The magnetic tunnel junction is the heart of the STT-MRAM memory. The MTJ is a spintronic device, which is used to store and read the data. With the advancement, most of the work is done online and a useful device is needed in order to store the data. Hence, it is important to design a promising device to store the data for a long time without any damage or loss of information. In this paper, first, we use the MTJ LAB simulator to check the important parameters such as TMR, resistance, and STT components and check how these parameters change for different oxide thicknesses. After this, the device was hybrid with the CMOS for 1-bit STT-MRAM and the results were drawn. So, in this paper, the main focus is to select appropriate oxide thickness and [Formula: see text][Formula: see text]nm is used to get better TMR ratio, resistance, and STT-components.
In this paper the spintronic-based memory MRAM is presented that showed how it can replace both SRAM and DRAM and provide the high speed with great chip size. Moreover, MRAM is the nonvolatile memory that provides great advancement in the storage process. The different types of MRAM are mentioned with the techniques used for writing purpose and also mention which one is more used and why. The basic working principle and the function performed by the MRAM are discussed. Artificial intelligence (AI) is mentioned with its pros and cons for intelligent systems. Neuromorphic computing is also explained along with its important role in intelligent systems. Some reasons are also discussed as to why neuromorphic computing is so important. This paper also presents how spintronic-based devices especially memory can be used in intelligent systems and neuromorphic computing. Nanoscale spintronic-based MRAM plays a key role in intelligent systems and neuromorphic computing applications.
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