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Spin—Valve and Spin—Tunneling Devices: Read Heads, MRAMs, Field Sensors

  • P. P. Freitas
Chapter
Part of the Lecture Notes in Physics book series (LNP, volume 569)

Abstract

Hard disk magnetic data storage is increasing at a steady state in terms of units sold, with 144 million drives sold in 1998 (107million for desktops, 18 million for portables, and 19 million for enterprise drives), corresponding to a total business of 34 billion US$ [1]. The growing need for storage coming from new PC operating systems, INTERNET applications, and a foreseen explosion of applications connected to consumer electronics(digital TV, video, digital cameras, GPS systems, etc), keep the magnetics community actively lookng for new solutions, concerning media, heads, tribology, and system electronics. current state of the art disk drives (January 2000),using dual inductive-write,magnetoresistive- read (MR)integrated heads reach areal densities of 15 to 23 bit/μ2 ,capable of putting a full 20 GB in one platter (a 2 hour film occupies 10 GB).Densities beyond 80 bit/μ2 have already been demonstrated in the laboratory (Fujitsu 87bit/μ Intermag 2000,Hitachi 81 bit/μ2 ,Read —Rite 78 bit/μ2 ,Seagate 70 bit/μ2 —all the last three demos done in the first 6 months of 2000,with IBM having demonstrated 56 bit/μ2 already at the end of 1999).At densities near 60 bit/μ2 ,the linear bit size is ∼43 nm,and the width of the written tracks is ∼0 .23 μm.Areal density in commercial drives is increasing steadily ata rate of nearly 100% per year [1],and consumer products above 60 bit/μ2 areexpected by 2002.These remarkable achievements are only possible by a stream of technological innovations,in media [2],write heads [3],read heads [4],and system electronics [5].In this chapter,recent advances on spin valve materials and spin valve sensor architectures,low resistance tunnel junctions and tunnel junction head architectures will be addressed.

Keywords

Tunnel Junction Areal Density Spin Valve Free Layer Static Random Access Memory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • P. P. Freitas
    • 1
    • 2
  1. 1.Instituto de Engenharia de Sistemas e ComputadoresLisbonPortugal
  2. 2.Departamento de FisicaInstituto Superior TecnicoLisbonPortugal

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