1. Computational Nanotechnology
A preliminary proposal
N. Chandra
Department of Mechanical Engineering
Florida A&M and Florida State University
Colloborators
Proposed Areas
Nanoscale composites
Nanoscale interface Mechanics
Defect Engineering in CNTs
Hydrogen Storage
Parallel computing, Time extension algorithms
Professor Ashok Srinivasan, Dept. of Computer Science, FSU
Professor Leon van Dommelen, Dept. of Mechanical engineering, FAMU-FSU

2. Application of Carbon Nanotubes (CNTs) to
Nanocomposites and Hydrogen Storage
Approaches:
Molecular mechanics/dynamics simultions based on Tresoff-Brenner, Lennard-Jones and Morse Potentials
Application of thermal and mechanical loading (tension, compression, shear or combination thereof)
Evaluation of atomic level stresses and strains in any selected regions of interest
Large scale parallel computations (IBM-p processors)
Integration with non-linear finite element method(atomic to continuum multiscale modeling)
Pre/Post processing for single/multi-walled CNTs with selected diameters, chiralty, defect and functionalization
Team:
Faculty from mechanical engineering and computer science
Graduate students/post-doc from ME and CS
Significant Results:
Developed atomic level stress measures (3 types), and strain measures (new) and validated the mechanical response of CNTs
Determined mechanical properties of CNTs for various chiralities, with and without defects (Stone-Wales)
Evaluated the effect of a single and multiple interacting and non-interacting defects on the mechanical properties using stress/strain measures
Role of functionalization (attachment of radical, e.g. vinyl)on the in-situ mechanical properties of CNTs and their effect on evolution of defects
Identification of the optimal set of parameters that maximizes the hydrogen storage? Parameters include chirality and diameter of single/multiwalled tubes, temperature, pressure and geometrical defects
Parallelization of codes in IBM-p processors

3. Research Areas NanoScale Interfaces Nano-Composites Hydrogen Storage
Parallel Algorithms C a r b o n t u e s i d f V c - l m

4. Nano-Scale Interfaces
Issues:
How does the thermo-mechanical load transfer take place at nano-scale?
Can the macro theories (chemical bonding, mechanical serrations Kelly-Tyson) be applicable and if not how they should be modified?
What methods enhance strength, stiffness and fracture behavior of nanocomposites ?
Will any addition of short radicals to smooth surface enhance bonding? Will the nature of bonding be chemical, mechanical or electronic ?
How will the application of mechanical loading (tension, compression, shear or combination thereof) and thermal loading affect the load transfer?
What is the equivalence of thermal residual stresses at the nano-scale interfaces?
Functionalized CNT have higher stiffness.
High temperature deformation- defects are formed at lower strains (6% strain) .
Fracture occurs at lower strains in functionalized tubes.
Functionalization a possible mechanism to increase interface strength ?
Different numbers and groups of hydrocarbons were attached and tested in tension

5. Defect Engineering in CNTs
Background: Defects (missing atoms, rotated bonds, diameter/chiralty transition) arise during processing and loading. They are either deleterious or beneficial
Results
Variation of longitudinal stress in CNT for different position of interacting defect at 8% applied strain.
Issues:
Effects of defects on elastic and also inelastic properties (strength, stiffness and elastic to plastic transition and failure)
Role of chirality, diameters and location of single and multiple interacting/non-interacting defects and their effect on properties
Aligned defects in single/multi-walled CNTs and their effect on mechanical properties and hydrogen storage
Interaction of defects and functionalization in load transfer
Origin of defects as a function of combined thermal and mechanical load application
Variation of longitudinal strain along the CNT for different position of defects at 8% applied strain.

6. Hydrogen Storage Back ground: Issues:
Interest in hydrogen as a fuel has grown dramatically since However, hydrogen storage technologies must be significantly advanced if a hydrogen based energy system is to be established.
Nanotubes have been long heralded as potentially useful for hydrogen storage to meet energy densities at values of 6.5wt% set by DOE.
Issues:
Mechanism of hydrogen adsorption: is it a purely physical or chemical interaction or is it somewhere in between.
Optimize a given carbon adsorbent system: simulation of different parameters such as temperature, pressure, diameter and chirality.
Simulation of adsorption considering nanotube with defects , disorder, diameter polydispersity, and functionlization.
Simulation of adsorption of Li-doped nanotube
Simulation of high energy hydrogen atoms implanting into nanoutbe.
In theory, close ends nanotube can have a volumetric densities of 142kg/m3 storage since nanotube has a high tensile strength.

7. Hydrogen Storage-MD Simulation
Preliminary Results:
Results:
After 100ps simulation, about 3.18 wt% hydrogen absorbed within the intratube spacing.
Initial condition:
Carbon nanotube (10,10) periods:4
Pressure, 15atm. Temperature: 77K
hydrogen atoms: carbon atoms:480
Periodic box size:60x78x9.84 A. Time step:0.25 fs.
Work in progress:
What forces are required to separate the tubes (magnetic?) to store and release hydrogen?

8. Nanocomposites
Process modeling of nanocomposite fabrication using multi-scale methods to enhance alignment
Modification of nanoscale interfaces to improve load transfer through functionalization or/and defect engineering or/and surface modification
Large-scale simulation of nanocomposites to determine thermo-mechanical properties; optimization studies for strength, stiffness and fracture
Enhance longitudinal and transverse stiffness by improved interfacial bonding
Mechanics of defect formation- loss in strength and stiffness C a r b o n n a n o t u b e s i n V i s c o - e l a s t i c m e d i u m d i f f e r e n t o r i e n t a t i o n

9. Computational Issues and Large scale parallel computing
Use FSU’s 512 processor IBM 690p server
Third fastest university owned supercomputer in the US
Science-aware parallelization
Predict regions likely to experience short time-scale phenomena and concentrate computational resources there
Avoid fine granularity where possible
Use Monte Carlo techniques for rare-event simulation when required, to avoid fine granularity
Efficiently parallelizable through replication
Faster versions of traditional parallelization techniques
Stochastic versions of traditional domain decomposition techniques
Trade computation for communication
Mixed shared and distributed memory parallelization
Optimize sequential component too
Cache-aware computation
Solutions
Large time scale
Small system size
Fine grained parallelization
High communication cost
Adaptive computations
Regions experiencing short time-scale phenomena simulated with a finer resolution
Spatial decomposition and granularity change dynamically, and quickly, with time
Need fast and efficient load balancing strategies
Resources:
Third largest computer in U.S universities (IBM-p processors)

10. Nanocomposite simulation-prelim. results
Model
Matrix-nanotube interface modeled with springs
An extra force term computed for atoms attached to springs
Springs can break, requiring substantial increase in computations in that region
Polymer matrix
Spring
Experimental parameters
Nanotube with 1000 atoms
Spring probability: 0.05
Probability of a spring breaking in an iteration: 0.01
Load increase factor due to spring break: 200
Disturbance region depth: 3
Number of time steps: 100

11. Detailed information on each of the topics
Click on the arrow for any topic for direct link
Mechanics of Defects (presentation)
Interaction of Defects in nanotubes
Nanoscale interface mechanics