The Experts below are selected from a list of 10962 Experts worldwide ranked by ideXlab platform
Wenxin Wang - One of the best experts on this subject based on the ideXlab platform.
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2d ultraThin core shell pd ptmonolayer nanosheets defect mediated Thin Film Growth and enhanced oxygen reduction performance
Nanoscale, 2015Co-Authors: Wenxin Wang, Yunfeng Zhao, Yi DingAbstract:An operational strategy for the synthesis of atomically smooth Pt skin by a defect-mediated Thin Film Growth method is reported. Extended ultraThin core–shell structured d@Ptmonolayer nanosheets (thickness below 5 nm) exhibit nearly seven-fold enhancement in mass-activity and surprisingly good durability toward oxygen reduction reaction as compared with the commercial Pt/C catalyst.
Yi Ding - One of the best experts on this subject based on the ideXlab platform.
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2d ultraThin core shell pd ptmonolayer nanosheets defect mediated Thin Film Growth and enhanced oxygen reduction performance
Nanoscale, 2015Co-Authors: Wenxin Wang, Yunfeng Zhao, Yi DingAbstract:An operational strategy for the synthesis of atomically smooth Pt skin by a defect-mediated Thin Film Growth method is reported. Extended ultraThin core–shell structured d@Ptmonolayer nanosheets (thickness below 5 nm) exhibit nearly seven-fold enhancement in mass-activity and surprisingly good durability toward oxygen reduction reaction as compared with the commercial Pt/C catalyst.
Panagiotis D. Christofides - One of the best experts on this subject based on the ideXlab platform.
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Controller and Estimator Design for Regulation of Film Thickness, Surface Roughness, and Porosity in a Multiscale Thin Film Growth Process
Industrial & Engineering Chemistry Research, 2010Co-Authors: Xinyu Zhang, Gangshi Hu, Gerassimos Orkoulas, Panagiotis D. ChristofidesAbstract:This work focuses on simultaneous regulation of Film thickness, surface roughness, and porosity in a multiscale model of a Thin Film Growth process using the inlet precursor concentration as the manipulated input. Specifically, under the assumption of continuum, a partial differential equation model is first derived to describe the dynamics of the precursor concentration in the gas phase. The Thin Film Growth process is modeled via a microscopic kinetic Monte Carlo simulation model on a triangular lattice with vacancies and overhangs allowed to develop inside the Film. Closed-form dynamic models of the Thin Film surface profile and porosity are developed and used as the basis for the design of model predictive control algorithms to simultaneously regulate Film thickness, surface roughness, and porosity. Both state feedback and porosity estimation-based output feedback control algorithms are presented. Simulation results demonstrate the applicability and effectiveness of the proposed modeling and control approach by applying the proposed controllers to the multiscale model of the Thin Film Growth process.
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CDC - Simultaneous regulation of Film thickness, surface roughness and porosity in a multiscale Thin Film Growth process
Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009Co-Authors: Gangshi Hu, Xinyu Zhang, Gerassimos Orkoulas, Panagiotis D. ChristofidesAbstract:This work focuses on simultaneous regulation of Film thickness, surface roughness and porosity in a multiscale model of a Thin Film Growth process using the inlet precursor concentration as the manipulated input. Specifically, a continuous macroscopic partial differential equation model is used to describe the dynamics of the gas phase. The Thin Film Growth process is modeled via a microscopic kinetic Monte Carlo simulation model on a triangular lattice with vacancies and overhangs allowed to develop inside the Film. Closed-form dynamic models of Thin Film surface profile and porosity are developed and used as the basis for the design of a model predictive control algorithm to simultaneously regulate Film thickness, surface roughness and Film porosity. Simulation results demonstrate the applicability and effectiveness of the proposed modeling and control approach by applying the proposed controller to the multiscale model.
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Feedback control of Growth rate and surface roughness in Thin Film Growth
42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2003Co-Authors: Panagiotis D. ChristofidesAbstract:In this work, we present an approach for multivariable feedback control of surface roughness and Growth rate in Thin Film Growth using kinetic Monte-Carlo (MC) models. We use the process of Thin Film Growth in a stagnation flow geometry and consider atom adsorption, desorption and surface migration as the three processes that shape Film micro-structure and determine Film Growth rate. A multiscale model is used to simulate the process. Following the methodology presented in, a roughness and Growth rate estimator is constructed that allows computing estimates of the surface roughness and Growth rate at a time-scale comparable to the real-time evolution of the process. The interactions between the inputs and outputs in the closed-loop system are studied and found to be significant. A multivariable feedback controller, which uses the state estimator and explicitly compensates for the effect of input/output interactions, is designed to simultaneously regulate the Growth rate and surface roughness by manipulating substrate temperature and inlet precursor mole fraction. Application of the proposed control system to the multiscale process model demonstrates successful regulation of the surface roughness and Growth rate to the desired set-point values. The proposed approach is found to be superior to control of the Growth rate and surface roughness using two independent feedback control loops.
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estimation and control of surface roughness in Thin Film Growth using kinetic monte carlo models
Chemical Engineering Science, 2003Co-Authors: Panagiotis D. ChristofidesAbstract:Abstract In this work, we present an approach to estimation and control of surface roughness in Thin Film Growth using kinetic Monte-Carlo (MC) models. We use the process of Thin Film Growth in a stagnation flow geometry and consider atom adsorption, desorption and surface migration as the three processes that shape Film micro-structure. A multiscale model that involves coupled partial differential equations (PDEs) for the modeling of the gas phase and a kinetic MC simulator, based on a high-order lattice, for the modeling of the Film micro-structure, is used to simulate the process. A roughness estimator is constructed that allows computing estimates of the surface roughness at a time-scale comparable to the real-time evolution of the process using discrete on-line roughness measurements. The estimator involves a kinetic MC simulator based on a reduced-order lattice, an adaptive filter used to reduce roughness stochastic fluctuations and an error compensator used to reduce the error between the roughness estimates and the discrete roughness measurements. The roughness estimates are fed to a proportional-integral (PI) controller. Application of the proposed estimator/controller structure to the multiscale process model demonstrates successful regulation of the surface roughness at the desired value. The proposed approach is shown to be superior to PI control with direct use of the discrete roughness measurements. The reason is that the available measurement techniques do not provide measurements at a frequency that is comparable to the time-scale of evolution of the dominant Film Growth dynamics.
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estimation and control of surface roughness in Thin Film Growth using kinetic monte carlo models
Conference on Decision and Control, 2002Co-Authors: Panagiotis D. ChristofidesAbstract:In this work, we present an approach to estimation and control of surface roughness in Thin Film Growth using kinetic Monte-Carlo (MC) models. We use the process of Thin Film Growth in a stagnation flow geometry and consider atom adsorption, desorption and surface migration as the three processes that shape Film micro-structure. A multiscale model that involves coupled partial differential equations (PDEs) for the modelling of the gas phase and a kinetic MC model, based on a high-order lattice, for the modelling of the Film micro-structure, is used to simulate the process. A roughness estimator is constructed that allows computing estimates of the surface roughness at a time-scale comparable to the real-time evolution of the process. The estimator involves a kinetic MC model based on a reduced-order lattice, an adaptive filter used to reduce roughness stochastic fluctuations and an error compensator used to reduce the error between the roughness estimates and measurements. The roughness estimates are fed to a proportional-integral (PI) controller. Application of the proposed estimator/controller structure to the multiscale process model demonstrates successful regulation of the surface roughness at the desired set-point value. The proposed approach is shown to be superior to PI control with direct use of the roughness measurements. The reason is that the available measurement techniques do not provide measurements at a time-scale comparable to the evolution of the dominant Film Growth dynamics.
Yunfeng Zhao - One of the best experts on this subject based on the ideXlab platform.
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2d ultraThin core shell pd ptmonolayer nanosheets defect mediated Thin Film Growth and enhanced oxygen reduction performance
Nanoscale, 2015Co-Authors: Wenxin Wang, Yunfeng Zhao, Yi DingAbstract:An operational strategy for the synthesis of atomically smooth Pt skin by a defect-mediated Thin Film Growth method is reported. Extended ultraThin core–shell structured d@Ptmonolayer nanosheets (thickness below 5 nm) exhibit nearly seven-fold enhancement in mass-activity and surprisingly good durability toward oxygen reduction reaction as compared with the commercial Pt/C catalyst.
Michael Moseler - One of the best experts on this subject based on the ideXlab platform.
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molecular dynamics simulation of Thin Film Growth by energetic cluster impact
Physical Review B, 1995Co-Authors: H Haberland, Z Insepov, Michael MoselerAbstract:Langevin-molecular-dynamics simulations of Thin-Film Growth by energetic cluster impact were carried out. The impact of a ${\mathrm{Mo}}_{1043}$ cluster on a Mo(001) surface was studied for impact energies of 0.1, 1, and 10 eV/atom using the Finnis-Sinclair many-body potential. The characteristics of the collision range from a soft touchdown at 0.1 eV/atom, over a flattening collision at 1 eV/atom, to a meteoric impact at 10 eV/atom. The highest energy impact creates a pressure of about 100 GPa in the impact zone and sends a strong shock wave into the material. The cluster temperature reaches a maximum of 596 K for 0.1 eV/atom, 1799 K for 1 eV/atom, and 6607 K for 10 eV/atom during the first ps after the touchdown. For energies of 1 and 10 eV/atom the cluster recrystallizes after 20 ps. The consecutive collision of 50 ${\mathrm{Mo}}_{1043}$ clusters with a Mo(001) surface at T=300 K was simulated for the three impact energies. The formation of a porous Film is calculated for clusters impinging with low kinetic energy, while for the clusters with the highest energy a dense mirrorlike Film is obtained, in good agreement with experiment.
