Composite metal gates: Suppressing self-heating and boosting temperature resilience in nano tube (NT) FETs
Vaibhav PURWAR, Manish TIWARI
Abstract. This paper covers the effects of a composite metal gate and high-k dielectric material on the self-heating and low/high-temperature behavior of a nano tube field effect transistor (NTFET). The composite gate material comprises tungsten disilicide and zinc in a 1:1 ratio, and hafnium oxide is used as the high-k dielectric material. The device behaviour has been evaluated for temperatures ranging from 250 K to 400 K. The results show a significant reduction in lattice temperature increment within the channel region; such behaviour reveals a reduction in thermal resistance and an improvement in the heat dissipation capability of the proposed device. This advantage of fast heat dissipation mitigates the self-heating effects. Additionally, the composite gate metal provides enhanced electrostatic control over the channel and suppresses short-channel effects such as drain-induced barrier lowering. At room temperature (300 K), the proposed device enhances the ON-state current by 49.9% and shows a reduction in leakage current by 66.1% in comparison to a conventional nanowire transistor. Mentioned parameter improvement improves power efficiency and sharpness of switching characteristic. Furthermore, results reflect that across the entire temperature range, the proposed device structure outperforms in comparision with nano wire FET. The device simulation has been done on Silvaco Atlas TCAD 3D simulator.
Keywords
Lattice Temperature, Trans-Conductance, Nanowire, Composite-Metal, High-K, Self-Heating
Published online 8/15/2026, 8 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Vaibhav PURWAR, Manish TIWARI, Composite metal gates: Suppressing self-heating and boosting temperature resilience in nano tube (NT) FETs, Materials Research Proceedings, Vol. 71, pp 197-204, 2026
DOI: https://doi.org/10.21741/97816449042312-27
The article was published as article 27 of the book AI-Driven Innovations in Mechanical, Manufacturing, and Energy Engineering
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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