A new approach to fabricate PDMS structures using femtosecond laser
Bibliographic record
Abstract
Polydimethylsiloxane (PDMS) is commonly used to prototype micro and nano featured components due to its beneficial properties. PDMS based devices have been used for diverse applications such as cell culturing, cell sorting and sensors. Motivated by such diverse applications possible through pure PDMS and reinforced PDMS, numerous efforts have been directed towards developing novel fabrication techniques. Prototyping 2D and 3D pure and reinforced PDMS microdevices normally require a long curing time and must go through multiple steps. This research explores the possibility of fabricating microscale and nanoscale structures directly from PDMS resin using femtosecond laser processing. This study offers an alternative fabrication route that potentially lead to a new way for prototyping of pure and reinforced PDMS devices, and the generation of hybrid nanomaterials. In depth investigation of femtosecond laser irradiation of PDMS resin reveals that the process is highly intensity-dependent. At low to intermediate intensity regime, femtosecond laser beam is able to rapidly cure the resin and create micron-sized structures directly from PDMS resin. At higher intensity regime, a total break-down of the resin material occurs and leads to the formation of PDMS nanoparticles. This work demonstrates a new way of rapid curing of PDMS resin on a microsecond timescale using femtosecond laser irradiation. The proposed technique permits maskless single-step curing and is capable of fabricating 2D and 3D structures in micro-scale. Reinforced PDMS microstructures also have been fabricated through this method. The proposed technique permits both reinforcement and rapid curing and is ideal for fabricating reinforced structures in microscale. The strength of the nanofiber reinforced PDMS microstructures has been investigated by means of Nanoindentation test. The results showed significant improvement in strength of the material. Hybrid PDMS-Si and hybrid PDMS-Al nanoparticle aggregate were generated using femtosecond laser. The results indicate that the hybrid PDMS nanostructures are clusters of nanoparticles that agglomerate and interweave three-dimensionally and also the possibility of formation of Si/Al nanoparticles enclosed in PDMS Shells. Presence of PDMS in the final hybrid structure is confirmed by micro-raman analysis. The versatility of our technique opens a new pathway to generate hybrid 3D fibrous nanostructures on any materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".