Promising method toward realization of ultra-low-cost silicon microrod array with nanotip
Bibliographic record
Abstract
A low-cost two-step method for fabrication of silicon microrod array with nanotip on a low-doped p-type substrate was demonstrated. The two-step process involved anisotropic and electrochemical etching of single crystalline silicon samples. The silicon surface was first textured using anisotropic etching to generate the pyramid-shaped structure on the surface and was further followed by electrochemical anodic etching to create silicon microrod arrays. The vertical silicon microrod arrays are a direct product of the anodization stage, where the shape of the pyramid structures was altered and transformed into free-standing microrods. The effects of several parameters including the time, the pyramid size uniformity, and HF concentration on the final products were studied. It was observed that the diameters of the pyramids were decreased as the anodic etching time was extended to 10 min. Beyond 10 min, anodic etching did not cause any further diameter change. Experiments revealed that in order to realize silicon microrods, the size of the pyramids was required to be greater than the space charge region width. An optimal range of HF concentration, where the silicon microrods can be obtained was determined.
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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".