재료현상을 관찰 하는 또 하나의 방법 : 전산모사

1. 재료현상을 관찰하는 또 하나의 방법 : 전산모사 2003년 5월 23일 서울대 재료공학부 콜로퀴움 KIST 미래기술연구본부 이 광 렬

2. Today’s Talk • What is atomic scale simulation? • Role of atomic simulation in nano-materials research • Brief survey of some cases • Where should we go?

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

4. i Time Evolution of Ri and vi Molecular Dynamic Simulation Interatomic Potentials • Empirical Approach • First Principle Approach

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

6. Pierre-Simon Laplace (1749-1827) 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.

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

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

10. 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

11. KIST 1024 CPU Cluster System

12. GRID Environment

13. 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

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

15. 과학에서 본다는 것의 의미 • 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

16. In case of 75 eV Max 0 1 2 3 4 5 Min

17. Virtual Reality & Visualization

18. Nanomaterials

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

20. 0.13 m 10 nm Case II : Scale Down Issues 2~4nm Kinetics based on continuum media hypothesis is not sufficient.

21. 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

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

23. Nanoscience or Nanotechnology • 물질을 원자∙분자 단위에서 규명하고 제어하여, 원자∙분자들을 적절히 분산 결합 시킴으로써 기존 물질의 변형∙개조 및 신물질의 창출이 가능한 기술 Needs Atomic Scale Understandings on the Structure, the Kinetics and the Properties

24. Insufficient Experimental Tools

25. Methodology of Science & Technology Synthesis & Manipulation Analysis & Characterization Modeling & Simulation

26. Synthesis & Manipulation Analysis & Characterization Modeling & Simulation Methodology of Nanotechnology

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

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

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

30. [001] z y x [010] [100] Adatom (0.1eV, normal incident) 300K Initial Temperature Substrate 300K Constant Temperature Fix Position Program : XMD 2.5.30 x,y-axis : Periodic Boundary Condition z-axis : Open Surface dt : 0.5fs , calculation time : 5ps/atom

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

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

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

34. Thin Film Growth • 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 Calculations of the acceleration of adatom and the activation barrier for the intermixing can provide a criteria for the atomic intermixing.

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

36. Electron Emission from CNT 서울대학교, 고체물질이론 연구실

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

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

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

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

41. 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 fails. • Allow fundamental theory (i.e.quantum mechanics) to be applied to a complex problem. Bridge the Gap between Fundamental Materials Science and Materials Engineering

42. Importance of Modeling & 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)

43. 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

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

45. Multiscale Simulation Classical MD First Principle Calculation Continuum Simulation

46. Multi-scale Approaches In Case of Fracture

47. 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)

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

49. 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

50. 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.