oxidative stability. The presence of some of these in natural esters can lead to a synergy in antioxidation processes. In this paper, we have used Ultraviolet–Visible Spectroscopy and Infrared Spectroscopy to demonstrate the occurrence of natural antioxidants, alfa-tocopherol and beta-carotene, in concentrations sufficient to offer a synergistic effect in samples of transformer fluids from a producer. One major role of beta-carotene is quenching of reactive singlet oxygen species in the oxidation reaction chain when a photosensitizer is present. Therefore, our findings in this paper is a useful guide to planning a cost-effective means of producing a quality transformer fluid where the cost involved in mitigating photoinduced degradation of oil is a problem. Accordingly, the findings shed light on the quality of bio-oils used by the producer of the transformer fluids used in this study.
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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 | 0.001 |
| 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