MRAM in Microcontroller and Microprocessor Product Applications

Jew, T.

doi:10.1109/iedm13553.2020.9372112

Cited by 7 publications

(2 citation statements)

References 3 publications

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“…The NVM elements and SRAM part are integrated in an nvSRAM bitcell by a bit-to-bit connection instead of a macro-to-macro connection [19,64]. By storing commonly used routines in the nvSRAM, the startup latency and associated energy consumption from data movement can be eliminated, enabling more efficient edge computing applications [65].…”

Section: Characteristics Of Various Storage Typesmentioning

confidence: 99%

A Survey of Emerging Memory in a Microcontroller Unit

Qi,

Fan,

Cai

et al. 2024

Micromachines

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In the era of widespread edge computing, energy conservation modes like complete power shutdown are crucial for battery-powered devices, but they risk data loss in volatile memory. Energy autonomous systems, relying on ambient energy, face operational challenges due to power losses. Recent advancements in emerging nonvolatile memories (NVMs) like FRAM, RRAM, MRAM, and PCM offer mature solutions to sustain work progress with minimal energy overhead during outages. This paper thoroughly reviews utilizing emerging NVMs in microcontroller units (MCUs), comparing their key attributes to describe unique benefits and potential applications. Furthermore, we discuss the intricate details of NVM circuit design and NVM-driven compute-in-memory (CIM) architectures. In summary, integrating emerging NVMs into MCUs showcases promising prospects for next-generation applications such as Internet of Things and neural networks.

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Section: Characteristics Of Various Storage Typesmentioning

confidence: 99%

A Survey of Emerging Memory in a Microcontroller Unit

Qi,

Fan,

Cai

et al. 2024

Micromachines

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“…The above disadvantages have emerged as unavoidable bottlenecks limiting their further development. [30,31] As a new type of two-terminal neuromorphic device, FTJ based on ferroelectric material has lower power consumption compared with the traditional RRAM and MRAM devices, and the smaller nonlinearity and multilevel conductivity state of FTJ can enhance the accuracy of signal conditioning. [32] Meanwhile, the behavior of tunnel resistance (TER) changing with external voltage alterations closely resembles synaptic plasticity, which can emulate the signal transduction process of the real synapse.…”

Section: Introductionmentioning

confidence: 99%

A Zero‐Voltage‐Writing Artificial Nervous System Based on Biosensor Integrated on Ferroelectric Tunnel Junction

Qin,

Zhong,

et al. 2024

Advanced Materials

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The artificial nervous system proves the great potential for the emulation of complex neural signal transduction. However, a more bionic system design for bio‐signal transduction still lags behind that of physical signals, and relies on additional external sources. Here, we present a zero‐voltage‐writing artificial nervous system (ZANS) that integrates a bio‐source‐sensing device (BSSD) for ion‐based sensing and power generation with a hafnium‐zirconium oxide‐ferroelectric tunnel junction (HZO‐FTJ) for the continuously adjustable resistance state. The BSSD can use ion bio‐source as both perception and energy source, and then output voltage signals varied with the change of ion concentrations to the HZO‐FTJ, which completes the zero‐voltage‐writing neuromorphic bio‐signal modulation. In view of in‐/ex‐vivo biocompatibility, we show the precise muscle control of a rabbit leg by integrating the ZANS with a flexible nerve stimulation electrode. The independence on external source enhances the application potential of ZANS in robotics and prosthetics.This article is protected by copyright. All rights reserved

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