Reconfigurable Field-Effect Transistor as a Synaptic Device for XNOR Binary Neural Network

Abstract

A reconfigurable field-effect transistor (RFET) with memory functionality is proposed as a new high-density synaptic device capable of exclusive NOR (XNOR) operation for a binary neural network (BNN). A RFET with three gates is used in this letter, consisting of two program gates (PGs) electrically connected to each other and a control gate (CG) between the PGs. By changing the polarity of the PG bias or the polarity of the charge trapped in Si <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> layer on the PGs, the RFET operates as an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> - or a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula> -MOSFET having a CG as a switching gate. The XNOR operation is successfully demonstrated in a fabricated RFET. The on/off current ratio (the ratio of 1 to 0 in the result of the XNOR operation) is ~10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> and the current is ~1 nA/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> . Using a RFET as a synaptic device for a BNN is efficient in terms of the area (~8F <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /synapse) because XNOR operation can be performed using only one RFET.