journal article·2017-01

Enhanced nonlinear optical absorption and optical limiting properties of superparamagnetic spinel zinc ferrite decorated reduced graphene oxide nanostructures

Saravanan M., Sabari Girisun T.C.

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Abstract

Abstract Nonlinear absorption and optical limiting properties of ZnFe 2 O 4 -rGO magnetic nanostructures was investigated by the Z-scan technique using Q-switched Nd:YAG laser (5 ns, 532 nm, 10 Hz) as an excitation source. Excited state absorption was the dominant process responsible for the observed nonlinearity in ZnFe 2 O 4 decorated rGO which arises due to photo-generated charge carriers in the conduction band of zinc ferrite and increases in defects at the surface of rGO due to the incorporation of ZnFe 2 O 4 . The magnitude of the nonlinear absorption co-efficient was found to be in the order of 10 −10 m/W. A noteworthy enhancement in the third-order NLO properties in ZnFe 2 O 4 -(15 wt%) rGO with those of individual counter parts and well known graphene composites was reported. Role of induced defects states (sp 3 ) arising from the functionalization of rGO in the enhancement of NLO response was explained through Raman studies. Earlier incorporation and distribution of ZnFe 2 O 4 upon GO through one-step hydrothermal method was analyzed by XRD and FTIR. Formation of (nanospheres/nanospindles) ZnFe 2 O 4 along with reduction of graphene oxide was confirmed through TEM analysis. VSM studies showed zinc ferrite decorated rGO posseses superparamagnetic behavior. The tuning of nonlinear optical and magnetic behavior with variation in the content of spinel ferrites upon reduced graphene oxide provides an easy way to attain tunable properties which are exceedingly required in both optoelectronics and photothermal therapy applications.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Nonlinear Optical Materials Studies · Laser-Ablation Synthesis of Nanoparticles · Nonlinear Optical Materials Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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