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Author

C. Fukumoto

Bio: C. Fukumoto is an academic researcher. The author has contributed to research in topics: Magnetoresistive random-access memory & Non-volatile memory. The author has an hindex of 2, co-authored 3 publications receiving 928 citations.

Papers
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Proceedings ArticleDOI
05 Dec 2005
TL;DR: In this article, a spin torque transfer magnetization switching (STS) based nonvolatile memory called spin-RAM was presented for the first time, which is based on magnetization reversal through an interaction of a spin momentum-torque-transferred current and a magnetic moment of memory layers in magnetic tunnel junctions (MTJ).
Abstract: A novel nonvolatile memory utilizing spin torque transfer magnetization switching (STS), abbreviated spin-RAM hereafter, is presented for the first time The spin-RAM is programmed by magnetization reversal through an interaction of a spin momentum-torque-transferred current and a magnetic moment of memory layers in magnetic tunnel junctions (MTJs), and therefore an external magnetic field is unnecessary as that for a conventional MRAM This new programming mode has been accomplished owing to our tailored MTJ, which has an oval shape of 100 times 150 nm The memory cell is based on a 1-transistor and a 1-MTJ (ITU) structure The 4kbit spin-RAM was fabricated on a 4 level metal, 018 mum CMOS process In this work, writing speed as high as 2 ns, and a write current as low as 200 muA were successfully demonstrated It has been proved that spin-RAM possesses outstanding characteristics such as high speed, low power and high scalability for the next generation universal memory

961 citations

Proceedings ArticleDOI
11 Jun 2002
TL;DR: In this article, an improved magnetic tunnel junction (MTJ) material was integrated with 0.4/spl times/0.8 /spl mu/m/sup 2/ MTJ elements without process-induced damage.
Abstract: This work is a report on high-performance MRAM technology. 0.4/spl times/0.8 /spl mu/m/sup 2/ MTJ elements were successfully integrated with 0.35 /spl mu/m CMOS technology without process-induced damage. A magnetoresistance (MR) ratio of more than 55% and the read/write operating point were obtained by introducing an improved magnetic tunnel junction (MTJ) material. The short-pulse writing in combination with an improved cell structure suggests that MRAM has a great deal of potential for low power applications.

7 citations

01 Jan 2002
TL;DR: In this paper, a report on high-@omce MRAh4 technology is presented, where 0.4 x 0.8 um' MTJ elements were integrated with 0.35 um magnetomistance (MR) mtio of more than 55%.
Abstract: This work is a report on high-@omce MRAh4 Technology. 0.4 x 0.8 um' MTJ elements were SUCCeSSfUUy integrated with 0.35 um magnetomistance (MR) mtio of more than 55% and the read/write ~eljunction~~mat eriaLThesh~~~inc omb~on with an improved cell strucZures sugestthatMR4M has a great deal of potential for low power applications. htKKlu~on Magnetcmidverandomaccessmemory(MRAM)hascandidatefor the role of the main form of non-volatile memory. This is because of its highsped opemicq UnlutliM read/write endurance [1,2], and its high degree of CMOS process compailfion between the "0" and "1". Fig 6 shows the askmid culves for conventional and improved MTJ material The ames for 80 individual MTJ cells in a die were superimposed to obtain each of the gmphs The measuremedt was done with the "xis-variable magnetic fields induced by magnetic coils. The conventional material provides no single operating point. All askmid ames for the mpmved material were, however, much more similar to each other and thus make the opemihgpoint obvious. Fig. 7 (a) and (b) are the asteroid curves obtainedby using an LSI tester to measure the 6254it cell anay. Nine curves picked up across the die are CMOS techn010gy without damages. A

Cited by
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Journal ArticleDOI
TL;DR: The authors are starting to see a new paradigm where magnetization dynamics and charge currents act on each other in nanostructured artificial materials, allowing faster, low-energy operations: spin electronics is on its way.
Abstract: Electrons have a charge and a spin, but until recently these were considered separately. In classical electronics, charges are moved by electric fields to transmit information and are stored in a capacitor to save it. In magnetic recording, magnetic fields have been used to read or write the information stored on the magnetization, which 'measures' the local orientation of spins in ferromagnets. The picture started to change in 1988, when the discovery of giant magnetoresistance opened the way to efficient control of charge transport through magnetization. The recent expansion of hard-disk recording owes much to this development. We are starting to see a new paradigm where magnetization dynamics and charge currents act on each other in nanostructured artificial materials. Ultimately, 'spin currents' could even replace charge currents for the transfer and treatment of information, allowing faster, low-energy operations: spin electronics is on its way.

2,191 citations

Journal ArticleDOI
TL;DR: NVSim is developed, a circuit-level model for NVM performance, energy, and area estimation, which supports various NVM technologies, including STT-RAM, PCRAM, ReRAM, and legacy NAND Flash and is expected to help boost architecture-level NVM-related studies.
Abstract: Various new nonvolatile memory (NVM) technologies have emerged recently. Among all the investigated new NVM candidate technologies, spin-torque-transfer memory (STT-RAM, or MRAM), phase-change random-access memory (PCRAM), and resistive random-access memory (ReRAM) are regarded as the most promising candidates. As the ultimate goal of this NVM research is to deploy them into multiple levels in the memory hierarchy, it is necessary to explore the wide NVM design space and find the proper implementation at different memory hierarchy levels from highly latency-optimized caches to highly density- optimized secondary storage. While abundant tools are available as SRAM/DRAM design assistants, similar tools for NVM designs are currently missing. Thus, in this paper, we develop NVSim, a circuit-level model for NVM performance, energy, and area estimation, which supports various NVM technologies, including STT-RAM, PCRAM, ReRAM, and legacy NAND Flash. NVSim is successfully validated against industrial NVM prototypes, and it is expected to help boost architecture-level NVM-related studies.

1,100 citations

Journal ArticleDOI
TL;DR: In this article, the authors survey the current state of phase change memory (PCM), a nonvolatile solid-state memory technology built around the large electrical contrast between the highly resistive amorphous and highly conductive crystalline states in so-called phase change materials.
Abstract: The authors survey the current state of phase change memory (PCM), a nonvolatile solid-state memory technology built around the large electrical contrast between the highly resistive amorphous and highly conductive crystalline states in so-called phase change materials. PCM technology has made rapid progress in a short time, having passed older technologies in terms of both sophisticated demonstrations of scaling to small device dimensions, as well as integrated large-array demonstrators with impressive retention, endurance, performance, and yield characteristics. They introduce the physics behind PCM technology, assess how its characteristics match up with various potential applications across the memory-storage hierarchy, and discuss its strengths including scalability and rapid switching speed. Challenges for the technology are addressed, including the design of PCM cells for low reset current, the need to control device-to-device variability, and undesirable changes in the phase change material that c...

921 citations

Journal ArticleDOI
27 Nov 2019-Nature
TL;DR: An overview of the developments in neuromorphic computing for both algorithms and hardware is provided and the fundamentals of learning and hardware frameworks are highlighted, with emphasis on algorithm–hardware codesign.
Abstract: Guided by brain-like ‘spiking’ computational frameworks, neuromorphic computing—brain-inspired computing for machine intelligence—promises to realize artificial intelligence while reducing the energy requirements of computing platforms. This interdisciplinary field began with the implementation of silicon circuits for biological neural routines, but has evolved to encompass the hardware implementation of algorithms with spike-based encoding and event-driven representations. Here we provide an overview of the developments in neuromorphic computing for both algorithms and hardware and highlight the fundamentals of learning and hardware frameworks. We discuss the main challenges and the future prospects of neuromorphic computing, with emphasis on algorithm–hardware codesign. The authors review the advantages and future prospects of neuromorphic computing, a multidisciplinary engineering concept for energy-efficient artificial intelligence with brain-inspired functionality.

877 citations

Journal ArticleDOI
25 Sep 2008-Nature
TL;DR: It is shown that the manipulation of magnetization can be achieved solely by electric fields in a ferromagnetic semiconductor, (Ga,Mn)As, allowing manipulation of the magnetization direction.
Abstract: Conventional semiconductor devices use electric fields to control conductivity, a scalar quantity, for information processing. In magnetic materials, the direction of magnetization, a vector quantity, is of fundamental importance. In magnetic data storage, magnetization is manipulated with a current-generated magnetic field (Oersted-Ampere field), and spin current is being studied for use in non-volatile magnetic memories. To make control of magnetization fully compatible with semiconductor devices, it is highly desirable to control magnetization using electric fields. Conventionally, this is achieved by means of magnetostriction produced by mechanically generated strain through the use of piezoelectricity. Multiferroics have been widely studied in an alternative approach where ferroelectricity is combined with ferromagnetism. Magnetic-field control of electric polarization has been reported in these multiferroics using the magnetoelectric effect, but the inverse effect-direct electrical control of magnetization-has not so far been observed. Here we show that the manipulation of magnetization can be achieved solely by electric fields in a ferromagnetic semiconductor, (Ga,Mn)As. The magnetic anisotropy, which determines the magnetization direction, depends on the charge carrier (hole) concentration in (Ga,Mn)As. By applying an electric field using a metal-insulator-semiconductor structure, the hole concentration and, thereby, the magnetic anisotropy can be controlled, allowing manipulation of the magnetization direction.

615 citations