Case Study: Hangzhou Dianzi University achieves validated self-heating-aware small-signal FinFET model with Keysight IC-CAP

Hangzhou Dianzi University Uses IC-CAP to Extract a Novel, Small-Signal Model for Bulk FinFETs

Hangzhou Dianzi University faced the challenge of accurately modeling self‑heating effects in bulk FinFETs—thermal phenomena that reduce on‑current and alter timing yet are not captured by conventional small‑signal models. To extract the novel compact model parameters that account for self‑heating, the researchers used Keysight’s IC‑CAP device‑modeling software.

Using Keysight IC‑CAP, the team implemented a parallel resistance–inductance thermal network and a new transfer‑gain model, extracting parameters via PEL/Python scripting and IC‑CAP’s random optimizer while measuring S‑parameters from 100 kHz to 50.2 GHz with Keysight E5072/E8363B network analyzers. The model was validated on a fabricated 4‑Fin N‑MOSFET (L = 16 nm) and showed excellent agreement with measured Y‑parameters up to 50.2 GHz; extracted values included Cgs = 11.45×10^−15 F, Cgd = 5.59×10^−15 F, Cds = 1.02×10^−15 F and Rsub ≈ 2.174×10^3 Ω, demonstrating accurate small‑signal prediction and efficient model generation using Keysight.

Hangzhou Dianzi University

Jun Liu

Professor