Development of Vernonia Amygdalina Photosynthetic Membraneless Electrochemical Cell
Bibliographic record
Abstract
Experimental analyses of Vernonia amygdalina pigment from plant collected in Ilorin, Nigeria, have been carried out using spectrophotometer, 1H nuclear magnetic resonance (400Hz) and X-ray diffractometer. Biological membraneless electrochemical cells were fabricated using ground hydrated chlorophyll containing tissues. The cells were assembled by compaction of hydrated pigment housed in an air-tight 6.5 cm3 cylindrical container, with similar electrodes of copper material. Experimental results showed that the visible part of the electromagnetic spectrum is strongly absorbed at 412 nm and 662 nm by Vernonia amygdalina. The qualitative analysis of the powdered sample of the material showed that the constituents of the sample include Magnesium Carbide (Mg2C3), Nitrogen (N2) and Biuret Hydrate (C2H5N3O2H2O). In addition to this, chlorophyll a ( chl a) and triglyceride were also shown to be major constituents of the pigment. The particle size of the pigment was deduced using X-ray diffractometer to be 2.6 nm, and as such, the processed Vernonia amygdalina pigment is therefore a nano-material for energy conversion by photosynthetic processes. The copper-copper electrodes photosynthetic cells generated current of about 4 µA and open circuit voltage of about 5 mV. The current generated by copper-zinc electrodes Photosynthetic Electrochemical Cell (PEC) ranged between 0.2 mA and 1.5 mA, while the open circuit voltage ranged between 0.4 V and 0.9 V. The simple preparation technique adopted, using widely available and low cost natural material showed that a biological photosynthetic electrochemical cell is feasible and promising.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".