Concave microlens arrays with tunable curvature for enhanced photodegradation of organic pollutants in water: A non‐contact approach
Bibliographic record
Abstract
Abstract Solar‐driven photodegradation for water treatment faces challenges such as low energy conversion rates, high maintenance costs, and over‐sensitivity to the environment. In this study, we develop reusable concave microlens arrays (MLAs) for more efficient solar photodegradation by optimizing light distribution. Concave MLAs with the base radius of μm are fabricated by imprinting convex MLAs to polydimethylsiloxane elastomers. Concave MLAs possess a non‐contact reactor configuration, preventing MLAs from detaching or being contaminated. By precisely controlling the solvent exchange, concave MLAs are fabricated with well‐defined curvature and adjustable volume on femtoliter scale. The focusing effects of MLAs are examined, and good agreement is presented between experiments and simulations. The photodegradation efficiency of organic pollutants in water is significantly enhanced by 5.1‐fold, attributed to higher intensity at focal points of concave MLAs. Furthermore, enhanced photodegradation by concave MLAs is demonstrated under low light irradiation, applicable to real river water and highly turbid water. image
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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) | 0.001 | 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) | 0.001 | 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".