Design of a Nanoscale, CMOS-Integrable, Thermal-Guiding Structure for Boolean-Logic and Neuromorphic Computation

Desmond Loke*, Jonathan M. Skelton, Tow Chong Chong, Stephen R. Elliott

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

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    Abstract

    One of the requirements for achieving faster CMOS electronics is to mitigate the unacceptably large chip areas required to steer heat away from or, more recently, toward the critical nodes of state-of-the-art devices. Thermal-guiding (TG) structures can efficiently direct heat by "meta-materials" engineering; however, some key aspects of the behavior of these systems are not fully understood. Here, we demonstrate control of the thermal-diffusion properties of TG structures by using nanometer-scale, CMOS-integrable, graphene-on-silica stacked materials through finite-element-methods simulations. It has been shown that it is possible to implement novel, controllable, thermally based Boolean-logic and spike-timing-dependent plasticity operations for advanced (neuromorphic) computing applications using such thermal-guide architectures.

    Original languageEnglish
    Pages (from-to)34530-34536
    Number of pages7
    JournalACS Applied Materials and Interfaces
    Volume8
    Issue number50
    Early online date18 Nov 2016
    DOIs
    Publication statusPublished - 21 Dec 2016

    Keywords

    • computing
    • FEM simulations
    • metamaterials
    • switches
    • thermal control

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