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Correction: Kang et al. Fluid Flow to Electricity: Capturing Flow-Induced Vibrations with Micro-Electromechanical-System-Based Piezoelectric Energy Harvester. <i>Micromachines</i> 2024, <i>15</i>, 581.

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Design of an RRAM-Based Joint Model for Embedded Cellular Smartphone Self-Charging Device.

Abhinav Vishwakarma1, Anubhav Vishwakarma1,2, Matej Komelj2

  • 1Computer Engineering, Brandenburgische Technische Universität, 03046 Cottbus, Germany.

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Summary
This summary is machine-generated.

A novel RRAM memristor model with a permanent magnet enables non-volatile data storage and self-charging for portable electronics. This magnetic field-assisted design offers eco-friendly energy harvesting for embedded systems.

Keywords:
CMOSResistive RAMs (RRAMs)emerging applicationsenergy harvestingpermanent magnetsself-chargingsmartphoneswireless-sensor

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Area of Science:

  • Materials Science
  • Electrical Engineering
  • Computer Engineering

Background:

  • Energy consumption is a critical challenge in modern embedded systems-on-a-chip.
  • Conventional SRAMs lack non-volatility, limiting their use in battery-powered devices.
  • Resistive Random-Access Memory (RRAM) offers non-volatility and multi-bit storage, addressing limitations of traditional memory.

Purpose of the Study:

  • To propose and simulate a new RRAM-based hybrid memristor model integrated with a permanent magnet.
  • To evaluate the model's potential for non-volatile data retention and energy harvesting in portable electronics.
  • To explore the development of magnetic field-assisted embedded devices for eco-friendly energy solutions.

Main Methods:

  • A 1T2R RRAM-based hybrid memristor model was designed.
  • Simulations were performed using Cadence Virtuoso with a 1.5 V power supply.
  • The finite-element approach was employed to simulate magnetization.

Main Results:

  • The proposed model demonstrated non-volatile data retention after power-off.
  • Fast power on/off transitions were achieved.
  • Simulation results indicated the device can generate high voltage for charging smartphone batteries, facilitating self-charging capabilities.

Conclusions:

  • The magnet-based RRAM hybrid memristor model is a promising solution for non-volatile memory and energy harvesting in portable electronics.
  • This technology addresses environmental concerns by enabling self-charging functionalities.
  • The findings pave the way for magnetic field-assisted embedded devices and novel energy harvesting techniques for RRAM.