Temperature-Dependent Modeling and Performance Evaluation of Multi-Walled CNT and Single-Walled CNT as Global Interconnects
The influence of temperature on multi-walled carbon nanotube (MWCNT) interconnects have been studied. A temperature-dependent equivalent circuit model is presented for the impedance parameters of MWCNT bundle interconnects that captures various electron–phonon scattering mechanisms as a function of temperature. To estimate the performance of MWCNT bundle interconnects, the signal delay, power dissipation and power delay product (PDP) were simulated based on a temperature-dependent model that results in improvement in the delay, power and PDP estimation accuracy compared to the temperature-independent model. The results revealed that the power delay product of MWCNT bundle interconnects increases with increasing temperature from 200 K to 450 K for three different technology nodes, i.e., 32 nm, 22 nm and 16 nm, based upon a 1000-μm interconnect length. A similar analysis was performed for single-walled carbon nanotube (SWCNT) bundle interconnects and the results are compared with MWCNT bundle interconnects, indicating that the delay, power and power delay product (PDP) also increased with increasing temperature from 200 K to 450 K. The interconnects of the MWCNT bundle interconnects gave a better performance in terms of delay, power and PDP as compared to the SWCNT bundle interconnects.
KeywordsSWCNT MWCNT temperature-dependent impedance model VLSI
Unable to display preview. Download preview PDF.
- 1.W. Steinhogl, G. Schindler, G. Steinlesberger, M. Traving, and M. Engelhardt, J. Appl. Phys. 97, 023706/1 (2005).Google Scholar
- 2.A. Naeemi, R. Sarvari, and J.D. Meindl, Electron. Device Lett. 26, 84 (2005).Google Scholar
- 4.N. Srivastava and K. Banerjee, IEEE/ACM Intl. Conf. on ICCAD (2005), pp. 383–390.Google Scholar
- 6.Q. Jiang, Y. Zhao, X.Y. Lu, Q. Zhan, and Y.L. Zhou, J. Mater. Sci. Mater. Electron. doi:10.1007/s10854-006-7473-4.
- 11.E. Pop, D. Mann, J. Reifenberg, K. Goodson, and H. Dai, Technical Digest of IEEE International Electron Device Meeting 2005 IEDM (2005), pp. 254–256.Google Scholar
- 12.A.G. Chiarillo, IEEE Electron Devices Lett. 55, 97 (2010).Google Scholar
- 15.M. Sahoo and H. Rahaman, IEEE XXXIII International Scientific Conference Electronics and Nanotechnology (ELNANO) (2013), pp. 200–203.Google Scholar
- 18.M.K. Majumder, P.K. Das, and B.K. Kaushik, Microelectron. Reliab. 54(11), 2570 (2014).Google Scholar
- 19.M.K. Majumder, N.D. Pandya, B.K. Kaushik, and S.K. Manhas, IEEE Electron Device Lett. 33, 1080 (2012).Google Scholar
- 20.A. Srivastav, Y. Xu, and A.K. Sharma, J. Nanophotonics 4(1), 041690 (2010).Google Scholar
- 21.Y.G. Yoon, P. Delaney, and S.G. Louie, Phys. Rev. B 66(7), 073407/1 (2002).Google Scholar
- 22.ITRS, International Technology Roadmap for Semiconductor, Edition (2009), http://public.itrs.net. Accessed 4 Sept 2014
- 23.B. Kumar, B.K. Kaushik, and Y.S. Negi, J. Mater. Sci. Mater. Electron. 25, 1 (2014)Google Scholar
- 24.P.G. Collins and P. Avouris, Appl. Phys. A, Solids Surf. 74(3), 329 (2002)Google Scholar
- 25.J.F. Xu, H. Li, W.Y. Yin, J.F. Mao, and L.W. Li, IEICE Trans. Electron. E90-C, 179 (2007).Google Scholar
- 26.Predictive technology model [Online], www.ptm.asu.edu. Accessed 12 Jan 2015