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Simulation based comparison between a transversal and a tangential memristor model with a capacitance in parallel.

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Organic memristors, like human skin, exhibit non-linear electrical properties. Simulations reveal that combining tangential and transversal memristor models with capacitance can accurately replicate complex memristive behaviors observed in biological tissues.

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Area of Science:

  • Biophysics
  • Materials Science
  • Electrical Engineering

Background:

  • Non-linear measurements reveal that applied stimuli alter tissue electrical properties.
  • Tissues exhibiting pinched hysteresis loops in voltage-current plots can be classified as memristors.
  • Organic memristors (e.g., human skin, Venus flytrap) have been demonstrated but are often affected by parasitic capacitance.

Purpose of the Study:

  • To simulate the parallel connection of tangential and transversal memristor models with capacitance.
  • To investigate the modeling of human skin's electrical properties using memristor concepts.
  • To understand how different memristor types and parasitic elements influence hysteresis loop characteristics.

Main Methods:

  • Simulations were performed on parallel connections of tangential memristor models, transversal memristor models, and capacitance.
  • The stratum corneum was proposed as a tangential memristor model, inspired by human skin's non-linear properties.
  • Simulated results were compared with experimental data from human skin recordings.

Main Results:

  • A parallel connection of a tangential memristor model and capacitance produced hysteresis loops with two pinched points.
  • Simulations incorporating both tangential and transversal memristor models yielded asymmetric pinched hysteresis loops.
  • The simulated results closely resembled experimental recordings from human skin subjects.

Conclusions:

  • The stratum corneum can be effectively modeled as a tangential memristor.
  • The combination of tangential and transversal memristor models with capacitance provides a robust framework for simulating complex biological memristive behaviors.
  • This modeling approach offers insights into the electrical characteristics of organic tissues.