: 2003 5 23

KIST

Todays TalkWhat is atomic scale simulation?Role of atomic simulation in nano-materials researchBrief survey of some cases Where should we go?

Computer Simulation ( ) 16KeV Au4 Cluster on Au (111)

Molecular Dynamic Simulation Empirical Approach First Principle ApproachInteratomic Potentials

Theory and Observations(Newtonian Mechanics)R. Feynman, Lectures on Physics, Ch. 7 & 9 (1963)

Laplaces Dream (1814)Pierre-Simon Laplace (1749-1827)Given for one instant, an intelligence which could comprehend all the forces by which nature is animated and the respective situation of the beings , nothing would be uncertain and the future, as the past, would be present to its eyes.

The intelligence in 21st CenturyHigh computing power at low cost High performance visualization tools

New Era of Computer SimulationC-plant @ Sandia National Lab.Beowulf Cluster @ CALTECHAlpha Cluster @ SAITAvalon @ Los Alamos National Lab.

KIST Beowulf System80 Execution Nodes X2 Pentium III (850~2050MHz) connected by 100Mbps Ethernet and Myrinet66 Gbyte RAM 4.9 Terabyte HDD

2 Head Execution NodesX4 Pentium III Xeon (700,2000MHz) for Head Execution 4Gbyte RAM 3,280Gbyte HDD

100Gflops

KIST 1024 CPU Cluster System

GRID Environment

Moors Law in Atomic SimulationEmpirical MDNumber of atoms has doubled every 19 months.864 atoms in 1964 (A. Rahman)6.44 billion atoms in 2000First Principle MDNumber of atoms has doubled every 12 months.8 atoms in 1985 (R. Car & M. Parrinello)111,000 atoms in 2000

The intelligence in 21st CenturyHigh computing power at low cost High performance visualization tools

Telescope : Galilei (1610) Microscope : Leeuwenhoek (1674) : Golgi & Cajal (1906 Nobel Prize)Neuroscience : Millikan (1923 Nobel Prize) STM / AFM : Binnig & Rohrer (1986 Nobel Prize)Nano-Technology

MinMax432105In case of 75 eV

Virtual Reality & Visualization

Nanomaterials

Characteristics of NanotechnologyContinuum media hypothesis is not allowed.Diffusion & MechanicsBand Theory

Case I : Size Dependent Properties

Case II : Scale Down Issues2~4nmKinetics based on continuum media hypothesis is not sufficient.

Chracteristics of NanotechnologyContinuum media hypothesis is not allowed.

Large fraction of the atom lies at the surface or interface.Abnormal WettingAbnormal Melting of Nano ParticlesChemical Instabilities

Case IV : GMR Spin ValveMajor Materials Issue is the interfacial structure and chemical diffusion in atomic scale

Nanoscience or Nanotechnology , Needs Atomic Scale Understandings on the Structure, the Kinetics and the Properties

Insufficient Experimental Tools

Methodology of Science & TechnologySynthesis & ManipulationAnalysis & CharacterizationModeling & Simulation

Methodology of Nanotechnology

Atomic Scale Simulation of Interfacial Intermixing during Low Temperature Deposition in Co-Al System

Magnetic RAM (MRAM)1 nmProperties of MRAM are largely depends on the Interface Structures of Metal/Metal or Metal/Insulator Controlling & UnderstandingThe atomic behavior at the interface are fundamental to improve the performance of the nano-devices!

Conventional Thin Film Growth Model Conventional thin film growth model simply assumes that intermixing between the adatom and the substrate is negligible.

Adatom (0.1eV, normal incident)SubstrateProgram : XMD 2.5.30x,y-axis : Periodic Boundary Conditionz-axis : Open Surfacedt : 0.5fs , calculation time : 5ps/atom300K Initial Temperature300K Constant TemperatureFix Position

Depostion Behavior on (001)Co on Al (001)

Deposition Behavior on (001)Al on Co (001)

Deposition Behavior on (001)Al on Al (100)Al on Al (001)

Thin Film GrowthConventional thin film growth model assumes negligible intermixing between the adatom and the substrate atom. In nano-scale processes, the model need to be extended to consider the atomic intermixing at the interface. Conventional Thin Film Growth ModelCalculations of the acceleration of adatom and the activation barrier for the intermixing can provide a criteria for the atomic intermixing.

Tensile Test of Cu Nanowires Computational Semiconductor Technology Lab.

Electron Emission from CNT,

Array of sub-nano Ag Wire Self Assembling of CHQ Nanotube

Search for New DMS MaterialsSiC:TM or AlN:TMDOS of AlN

Search for New DMS MaterialsSiC:TM or AlN:TMDOS of AlN

Half Metal!!

Spintronics Spin as new degree of freedom in quantum device structures

Combine nonvolatile character with band gap engineering

New FunctionalityMotivation

Role of Computational Modeling Provide physical intuition and insight where the continuum world is replaced by the granularity of the atomic world.Bridge the Gap between Fundamental Materials Science and Materials EngineeringProvide virtual experimental tools where the physical experiment or analysis fails.Allow fundamental theory (i.e.quantum mechanics) to be applied to a complex problem.

Importance of Modeling & SimulationThe emergence of new behaviors and processes in nanostructures, nanodevices and nanosystems creates an urgent need for theory, modeling, large-scale computer simulation and design tools and infrastructure in order to understand, control and accelerate the development in new nano scale regimes and systems. NSF announcement for multi-scale, multi-phenomena theory, modeling and simulation at nanoscle activity (2000)

Materials Science in 21st CenturyComputational simulation was frequently emphasized in many articles.

H. Gleiter : Nanostructured MaterialsW.J. Boettinger et al : Solidification MicrostructuresJ. Hafner : Atomic-scale Computational Materials ScienceA. Needleman : Computational Mechanics in mesoscale

Hierarchy of Computer SimulationFundamental Models- Ab initio MD- First Principle CalculationAtomic Level Simulation- Monte Carlo Approach- Classical MD Engineering DesignnsfsmsmspsminTIMEDISTANCE1A10A100A1mm1mm

First Principle CalculationClassical MDContinuum SimulationMultiscale Simulation

Multi-scale ApproachesIn Case of Fracture

TechnologiesProducts200020102020National TRM for Modeling & Simulation Scale Molecular Manipulation Smart Nanosystem & Process Designer Multiscale Materials Simulation Empirical MD Quantum MD Mesoscale Simul.Virtual Reality & Smart MMIIHigh Performance Computing & Algorithm Cluster Computing Smart Parallel Algorithm Quantum ComputingIntegrated Simulation Technology Multiscale Simulator Nano Materials & System DBSource : (, 2002)

Multiscale Simulation

Multiscale Simulation Model

Experimental Research GroupsMultiscale Interfacing Algorithm

Application I/F

Cluster Supercomputer & Computing

Scale

Inter-ScaleInterfacing

First Principle SimulationClassical MD andMC SimulationForce Field DBMesoscale and Continuum SimulationDevice Simulation

Within five to ten years, there must be robust tools for quantitative understanding of structure and dynamics at the nanoscale, without which the scientific community will have missed many scientific opportunities as well as a broad range of nanotechnology applications.

http://diamond.kist.re.kr/SMS

First Emblem of KIST (New CI) KIST : research

This show the snapshot of coordination number and strain energy in the case of 75 eV. depositon diffusion nucleation and growth . depositon diffusion nucleation and growth .