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Fabrication of patterned graphitized carbon wires using low voltage near-field electrospinning, pyrolysis, electrodeposition, and chemical vapor deposition.

Derosh GeorgeAdrian GarciaQuang PhamMario Ramos PerezJufeng DengMichelle Trang NguyenTuo ZhouSergio O Martinez-ChapaYoonjin WonChong LiuRoger C LoRegina RaganMarc Madou
Published in: Microsystems & nanoengineering (2020)
We herein report a high-resolution nanopatterning method using low voltage electromechanical spinning with a rotating collector to obtain aligned graphitized micro and nanowires for carbon nanomanufacturing. A small wire diameter and a small inter-wire spacing were obtained by controlling the electric field, the spinneret-to-collector distance, the pyrolysis parameters, the linear speed of the spinneret, the rotational speed of the collector. Using a simple scaling analysis, we show how the straightness and the diameter of the wires can be controlled by the electric field and the distance of the spinneret to the collector. A small inter-wire spacing, as predicted by a simple model, was achieved by simultaneously controlling the linear speed of the spinneret and the rotational speed of the collector. Rapid drying of the polymer nanowires enabled the facile fabrication of suspended wires over various structures. Patterned polyacrylonitrile wires were carbonized using standard stabilization and pyrolysis to obtain carbon nanowires. Suspended carbon nanowires with a diameter of <50 nm were obtained. We also established a method for making patterned, highly graphitized structures by using the aforementioned carbon wire structures as a template for chemical vapor deposition of graphite. This patterning technique offers high throughput for nano writing, which outperforms other existing nanopatterning techniques, making it a potential candidate for large-scale carbon nanomanufacturing.
Keyphrases
  • high resolution
  • reduced graphene oxide
  • high throughput
  • room temperature
  • optic nerve
  • quantum dots
  • optical coherence tomography
  • single cell
  • low cost
  • liquid chromatography
  • neural network
  • metal organic framework