Computational Nanotechnology

Computational Nanotechnology: Modeling and Applications with MATLAB®

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  • Includes numerous MATLAB codes and mathematical formulae that can be used in computational nanotechnology
  • Covers computational methods associated with molecular magnetism and semiconductor quantum dots, as well as modeling of nanoparticles
  • Deals with micromagnetics and finite element analysis of nano-sized magnetic materials
  • Addresses system-level modeling of N/MEMS and numerical integrator for continuum equations of surface growth and erosion
  • Explores configuration optimizations and photophysics simulations of single-wall nanotubes of carbon, silicon-carbide, and carbon-nitride
  • Presents MATLAB applications in behavioral analysis of systems and in nanoscale transistor modeling


Applications of nanotechnology continue to fuel significant innovations in areas ranging from electronics, microcomputing, and biotechnology to medicine, consumer supplies, aerospace, and energy production. As progress in nanoscale science and engineering leads to the continued development of advanced materials and new devices, improved methods of modeling and simulation are required to achieve a more robust quantitative understanding of matter at the nanoscale.

Computational Nanotechnology: Modeling and Applications with MATLAB® provides expert insights into current and emerging methods, opportunities, and challenges associated with the computational techniques involved in nanoscale research. Written by, and for, those working in the interdisciplinary fields that comprise nanotechnology—including engineering, physics, chemistry, biology, and medicine—this book covers a broad spectrum of technical information, research ideas, and practical knowledge. It presents an introduction to computational methods in nanotechnology, including a closer look at the theory and modeling of two important nanoscale systems: molecular magnets and semiconductor quantum dots.

Topics covered include:

  • Modeling of nanoparticles and complex nano and MEMS systems
  • Theory associated with micromagnetics
  • Surface modeling of thin films
  • Computational techniques used to validate hypotheses that may not be accessible through traditional experimentation
  • Simulation methods for various nanotubes and modeling of carbon nanotube and silicon nanowire transistors

In regard to applications of computational nanotechnology in biology, contributors describe tracking of nanoscale structures in cells, effects of various forces on cellular behavior, and use of protein-coated gold nanoparticles to better understand protein-associated nanomaterials. Emphasizing the importance of MATLAB for biological simulations in nanomedicine, this wide-ranging survey of computational nanotechnology concludes by discussing future directions in the field, highlighting the importance of the algorithms, modeling software, and computational tools in the development of efficient nanoscale systems.

Table of Contents

Introduction to Computational Methods in Nanotechnology, O. Ciftja and S.M. Musa

Computational Modeling of Nanoparticles, U. Riaz and S.M. Ashraf

Micromagnetics: Finite Element Analysis of Nano- Sized Magnetic Materials Using MATLAB®, S.-L. Chin and T. Flack

System-Level Modeling of N/MEMS, J.V. Clark

Numerical Integrator for Continuum Equations of Surface Growth and Erosion, A. Keller, S. Facsko, and R. Cuerno

Configuration Optimizations and Photophysics Simulations of Single-Wall Nanotubes of Carbon, Silicon-Carbide, and Carbon-Nitride, W.-D. Cheng, C.-S. Lin, G.-L. Chai, and S.-P. Huang

MATLAB® Applications in Behavior Analysis of Systems Consisting of Carbon Nanotubes through Molecular Dynamics Simulation, M. Foroutan and S. Khoee

Device and Circuit Modeling of Nano-CMOS, M.L.P. Tan, D.C.Y. Chek, and V.K. Arora

Computational and Experimental Approaches to Cellular and Subcellular Tracking at the Nanoscale, Z. Al-Rekabi, D. Tremblay, K. Haase, R.L. Leask, and A.E. Pelling

Computational Simulations of Nanoindentation and Nanoscratch, C.-D. Wu, T.-H. Fang, and J.-F. Lin

Modeling of Reversible Protein Conjugation on Nanoscale Surface, K. Yokoyama

Computational Technology in Nanomedicine, V. Wiwanitkit

Future Directions: Opportunities and Challenges, G.C. Giakos


Appendix A: Material and Physical Constants

Appendix B: Symbols and Formulas

Appendix C: MATLAB®

Author Bio(s)

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