Development of Gold Electrodes for Microbial Fuel Cells
Bibliographic record
Abstract
The microbial fuel cell (MFC) has been an important subject of study in the last decades because of its technological significance that one can produce hydrogen or electricity by wastewater treatment (bio-remediation). One of the main issues for the application of these devices on large scale is the processes and materials for the electrode fabrication. The cathode for MFC requires a catalyst to perform the reduction reaction and this work presents a simple technique to obtain thin layers of gold (TLG) supported on glass. This technique was employed to obtain TLG with different thicknesses from 848 nm to the thinnest of 137 nm. Since the gold of the TLGs presented adherence issues, a successful thermal treatment with different temperatures from 150-300 ºC was developed to avoid the gold detachment. The TLGs were tested as cathodes in a MFC and a maximum Voc of 431 mV and an Isc of 10 × 10−2 mA were obtained. The process to obtain TLGs presented here has probed to be a good option for this application since the thickness obtained and the accessible material (glass) employed as support offers a solution to the costs and the scaling issues.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".