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The goal of this research work is to develop a particle-based device simulator for modeling strained silicon devices. Two separate modules had to be developed for that purpose: A generic bulk Monte Carlo simulation code which in the long-time limit solves the Boltzmann transport equation for electrons; and an extension

The goal of this research work is to develop a particle-based device simulator for modeling strained silicon devices. Two separate modules had to be developed for that purpose: A generic bulk Monte Carlo simulation code which in the long-time limit solves the Boltzmann transport equation for electrons; and an extension to this code that solves for the bulk properties of strained silicon. One scattering table is needed for conventional silicon, whereas, because of the strain breaking the symmetry of the system, three scattering tables are needed for modeling strained silicon material. Simulation results for the average drift velocity and the average electron energy are in close agreement with published data. A Monte Carlo device simulation tool has also been employed to integrate the effects of self-heating into device simulation for Silicon on Insulator devices. The effects of different types of materials for buried oxide layers have been studied. Sapphire, Aluminum Nitride (AlN), Silicon dioxide (SiO2) and Diamond have been used as target materials of interest in the analysis and the effects of varying insulator layer thickness have also been investigated. It was observed that although AlN exhibits the best isothermal behavior, diamond is the best choice when thermal effects are accounted for.
ContributorsQazi, Suleman (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Tao, Meng (Committee member) / Arizona State University (Publisher)
Created2013
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ABSTRACT An Ensemble Monte Carlo (EMC) computer code has been developed to simulate, semi-classically, spin-dependent electron transport in quasi two-dimensional (2D) III-V semiconductors. The code accounts for both three-dimensional (3D) and quasi-2D transport, utilizing either 3D or 2D scattering mechanisms, as appropriate. Phonon, alloy, interface roughness, and impurity scattering mechanisms

ABSTRACT An Ensemble Monte Carlo (EMC) computer code has been developed to simulate, semi-classically, spin-dependent electron transport in quasi two-dimensional (2D) III-V semiconductors. The code accounts for both three-dimensional (3D) and quasi-2D transport, utilizing either 3D or 2D scattering mechanisms, as appropriate. Phonon, alloy, interface roughness, and impurity scattering mechanisms are included, accounting for the Pauli Exclusion Principle via a rejection algorithm. The 2D carrier states are calculated via a self-consistent 1D Schrödinger-3D-Poisson solution in which the charge distribution of the 2D carriers in the quantization direction is taken as the spatial distribution of the squared envelope functions within the Hartree approximation. The wavefunctions, subband energies, and 2D scattering rates are updated periodically by solving a series of 1D Schrödinger wave equations (SWE) over the real-space domain of the device at fixed time intervals. The electrostatic potential is updated by periodically solving the 3D Poisson equation. Spin-polarized transport is modeled via a spin density-matrix formalism that accounts for D'yakanov-Perel (DP) scattering. Also, the code allows for the easy inclusion of additional scattering mechanisms and structural modifications to devices. As an application of the simulator, the current voltage characteristics of an InGaAs/InAlAs HEMT are simulated, corresponding to nanoscale III-V HEMTs currently being fabricated by Intel Corporation. The comparative effects of various scattering parameters, material properties and structural attributes are investigated and compared with experiments where reasonable agreement is obtained. The spatial evolution of spin-polarized carriers in prototypical Spin Field Effect Transistor (SpinFET) devices is then simulated. Studies of the spin coherence times in quasi-2D structures is first investigated and compared to experimental results. It is found that the simulated spin coherence times for GaAs structures are in reasonable agreement with experiment. The SpinFET structure studied is a scaled-down version of the InGaAs/InAlAs HEMT discussed in this work, in which spin-polarized carriers are injected at the source, and the coherence length is studied as a function of gate voltage via the Rashba effect.
ContributorsTierney, Brian David (Author) / Goodnick, Stephen (Thesis advisor) / Ferry, David (Committee member) / Akis, Richard (Committee member) / Saraniti, Marco (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2011
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Richard Feynman said “There’s plenty of room at the bottom”. This inspired the techniques to improve the single molecule measurements. Since the first single molecule study was in 1961, it has been developed in various field and evolved into powerful tools to understand chemical and biological property of molecules. This

Richard Feynman said “There’s plenty of room at the bottom”. This inspired the techniques to improve the single molecule measurements. Since the first single molecule study was in 1961, it has been developed in various field and evolved into powerful tools to understand chemical and biological property of molecules. This thesis demonstrates electronic single molecule measurement with Scanning Tunneling Microscopy (STM) and two of applications of STM; Break Junction (BJ) and Recognition Tunneling (RT). First, the two series of carotenoid molecules with four different substituents were investigated to show how substituents relate to the conductance and molecular structure. The measured conductance by STM-BJ shows that Nitrogen induces molecular twist of phenyl distal substituents and conductivity increasing rather than Carbon. Also, the conductivity is adjustable by replacing the sort of residues at phenyl substituents. Next, amino acids and peptides were identified through STM-RT. The distribution of the intuitive features (such as amplitude or width) are mostly overlapped and gives only a little bit higher separation probability than random separation. By generating some features in frequency and cepstrum domain, the classification accuracy was dramatically increased. Because of large data size and many features, supporting vector machine (machine learning algorithm for big data) was used to identify the analyte from a data pool of all analytes RT data. The STM-RT opens a possibility of molecular sequencing in single molecule level. Similarly, carbohydrates were studied by STM-RT. Carbohydrates are difficult to read the sequence, due to their huge number of possible isomeric configurations. This study shows that STM-RT can identify not only isomers of mono-saccharides and disaccharides, but also various mono-saccharides from a data pool of eleven analytes. In addition, the binding affinity between recognition molecule and analyte was investigated by comparing with surface plasmon resonance. In present, the RT technique is applying to chip type sequencing device onto solid-state nanopore to read out glycosaminoglycans which is ubiquitous to all mammalian cells and controls biological activities.
ContributorsIm, Jong One (Author) / Lindsay, Stuart M (Thesis advisor) / Zhang, Peiming (Committee member) / Ros, Robert (Committee member) / Chamberlin, Ralph (Committee member) / Arizona State University (Publisher)
Created2016