Tuning magnetic nanostructures and flux concentrators for magnetoresistive sensors

Xiaolu Yin, Yen Fu Liu, Dan Ewing, Carmen K. Ruder, Paul J. De Rego, A. S. Edelstein, Sy Hwang Liou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations


The methods for the optimization of the magnetoresistive (MR) sensors are to reduce sources of noises, to increase the signal, and to understand the involved fundamental limitations. The high-performance MR sensors result from important magnetic tunnel junction (MTJ) properties, such as tunneling magnetoresistance ratio (TMR), coercivity (Hc), exchange coupling field (He), domain structures, and noise properties as well as the external magnetic flux concentrators. All these parameters are sensitively controlled by the magnetic nanostructures, which can be tuned by varying junction free layer nanostructures, geometry, and magnetic annealing process etc. In this paper, we discuss some of efforts that an optimized magnetic sensor with a sensitivity as high as 5,146 %/mT. This sensitivity is currently the highest among all MR-type sensors that have been reported. The estimated noise of our magnetoresistive sensor is 47 pT/Hz1/2 at 1 Hz. This magnetoresistance sensor dissipates only 100 μW of power while operating under an applied voltage of 1 V at room temperature.

Original languageEnglish (US)
Title of host publicationSpintronics VIII
EditorsHenri-Jean Drouhin, Jean-Eric Wegrowe, Manijeh Razeghi
ISBN (Electronic)9781628417173
StatePublished - 2015
EventSpintronics VIII - San Diego, United States
Duration: Aug 9 2015Aug 13 2015

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherSpintronics VIII
Country/TerritoryUnited States
CitySan Diego


  • Magnetic flux concentrators
  • Magnetic tunnel junction
  • Magnetoresistive sensor
  • Multilayer thin films

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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