Application of Memristors

Resistor, Capacitor and Inductor make up some of the basic elements in any circuit system. Memristor or a memory resistor is described as a resistor which can store data. This characteristic of the memristor is the reason it is most sought after for use in memory related systems. [6] The concept of memristors was first theorized by Prof. Leon. O. Chua in 1971. It wasn’t until Stanley Williams invented the crossbar latch in 2008 that the scientists realized the memristor could be made possible.

It was observed that the switches in the crossbar latch had the same characteristics as that of the memristor which was described in 1971 by Prof. Chua. [4] Memristor as a basic circuit element has created a lot of interest because of its ability to realize RRAM (Resistive Random Access Memory). It also opened up a whole new field of electronics and nanotechnology with their applicability to neuro-morphic systems. [1] For years scientists have been trying to duplicate the actions performed by the human brain.

With the help of memristors they might actually become a reality. The memristor is still in the developmental stages. One problem faced with the memristor is the scaling issue. Also, the economic factors have to be taken into consideration. The initial cost of production is high but later on the mass production rates are cheaper than the current costs of manufacturing a memory device. Not much is known about the limitations of memristors as the boundaries of the memristor haven’t been determined yet.

One limitation however is the design issues related to the memristor. It has to be designed keeping in mind the ever changing technology trends and thus has to be flexible. Memristors can behave as both a gate and a latch. Thus two different devices would not be required to do a job that can be done by one. This significantly reduces the area of the system. It is because of this property that memristors are being considered as a replacement to Flash memory and maybe DRAM (Dynamic Random Access Memory) and SRAM (Static Random Access Memory) in the near future.

Apart from being the successor to flash memory, memristors are also being incorporated into the flexible electronics industry. The flexible electronics industry will benefit greatly by the use of memristors as smaller circuit area is one of the major concerns while designing flexible electronics. For use in flexible electronics, memristor is combined with organic devices, zinc oxide or silicon dioxide to provide stability and flexibility to the material. Apart from being economical these materials also bond with the memristors easily.

The next step after flexible electronics was incorporating them into building brain like machines. Previous attempts at building them have proved to be futile but the advent of memristors has made it possible to realize them in the near future. The characteristics of memristors closely resemble that of the synapses present in the brain. [6] Brain has been found to contain 2 kinds of memristors, the passive memristors and the active memristors. The passive memristors are responsible for long term memory and independent thinking.

The active memristors are responsible for response to stimulus and quick thinking. Neuro-morphic systems are still in the developmental stages. SPICE (Simulation Program with Integrated Circuit Emphasis) models are being used to test and analyze the memristor circuits and are modeling their behavior for further analysis. From being directly integrated onto the processor to being involved in neuro-morphic systems as a main component memristors have a wide range of applications. Although the recent SPICE model simulations have been shown to be very promising, the design issues still remain unresolved.

Memristors have enabled the reduction in the size of the circuit area significantly. It is also the only element which is capable of going beyond Moore’s law thus helping us break free of the design constraints placed by that law. Further tests are being conducted to determine the boundaries of memristors and also to determine to what extent they can be used in neuro-morphic systems. It is too early to tell whether or not memristors are the next big thing in memory devices but the results so far are certainly promising.

Memristors are geared to replace Flash memory in a short time and when this happens it will be a huge leap in the world of nanotechnology. The system has to be designed in such a way that it is compatible with most software and hardware systems. The design has to be compromised on either power supply or die area parameters. APPENDIX: Fig 1. Memristor integrated into flexible electronics. [1] REFERENCES: [1] N. Gergel-Hackett et al. “Memristors with Flexible Electronic Applications” Vol. 0018-9219, 2011 IEEE 100, No. 6, June 2012, pp: 34- 49. [2] Y. V. Pershin and M.

Ventra, “Practical Approach to Programmable Analog Circuits with Memristors” IEEE transactions on circuits and systems, 1857(2010), pp: 157- 170 [3] Wikipedia contibutors, “Memristor” http://en. wikipedia. org/wiki/Memristor [4] R. C. Johnson, “Will memristors prove irresistible? ” EE-Times, issue-1538, http://www. eetimes. com/electronics-news/4076910/-Missing-link-memristor-created-Rewrite-the-textbooks [5] S. Shin et al. “Memristor applications for programmable analog IC’s” Nanotechnology, IEEE Transactions on Volume: 10 , Issue: 2 Digital Object Identifier: 10. 109/TNANO. 2009. 2038610 Publication Year: 2011 , pp: 266 – 274 [6] R. Tetzlaff1 and T. Schmidt “Memristors and Memristive circuits-an overview” Circuits and Systems (ISCAS), 2012 IEEE International Symposium on Digital Object Identifier: 10. 1109/ISCAS. 2012. 6271557 Publication Year: 2012, pp: 1590 – 1595 [7] R. Tetzlaff and A. Bruening “Memristor Technology in Future Electronic System Design” Design, Automation & Test in Europe Conference & Exhibition (DATE), 2012 Publication Year: 2012, pp: 592 [8] C. Yakopcic et al. Fabrication and Testing of Memristive Devices” Neural Networks (IJCNN), the 2010 International Joint Conference on Digital Object Identifier: 10. 1109/IJCNN. 2010. 5596755 Publication Year: 2010, pp: 1 – 4 [9] A. S. Oblea et al. “Silver chalcogenide based Memristor devices” Neural Networks (IJCNN), The 2010 International Joint Conference on Digital Object Identifier: 10. 1109/IJCNN. 2010. 5596775 Publication Year: 2010, pp: 1 – 3 [10] X. Wang and Y. Chen, “Spintronic Memristor devices and applications” Seagate Technology Design, Automation & Test in Europe Conference & Exhibition (DATE), 2010 Publication Year: 2010, pp: 667 – 672