Literature DB >> 27709957

Colorimetry Technique for Scalable Characterization of Suspended Graphene.

Santiago J Cartamil-Bueno1, Peter G Steeneken1, Alba Centeno2, Amaia Zurutuza2, Herre S J van der Zant1, Samer Houri1.   

Abstract

Previous statistical studies on the mechanical properties of chemical-vapor-deposited (CVD) suspended graphene membranes have been performed by means of measuring individual devices or with techniques that affect the material. Here, we present a colorimetry technique as a parallel, noninvasive, and affordable way of characterizing suspended graphene devices. We exploit Newton's rings interference patterns to study the deformation of a double-layer graphene drum 13.2 μm in diameter when a pressure step is applied. By studying the time evolution of the deformation, we find that filling the drum cavity with air is 2-5 times slower than when it is purged.

Entities:  

Keywords:  Colorimetry; characterization technique; gas diffusion; graphene; pressure sensor; suspended

Year:  2016        PMID: 27709957     DOI: 10.1021/acs.nanolett.6b02416

Source DB:  PubMed          Journal:  Nano Lett        ISSN: 1530-6984            Impact factor:   11.189


  4 in total

1.  Graphene mechanical pixels for Interferometric Modulator Displays.

Authors:  Santiago J Cartamil-Bueno; Dejan Davidovikj; Alba Centeno; Amaia Zurutuza; Herre S J van der Zant; Peter G Steeneken; Samer Houri
Journal:  Nat Commun       Date:  2018-11-16       Impact factor: 14.919

2.  A suspended graphene-based optical interferometric surface stress sensor for selective biomolecular detection.

Authors:  Shin Kidane; Hayato Ishida; Kazuaki Sawada; Kazuhiro Takahashi
Journal:  Nanoscale Adv       Date:  2020-03-19

3.  Efficient Structural Relaxation of Polycrystalline Graphene Models.

Authors:  Federico D'Ambrosio; Joris Barkema; Gerard T Barkema
Journal:  Nanomaterials (Basel)       Date:  2021-05-08       Impact factor: 5.076

Review 4.  Towards Repeatable, Scalable Graphene Integrated Micro-Nano Electromechanical Systems (MEMS/NEMS).

Authors:  Joon Hyong Cho; David Cayll; Dipankar Behera; Michael Cullinan
Journal:  Micromachines (Basel)       Date:  2021-12-26       Impact factor: 2.891

  4 in total

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