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NanomaterialsBoxuan Gu and David McQuilling
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What are they? Nano = 10-9 or one billionth in size
Materials with dimensions and tolerances in
the range of 100 nm to 0.1 nm Metals, ceramics, polymeric materials, or
composite materials
One nanometer spans 3-5 atoms lined up in a
row Human hair is five orders of magnitude larger
than nanomaterials
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Nanomaterial Composition Comprised of many different elements
such as carbons and metals
Combinations of elements can make upnanomaterial grains such as titaniumcarbide and zinc sulfide
Allows construction of new materialssuch as C60 (Bucky Balls or fullerenes)and nanotubes
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How they are made Clay/polymer nanocomposites can be made
by subjecting clay to ion exchange and then
mixing it with polymer melts Fullerenes can be made by vaporizing carbon
within a gas medium
Current carbon fullerenes are in the gaseousphase although samples of solid state
fullerenes have been found in nature
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Bucky Ball properties Arranged in pentagons and hexagons A one atom thick seperation of two spaces; inside
the ball and outside Highest tensile strength of any known 2D structure or
element, including cross-section of diamonds whichhave the highest tensile strength of all known 3Dstructures (which is also a formation of carbonatoms)
Also has the highest packing density of all knownstructures (including diamonds) Impenetrable to all elements under normal
circumstances, even a helium atom with an energy of5eV (electron Volt)
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Bucky Ball properties cont. Even though each carbon atom is only bonded with
three other carbons (they are mosthappy with fourbonds) in a fullerene, dangling a single carbon atom
next to the structure will not affect the structure, i.e.the bond made with the dangling carbon is notstrong enough to break the structure of the fullerene
No other elementhas such wonderful properties ascarbon which allows costs to be relatively cheap;after all its just carbon and carbon is everywhere
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Buckminsterfullerene uses Due to their extremely resilient and sturdy nature bucky
balls are debated for use in combat armor Bucky balls have been shown to be impervious to lasers,
allowing for defenses from future warfare Bucky balls have also been shown to be useful at fighting
the HIV virus that leads to AIDS Researchers Kenyan and Wudl found that water soluble
derivates of C60 inhibit the HIV-1 protease, the enzymeresponsible for the development of the virus
Elements can be bonded with the bucky ball to createmore diverse materials including superconductors andinsulators
Can be used to fashion nanotubes
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Bucky Ball (C60) C240 colliding with C60 at
300 eV (Kinetic energy)
Bucky Balls
http://www.pa.msu.edu/cmp/csc/simindex.html
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Nanotube properties Superior stiffness and strength to all other materials Extraordinary electric properties Reported to be thermally stable in a vacuum up to
2800 degrees Centigrade (and we fret over CPUtemps over 50o C)
Capacity to carry an electric current 1000 timesbetter than copper wires
Twice the thermal conductivity of diamonds Pressing or stretching nanotubes can change their
electrical properties by changing the quantum statesof the electrons in the carbon bonds
They are either conducting or semi-conductingdepending on the their structure
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Nanotube uses Can be used for containers to hold various
materials on the nano-scale level
Due to their exceptional electrical properties,nanotubes have a potential for use ineveryday electronics such as televisions andcomputers to more complex uses likeaerospace materials and circuits
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Nanotubes
Switching nanotube-based memoryCarbon based nanotubes
http://www.pa.msu.edu/cmp/csc/simindex.html
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Applications of
Nanotechnology Next-generation computer chips
Ultra-high purity materials, enhanced thermalconductivity and longer lasting nanocrystalline
materials Kinetic Energy penetrators (DoD weapon)
Nanocrystalline tungsten heavy alloy to replaceradioactive depleted uranium
Better insulation materials Create foam-like structures called aerogels from
nanocrystalline materials Porous and extremely lightweight, can hold up to
100 times their weight
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More applications Improved HDTV and LCD monitors
Nanocrystalline selenide, zinc sulfide, cadmiumsulfide, and lead telluride to replace current
phosphors Cheaper and more durable
Harder and more durable cutting materials Tungsten carbide, tantalum carbide, and titanium
carbide Much more wear-resistant and corrosion-resistant
than conventional materials Reduces time needed to manufacture parts,
cheaper manufacturing
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Even more applications High power magnets
Nanocrystalline yttrium-samarium-cobalt grainspossess unusually large surface area compared to
traditional magnet materials Allows for muchhigher magnetization values Possibility for quieter submarines, ultra-sensitive
analyzing devices, magnetic resonance imaging(MRI) or automobile alternators to name a few
Pollution clean up materials Engineered to be chemically reactive to carbon
monoxide and nitrous oxide More efficient pollution controls and cleanup
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Still more applications Greater fuel efficiency for cars
Improved spark plug materials, railplug Stronger bio-based plastics
Bio-based plastics made from plant oils lacksufficient structural strength to be useful
Merge nanomaterials such as clays, fibers andtubes with bio-based plastics to enhance strengthand durability
Allows for stronger, more environment friendlymaterials to construct cars, space shuttles and amyriad of other products
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Applications wrapup Higher quality medical implants
Current micro-scale implants arent porous enough for tissueto penetrate and adapt to
Nano-scale materials not only enhance durability andstrength of implants but also allow tissue cells to adapt morereadily
Home pregnancy tests Current tests such as First Response use gold nanoparticles
in conjunction with micro-meter sized latex particles
Derived with antibodies to the human chorionicgonadotrophin hormone that is released by pregnant women The antibodies react with the hormone in urine and clump
together and show up pink due to the nanoparticlesplamson resonance absortion qualities
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Modeling and Simulation ofNanostructured Materials and
Systems
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Preface Each distinct age in the development of
humankind has been associated with
advances in materials technology.
Historians have linked key technological and
societal events with the materials technology
that was prevalent during the stone age,bronze age, and so forth.
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Significant events In materials 1665 - Robert Hooke material microstructure
1808 - John Dalton atomic theory
1824 - Portland cement 1839 - Vulcanization
1856 - Large-scale steel production
1869 - Mendeleev and Meyer Periodic Tableof the Chemical Elements
1886 - Aluminum
1900 - Max Planck . quantum mechanics
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Cont. 1909 - Bakelite
1921 - A. A. Griffith . fracture strength
1928 - Staudinger polymers (small moleculesthat link to form chains)
1955 - Synthetic diamond
1970 - Optical fibers
1985 - First university initiatives attemptcomputational materials design
1985 - Bucky balls (C60) discovered at RiceUniversity
1991 - Carbon nanotubes discovered by Sumio
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Why we need Computational
Materials?Traditionally, research institutions have relied on a
discipline-oriented approach to material
development and design with new materials.
It is recognized, however, that within the scope of
materials and structures research, the breadth of
length and time scales may range more than 12
orders of
magnitude, and different scientific and engineering
disciplines are involved at each level.
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To help address this wide-ranging
interdisciplinary research, Computational
Materials has been formulated with the specificgoal of exploiting the tremendous physical and
mechanical properties of new nano-materials b
understanding materials at atomic, molecular,and supramolecular levels.
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Computational Materials at LaRC draws
from physics and chemistry, but focuses
on constitutive descriptions of materials
that are useful in formulating
macroscopic models of material
performance.
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Benefit of Computational
materials First, it encourages a reduced reliance on costly
trial and error, or serendipity, of the Edisonian
approach to materials research. Second, it increases the confidence that new
materials will possess the desired properties whenscaled up from the laboratory level, so that lead-
time for the introduction of new technologies isreduced.
Third, the Computational Materials approachlowers the likelihood of conservative orcompromised designs that might have resultedfrom reliance on less-than-perfect materials.
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Schematic illustration of relationships between time
and length scales for the multi-scale simulation
methodology.
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Cont.
The starting point is a quantum
description of materials; this is carried
forward to an atomistic scale for initial
model development.
Models at this scale are based on
molecular mechanics or moleculardynamics.
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Cont. At the next scale, the models can incorporate
micro-scale features and simplified
constitutive relationships.
Further progress up, the scale leads to the
meso or in-between levels that rely on
combinations of micromechanics andwellestablished theories such as elasticity.
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Cont. The last step towards engineering-level
performance is to move from mechanics of
materials to structural mechanics by using
methods that rely on empirical
data,constitutive models, and fundamental
mechanics.
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Nanostructured Materials The origins of focused research into
nanostructured materials can be traced back to a
seminal lecture given by Richard Feynman in1959[1].
In this lecture, he proposed an approach to the
problem of manipulating and controlling things on a
small scale. The scale he referred to was not themicroscopic scale that was familiar to scientists of
the day but the unexplored atomistic scale.
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The nanostructured materials based on
carbon nanotubes and related carbon
structures are of current interest for much ofthe materials community.
More broadly then, nanotechnology presents
the vision of working at the molecular level,atom by atom, to create large structures with
fundamentally new molecular organization.
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Simluation methods
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Atomistic, Molecular
Methods The approach taken by the Computational
Materials is formulation of a set of integrated
predictive models that bridge the time andlength scales associated with material
behavior from the nano through the meso
scale.
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At the atomistic or molecular level, the reliance is
on molecular mechanics,
molecular dynamics, and coarse-grained, Monte-Carlo simulation.
Molecular models encompassing thousands and
perhaps millions of atoms can be solved by these
methods and used to predict fundamental,
molecular level material behavior. The methods
are both static and dynamic.
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Molecular dynamics simulations generate
information at the nano-level, including
atomic positions and velocities.
The conversion of this information to
macroscopic observables such as pressure,
energy, heat capacities, etc., requiresstatistical mechanics.
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An experiment is usually made on a macroscopic
sample that contains an extremely large number
of atoms or molecules, representing anenormous number of conformations.
In statistical mechanics, averages corresponding
to experimental measurements are defined in
terms of ensemble averages.
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For example
!
!M
i
iVMV
1
*/1
where Mis the number of configurations in the molecular
dynamics trajectory and Viis the potential energy of each
configuration.
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j
M
j
N
i
ii
ivv
m
M
K ! !
!1 1 2
1
where Mis the number of configurations in the simulation, Nis
the number of atoms in the system, miis the mass of the
particle iand viis the velocity of particle i.
To ensure a proper average, a molecular dynamics simulation
must account for a large number of representative
conformations.
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By using Newtons second law to calculate atrajectory, one only needs the initial positions of
the atoms, an initial distribution of velocities andthe acceleration, which is determined by thegradient of the potential energy function.
The equations of motion are deterministic; i.e.,the positions and the velocities at time zerodetermine the positions and velocities at all othertimes, t. In some systems, the initial positionscan be obtained from experimentally determinedstructures.
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In a molecular dynamics simulation, the timedependent behavior of the molecular system is
obtained by integrating Newtons equations ofmotion.
The result of the simulation is a time series ofconformations or the path followed by each atom.
Most molecular dynamics simulations areperformed under conditions of constant number ofatoms, volume, and energy (N,V,E) or constantnumber of atoms, temperature, and pressure(N,T,P) to better simulate experimental conditions.
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Basic steps in the MD
simulation
1. Establish initial coordinates.
2. Minimize the structure.
3. Assign initial velocities.
4. Establish heating dynamics.
5. Perform equilibration dynamics.
6. Rescale the velocities and check if thetemperature is correct.
7. Perform dynamic analysis of trajectories.
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Monte Carlo Simulation Although molecular dynamics methods
provide the kind of detail necessary to
resolve molecular structure and localizedinteractions, this fidelity comes with a price.
Namely, both the size and time scales of the
model are limited by numerical andcomputational boundaries.
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To help overcome these limitations,coarse-
grained methods are available that represent
molecular chains as simpler, bead-spring models. Coarse-grain models are often linked to Monte
Carlo (MC) simulations to provide a timely
solution.
The MC method is used to simulate stochastic
events and provide statistical approaches to
numerical Integration.
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There are three characteristic steps in the MCsimulation that are given as follows.
1. Translate the physical problem into ananalogous probabilistic or statistical model.
2. Solve the probabilistic model by a numerical
sampling experiment.3. Analyze the resultant data by usingstatistical methods.
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Continum Methods Despite the importance of understanding the
molecular structure and nature of materials,
at some level in the multi-scale analysis thebehaviour of collections of molecules and
atoms can be homogenized.
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At this level, the continuum level, the observed
macroscopic behaviour is explained by
disregarding thediscrete atomistic and molecular structure and
assuming that the material is continuously
distributed throughout its volume.
The continuum material is assumed to have an
average density and can be subjected to body
forces such as gravity and surface forces such as
the contact between two bodies.
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The continuum can be assumed to obey severalfundamental laws.
The first, continuity, is derived from theconservation of mass.
The second, equilibrium, is derived frommomentum considerations and Newtons second
law. The third, the moment of momentum principle, is
based on the model that the time rate of changeof angular momentum with respect to an arbitrarypoint is equal to the resultant moment.
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These laws provide the basis for the continuum
model and must be coupled with the appropriate
constitutive equations and equations of state toprovide all the equations necessary for solving a
continuum problem.
The state of the continuum system is described by
several thermodynamic and kinematic statevariables.
The equations of state provide the relationships
between the non-independent state variables.
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The continuum method relates the
deformation of a continuous medium to the
external forces acting on the medium and theresulting internal stress and strain.
Computational approaches range from
simple closed-form analytical expressions tomicromechanics to complex structural
mechanics calculations basedon beam and
shell theory.
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The continuum-mechanics methods rely on
describing the geometry, (I.e.physical
model), and must have a constitutiverelationship to achieve a solution.
For a displacement based form of
continuum solution, the principle of virtualwork is assumed valid.
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In general, this is given as:
jjj
S
jj
V
j
V
ijij
uFdSuTdVuP
dVW
HHH
HIWH
!
!
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where Wis the virtual work which is the work done by
imaginary or virtual displacements, is the strain, is the
stress, Pis the body force, u is the virtual displacement, T
is the tractions and Fis the point forces. The symbol is thevariational operator designating the virtual quantity.
For a continuum system, a necessary and sufficient
condition for equilibrium is that the virtual work done by
sum of the external forces and internal forces vanish forany virtual displacement.
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Software for Nanomaterials
SS
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BOSS-Biochemical and OrganicSimulation System
The B O S S program performs (a)Monte Carlo (MC) statistical mechanics
simulations for solutes in a periodicsolvent box, in a solvent cluster, or in adielectric continuum including the gas
phase, and (b) standard energyminimizations, normal mode analysis,and conformational searching.
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XMakemol
XMakemol is a mouse-based program,written using the LessTifwidget set, for
viewing and manipulating atomic andother chemical systems. It reads XYZinput and renders atoms, bonds and
hydrogen bonds.
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Features Animating multiple frame files
Interactive measurement of bond lengths,
bond angles and torsion angles Control over atom/bond sizes
Exporting to XPM, Encapsulated PostScriptand Fig formats
Toggling the visibility of groups of atoms
Editing the positions of subsets of atoms
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A watermolecule withvectors alongthe principalaxes
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As above,
withlightingturned off
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Candidate
structure for theH2O(20) globalminimum
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Buckminster
Fullerene
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Amsterdam Density Functional
(ADF) package The Amsterdam Density Functional (ADF)
package is software for first-principles
electronic structure calculations. ADF isused by academic and industrialresearchers worldwide in such diverse fields
as pharmacochemistry and materialsscience
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It is currently particularly popular in theresearch areas of:
homogeneous and heterogeneous catalysis
inorganic chemistry
heavy element chemistry
various types of spectroscopy
biochemistry
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ARP/wARP
ARP/wARP is a package for automated protein
model building and structure refinement. It isbased on a unified approach to the structuresolution process by combining electron densityinterpretation using the concept of the hybrid
model, pattern recognition in an electron densitymap and maximum likelihood model parameterrefinement.
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The ARP/wARP suite is under continuousdevelopment. The present release, Version 6.0,
can be used in the following ways:1. Automatic tracing of the density map and model
building. This includes the refinement of MRsolutions and the improvement of MAD and
M(S)IR(AS) phases via map interpretation2. Free atoms density modification
3. Building of the solvent structure
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Chemsuite - A suite designed for
chemistry on LinuxChemsuite is composed by several program:
Chem2D: A 2D molecular drawer.
Molcalc: A molecular weight calculator ChemModel3D: Molecular 3D modeler
ChemIR: An infrared spectra processor.
It can read, process, export and print Perkin
Elmerspectra. ChemNMR: 1D NMR Processor
ChemMC: Monte carlo Simulator and Integrator
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General Atomic and Molecular
Electronic Structure System (GAMESS) GAMESS is a program for ab initio quantum
chemistry. Briefly, GAMESS can compute
SCF wavefunctions ranging from RHF,ROHF, UHF, GVB, and MCSCF. Correlationcorrections to these SCF wavefunctionsinclude Configuration Interaction, second
order perturbation theory, and Coupled-Cluster approaches, as well as the DensityFunctional Theory approximation.
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Useful sitehttp://www.linuxlinks.com/Software/Scien
tific/Chemistry/