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Energy-efficient computing: Damping gives a faster switch

Date:
April 18, 2017
Source:
The Agency for Science, Technology and Research (A*STAR)
Summary:
Controlling memory with electric fields enables faster and more energy-efficient computing.
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Controlling memory with electric fields enables faster and more energy-efficient computing.

The optimal material properties required for magnetic memories to have ultra-low power consumption are identified using simulations performed by researchers at Agency for Science, Technology and Research (A*STAR), Singapore.

Random access memory, or RAM, is a crucial element in most computers. RAM devices store the information required for the system to complete processes. This information can be written to and retrieved from the random-access memory at a much faster rate than other data storage media, which means that computational processes can be completed more quickly.

Most RAM devices store data electrically in an integrated circuit. However, storing information magnetically could enable even faster operation, making faster computers. Another feature is that magnetic random access memory (MRAM) is non-volatile -- which means that, unlike conventional electrical RAM, it doesn't lose its data when the device is powered down. MRAM store data as the direction of magnetization in a ferromagnetic film. Switching the magnetization, and thus changing the memory from one binary state to another, can be achieved by just applying a magnetic field, but this requires a lot of power.

BingJin Chen and Guchang Han from the A*STAR Data Storage Institute use micromagnetic simulations to investigate electric-field assisted magnetization switching in magnetic random access memories. They identify the ideal material properties required for minimizing the switching time. "We show that a reliable magnetic switching can take place within five nanoseconds for electric-field assisted switching and no other external driving force is needed," says Chen.

Electric-field assisted switching works because the applied electrical current alters the magnetic properties of the ferromagnetic material, making it more susceptible to a change of magnetization. The small magnetic field associated with the current, known as the Oersted field, is then sufficient to switch the magnetization.

The simulations indicated that a material property known as magnetic damping was important in optimizing the switching time. Damping is a reduction in magnetic field strength as the field penetrates deeper into the material. Chen and Han show that the switching time decreases with an increase in the damping constant and the strength of the Oersted field. The results indicated that when choosing a ferromagnetic material with the best damping constant, switching of an electric-field assisted magnetic random access memory could be as fast as three nanoseconds.

"We hope to move our study from two-terminal devices that both read and write data using the same connections to more stable three-terminal memory structures where these two paths are separated," says Chen.


Story Source:

Materials provided by The Agency for Science, Technology and Research (A*STAR). Note: Content may be edited for style and length.


Journal Reference:

  1. B. J. Chen, G. C. Han. Oersted Field-Guided Electric Field Switching in Perpendicular Magnetic Free Layer. IEEE Transactions on Magnetics, 2016; 52 (9): 1 DOI: 10.1109/TMAG.2016.2569066

Cite This Page:

The Agency for Science, Technology and Research (A*STAR). "Energy-efficient computing: Damping gives a faster switch." ScienceDaily. ScienceDaily, 18 April 2017. <www.sciencedaily.com/releases/2017/04/170418115353.htm>.
The Agency for Science, Technology and Research (A*STAR). (2017, April 18). Energy-efficient computing: Damping gives a faster switch. ScienceDaily. Retrieved November 5, 2024 from www.sciencedaily.com/releases/2017/04/170418115353.htm
The Agency for Science, Technology and Research (A*STAR). "Energy-efficient computing: Damping gives a faster switch." ScienceDaily. www.sciencedaily.com/releases/2017/04/170418115353.htm (accessed November 5, 2024).

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