Selective Area Modification of Silicon Surface Wettability by Pulsed UV Laser Irradiation in Liquid Environment
Bibliographic record
Abstract
The wettability of silicon (Si) is one of the important parameters in the technology of surface functionalization of this material and fabrication of biosensing devices. We report on a protocol of using KrF and ArF lasers irradiating Si (001) samples immersed in a liquid environment with low number of pulses and operating at moderately low pulse fluences to induce Si wettability modification. Wafers immersed for up to 4 hr in a 0.01% H2O2/H2O solution did not show measurable change in their initial contact angle (CA) ~75°. However, the 500-pulse KrF and ArF lasers irradiation of such wafers in a microchamber filled with 0.01% H2O2/H2O solution at 250 and 65 mJ/cm(2), respectively, has decreased the CA to near 15°, indicating the formation of a superhydrophilic surface. The formation of OH-terminated Si (001), with no measurable change of the wafer's surface morphology, has been confirmed by X-ray photoelectron spectroscopy and atomic force microscopy measurements. The selective area irradiated samples were then immersed in a biotin-conjugated fluorescein-stained nanospheres solution for 2 hr, resulting in a successful immobilization of the nanospheres in the non-irradiated area. This illustrates the potential of the method for selective area biofunctionalization and fabrication of advanced Si-based biosensing architectures. We also describe a similar protocol of irradiation of wafers immersed in methanol (CH3OH) using ArF laser operating at pulse fluence of 65 mJ/cm(2) and in situ formation of a strongly hydrophobic surface of Si (001) with the CA of 103°. The XPS results indicate ArF laser induced formation of Si-(OCH3)x compounds responsible for the observed hydrophobicity. However, no such compounds were found by XPS on the Si surface irradiated by KrF laser in methanol, demonstrating the inability of the KrF laser to photodissociate methanol and create -OCH3 radicals.
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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) | 0.000 | 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) | 0.001 | 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".