Fabrication of Micrometer-Scale Self-Organized Pore Arrays in Anodic Alumina
Bibliographic record
Abstract
We demonstrate the fabrication of self-organized ordered porous anodic alumina (PAA) with pore spacing in the micrometer range using a solution of citric acid. More specifically, we have fabricated PAA samples with regular pore spacings of 970 nm, 1070 nm, 1260 nm and 1420 nm, respectively. While pore spacing is expected to be proportional to the anodization voltage, the proportionality factor observed here (1.94 nm/V) is slightly lower than that reported in the literature (∼2.5 nm/V). These results were obtained following a careful characterization of the burning voltages of aluminum for various concentrations of citric acid. Voltage limits of 300 V, 370 V and 425 V for concentrations of 4%, 2% and 0,5%, respectively, have been established. We also established that the maximum anodization voltage in pure citric acid at very low concentration (0.05%) is in the range of 540 V. Beyond this voltage, breakdown of the alumina barrier occurs. We discuss the phenomenon of aluminum burning, which occurs when anodizing at voltages too high for a given acid concentration. We also show that high voltage anodization produces less compact PAA than lower voltage ones, and that it is increasingly difficult to obtain a thick PAA as the anodization voltage increases.
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 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) | 0.000 | 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 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".