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

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

Research Areas NanoScale Interfaces Nano-Composites Hydrogen Storage Parallel Algorithms

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

Results Defect Engineering in CNTs Background: Defects (missing atoms, rotated bonds, diameter/chiralty transition) arise during processing and loading. They are either deleterious or beneficial 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 stress in CNT for different position of interacting defect at 8% applied strain. Variation of longitudinal strain along the CNT for different position of defects at 8% applied strain.

Back ground: 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. Hydrogen Storage

Preliminary Results: Initial condition : Carbon nanotube (10,10) periods:4 Pressure, 15atm. Temperature: 77K hydrogen atoms:160 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? Hydrogen Storage-MD Simulation Results : After 100ps simulation, about 3.18 wt% hydrogen absorbed within the intratube spacing.

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 Carbonnanotubesin differentorientation Visco-elasticmedium

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 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 Issues Solutions Computational Issues and Large scale parallel computing Resources: Third largest computer in U.S universities (IBM-p processors)

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 Spring Polymer matrix 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 Nanocomposite simulation-prelim. results

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