2008
DOI: 10.1021/nl0730965
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A 1 GHz Integrated Circuit with Carbon Nanotube Interconnects and Silicon Transistors

Abstract: Due to their excellent electrical properties, metallic carbon nanotubes are promising materials for interconnect wires in future integrated circuits. Simulations have shown that the use of metallic carbon nanotube interconnects could yield more energy efficient and faster integrated circuits. The next step is to build an experimental prototype integrated circuit using carbon nanotube interconnects operating at high speed. Here, we report the fabrication of the first stand-alone integrated circuit combining sil… Show more

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Cited by 180 publications
(105 citation statements)
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“…Despite promising demonstrations of the integration of CNT devices into CMOS systems, [14][15][16] In this study, we developed an individually addressable array of 1024 CNT electronic nanosensors, each consisting of only one single or very few CNTs as sensing element. We focused on the development of a reliable fabrication process based on the floating-electrode DEP method to directly integrate the CNT devices into a CMOS system without the need to transfer them.…”
Section: Europe Pmc Funders Author Manuscriptsmentioning
confidence: 99%
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“…Despite promising demonstrations of the integration of CNT devices into CMOS systems, [14][15][16] In this study, we developed an individually addressable array of 1024 CNT electronic nanosensors, each consisting of only one single or very few CNTs as sensing element. We focused on the development of a reliable fabrication process based on the floating-electrode DEP method to directly integrate the CNT devices into a CMOS system without the need to transfer them.…”
Section: Europe Pmc Funders Author Manuscriptsmentioning
confidence: 99%
“…Additionally, the integration of an array of sensors with differently functionalized devices or graded sensitivity will offer the possibility to multiplex sensor signals or to achieve a larger dynamic range. The use of an array will also offer the possibility to detect and select devices that have been functionalized through low-yield techniques, such as point functionalization.[11] Finally, a dense spatial integration of many sensors reduces the detection volume and external interference and even allows for spatially resolved detection of low-concentration analytes.[12] The most suitable way for monolithic integration of multiple nanoscale devices in arrays is the use of complementary-metal-oxide-semiconductor (CMOS) technology, as it enables the direct integration of the transducers with readout and amplification electronics in a dedicated microsystem.[13] However, a CMOS approach also introduces restrictions in the choice of materials and fabrication process steps (e.g., temperature limitations), as CMOS compatibility has to be ensured.Despite promising demonstrations of the integration of CNT devices into CMOS systems, [14][15][16] In this study, we developed an individually addressable array of 1024 CNT electronic nanosensors, each consisting of only one single or very few CNTs as sensing element. We focused on the development of a reliable fabrication process based on the floating-electrode DEP method to directly integrate the CNT devices into a CMOS system without the need to transfer them.…”
mentioning
confidence: 99%
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“…Chiral selectivity, with respect to metallic or semiconducting behaviour, is important for optimal operation of many types of devices. Metallic CNTs are obviously well suited for applications requiring high current carrying capacity, such as electrical interconnects (Close, et al, 2008;Kreupl, et al, 2002); however, they may also be advantageous in devices requiring high sensitivity to small electrical potential changes, such as electro-chemical biological sensors (Claussen, et al, 2009). Field effect transistors utilizing semiconducting SWNT channels have been extensively studied and have been found to exhibit ballistic electronic transport even at room temperature operation (Franklin and Chen, 2010).…”
Section: Negative Polarity Electrical Biasmentioning
confidence: 99%