Realizing Neuromorphic Computing
with Ferroelectric 2D Materials


(Zidan et al.,  Nat Electron 1, 22–29 (2018))
(Jiang et al., Mat. Tod. Nano, 8, 100059 (2019))
(Ayadi et al., Physica E, 114, 113582 (2019))

As exponentially more data is generated each year, the power consumed to process such data is also increasing at an overwhelming rate. Some worry that if this trend continues, projected global power generation may not keep up with the power consumed for computing alone by the year 2040. Contrary to the high power consumption of computing devices of current technology, the human brain processes an enormous amount of data all day, yet it is extremely power-efficient that only requires a few thousand kilo-calories. 

In an effort to mimic the working principle of the human brain comes the concept of neuromorphic computing. The realization of neuromorphic computing at the hardware level requires device elements that are capable of both processing and storing data--just like human neurons and synapses do. The elemental devices for such neuromorphic systems, named memtransistors or memristors, will allow for quick access to locally distributed memories without the need for long data transmission between logic and memory units, hence reducing power consumption and operation speed.  

Memtransistors can be implemented in various ways, but the use of ferroelectric materials is a particularly appealing approach. Ferroelectrics are a family of materials that exhibit spontaneous polarization upon an external electric field, which is then retained even after the field is removed. The remnant polarization generates a memory effect that could reconfigure opto-electronic response of a device. Combining 2D semiconductors' excellent electronic transport properties and room temperature-stable excitonic emission with ferroelectrics will allow for power-efficient opto-electronic devices for neuromorphic applications. 

Realizing Electronic Neuromorphics

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Realizing Excitonic/Optical Neuromorphics

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