Spacer Layer Thickness Dependence of the Giant Magnetoresistance in Electrodeposited Ni-Co/Cu Multilayers.
Sándor ZsurzsaMoustafa El-TahawyLászló PéterLászló Ferenc KissJenő GubiczaGyörgy MolnárImre BakonyiPublished in: Nanomaterials (Basel, Switzerland) (2022)
Electrodeposited Ni 65 Co 35 /Cu multilayers were prepared with Cu spacer layer thicknesses between 0.5 nm and 7 nm. Their structure and magnetic and magnetoresistance properties were investigated. An important feature was that the Cu layers were deposited at the electrochemically optimized Cu deposition potential, ensuring a reliable control of the spacer layer thickness to reveal the true evolution of the giant magnetoresistance (GMR). X-ray diffraction indicated satellite reflections, demonstrating the highly coherent growth of these multilayer stacks. All of the multilayers exhibited a GMR effect, the magnitude of which did not show an oscillatory behavior with spacer layer thickness, just a steep rise of GMR around 1.5 nm and then, after 3 nm, it remained nearly constant, with a value around 4%. The high relative remanence of the magnetization hinted at the lack of an antiferromagnetic coupling between the magnetic layers, explaining the absence of oscillatory GMR. The occurrence of GMR can be attributed to the fact that, for spacer layer thicknesses above about 1.5 nm, the adjacent magnetic layers become uncoupled and their magnetization orientation is random, giving rise to a GMR effect. The coercive field and magnetoresistance peak field data also corroborate this picture: with increasing spacer layer thickness, both parameters progressively approached values characteristic of individual magnetic layers. At the end, a critical analysis of previously reported GMR data on electrodeposited Ni-Co/Cu multilayers is provided in view of the present results. A discussion of the layer formation processes in electrodeposited multilayers is also included, together with a comparison with physically deposited multilayers.
Keyphrases
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- molecularly imprinted
- aqueous solution
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- magnetic resonance imaging
- big data
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- magnetic resonance
- deep learning
- dna methylation
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- room temperature
- transition metal
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- electron microscopy