Emerging devices such as double gate carbon nanotube field effect transistors (DG CNTFETs) have opened up manifold possibilities for reconfigurable logic design. The thickness of gate oxide and the employment of inhomogeneous dielectrics over and under the carbon nanotubes (CNTs) impact the operation of DG CNTFETs. In this work, the dielectric constant and the thickness of the gate oxide are optimised to suppress the ambipolar conduction in CNTFETs. A multi-objective genetic algorithm-based approach is proposed to optimise these parameters. The contributions in this study are two-fold: firstly, a DG CNTFET is fabricated with the optimised parameters. By exploiting the ability to select the conduction behaviour using a second gate in the fabricated DG CNTFETs, the device is electrostatically programmed to behave as an n or p-type CNTFET. Secondly, a one instruction set computer is simulated with the optimised model of DG CNTFET. A universal static logic cell which implements 16 logic functions, a D-Latch and a D-FF were built with DG CNTFETs. The logic circuits with polarity-tunable DG CNTFETs outperform other logic structures. There is a 40% betterment in performance primarily due to the reduced number of logic levels and by 25% due to the reduced delay.

中文翻译：

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一台指令集计算机，具有优化的双栅极CNTFET极性可调模型

诸如双栅碳纳米管场效应晶体管（DG CNTFET）等新兴设备为可重构逻辑设计开辟了多种可能性。栅极氧化物的厚度以及碳纳米管（CNT）上方和下方的不均匀电介质的使用会影响DG CNTFET的操作。在这项工作中，对介电常数和栅极氧化物的厚度进行了优化，以抑制CNTFET中的双极性传导。提出了一种基于多目标遗传算法的方法来优化这些参数。该研究的贡献有两个方面：首先，利用优化的参数制造了DG CNTFET。通过利用已制造的DG CNTFET中的第二个栅极来选择导电行为的能力，该器件经过静电编程，可表现为n型或p型CNTFET。其次，利用DG CNTFET的优化模型对一台指令集计算机进行了仿真。具有DG CNTFET的通用静态逻辑单元可实现16种逻辑功能，并具有D-Latch和D-FF。具有极性可调DG CNTFET的逻辑电路优于其他逻辑结构。性能的提高主要归因于逻辑级别数量的减少40％和归因于延迟的减少25％。