2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS) 2015
DOI: 10.1109/memsys.2015.7050954
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A low-cost and label-free alpha-fetoprotein sensor based on self-assembled graphene on shrink polymer

Abstract: Self-assembled graphene by layer-by-layer (LbL) self-assembly on a shrink polymer substrate demonstrates nano wrinkles after heating. As a result, graphene with nano wrinkles shows different wettability and surface roughness, depending on shrink temperatures. The graphene on shrink polymer performs sensing applications for pH and alpha-fetoprotein (AFP) detection with advantages of low cost and label free, due to self-assembly technique, ease of modification, and antigen-antibody surface reaction.

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Cited by 3 publications
(1 citation statement)
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“…It promises that graphene self-assembly can be used in further applications, such as micro-electro-mechanical systems (MEMS) [12]. By applying the method, we report experimental results in controlling surface morphology with both self-assembled graphene nanoplatelets and shrink-induced polymer structures [13]. Through our experiments, we demonstrated tunability of shrink induced self-assembled graphene on shape-memory polymers adjusted by shrink temperatures, and this promises to widen the range of graphene applications to high-surfacearea conductors and molecular detections [14].…”
Section: Introductionmentioning
confidence: 99%
“…It promises that graphene self-assembly can be used in further applications, such as micro-electro-mechanical systems (MEMS) [12]. By applying the method, we report experimental results in controlling surface morphology with both self-assembled graphene nanoplatelets and shrink-induced polymer structures [13]. Through our experiments, we demonstrated tunability of shrink induced self-assembled graphene on shape-memory polymers adjusted by shrink temperatures, and this promises to widen the range of graphene applications to high-surfacearea conductors and molecular detections [14].…”
Section: Introductionmentioning
confidence: 99%