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(r) 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.
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