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This work highlights the potential application of raised source and drain (RSD) MOSFETs-based charge trapping memory (CTM) for next-generation computing applications. This simulation study presents a double-gate (DG)-RSD MOSFET technology with a short gate length (50 nm) to significantly improve the performance of logic-in-memory (LIM) and neuromorphic computing (NC) systems. …
This article introduces a framework that establishes a cohesive link between the first principles-based simulations and circuit-level analyses using a machine learning-based compact modeling platform. Starting with atomistic simulations, the framework examines the microscopic details of material behavior, forming the foundation for later stages. The generated datasets, with molecular insights, …
This work presents a comparative analysis of complementary field-effect transistor (CFET) and nanosheet FET (NSFET) architectures, with a focus on self-heating effects (SHEs), negative bias temperature instability (NBTI), hot carrier degradation (HCD), and the impact of back-end-of-line (BEOL) parasitics on standard cell performance. NBTI degradation is modeled using a framework …
In this work, for the first time, we present a SPICE-compatible compact model of ferroelectric (FE) diodes to enable their design exploration for diverse applications, including memory and unconventional computing paradigms. We propose modified Schottky barrier and hopping models for capturing the on- and off-mode operations of the FE diode, …
We explore the effects of layered geometries of 2-D quantum spin systems as a method to tune and control material properties for spintronic devices. We analyze the dispersion relation of a 2-D quantum spin system with a shifted bilayer square lattice through the linear spin wave (LSW) approximation of quantum …
Ternary weight neural networks (TWNs), with weights quantized to three states (−1, 0, and 1), have emerged as promising solutions for resource-constrained edge artificial intelligence (AI) platforms due to their high energy efficiency with acceptable inference accuracy. Further energy savings can be achieved with TWN accelerators utilizing techniques such as compute-in-memory (CiM) and …
This work presents a comprehensive spin-orbit torque (SOT)-based magnetic random access memory (MRAM) design at the 7 nm technology node, spanning from device-level characteristics to system-level power performance area (PPA). At the device level, we show the tradeoffs among the write current, error rate, and time, based on mircomagnetic simulations. …
