Propose a biological implementation of a memristor using any available genetic c

Question

Propose a biological implementation of a memristor using any available genetic component. You are free to assume component properties beyond what is readily available and biological relevant. Model and simulate the proposed system and demonstrate the basic features of the memristor behavior. Discuss how a memristor can be useful for practical applications.

“A memristor is a hypothetical nonlinear passive two terminal electrical component relating electric charge and magnetic flux linkage. According to the characterizing mathematical relations, the memristor would hypothetically operate in the following way: The memristor's electrical resistance is not constant but depends on the history of current that had previously flowed through the device, i.e., its present resistance depends on how much electric charge has flowed in what direction through it in the past; the device remembers its history — the so-called non-volatility property. When the electric power supply is turned off, the memristor remembers its most recent resistance until it is turned on again.”

Explanation / Answer

A MEMORY RESISTOR IS CALLED MIMRISTOR

Memristors are basically a fourth class of electrical circuit, joining the resistor, the capacitor, and the inductor, that exhibit their unique properties primarily at the nanoscale. Theoretically, Memristors, a concatenation of “memory resistors”, are a type of passive circuit elements that maintain a relationship between the time integrals of current and voltage across a two terminal element. Thus, a memristors resistance varies according to a devices memristance function, allowing, via tiny read charges, access to a “history” of applied voltage. The material implementation of memristive effects can be determined in part by the presence of hysteresis (an accelerating rate of change as an object moves from one state to another) which, like many other non-linear “anomalies” in contemporary circuit theory, turns out to be less an anomaly than a fundamental property of passive circuitry.

Until recently, when HP Labs under Stanley Williams developed the first stable prototype, memristance as a property of a known material was nearly nonexistant. The memristance effect at non-nanoscale distances is dwarfed by other electronic and field effects, until scales and materials that are nanometers in size are utilized. At the nanoscale, such properties have even been observed in action prior to the HP Lab prototypes.

But beyond the physics of electrical engineering, they are a reconceptualizing of passive electronic circuit theory first proposed in 1971 by the nonlinear circuit theorist Leon Chua. What Leon Chua, a UC Berkeley Professor, contended in his 1971 paper Transactions on Circuit Theory, is that the fundamental relationship in passive circuitry was not between voltage and charge as assumed, but between changes-in-voltage, or flux, and charge. Chua has stated: “The situation is analogous to what is called “Aristotle’s Law of Motion, which was wrong, because he said that force must be proportional to velocity. That misled people for 2000 years until Newton came along and pointed out that Aristotle was using the wrong variables. Newton said that force is proportional to acceleration–the change in velocity. This is exactly the situation with electronic circuit theory today. All electronic textbooks have been teaching using the wrong variables–voltage and charge–explaining away inaccuracies as anomalies. What they should have been teaching is the relationship between changes in voltage, or flux, and charge.”

As memristors develop, its going to come down to, in part, who can come up with the best material implementation. Currently IBM, Hewlett Packard, HRL, Samsung and many other research labs seem to be hovering around the titanium dioxide memristor,

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There are quite a few vectors of inquiry researching various types of memristors. The material implementation of a memristor is important to how they behave in a memristive system. its important to understand the difference between a memristor, and a memristive system, because the specific type of memristor can highlight different strengths and weaknesses, and they can be used in a memristive system for different applications of scale or purpose. There are currently no memristor datasheets available, as much of the material implementations are experimental and in development. In general, though, for any material, Hysterisis, an accelerating rate of change of a property as objects move from one state to another, is an indicator of memristive properties.

Currently Hewlett Packard’s version of the Titanium Dioxide susbtrate memristor is the most generally pursued type of memristor, but the list of different memristor types below shows there are a wide variety of systems that exhibit memristive behavior, and more are being discovered as industries begin to build out their research, prototyping, and manufacturing infrastructures.

1. Molecular and Ionic Thin Film Memristive Systems

These type of memristors primarily rely on different material properties of thin film atomic lattices that exhibit hysterisis under the application of charge.

a). Titanium dioxide memristors

The Titanium Dioxide memristor first developed at HP Labs is based on a two-layer thin “sandwich” of titanium dioxide films, composed of symmetrical lattices of titanium and oxygen atoms. (Titanium dioxide changes its resistance in the presence of oxygen, which is why its used in oxygen sensors.) The motion of atoms in the films are tied to the movement of electrons in the material, which allows a state change in the atomic structure of the memristor. The bottom layer acts as an insulator, and the top film layer acts as a conductor via oxygen vacancies in the titanium dioxide. The oxygen vacancies in the top layer are moved to the bottom layer, changing the resistance, and maintaining the state. To access the memristive properties, crossbars of nanowires are placed above and below the top and bottom layers, so that a charge can be passed through.

Its interesting to note that Stan Williams at HP came to the material property of titanium dioxide memristive effects in part through his interests in the miniaturization of sensor technology for distributed sensing.

b. Polymeric (ionic) memristors

Utilizing the properties of various solid-state ionics, one component of the material structure, the cationic or anionic, is free to move throughout the structure as a charge carrier. Polymeric memristors explore dynamic doping of polymer and inorganic dielectric-type material to attempt and provoke hysterisis type behaviors. Usually, a single passive layer between an electrode and an active thin film attempt to exaggerate the extraction of ions from the electrode. The terms polymeric and ionic are often used somewhat loosely and generically.

c. Manganite memristive systems

A substrate of bilayer oxide films based on manganite, as opposed to titanium dioxide, were exhibited as describing memristive properties at the University of Houston in 2001.

d. Resonant-tunneling diode memristors

Certain types of quantum-well diodes with special doping designs of the spacer layers between the source and drain regions have been shown to exhibit memristive properties.

2. Spin Based and Magnetic memristive systems

Spin-based memristive systems, as opposed to molecular and ionic nanostructure based systems, rely on the property of degree of freedom in electron spin. In these types of system, electron spin polarization is altered, usually through the movement of a magnetic “domain” wall separating polarities, allowing for hysteresis like behaviors to occur.

a). Spintronic Memristors

A type of magnetic memristor under development by several labs, notably Seagate, is called a spintronic memristor. In same way that the titanium dixoide memristor changes state by altering oxygen vacanccies between two seperate layers, changing a spintronic memristors resistance state uses magnetization to alter the spin direction of electrons in two different sections of a device. Two sections of different electron spin directions are kept separate based on a moving “wall”, controlled by magnetization, and the relation of the wall dividing the electron spins is what controls the devices overall resistance state.

b). Spin Torque Transfer (STT) MRAM

Since the 1990s, the development of MRAM has shown, in certain cases, memristive properties. The configuration known as a spin valve, the simplest structure for a MRAM bit, allows for state change. The resistance in a memristive effective spin-torque transfer is controlled by a spin torque induced by a current flowing through a magnetic junction, and is dependent on the difference in spin orientation between the two sides of the junction. Depending on the material used to construct some MRAM bits, these spin torque constructions can exhibit both ionic and magnetic properties, and are sometimes referred to as “second-order memristive systems”.

3. 3-terminal memistors

As an early outlier from the 1960s, the advanced technology of Electroplating ;), was used to demonstrate the viability of a non solid state, three terminal memristor by Bernard Widrow at Stanford. The conductance was described as being controlled by the time integral of current. Interesting to note here is the research was part of a larger research project into the mathematics of early neural network modeling. The Adaptive Linear Element of Widrow (and his then-student Ted Hoff, of Intel fame) is a single layer neural network based on the McCulloch-Pitts neuron, and shows that even in the early days, the modeling of memristive systems was closely related to neuronal learning algorithms.

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