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Hanchen Huang - One of the best experts on this subject based on the ideXlab platform.

  • Texture Evolution During Thin Film Deposition
    Handbook of Materials Modeling, 2020
    Co-Authors: Hanchen Huang
    Abstract:

    The modeling of materials processing intrinsically spans multiple scales, in terms of both space and time. The modeling of Thin Film Deposition, together with the accompanying texture evolution, spans 15 orders of magnitude in time, from fundamental atomic vibration period of 10−13 s to Deposition duration of 102 s. This section describes challenging issues, critically presents existing approaches, and offers an outlook of future developments in the modeling of Thin Film texture evolution.

  • Atomistic simulator of polycrystalline Thin Film Deposition in three dimensions
    Journal of Computer-aided Materials Design, 2020
    Co-Authors: Hanchen Huang, L.g. Zhou
    Abstract:

    Thin Film Deposition involves processes from 10−13 to 102 s in time scale. It is desirable, and also challenging, to include important physics of all the time scales in modeling the Deposition. The hierarchical bridging of ab initio, molecular dynamics, and lattice kinetic Monte Carlo has proven feasible in incorporating important time scales of Thin Film Deposition. However, one bottleneck is the representation of polycrystals wiThin the lattice kinetic Monte Carlo method. A brutal force representation of N grains each with linear dimension L requires additional computer memory of order NL3, beyond that of a single crystal. Instead, we here propose and implement a memory efficient algorithm of three consecutive two-dimensional mappings to represent the N grains. As a result, the additional memory requirement is on the order of NL2. Using energetics representative of Al, we demonstrate the new implementation by simulating texture competition with and without sufficient diffusion. Our demonstrations show that the implementation (1) allows the physical representation of texture evolution, and (2) enables atomistic simulations of polycrystalline Thin Films of 0.15--0.20 m or larger in linear dimension, on a standalone PC in the year of 2004; without the memory efficient algorithm, this would have not been possible until a decade later.

  • Texture competition during Thin Film Deposition – effects of grain boundary migration
    Computational Materials Science, 2020
    Co-Authors: Hanchen Huang, George H. Gilmer
    Abstract:

    In this paper, we describe an implementation of grain boundary migration in the atomistic simulator of Thin Film Deposition (ADEPT), and apply the simulator to study effects of the grain boundary migration on texture evolution. In the implementation, atoms are classified into two categories: those belong to a single grain and those at grain boundaries. An atom is defined as one at a grain boundary if it has more than half of its neighbors occupied and not all of the neighboring atoms are in the same grain. The grain boundary atom is attempted to re-align with neighboring grains to represent the grain boundary migration; the attempt probability is defined by the grain boundary migration coefficient. Our studies show that grain boundary migration does not always assist formation of texture with a top surface of the lowest energy. At the nucleation stage of Thin Film Deposition, high migration coefficient of grain boundaries may enhance the formation of grain nuclei with top surfaces of higher energy, and therefore effectively may suppress formation of textures with a top surface of the lowest energy. This effect may provide an extra dimension to engineer textures of Thin Films.Department of Mechanical Engineerin

  • Texture competition during Thin Film Deposition – effects of grain boundary migration
    Computational Materials Science, 2002
    Co-Authors: Hanchen Huang, George H. Gilmer
    Abstract:

    In this paper, we describe an implementation of grain boundary migration in the atomistic simulator of Thin Film Deposition (ADEPT), and apply the simulator to study effects of the grain boundary migration on texture evolution. In the implementation, atoms are classified into two categories: those belong to a single grain and those at grain boundaries. An atom is defined as one at a grain boundary if it has more than half of its neighbors occupied and not all of the neighboring atoms are in the same grain. The grain boundary atom is attempted to re-align with neighboring grains to represent the grain boundary migration; the attempt probability is defined by the grain boundary migration coefficient. Our studies show that grain boundary migration does not always assist formation of texture with a top surface of the lowest energy. At the nucleation stage of Thin Film Deposition, high migration coefficient of grain boundaries may enhance the formation of grain nuclei with top surfaces of higher energy, and therefore effectively may suppress formation of textures with a top surface of the lowest energy. This effect may provide an extra dimension to engineer textures of Thin Films.

  • Parallelization strategies for Monte Carlo simulations of Thin Film Deposition
    Computer Physics Communications, 2002
    Co-Authors: Qin Lu, Waion Wong, Hanchen Huang
    Abstract:

    Abstract Atomistic simulations of Thin Film Deposition, based on the lattice Monte Carlo method, provide insights into the microstructure evolution at the atomic level. However, large-scale atomistic simulation is limited on a single computer—due to memory and speed constraints. Parallel computation, although promising in memory and speed, has not been widely applied in these simulations because of the intimidating overhead. The key issue in achieving optimal performance is, therefore, to reduce communication overhead among processors. In this paper, we propose a new parallel algorithm for the simulation of large-scale Thin Film Deposition incorporating two optimization strategies: (1) domain decomposition with sub-domain overlapping and (2) asynchronous communication . This algorithm was implemented both on message-passing-processor systems (MPP) and on cluster computers. We found that both architectures are suitable for parallel Monte Carlo simulation of Thin Film Deposition in either a distributed memory mode or a shared memory mode with message-passing libraries.

Panagiotis D. Christofides - One of the best experts on this subject based on the ideXlab platform.

  • Lattice-size Dependence and Dynamics of Surface Mean Slope in a Thin Film Deposition Process
    IFAC Proceedings Volumes, 2020
    Co-Authors: Jianqiao Huang, Gangshi Hu, Gerassimos Orkoulas, Panagiotis D. Christofides
    Abstract:

    Abstract This work focuses on the study of the dynamic behavior and lattice size dependence of the surface root-mean-square slope in a porous Thin Film Deposition process taking place on a triangular lattice. The simulation results indicate that the expected mean slope square reaches quickly a steady-state value and exhibits a very weak dependence with respect to lattice size variation. The simulation findings are corroborated by an analysis of appropriate finite-difference discretizations of surface height profiles computed by an Edwards-Wilkinson-type partial differential equation that can be used to describe the dynamics of surface height profile in the Thin Film Deposition process under consideration.

  • Construction of Stochastic PDEs and Predictive Control of Surface Roughness in Thin Film Deposition
    Model Reduction and Coarse-Graining Approaches for Multiscale Phenomena, 2020
    Co-Authors: Dong Ni, Panagiotis D. Christofides
    Abstract:

    In this work, we develop a systematic method for the construction of linear stochastic partial differential equation (PDE) models for feedback control of surface roughness in Thin Film Deposition using kinetic Monte-Carlo simulations. The method is applied to a representative Deposition process and is successfully validated through simulations.

  • Dependence of Film surface roughness on surface migration and lattice size in Thin Film Deposition
    Proceedings of the 2011 American Control Conference, 2011
    Co-Authors: Jianqiao Huang, Gangshi Hu, Gerassimos Orkoulas, Panagiotis D. Christofides
    Abstract:

    This work focuses on the study of the dependence of Film surface roughness on surface migration and lattice size in Thin Film Deposition processes. Two different models of Thin Film Deposition processes, in both one-dimension and two-dimensions, are considered: random Deposition with surface relaxation model and Deposition/migration model. Surface roughness is defined as the root-mean-squares of the surface height profile and is found to evolve (starting from a flat initial surface zero value) to steady-state values at large times. A linear and a logarithmic dependence of surface roughness square on lattice size are observed in the one-dimensional and two-dimensional lattice models, respectively, in both the random Deposition with surface relaxation model and the Deposition/migration model with zero activation energy contribution from each neighboring particle. Furthermore, a stronger lattice-size dependence is found in the Deposition/migration model when the migration activation energy contribution from each neighboring particle becomes significant.

  • Dynamics and Lattice-Size Dependence of Surface Mean Slope in Thin-Film Deposition
    Industrial & Engineering Chemistry Research, 2011
    Co-Authors: Jianqiao Huang, Gangshi Hu, Gerassimos Orkoulas, Panagiotis D. Christofides
    Abstract:

    This work focuses on the study of the dynamic behavior and lattice-size dependence of the surface root-mean-square slope of Thin-Film Deposition processes that involve thermal balance between Film ...

  • Predictive control of surface mean slope and roughness in a Thin Film Deposition process
    Chemical Engineering Science, 2010
    Co-Authors: Xinyu Zhang, Gangshi Hu, Gerassimos Orkoulas, Panagiotis D. Christofides
    Abstract:

    Abstract This work focuses on the development of a model predictive control algorithm to simultaneously regulate the surface slope and roughness of a Thin Film growth process to optimize Thin Film light reflectance and transmittance. Specifically, a Thin Film Deposition process modeled on a one-dimensional triangular lattice that involves two microscopic processes: an adsorption process and a migration process, is considered. Kinetic Monte Carlo (kMC) methods are used to simulate the Thin Film Deposition process. To characterize the surface morphology and to evaluate the light trapping efficiency of the Thin Film, surface roughness and surface slope are introduced as the root mean squares of the surface height profile and surface slope profile. An Edwards–Wilkinson (EW)-type equation is used to describe the dynamics of the surface height profile and predict the evolution of the root-mean-square (RMS) roughness and RMS slope. A model predictive control algorithm is then developed on the basis of the EW equation model to regulate the RMS slope and the RMS roughness at desired levels by optimizing the substrate temperature at each sampling time. The model parameters of the EW equation are estimated from simulation data through least-square methods. Closed-loop simulation results demonstrate the effectiveness of the proposed model predictive control algorithm in successfully regulating the RMS slope and the RMS roughness at desired levels that optimize Thin Film light reflectance and transmittance.

George H. Gilmer - One of the best experts on this subject based on the ideXlab platform.

  • Texture competition during Thin Film Deposition – effects of grain boundary migration
    Computational Materials Science, 2020
    Co-Authors: Hanchen Huang, George H. Gilmer
    Abstract:

    In this paper, we describe an implementation of grain boundary migration in the atomistic simulator of Thin Film Deposition (ADEPT), and apply the simulator to study effects of the grain boundary migration on texture evolution. In the implementation, atoms are classified into two categories: those belong to a single grain and those at grain boundaries. An atom is defined as one at a grain boundary if it has more than half of its neighbors occupied and not all of the neighboring atoms are in the same grain. The grain boundary atom is attempted to re-align with neighboring grains to represent the grain boundary migration; the attempt probability is defined by the grain boundary migration coefficient. Our studies show that grain boundary migration does not always assist formation of texture with a top surface of the lowest energy. At the nucleation stage of Thin Film Deposition, high migration coefficient of grain boundaries may enhance the formation of grain nuclei with top surfaces of higher energy, and therefore effectively may suppress formation of textures with a top surface of the lowest energy. This effect may provide an extra dimension to engineer textures of Thin Films.Department of Mechanical Engineerin

  • Texture competition during Thin Film Deposition – effects of grain boundary migration
    Computational Materials Science, 2002
    Co-Authors: Hanchen Huang, George H. Gilmer
    Abstract:

    In this paper, we describe an implementation of grain boundary migration in the atomistic simulator of Thin Film Deposition (ADEPT), and apply the simulator to study effects of the grain boundary migration on texture evolution. In the implementation, atoms are classified into two categories: those belong to a single grain and those at grain boundaries. An atom is defined as one at a grain boundary if it has more than half of its neighbors occupied and not all of the neighboring atoms are in the same grain. The grain boundary atom is attempted to re-align with neighboring grains to represent the grain boundary migration; the attempt probability is defined by the grain boundary migration coefficient. Our studies show that grain boundary migration does not always assist formation of texture with a top surface of the lowest energy. At the nucleation stage of Thin Film Deposition, high migration coefficient of grain boundaries may enhance the formation of grain nuclei with top surfaces of higher energy, and therefore effectively may suppress formation of textures with a top surface of the lowest energy. This effect may provide an extra dimension to engineer textures of Thin Films.

  • Atomistic simulation of texture competition during Thin Film Deposition
    Journal of Computer-aided Materials Design, 2000
    Co-Authors: Hanchen Huang, George H. Gilmer
    Abstract:

    In this paper, we review the principles and the applications of an atomistic simulator for Thin Film Deposition (ADEPT), which is a hybrid of classical molecular dynamics and lattice Monte Carlo methods. Molecular dynamics is used to study details of the atomic movement, whereas lattice Monte Carlo method is used to simulate the long time evolution of Thin Film Deposition. In the first stage development of the ADEPT, a single lattice is used with all atoms placed on one lattice representing a single crystal. Later, the description is extended to two lattices to simulate the competition of two textures during Deposition, the model being called Monte Carlo Poly. More recently, multiple lattices are incorporated in Monte Carlo Poly to treat the competition of all possible textures. At each stage, ADEPT was applied to simulate Deposition of various Thin Films, with a focus on the electronic materials. The atomistic simulations, in particular those based on Monte Carlo Poly, provide insights to mechanisms of texture competition.

  • an atomistic simulator for Thin Film Deposition in three dimensions
    Journal of Applied Physics, 1998
    Co-Authors: Hanchen Huang, George H. Gilmer, Tomas Diaz De La Rubia
    Abstract:

    We describe an atomistic simulator for Thin Film Deposition in three dimensions (ADEPT). The simulator is designed to bridge the atomic and mesoscopic length scales by using efficient algorithms, including an option to speed up surface diffusion using events with multiple diffusion hops. Sputtered particles are inserted and assigned ballistic trajectories with angular distributions appropriate for magnetron sputtering. Atoms on the surface of the Film execute surface diffusion hops with rates that depend on the local configuration, and are consistent with microscopic reversibility. The potential energies are chosen to match information obtained from a database of first principles and molecular dynamics (MD) calculations. Efficient computation is accomplished by selecting atoms with probabilities that are proportional to their hop rates. A first implementation of grain boundary effects is accomplished by including an orientation variable with each occupied site. Energies and mobilities are assigned to atom...

Nicolas Gherardi - One of the best experts on this subject based on the ideXlab platform.

  • atmospheric pressure low temperature direct plasma technology status and challenges for Thin Film Deposition
    Plasma Processes and Polymers, 2012
    Co-Authors: F Massines, Christian Sarrabournet, Fiorenza Fanelli, Nicolas Naude, Nicolas Gherardi
    Abstract:

    Over the last ten years, expansion of atmospheric pressure plasma solutions for surface treatment of materials has been remarkable, however direct plasma technology for Thin Film Deposition needs still great effort. The objective of this paper is to establish the state of the art on scientific and technologic locks, which have to be opened to consider direct atmospheric pressure plasma-enhanced chemical vapor Deposition (AP-PECVD) a viable option for industrial application. Basic scientific principles to understand and optimize an AP-PECVD process are summarized. Laboratory reactor configurations are reviewed. Reference points for the design and use of AP-PECVD reactors according to the desired Thin Film properties are given. Finally, solutions to avoid powder formation and to increase the Thin Film growth rate are discussed.

John A. Rogers - One of the best experts on this subject based on the ideXlab platform.