T H Heat flow across a SiO2 layer EXAS TEC

Slides:



Advertisements
Similar presentations
Biological fluid mechanics at the micro‐ and nanoscale Lecture 7: Atomistic Modelling Classical Molecular Dynamics Simulations of Driven Systems Anne Tanguy.
Advertisements

University of Illinois at Urbana-Champaign Daniel Go, Alfonso Reina-Cecco, Benjamin Cho Simulation of Silicon Twist Wafer Bonding MATSE 385 Final Project.
Modelling of Defects DFT and complementary methods
Maykel L. González-Martínez 6 th IMP, Feb. 1-5, C. Habana.
Thermodynamics of Oxygen Defective Magnéli Phases in Rutile: A First Principles Study Leandro Liborio and Nicholas Harrison Department of Chemistry, Imperial.
EQUILIBRIUM AND KINETICS. Mechanical Equilibrium of a Rectangular Block Centre Of Gravity Potential Energy = f(height of CG) Metastable state Unstable.
Thermal properties from first principles with the use of the Free Energy Surface concept Dr inż. Paweł Scharoch Institute of Physics, Wroclaw University.
Characterisation and Reliability Testing of THz Schottky Diodes Chris Price University of Birmingham, UK
Molecular Dynamic Simulation of Atomic Scale Intermixing in Co-Al Thin Multilayer Sang-Pil Kim *, Seung-Cheol Lee and Kwang-Ryeol Lee Future Technology.
Introduction to Monte Carlo Simulation. What is a Monte Carlo simulation? In a Monte Carlo simulation we attempt to follow the `time dependence’ of a.
Yibin Xu National Institute for Materials Science, Japan Thermal Conductivity of Amorphous Si and Ge Thin Films.
Basics of molecular dynamics. Equations of motion for MD simulations The classical MD simulations boil down to numerically integrating Newton’s equations.
UNIT 1 FREE ELECTRON THEORY.
Atomic Scale Computational Simulation for Nano-materials and Devices: A New Research Tool for Nanotechnology Kwang-Ryeol Lee Future Technology Research.
Atomic scale understandings on hydrogen behavior in Li 2 O - toward a multi-scale modeling - Satoru Tanaka, Takuji Oda and Yasuhisa Oya The University.
By Francesco Maddalena 500 nm. 1. Introduction To uphold Moore’s Law in the future a new generation of devices that fully operate in the “quantum realm”
ECE 4339 L. Trombetta ECE 4339: Physical Principles of Solid State Devices Len Trombetta Summer 2007 Chapters 16-17: MOS Introduction and MOSFET Basics.
Metals I: Free Electron Model
EEE 3394 Electronic Materials Chris Ferekides SPRING 2014 WEEK 2.
Quantum Monte Carlo on geomaterials Dario Alfè 2007 Summer School on Computational Materials Science Quantum Monte Carlo: From Minerals.
HW/Tutorial # 1 WRF Chapters 14-15; WWWR Chapters ID Chapters 1-2
Fyzika tokamaků1: Úvod, opakování1 Tokamak Physics Jan Mlynář 6. Neoclassical particle and heat transport Random walk model, diffusion coefficient, particle.
HW/Tutorial # 1 WRF Chapters 14-15; WWWR Chapters ID Chapters 1-2 Tutorial #1 WRF#14.12, WWWR #15.26, WRF#14.1, WWWR#15.2, WWWR#15.3, WRF#15.1, WWWR.
Advanced methods of molecular dynamics 1.Monte Carlo methods 2.Free energy calculations 3.Ab initio molecular dynamics 4.Quantum molecular dynamics 5.Trajectory.
Corey Flack Department of Physics, University of Arizona Thesis Advisors: Dr. Jérôme Bürki Dr. Charles Stafford.
A Thermodynamic Perspective on the Interaction of Radio Frequency Radiation with Living Tissue Michael Peleg.
Non-equilibrium theory of rheology for non-Brownian dense suspensions
Electrical Engineering Materials
Applications of the Canonical Ensemble: Simple Models of Paramagnetism
HW/Tutorial # 1 WRF Chapters 14-15; WWWR Chapters ID Chapters 1-2
Boltzmann Transport Equation for Particle Transport
Sanghamitra Mukhopadhyay Peter. V. Sushko and Alexander L. Shluger
Overview of Molecular Dynamics Simulation Theory
16 Heat Capacity.
Production of an S(α,β) Covariance Matrix with a Monte Carlo-Generated
Yongxing Shen1, Annica Heyman2, and Ningdong Huang2
4.6 Anharmonic Effects Any real crystal resists compression to a smaller volume than its equilibrium value more strongly than expansion due to a larger.
of interfaces in glass/crystal composites for nuclear wasteforms
Theoretical & Computational Materials Physics
S.-C. Lee*, K.-R. Lee, and K.-H. Lee Computational Science Center
Fundamentals of Heat Transfer
Applications of the Canonical Ensemble:
Anharmonic Effects.
Fermi Level Dependent Diffusion in Silicon
Atomistic simulations of contact physics Alejandro Strachan Materials Engineering PRISM, Fall 2007.
Atomistic materials simulations at The DoE NNSA/PSAAP PRISM Center
Algorithms and Software for Large-Scale Simulation of Reactive Systems
Prof. Sanjay. V. Khare Department of Physics and Astronomy,
Validity of Molecular Dynamics by Quantum Mechanics
Deviations from the Ideal I-V Behavior
Masoud Aryanpour & Varun Rai
Lattice Boltzmann Simulation of Water Transport in Gas Diffusion Layers of PEMFCs with Different Inlet Conditions Seung Hun Lee1, Jin Hyun Nam2,*, Hyung.
16 Heat Capacity.
Equilibrium and Kinetics
Heat Conduction in Solids
Metastability of the boron-vacancy complex (C center) in silicon: A hybrid functional study Cecil Ouma and Walter Meyer Department of Physics, University.
Computational Materials Science Group
Instructor: Yuntian Zhu
Electro-Thermal Analysis of Contact Resistance
PHY 752 Solid State Physics Plan for Lecture 28: Chap. 9 of GGGPP
Multiscale modeling of hydrogen isotope transport in porous graphite
Co-Al 시스템의 비대칭적 혼합거동에 관한 이론 및 실험적 고찰
Molecular Transport Group
Algorithms and Software for Large-Scale Simulation of Reactive Systems
Sang-Pil Kim and Kwang-Ryeol Lee Computational Science Center
Convective Heat Transfer
Fundamentals of Heat Transfer
The Atomic-scale Structure of the SiO2-Si(100) Interface
Fig. 5 Classical MD simulations.
Presentation transcript:

T H Heat flow across a SiO2 layer EXAS TEC Motivation Si|SiO2 interfaces are ubiquitous in Si technology. How does heat generated by a CPU in Si interact with this layer? Our study: ‘first-principles’ theory Existing theoretical studies: all are empirical [1-5] Experiment: focus on the ‘interface boundary resistance’ [8-10] Interface vibrational modes ΔT 1 ΔT 2 𝑇0 𝑇ℎ𝑓 𝑇0 = background T 𝑇ℎ𝑓= heat front T as it reaches the interface ΔT 1 = ‘low-T’ window ΔT 2 = ‘high-T’ window Result: monitoring heat flow Theory Electronic structure: SIESTA[7] valence regions: DFT (LDA) core regions: ab-initio pseudopotentials Nuclei classical Host material H-saturated Si nanowire in a large 1D- periodic box (strictly microcanonical) Non-equilibrium MD: ‘supercell preparation’ technique [6] NO thermostat or thermalization runs excellent T control t=0: distribution of normal vibrational modes with random phases averaging: 20-30 microstates Physics Department T EXAS TEC H U N I V E R S I T Y Christopher M. Stanley and Stefan K. Estreicher Heat flow across a SiO2 layer Result: oxide layer is a barrier to heat flow With an oxide: considerably more time needed to equilibrate With oxide: time constant increases by factors of 2.4 (low-T window) to 2.3 (high-T window) Difference between the T windows: due to difference in thermal conductivity of nanowire at different temperatures With Oxide Without Oxide Oxide construction: a-SiO2 layer Simulate experimental approach repeat steps 1-3 remove self-interstitial when needed coordinates relaxed by CG one O2 molecule added at a time Construction Summary Typical initial position O2 final structure: Si230O54H56 Set up a T gradient at t=0 A slice of the nanowire is heated above background temperature (T0) at t=0 MD run: the heat initially flows only to the right Temperature gradients are chosen based on frequency range of oxide-related vibrational modes [1] B. Deng et al., J. App. Phys. 115, 084910 (2014). [2] S.S .Mahajan et al., Therm. Thermomech. Phenom. Ele. Sys. 1055 (2008) [3] E. Lampin et al., Appl. Phys. Lett. 100, 131906 (2012) [4] J Chen et al. J. App. Phys. 112, 064319 (2012) [5] S. Munetoh et al., Comput. Mater. Sci. 39, 334 (2007) [6] T.M. Gibbons et al., J. App. Phys. 118, 085103 (2015) [7] J.M. Soler, et al., J. Phys. Cond. Matt. 14, 11 (2002) [8] D.H. Hurley et al. J. App. Phys. 109,083504 (2011) [9] R Kato et al. Int J Thermophys. 29, p2062-2071 (2008) [10] S.M. Lee. J. App. Phys. 81, p2590-2595 (1997) References Oxides:barriers to heat flow The heat generated in the Si (e.g. by a CPU) finds it harder to escape The results point towards the possibility of non-propagating vibrational modes, which cannot be explained by conventional models of heat flow. Conclusions