Investigation of recessed-source/drain SOI feedback FET-based integrate and fire neuron circuit with compact model of threshold switching devices

Abstract

In this article, the investigation of recessed-source/drain (Re-S/D) SOI feedback FET (FBFET)-based integrate and fire (IF) neuron circuit parameters is presented using a threshold switching device compact model. FBFETs offer high I_ON and low SS with minimal power consumption, operating efficiently at lower voltages and currents than conventional MOSFETs. Utilizing I_ON/I_OFF ratio and threshold voltage limits (V_t2/V_t1) of the device, a model is developed to mimic hysteresis characteristics, which is then used to implement an IF neuron circuit. Our findings show that altering the Re-S/D thickness between 0 and 50 nm enhances the I_ON of the device under study while decreasing hysteresis width. We detected a significant increase in output spike frequency of 46.8% and 65.14% for input current pulse amplitudes of 5 and 20 nA, respectively. Furthermore, increasing the Re-S/D thickness from 0 to 50 nm led to a significant 29.97% enhancement in spike amplitude. In addition, when using input current pulse amplitudes of 5 and 20 nA, we saw energy savings per spike of 3.36% and 12.7%, respectively. At the same time, there was an increase in power of 8.69% and 9.54%. These enhancements in performance metrics establish our proposed integrate and fire neuron circuit as a promising candidate for efficient neuromorphic system implementation.