Improved Thermal Signature of Composite Beams with GNP Smart Skin for Defect Investigation

Sethy, Debadatta; Sai, M. Swapna; Varghese, F. V.; Balasubramaniam, Krishnan

doi:10.1007/s10921-021-00817-2

Cited by 2 publications

(1 citation statement)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many graphene-doped PMMA sensors for human health monitoring have been reported from heart rate, pulse oxygenation, blood glucose meter, to electrocardiogram signal, etc., by novel monitoring devices made out of graphene [ 16 ]. In addition, thermal management work taking graphene as a sensing indicator has been studied in which PMMA acts as a substrate in GNPs-based nanocomposite sensors [ 17 , 18 ]. In our previous work, the thermal signature was improved by making PMMA a substrate by doping graphene into it.…”

Section: Introductionmentioning

confidence: 99%

Smart Graphene Nanoplatelet Strain Sensor for Natural Frequency Sensing of Stainless Steel (SS304) and Human Health Monitoring

Sethy

Balasubramaniam

2022

Materials

Self Cite

View full text Add to dashboard Cite

The main purpose of this article is to monitor the natural frequency of stainless steel (SS304) with and without defect by spray-coated smart graphene nanoplatelet (GNPs)-doped poly (methyl methacrylate) (PMMA) nanocomposite strain sensor and human health by smart Lycra denim textile sensor. Methods such as impact hammer test and NI-daq, finite element method (FEM) simulation by abacus 6.12, and fast Fourier transform (FFT) study were applied for frequency monitoring of SS304. For human health monitoring, edema disease inspection, cough, and biceps locomotion were studied by graphene sol–gel textile sensor. We report eight sensors fabricated by scotch tape exfoliation method and their sensitivity was checked in terms of gauge factor (GF). The highest and lowest GF-based sensors were checked for sensitivity in the defect (hole) specimen. These sensors were used to sense the natural frequency of SS304 at three different positions in the cantilever beam. The same quantity of GNPs was used for making Lycra denim textile sensors for human health monitoring. The Lycra denim textile sensor showed a 216% change in resistance in the left calf muscle, which is less than right leg flexibility, indicating good sensitivity. In addition, the textile sensor helped in sensing coughing and biceps monitoring. The ease in fabrication and high sensitivity demonstrate the potential ability of GNPs for futuristic smart material for structural and human health monitoring.

show abstract

Section: Introductionmentioning

confidence: 99%