Completely Aqueous Route for Metallization of Structural Polymeric Materials in Micro-Electro-Mechanical Systems
Bibliographic record
Abstract
Recent developments in the fabrication of micro-electro-mechanical systems (MEMS) are moving away from the deposition/mask/etch paradigm and instead exploiting useful properties of polymers. Many polymeric insulating materials, such as Parylene, PMMA, HSQ, SU-8 and KMPR, have attracted attention in microfabrication lately, because of their low cost and significantly easy processing procedures [1,2]. Metallization of these polymers is required for their integration in MEMS technology. While conventional microfabrication methods for preparing metallic thin films on insulating substrates are limited to vapor deposition techniques, it has recently demonstrated that electroless deposition can be considered as an alternative and efficient approach [3,4]. Presently used process of electroless plating onto plastics requires a pretreatment based on chromic acid etching for oxidizing the surface. This pretreatment increases the surface energy and wettability for the subsequent step of surface activation with noble metal catalysts. Thus, the development of simple, cost-effective and environment friendly strategies, such as avoiding chromic acid etching and/or minimizing the gravimetric use of noble metal, to metallize the surface of insulating substrates is of huge interest. Here, we report a simple one step covalent amination of the surface of commercial structural polymers employing diazonium-based aqueous chemistry. These amine-terminated functionalities allow minimizing the quantity of palladium cations used as catalyst for the subsequent electroless nickel deposition, as well as offer excellent adhesion between the polymer substrate and the nickel film. X-ray photoelectron spectroscopy is carried out to elucidate the mechanism of surface functionalization with amine groups. We then focus our attention on the comprehensive characterization of the metallic thin film through scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy techniques. Keywords: Metallization of plastics, diazonium chemistry, covalent grafting, environment plating process, MEMS fabrication Reference W. Dai et al., Sensors and Actuators A 135 (2007) 300–307. Y. Liu et al., Progress in Polymer Science 52 (2016) 79–106. Y. Shacham-Diamand et al. Microelectron. Eng. 132 (2015) 35–45. G. Zeb et al., Applied Surface Science 407 (2017) 518–525.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".