By combining bipolar spin neurons with memristors (phase change memory), input signals can program self-adaptive weights sandwiched between metal interconnects. SOURCE: Purdue
Traditional semiconductor chips use electrical charge to store information, requiring thousands of electrons to be transferred onto a storage device, like a capacitor, until its voltage exceeds a threshold. However, switching from encoding digital ones and zeros with electrical charge to using the spin-state of electrons can drastically cut the energy consumption of electronic circuits.
Spin states are inherent to electrons, which are constantly spinning, imparting a momentum to their electrical charge which can be oriented “up” or “down”. Such spin-polarized electrons can be used to encode digital ones and zeros using much less energy than just piling up charge on a capacitor. Ideally, a single electron could be used to store a digital one as “up” spin and a digital zero as “down” spin, enabling the ultimate downsizing for parallel processors to one-bit-per-electron. And for intrinsically parallel applications, such as emulating the billions of neurons in the human brain, the super low power achieved by spin-polarized digital encodings could enable the ultimate parallel processing applications of the future.
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