An Efficient Electrostatic Discharge Analytical Model for a Local Bottom-Gate Carbon Nanotube Field-Effect Transistor
In the post-Moore era, carbon nanotube field-effect transistors (CNTFETs) are a promising alternative to complementary metal-oxide-semiconductor (CMOS) technology at and below the 5 nm node. Compact models bridge circuit design and device physics, yet the electrostatic discharge (ESD) behavior of CNTFETs remains insufficiently captured. Focusing on the local bottom-gate (LBG) CNTFET structure, which offers enhanced gate control due to its bottom-gate configuration, this paper investigates three dominant ESD-triggering mechanisms—thermionic current, tunneling leakage current, and thermal failure breakdown. Then, a hybrid compact–behavioral ESD model for CNTFETs is established. After theoretical derivation and comparison with test results, the model parameters are optimized through fitting. The simulation results exhibit excellent agreement with CNTFET measurements, particularly capturing the Human Body Model (HBM) pre-charge threshold phenomenon at 72 V and accurately predicting the subsequent voltage collapse behavior. This validates the accuracy and effectiveness of the model, laying a theoretical and experimental foundation for further construction of carbon-based standard-cell and I/O libraries.
Authors
- Jianhua Jiang (ORCID: https://orcid.org/0000-0002-9149-2922)
- Cheng–Ying Chen (ORCID: https://orcid.org/0000-0002-0802-6681)
- Yuyan Zhang (ORCID: https://orcid.org/0009-0007-5810-328X)
- Quan Gan (ORCID: https://orcid.org/0000-0003-3703-5453)
- Xuefang Xiao
- Zhifeng Chen
- Ying Gao
- Weiyi Zheng
Institutions
- New York City Fire Department (US)
- Peking University (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Electronic Materials
- Published
- 2025-10-23
- DOI
- https://doi.org/10.3390/electronicmat6040017
- Primary Topic
- Carbon Nanotubes in Composites
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province