Recessed-Source/Drain Junctionless GAA MOSFETs and their Sensitivity to Temperature: A Machine learning based Analysis

• Published in: 2023 International Conference on Next Generation Electronics (NEleX) pp. 1 - 6
• Main Authors: Singh, Abhay Pratap, Kumar, Alok, Chaudhary, Bharat Singh, Tiwari, Gaurav, Baghel, R. K., Tirkey, Sukeshni
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14-12-2023
• Subjects: Gallium arsenide; Hot carrier Injection (HCI); Junction Less Gate All Around (JL-GAA); Junctions; Logic gates; Machine learning; Machine Learning (ML); Machine learning algorithms; MOSFET; Recessed -Source/Drain (Re -S/D ); Silicon on Insulator (SOI); Temperature sensors
• DOI: 10.1109/NEleX59773.2023.10421160

This article compares the performance of Recessed -Source/Drain Junction less Gate All Around (Re -S/D-JL-GAA ) MOSFETs to Junction less Gate All Around (JL-GAA) MOSFETs and analyses the effects of temperature variations on analogue parameters and Hot-Carrier Injection (HCI) degradation, additionally a Machine Learning (ML) base technique is introduce to find alternative results based on the TCAD simulations which leads to improved performance, reduced development time, and cost savings in the semiconductor industry. The study reveals that temperature differences have minimal impact on analog characteristics. Simulation results show that Re- S/D-JL-GAA shows better switching characteristics as compared with JL-GAA MOSFET, makes it a batter choice for analog circuits having a wide range of temperature.