Methods of Soft PDMS Microlens Arrays Fabrication via Air‐Expansion‐Induced Molding with 3D‐Printed Templates
Bibliographic record
Abstract
Conventional methods for microlens array (MLA) fabrication suffer from high costs, long prototyping time, and limited geometric control. To address these problems, this study introduces an air-expansion-induced molding method for soft lens array fabrication. This method works by heating the air trapped in 3D-printed photoresist microcavities. The photoresist becomes convex due to the thermal expansion of the trapped air and is then solidified after UV curing as a mold for Polydimethylsiloxane (PDMS) casting. The deformation of the photoresist is theoretically analyzed and experimentally verified. It is found that the fabricated MLAs exhibit sub-10 nm surface roughness and their curvature scales with both microcavity depth and temperature. The MLAs achieve an imaging resolution of 228.1 line pairs per millimeter and enable multi-focal plane imaging of microalgae in a microfluidic chip.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".