재료현상을 관찰하는 또 하나의 방법 : 재료전산모사 2003년 10월 23일 KIST 미래기술연구본부 콜로퀴움 이 광 렬 초청에 감사 First Emblem of KIST (New CI)  새로운 위상 KIST : 기업지원 응용연구  기반기술 research의 중요성을 강조

Today’s Talk Introduction to computational simulation Role of atomic scale simulation in nano-materials/devices research Brief survey of some cases Where should we go? Present limitation and the vision (of SMS Lab.)

Computer Simulation 물리적으로 타당한 (혹은 타당하다고 판단되는) 단순계의 원리로부터 복잡계의 현상을 고찰하고자 하는 연구방법

Computer Simulation 물리적으로 타당한 (혹은 타당하다고 생각되는) 단순계의 원리로부터 복잡계의 현상을 고찰하고자 하는 연구방법 16KeV Au4 Cluster on Au (111)

Molecular Dynamic Simulation Time Evolution of Ri and vi Interatomic Potentials Empirical Approach First Principle Approach

재료현상을 관찰하는 또 하나의 방법 : 재료전산모사 2003년 10월 23일 KIST 미래기술연구본부 콜로퀴움 이 광 렬 초청에 감사 First Emblem of KIST (New CI)  새로운 위상 KIST : 기업지원 응용연구  기반기술 research의 중요성을 강조

관찰이란 무엇인가? 어떤 현상을 오감을 통해 인지하는 것. 五感 (Sensing) : Natural Phenomena (physics) 認知 (Recognition) : Brain’s Job (human factor)

눈으로 관찰하기                                            

AFM/STM

Molecular Dynamic Simulation Time Evolution of Ri and vi Interatomic Potentials Empirical Approach First Principle Approach

Hierarchy of Computer Simulation Engineering Design min Continuum Models ms - FEM/FDM Monte Carlo Approach Phase Field Theory TIME ms ns Atomic Level Simulation - Monte Carlo Approach - Classical MD ps Fundamental Models First Principle Calculation Ab initio MD fs 1A 10A 100A 1mm 1mm DISTANCE

Hierarchy of Computer Simulation Engineering Design min Continuum Models ms - FEM/FDM Monte Carlo Approach Phase Field Theory TIME ms ns Atomic Level Simulation - Monte Carlo Approach - Classical MD ps Fundamental Models First Principle Calculation Ab initio MD fs 1A 10A 100A 1mm 1mm DISTANCE

Phase Field Method

FEM/FDM Approach

Computer Simulation 물리적으로 타당한 (혹은 타당하다고 생각되는) 단순계의 원리로부터 복잡계의 현상을 고찰하고자 하는 연구방법 16KeV Au4 Cluster on Au (111)

Theory and Observations (Newtonian Mechanics) Motion of a Mass on a Spring Orbit of Sirius Double Star R. Feynman, Lectures on Physics, Ch. 7 & 9 (1963)

Laplace’s Dream (1814) 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. Pierre-Simon Laplace (1749-1827)

The Intelligence in 21st Century High computing power at low cost High performance visualization tools

New Era of Computer Simulation C-plant @ Sandia National Lab. Beowulf Cluster @ CALTECH Avalon @ Los Alamos National Lab. Alpha Cluster @ SAIT

KIST Beowulf System 100Gflops 80 Execution Nodes X2 Pentium III (850~2050MHz) connected by 100Mbps Ethernet and Myrinet 66 Gbyte RAM 4.9 Terabyte HDD 2 Head Execution Nodes X4 Pentium III Xeon (700,2000MHz) for Head Execution 4Gbyte RAM 3,280Gbyte HDD

KIST 1024 CPU Cluster System

GRID Environment

Moor’s Law in Atomic Simulation Empirical MD Number of atoms has doubled every 19 months. 864 atoms in 1964 (A. Rahman) 6.44 billion atoms in ’2000 First Principle MD Number of atoms has doubled every 12 months. 8 atoms in 1985 (R. Car & M. Parrinello) 111,000 atoms in ’2000

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

과학에서 관찰한다는 것의 중요성 Telescope : Galilei (1610) 새로운 우주관의 시발점 Microscope : Leeuwenhoek (1674) 박테리아 정복의 시발점 신경세포의 가시화 : Golgi & Cajal (1906 Nobel Prize) Neuroscience의 시작 유적실험 : Millikan (1923 Nobel Prize) 전하량 측정  근대적 원자구조의 이해 STM / AFM : Binnig & Rohrer (1986 Nobel Prize) Nano-Technology의 시작

In case of 75 eV Max This show the snapshot of coordination number and strain energy in the case of 75 eV. 1 2 3 4 5 Min

Virtual Reality & Visualization

Nanomaterials

Nanomaterials

Characteristics of Nanotechnology Continuum media hypothesis is not allowed. Diffusion & Mechanics Band Theory ~ nm

Case I : Size Dependent Properties Atomic Orbitals N=1 Molecules N=2 Clusters N=10 Q-Size Particles N=2,000 Semiconductor N>>2,000 hn Energy Conduction Band Valence Vacuum CdSe Nanoparticles Smaller Size

Case II : Scale Down Issues 0.13 m 2~4nm 10 nm Kinetics based on continuum media hypothesis is not sufficient.

Chracteristics of Nanotechnology Continuum media hypothesis is not allowed. Large fraction of the atom lies at the surface or interface. Abnormal Wetting Abnormal Melting of Nano Particles Chemical Instabilities

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

Nanoscience or Nanotechnology 현상을 원자∙분자 단위에서 규명하고 제어하여, 구성 원자 및 분자들을 적절히 분산 결합 시킴으로써 새로운 물성의 재료/소자를 창출하는 기술 Needs Atomic Scale Understandings on the Structure, the Kinetics and the Properties

Insufficient Experimental Tools

Methodology of Conventional R&D Synthesis & Manipulation Analysis & Characterization Modeling & Simulation

Methodology of Nano-R&D Synthesis & Manipulation Modeling & Simulation Analysis & Characterization

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

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

Conventional Thin Film Growth Model 흥미롭게도 기존의 증착메커니즘은 기판 위에서 원자는 depositon diffusion nucleation and growth만이 발생한다고 하였지만 본 실험에서는 기존의 개념과는 다른 새로운 형태의 증착 메커니즘을 발견할 수 있었습니다. Conventional thin film growth model simply assumes that intermixing between the adatom and the substrate is negligible.

Substrate Adatom (0.1eV, normal incident) Program : XMD 2.5.30 300K Initial Temperature Substrate 300K Constant Temperature Fix Position [100] [001] [010] z y x Program : XMD 2.5.30 x,y-axis : Periodic Boundary Condition z-axis : Open Surface dt : 0.5fs , calculation time : 5ps/atom

MD Simulation Interatomic Potentials Time Evolution of Ri and vi Lennard-Jones: Inert Gas Embedded Atom Method: Metals Many Body Potential: Si, C Interatomic Potentials

EAM Potential for Co and Al HCP - Co FCC - Al Property Al* Co** Expt. Calc. A0 (Å) 4.05 4.049 2.507 2.512 Ecoh (eV) 3.36 3.39 4.39 4.29 B (GPa) 79 79.4 180 185 * A. Voter et al. MRS Symp.Proc. , 175 (1987) ** R. Pasianot et al , PRB 45 12704 (1992)

EAM Potential for Co–Al Property CoAl(B2) Expt.* Calc. ** Calc. *** A0 (Å) 2.86 2.867 2.994 Ecoh (eV) 4.45 4.468 4.083 B (GPa) 162 178 169 CoAl B2 * Intermetallic Compound , Vol 1, 885 (1994) ** C. Vailhe et al. J. Mater. Res., 12 No. 10 2559 (1997) *** R.A. Johnson, PRB 39 12554 (1989)

Phase Diagram of Co-Al CoAl: B2

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

Al on Co-FCC(001)

Co on Al (100) 6144 substrate atoms (16x16x6)a0 (512 atoms/ML) Deposition Energy : 0.1eV

Phase Diagram of Co-Al CoAl: B2

Deposition Behavior on (111) Co on Al Al on Co

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

Al on Al (100)

Co on Co (0001) 1344 substrate atoms(168atoms/ML) Remove misfits <Stacking sequence> a  misfit! c b a Remove misfits Co-substrate After 10ML (1680atoms) in 5 eV

Co on Al (100) 6144 substrate atoms (16x16x6)a0 (512 atoms/ML) Deposition Energy : 0.1eV

Co on Al (100)

Co on Al (100) 1.4 ML 2.8 ML 4.2 ML N.R. Shivaparan, et al Surf. Sci. 476, 152 (2001)

CoAl compound layer was formed spontaneously. Structural Analysis CoAl CoAl compound layer was formed spontaneously.

Co on Al (100) Co

Energy Barrier for Co Penetration (1) (2) (3) (1) (2) (3) Reaction Coordinate Actavation barrier is larger than the incident kinetic energy (0.1eV) of Co. How can deposited Co atom get sufficient energy to overcome the activation barrier?

Acceleration of Deposited Co Near Al Substrate 1 2 3 4 3.5eV Co Hollow site Al (1) (2) (3) (4)

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

Contour of Acceleration Al on Co (001) Co on Al (001)

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

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

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

Conventional Thin Film Growth Model Conventional 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 Model 흥미롭게도 기존의 증착메커니즘은 기판 위에서 원자는 depositon diffusion nucleation and growth만이 발생한다고 하였지만 본 실험에서는 기존의 개념과는 다른 새로운 형태의 증착 메커니즘을 발견할 수 있었습니다. Calculations 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 B D C {111} plane 중앙대 전자공학과 Computational Semiconductor Technology Lab.

Nano-Gear Using CNT (NASA)

Electron Emission from CNT 서울대학교, 고체물질이론 연구실

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

Search for New DMS Materials SiC:TM or AlN:TM DOS of AlN

Search for New DMS Materials Half Metal!! SiC:TM or AlN:TM DOS of AlN

Spintronics ~ Motivation spin-LED  FM p+ ~ circularly polarized output Motivation Spin as new degree of freedom in quantum device structures Combine nonvolatile character with band gap engineering New Functionality 2DEG transport 2 D E G V g spin-FET source gate drain single transistor nonvolatile memory

Effect of Nitrogen on CNT Growth Carbon nanotube is the most famous structure in carbon nanotechnology. Since the discovery of CNT, tremendous researches on this unique material have been done and still in progress. the application of CNT is also an important and big job. Due to the electron emission property, Vertically aligned CNT, became a promising structure for filed emitter or display To fabricate VACNT, it is reported that Nitrogen atmosphere is a necessary condition. With this condition, Nitrogen is incorporated into CNT. this nitrogen incorporation accelerates the growth rate and makes CNTs aligned. Through the observation, We know that nitrogen incorporation enhances CNT growth. But, in what way, the growth rate becomes higher, we have no idea In this presentation, I will talk about the role of nitrogen in CNT growth Nitrogen incorporation enhances CNT growth drastically that vertically aligned CNT can be fabricated

Strain energy due to curved wall 40nm At first, let’s look at the nitrogen effect on the strain energy of CNT The relationship between strain energy and radius is well known and calculation of Energy vs radius is a kind of basic set of CNT system. So there are many calculation results. Generally, we use this design for the calculation of CNT. As radius of CNT gets larger, more atoms are needed to make structure. In case of larger radius CNT, the number of atoms for calculation exceeds the limit. you can see on this graph, the radius is less than 6 angstrom, and generally less than 10 angstroms. But real CNTs radius is about 20-30 diameter, 6A is too small to describe real CNT. First, we have to overcome this problem.

Here are the results. These points are obtained from the calculation of conventional design and like the data that I showed previously, Size is limited to 10A After using cluster design, I could get the calculation results of which radius is up to 80A. The radius can be extend even more.. These data also correspondent to the equation of E vs radius, which is predicted earlier. Now, we can find an interesting point. This green dashed line is the energy of flat graphite plate. Around the radius of 35A, two graphs meet. When radius is larger than 35A, there is no more strain energy in CNT This result tells gives us very important message

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

Importance of Modeling & Computational Simulation The 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 Century Computational simulation was frequently emphasized in many articles. H. Gleiter : Nanostructured Materials W.J. Boettinger et al : Solidification Microstructures J. Hafner : Atomic-scale Computational Materials Science A. Needleman : Computational Mechanics in mesoscale

Hierarchy of Computer Simulation Engineering Design min Continuum Models - FEM/FDM - Monte Carlo Approach ms TIME ms ns Atomic Level Simulation - Monte Carlo Approach - Classical MD ps Fundamental Models - Ab initio MD - First Principle Calculation fs 1A 10A 100A 1mm 1mm DISTANCE

High Energy Carbon Deposition Growth Rate ~ 1m/s This show the behavior of potential energy with incident energy. As you can see, under 10 eV, there is not occurred sharpen peak. It means the atom intermixing is not occurred under 10 eV. It is dominated Deposition with high energy is

Tensile Test of Cu Nanowires B D C {111} plane 중앙대 전자공학과 Computational Semiconductor Technology Lab.

Search for New DMS Materials SiC:TM or AlN:TM DOS of AlN

Multiscale Simulation First Principle Calculation Classical MD Continuum Simulation

Multi-scale Approaches In Case of Fracture

Multiscale Simulation Ab-initio Calc. Classical MD Continuum Simul. Smart Inter-scale Interfacing Computing Method & Algorithm Massively Parallel Computing Facility Supercomputer & Code Optimization 다차원 전산모사의 성공요건

Multiscale Simulation 환경 Model Experimental Research Groups Device Simulation Application I/F Mesoscale and Continuum Simulation Scale 별 전산모사 기술 Inter-Scale Interfacing 기술 Multiscale Interfacing Algorithm 개발 Classical MD and MC Simulation Cluster Supercomputer & 최적 Computing 환경 Force Field DB First Principle Simulation 수퍼컴 성능 최적화 및 병렬화 환경구축

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.

Source : 중점 전략 연구분야의 테크놀로지 로드맵 정립에 관한 연구 (기초기술연구회, 2002) National TRM for Modeling & Simulation Technologies High Performance Computing & Algorithm Cluster Computing Smart Parallel Algorithm Quantum Computing Multiscale Materials Simulation Empirical MD Quantum MD Mesoscale Simul. Virtual Reality & Smart MMII Integrated Simulation Technology 2000 2010 2020 Scale별 전산모사 Molecular Manipulation Smart Nanosystem & Process Designer Multiscale Simulator Products Nano Materials & System DB Source : 중점 전략 연구분야의 테크놀로지 로드맵 정립에 관한 연구 (기초기술연구회, 2002)

http://diamond.kist.re.kr/SMS 본 연구는 KIST 기관고유사업과 KIST Vision 21 사업의 지원을 통해 수행되고 있으며, 이에 깊이 감사드립니다.

감사합니다. 박수~~~!

Energy Barrier for Intermixing Reaction Coordinate (1) (2) (3) (1) (2) (3) Reaction Coordinate (1) (2) (3)

Contour of Acceleration Al on Al (001) Co on Co (001)

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

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

Hierarchy of Computer Simulation Engineering Design min Continuum Models - FEM/FDM - Monte Carlo Approach ms TIME ms ns Atomic Level Simulation - Monte Carlo Approach - Classical MD ps Fundamental Models - Ab initio MD - First Principle Calculation fs 1A 10A 100A 1mm 1mm DISTANCE