0
Research Papers

Computational Monolayer for Tertiary Nanoparticles Using Supercomputer

[+] Author and Article Information
Kyungdeok Jang

Department of Metallurgical and Materials Engineering,
The University of Texas at El Paso,
El Paso, TX 79968
e-mail: playzanggu@gmail.com

Nubia Zuverza

Department of Metallurgical and Materials Engineering,
The University of Texas at El Paso,
El Paso, TX 79968
e-mail: nzuverza@miners.utep.edu

Tae Eui Jeong

Department of Nano Convergence Engineering,
Seokyeong University,
Seoul, 136-704, Korea
e-mail: tejeong@skuniv.ac.kr

Sung Suk Kim

Department of Computer Science,
Seokyeong University,
Seoul 136-704, Korea
e-mail: sskim03@skuniv.ac.kr

Nam Soo Kim

Department of Metallurgical and Materials Engineering,
The University of Texas at El Paso,
El Paso, TX 79968
e-mail: nkim@utep.edu

1Corresponding author.

Contributed by the Electronic and Photonic Packaging Division of ASME for publication in the JOURNAL OF ELECTRONIC PACKAGING. Manuscript received January 5, 2012; final manuscript received December 29, 2012; published online March 26, 2013. Assoc. Editor: Kyoung-sik Moon.

J. Electron. Packag 135(1), 011003 (Mar 26, 2013) (6 pages) Paper No: EP-12-1004; doi: 10.1115/1.4023527 History: Received January 05, 2012; Revised December 29, 2012

Computer simulation is a practical approach for the accurate study of nanosized materials. In order to produce conductive nano-inks for microelectrodes, we need to simulate different nanoparticles (NPs)’ arrangements to maximize their packing. Even though modeling can be performed on desktop computers using binary packing, this is a time consuming process that may not provide optimal results for practical applications. In this study, we developed a simulation program for a supercomputer to obtain precise results from tertiary packing while reducing the simulation time. The simulation of nanoparticles' packing consists of three different sized particles resulting in a high packing factor of 93.44%. Therefore, the optimal sizes and volumes of particles required for nano-inks with various viscosities can be predetermined. Furthermore, a wide range of applications can be derived such as finding ideal ratios of particles or inks for different mixtures.

FIGURES IN THIS ARTICLE
<>
Copyright © 2013 by ASME
Your Session has timed out. Please sign back in to continue.

References

Kim, N. S., Han, K. N., and Church, K. H., 2007, “Direct Writing Technology for 21st Century Industries—Focus on Micro-Dispensing Deposition Write Technology,” Transactions of the KSMTE Spring Conference, 2007, pp. 511–515.
Satake, S. I., Sorimachi, G., Kanai, T., Taniguchi, J., and Unno, N., 2010, “Three Dimensional Measurements of Photo-Curing Process With Photo-Curable Resin for UV-Nanoimprint by Micro-Digital-Holographic-PTV,” ASME J. Electron. Packag., 132, 031003. [CrossRef]
Kim, N. S., Amert, A. K., Woessner, S. M., Decker, S., Kang, S. M., and Han, K. N., 2007, “Effect of Metal Powder Packing on the Conductivity of Nanometal Ink,” J. Nanosci. Nanotechnol, 7(11), pp. 3902–3905. [CrossRef] [PubMed]
Amert, A. K., Oh, D. H., and Kim, N. S., 2010, “A Simulation and Experimental Study on Packing on Nano-Inks to Attain Better Conductivity,” J. Appl. Phys., 108, pp. 25–30. [CrossRef]
Zhang, Z. P., Liu, L. F., Yuan, Y. D., and Yu, A. B., Yu, 2001, “A Simulation Study of the Effects of Dynamic Variables on the Packing of Spheres,” Powder Technol., 116, pp. 23–32. [CrossRef]
Chenf, Y. F., Guo, S. J., and Lai, H. Y., 2000, “Dynamic Simulation of Random Packing of Spherical Particles,” Powder Technol., 107, pp. 123–130. [CrossRef]
Zou, R. P., Xu, J. Q., Feng, C. L., Yu, A. B., Johnston, S., and Standish, N., 2003, “Packing of Multi-Sized Mixtures of Wet Coarse Spheres,” Powder Technol., 130, pp. 77–83. [CrossRef]
Sobolev, K., and Amirjanov, A., 2004, “A Simulation Model of the Dense Packing of Particulate Materials,” Adv. Powder Technol., 15(3), pp. 365–376. [CrossRef]
Sobolev, K., and Amirjanov, A., 2004, “The Development of a Simulation Model of the Dense Packing of Large Particulate Assemblies,” Powder Technol., 141, pp. 155–160. [CrossRef]
Robinson, D. A., and Friedman, S. P., 2005, “Electrical Conductivity and Dielectric Permittivity of Sphere Packing: Measurements and Modeling of Cubic Lattices, Randomly Packed Monosize Spheres and Multi-Size Mixtures,” Physica A, 358(4), pp. 447–465. [CrossRef]
Gan, M., Gopinathan, N., Jia, X., and Williams, R. A., 2004, “Predicting Packing Characteristics of Particles of Arbitrary Shapes,” KONA, 22, pp. 82–93.
Brouwers, H. J. H., 2006, “Particle-Size Distribution and Packing Fraction of Geometric Random,” Physical Rev. E, 74, 031309. [CrossRef]
Yang, R. Y., Zou, R. P., Dong, K. J., An, X. Z., and Yu, A., 2007, “Simulation of the Packing of Cohesive Particles,” Comput. Phys. Commun., 177, pp. 206–209. [CrossRef]
Siiria, S., and Yliruusi, J., 2007, “Particle Packing Simulation Based on Newtonian Mechanics,” Powder Technol., 174, pp. 82–92. [CrossRef]
Zhang, Z. P., Liu, L. F., Yuan, Y. D., and Yu, A. B., 2001, “A Simulation Study of the Effects of Dynamic Variables on the Packing of Spheres,” Powder Technol., 116, pp. 23–32. [CrossRef]
Riyadh, A. R., and Mustafa, A., 2007, “Simulation of Random Packing of Polydisperse Paricle,” Powder Technol., 176, pp. 47–55. [CrossRef]
Smith, L. N., and Midha, P. S., 1997, “Computer Simulation of Morphology and Packing Behavior of Irregular Particles, for Predicting Apparent Powder Densities,” Comput. Mater. Sci., 7, pp. 377–383. [CrossRef]
Chen, Z., Gibilaro, L. G., and Jand, N., 2003, “Particle Packing Constraints in Fluid–Particle System Simulation,” Comput. Chem. Eng., 29(5), pp. 681–687. [CrossRef]
Latham, J. P., Munjiza, A., and Lu, Y., 2002, “On the Prediction of Void Porosity and Packing of Rock Particulates,” Powder Technol., 125(1), pp. 10–27. [CrossRef]
Lochmann, K., Oger, L., and Stoyan, D., 2006, “Statistical Analysis of Random Sphere Packings With Variable Radius Distribution,” Solid State Sci., 8(12), pp. 1397–1413. [CrossRef]
Kim, J. C., Martin, D. M., and Lim, C. S., 2002, “Effect of Rearrangement on Simulated Particle Packing,” Powder Technol., 126(3), pp. 211–216. [CrossRef]
Jia, X., and Williams, R. A., 2001, “A Packing Algorithm for Particles of Arbitrary Shapes,” Powder Technol., 120(3), pp. 175–186. [CrossRef]
Jung, H. K., Ko, H., Kim, S. S., “Large Amounts of Data Processing by Using Supercomputer,” Trans. KIIT, pp. 487–491.

Figures

Grahic Jump Location
Fig. 2

Skeleton of computing system of the supercomputer simulator

Grahic Jump Location
Fig. 3

Algorithm of supercomputers simulating system

Grahic Jump Location
Fig. 4

Comparison of the number of overlapping particles on boundary according to the number of divided space

Grahic Jump Location
Fig. 5

Comparison of supercomputer and desktop data (repeating count: 1000, number of CPU: desktop 1, supercomputer 2)

Grahic Jump Location
Fig. 6

Changes in packing factor according to the repeating count (use 6 CPU)

Grahic Jump Location
Fig. 7

Packing factor according to the number of CPU's

Grahic Jump Location
Fig. 8

Simulation of tertiary packing

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In