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A quantum sensing metrology for magnetic memories.
Borràs, Vicent J; Carpenter, Robert; Zaper, Liza; Rao, Siddharth; Couet, Sebastien; Munsch, Mathieu; Maletinsky, Patrick; Rickhaus, Peter.
Afiliação
  • Borràs VJ; Qnami AG, Muttenz, Switzerland.
  • Carpenter R; Imec, Kapeldreef 75, 3001 Leuven, Belgium.
  • Zaper L; Qnami AG, Muttenz, Switzerland.
  • Rao S; Department of Physics, University of Basel, Basel, Switzerland.
  • Couet S; Imec, Kapeldreef 75, 3001 Leuven, Belgium.
  • Munsch M; Imec, Kapeldreef 75, 3001 Leuven, Belgium.
  • Maletinsky P; Qnami AG, Muttenz, Switzerland.
  • Rickhaus P; Department of Physics, University of Basel, Basel, Switzerland.
Npj Spintron ; 2(1): 14, 2024.
Article em En | MEDLINE | ID: mdl-38883426
ABSTRACT
Magnetic random access memory (MRAM) is a leading emergent memory technology that is poised to replace current non-volatile memory technologies such as eFlash. However, controlling and improving distributions of device properties becomes a key enabler of new applications at this stage of technology development. Here, we introduce a non-contact metrology technique deploying scanning NV magnetometry (SNVM) to investigate MRAM performance at the individual bit level. We demonstrate magnetic reversal characterization in individual, <60 nm-sized bits, to extract key magnetic properties, thermal stability, and switching statistics, and thereby gauge bit-to-bit uniformity. We showcase the performance of our method by benchmarking two distinct bit etching processes immediately after pattern formation. In contrast to ensemble averaging methods such as perpendicular magneto-optical Kerr effect, we show that it is possible to identify out of distribution (tail-bits) bits that seem associated to the edges of the array, enabling failure analysis of tail bits. Our findings highlight the potential of nanoscale quantum sensing of MRAM devices for early-stage screening in the processing line, paving the way for future incorporation of this nanoscale characterization tool in the semiconductor industry.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article