Download or read book Modeling and Control for Rapid Thermally Driven Deposition Processes written by and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objectives of this program were the study of the chemistry of YBCO thin film deposition by MOCVD, and the model-based control of MOCVD reactors. Model reduction techniques were applied to chemical vapor deposition (CVD) of YBCO thin films. This work has paralleled some of the work of Goodwin et al at Caltech sponsored under the DARPA VIP Phase I program, but with significantly different approach and emphasis. Under this program, the above chemistry was investigated from first principles using quantum chemistry computations (led by MIT). The kinetic and thermodynamic information obtained from these studies were used to generate a kinetic mechanism, which was then coupled to transport models for fluid flow, heat and mass transfer in CVD reactors. These coupled reaction-transport models were used to derive reduced order models for process control.

Download or read book Nonlinear Model Reduction Methods for Rapid Thermal and Chemical Vapor Deposition Processes written by Suman Kumar Banerjee and published by . This book was released on 1998 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of the Second International Symposium on Process Control Diagnostics and Modeling in Semiconductor Manufacturing written by M. Meyyappan and published by The Electrochemical Society. This book was released on 1997 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advancement in Thermo material Modeling of Direct Energy Deposition Processes written by Michael Gouge and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this work is to advance the abilities of finite element models of direct energy deposition (DED) processes. DED uses a laser or electron beam to melt either metallic powder or wire, which is controlled numerically to deposit the material onto a substrate or existant component. Computational models of DED processes are used for two primary reasons: process parametization and prediction of material properties. For the first reason, thermo-mechanical models are completed to determine the distortion and residual stresses that develop due to the high thermal gradients inherent during deposition. With accurate models, investigations can be made to mitigate these negative phenomena by alteration of process parameters including laser power, laser path, and environmental conditions. For the 2nd modeling motivation, thermal models are completed from which the thermal gradients, cooling rates, or solidification rates may be computed, which are the phenomenon which drive microstructural development, which in turn determines the final material properties of the deposited material.While DED technology is mature, having long been used to rapidly clad, repair, or build new components, the modeling of these processes is only now able to achieve the accuracy and speed necessary for industrial implementation. In this work finite element (FE) models are developed and validated for DED processes. In situ measurements of temperature are taken during the single layer laser cladding of Inconel® 625625. These are used to develop and validate the application of thermal boundary conditions aiming to improve model accuracy. First, the application of convection boundary conditions are explored. During DED deposition, the gases used to propel the powder and prevent material contamination in the melt pool cause a significant convective cooling. Comparisons are made between various methods of applying convection including using natural convection only, forced convection measured from the lumped capacitance method, convection from an impinging jet heat transfer paper, convection measured by hot film anemometry, and ignoring convection. The importance of applying convection to the evolving free surface was also investigated. It was shown that using the hot film anemometry values applied to an evolving free surface yielded the most accurate model, with 3-13% error. Secondly, conduction losses due to fixturing during laser cladding processes were investigated. Two Inconel® 625625 laser cladding experiments were completed, each using identical processes parameters, one which was held in a cantilevered fixture, one bolted directly to the work bench. These represent the minimum and maximum contact area during deposition. In situ measurements of temperature were taken, which were used for the calibration and validation of the subsequent thermal simulations. Though two bodies may be in contact, there is a loss of thermal conduction at their junction due to the microscopic irregularities of the surfaces. The drop in thermal heat transfer is called contact resistance and the effective conductivity through the point of contact is called gap conductance. A method for estimating the maximum gap conductance and application to FE models was developed. Calibration of gap conductance was completed for each experimental case. For the cantlivered clad, it was estimated that that merely 2% of the total heat loss occurred through the fixture. Application of the gap conductance model improved the accuracy of the model near the point of contact, but did not greatly affect the remainder of the substrate or clad material. For the work bench bolted clad, it was estimate that between 70-85% of the input heat left via conduction. It was shown that the accuracy of the thermal model for this case was vastly improved by using the gap conductance model, but that the effectiveness of the modeling was limited somewhat by the thermo-mechanical interaction. With the improved accuracy of the thermal models gained by the preceding advancements in boundary condition handling, the focus was shifted towards capturing the material solidification and ensuing microstructure with the FE model. To this end, single track depositions were performed using 4 sets of laser power and scan speed, for both Inconel® 625625 and Ti-6Al -4V. Type K thermocouples were used for far-field validation of the thermal model while high temperature Type C thermocouples were threaded through the underside of the substrate, to lay flush with the surface. This allowed for the in situ measurement of melt pool temperatures during deposition. Post process, the plates were sectioned and the melt depth was measured. Two modeling techniques were used to improve the accuracy for attaining both of these measured phenomenon: altering the melt temperature specific heat to account for changes in liquid density and altering the melt temperature thermal conductivity to approximate convection within the melt pool. This method reduced the simulated melt depth error to under 10% for 5 of the cases and the simulated melt temperature error under 25% for all 8 cases. It being concluded the model can accurately predict melt pool behavior, a model for predicting the material properties of laser clad Inconel® 625 was developed. Empirical correlations have been produced from Inconel® 625 hardness, yield strength, and microstructure measurements from published works from a variety of AM processes. Using the preceding single track study it was shown that using similar processing parameters the model could approximate the solidification time. It is the solidification time which controls the microstructure of Inconel® 625. The thermo-property model was calibrated against microstructure and hardness measurements from the laser clad. Experimental measurements of microstructure, hardness, and yield strength from 3 Inconel® 625 wall builds were used to validate the semiempirical model.This work yields a pathway from the process parameters to the material properties of laser clad Inconel® 625 which can be used to estimate or design the mechanical properties of DED Inconel® 625 components.

Download or read book Dynamics and Control of Process Systems 2004 written by Sirish Shah and published by Elsevier. This book was released on 2005-06-10 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A New Thermal Rapid Prototyping Process by Fused Material Deposition written by Nikolaos Fourligkas and published by . This book was released on 1999 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the recent and most spectacular advances in agile manufacturing technology is the development of Rapid Prototyping (RP) or Desktop Manufacturing methods. The limitation with the current RP techniques is their utilization of custom materials. Metals are more suitable for prototypes or customized tools. In this direction, a new RP technique was studied and developed, based on robotic Plasma Arc Welding material deposition by cold wire feeding. Proper guidance of this spot material addition in adjacent 1-D beads and overlaying 2-D layers generates the desired solid 3-D geometry. In such a thermal material deposition method, the solid part is developed by combined heat and mass transfer mechanisms, determining the composite prototype quality. The resulting metallurgical microstructure is of paramount significance for functional metal prototypes, where material properties comparable to those of cast or molded parts are desired. To succeed in achieving such a favorable material properties distribution, each level of material should be heat treated after its deposition. The heat treatment is done in a closed-loop fashion, using the recently developed scanned thermal process where a welding torch sweeps in a fast, repetitive motion the whole area of interest on the workpiece and provides at each location the heat needed, dictated by the control algorithm. The necessary temperature feedback is given from selected surface locations using non-conduct infrared sensing. The inherent nonlinearity of heat transfer mechanisms and the limitations of infrared thermal sensing lead to the establishment of a linearized multiple-input, multiple-output model, with in-process identification of its parameters. The thermal regulation system adjusts the power and guides the motion of the torch to the part region with the largest deviation from the desired temperature distribution, using two different in-process thermal optimization methods, the complex optimization and the simulated annealing optimization. Both those methods were successfully implemented in computer simulations and real-time experiments, using a Robotic Plasma Arc Welding experimental workstation.

Download or read book Model based Control Applied to Rapid Thermal Processing written by Paul Gyugyi and published by . This book was released on 1993 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Real time Computerized Process Control of a Rapid Thermal Chemical Vapor Deposition System written by Brian Lynn Carter and published by . This book was released on 1995 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Control and Simulation of Rapid Thermal Processes written by Joshua Benjamin and published by . This book was released on 2003 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Model identification and nonlinear predictive control of rapid thermal processing systems written by Terence Breedijk and published by . This book was released on 1994 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Microscopic Modeling Machine Learning Based Modeling and Optimal Operation of Thermal and Plasma Atomic Layer Deposition written by Yangyao Ding and published by . This book was released on 2021 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Atomic layer deposition (ALD) and plasma enhanced atomic layer deposition (PEALD) are the most widely utilized deposition techniques in the semiconductor industry due to their superior ability to produce highly conformal films and to deposit materials into high aspect-ratio geometric structures. Additionally, plasma enhanced ALD is able to further speed up the deposition process and to reduce the temperature requirement through the utilization of high energy particles. However, ALD and PEALD experiments remain expensive and time-consuming, and the existing first-principles based models have not yet been able to provide solutions to key process outputs that are computationally efficient, which is necessary for on-line optimization and real-time control. Motivated by the above considerations, this dissertation focuses on addressing these issues for both ALD and PEALD. First, for ALD, the development of key components of a comprehensive simulation framework is presented. The simulation framework integrates first-principles-based microscopic modeling, input/output modeling and optimal operation of thermal atomic layer deposition (ALD) of SiO2 thin-films using bis(tertiary-butylamino)silane (BTBAS) and ozone as precursors. Specifically, we initially utilize Density Functional Theory (DFT)-based calculations for the computation of the key thermodynamic and kinetic parameters, which are then used in the microscopic modeling of the ALD process. Subsequently, a detailed microscopic model is constructed, accounting for the microscopic lattice structure and atomic interactions, as well as multiple microscopic film growth processes including physisorption, abstraction and competing chemical reaction pathways. Kinetic Monte-Carlo (kMC) algorithms are utilized to obtain computationally efficient microscopic model solutions while preserving model fidelity. The obtained kMC simulation results are used to train Artificial Neural Network (ANN)-based data-driven models that capture the relationship between operating process parameters and time to ALD cycle completion. Specifically, a two-hidden-layer feed-forward ANN is constructed to find a feasible range of ALD operating conditions accounting for industrial considerations, and a Bayesian Regularized ANN is constructed to implement the cycle-to-cycle optimization of ALD cycle time. Extensive simulation results demonstrate the effectiveness of the proposed approaches. The kMC models successfully achieves a growth per cycle (GPC) of 1.8 A per cycle, which is in the range of reported experimental values. The ANN models accurately predict deposition time to steady-state from the given operating condition input, and the cycle time optimization using BRANN model reduces the conventional BTBAS cycle time by 60%. After developing an efficient simulation framework, a more detailed study on the optimal operation policy is performed using a multiscale data-driven model. The multiscale data-driven model captures the macroscopic process domain dynamics with a linear parameter varying model, and characterizes the microscopic domain film growth dynamics with a feed-forward artificial neural network (ANN) model. The multiscale data-driven model predicts the transient deposition rate from the following four key process operating parameters that can be manipulated, measured or estimated by process engineers: precursor feed flow rate, operating pressure, surface heating, and transient film coverage. Our results demonstrate that the multiscale data-driven model can efficiently characterize the transient input-output relationship for the SiO2 thermal ALD process using Bis(tertiary-butylamino)silane (BTBAS) as the Si precursor. The multiscale data-driven model successfully reduces the computational time from 0.6 - 1.2 hr for each time step, which is required for the first-principles based multiscale computational fluid dynamics (CFD) model, to less than 0.1 s, making its real-time usage feasible. The developed data-driven modeling methodology can be further generalized and used for other thermal ALD or similar deposition systems, which will greatly enhance the feasibility of industrial manufacturing processes. For PEALD, a similar methodology is adopted. First, an accurate, yet efficient kinetic Monte Carlo (kMC) model and an associated machine learning (ML) analysis are proposed to capture the surface deposition mechanism of the HfO2 thin-film PEALD using Tetrakis-dimethylamino-Hafnium (TDMAHf) and oxygen plasma. Density Functional Theory (DFT) calculations are performed to obtain the key kinetic parameters and the structural details. After the model is validated by experimental data, a database is generated to explore a variety of precursor partial pressure and substrate temperature combinations using the kMC algorithm. A feed-forward Bayesian regularized artificial neural network (BRANN) is then constructed to characterize the input-output relationship and to investigate the optimal operating condition. Next, based on an associated work on a comprehensive 3D multiscale computational fluid dynamics (CFD) model for the PEALD process, a 2D axisymmetric reduction of the previous 3D model of PEALD reactors with and without the showerhead design has been adopted to enhance the computational efficiency. Using the derived 2D CFD model, a data-driven model is constructed based on a recurrent neural network (RNN) for process characterization. The developed integrated data-driven model is demonstrated to accurately characterize the key aspects of the deposition process as well as the gas-phase transport profile while maintaining computational efficiency. The derived data-driven model is further validated with the results from a full 3D multiscale CFD model to evaluate model discrepancy. Using the data-driven model, an operational strategy database is generated, from which the optimal operating conditions can be determined for the deposition of HfO2 thin-film based on an elementary cost analysis.

Download or read book Model based control applied to rapid thermal processing thesis written by Paul John Gyugyi and published by . This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Rapid Thermal and Other Short time Processing Technologies II written by Dim-Lee Kwong and published by The Electrochemical Society. This book was released on 2001 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Electronics, Dielectric Science and Technology, and High Temperature Materials Divisions."

Download or read book CVD XV written by Mark Donald Allendorf and published by The Electrochemical Society. This book was released on 2000 with total page 826 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modelling of Directed Energy Deposition Processes written by Xueyang Chen and published by . This book was released on 2014 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The laser additive manufacturing technique of laser deposition allows quick fabrication of fully-dense metallic components directly from Computer Aided Design (CAD) solid models. The applications of laser deposition include rapid prototyping, rapid tooling and part refurbishment. The development of an accurate predictive model for laser deposition is extremely complicated due to the multitude of process parameters and materials properties involved. In this work, a heat transfer and fluid flow model is developed. In the heat transfer and fluid flow model, the governing equations for solid, liquid and gas phases in the calculation domain have been formulated using the continuum model. The free surface in the melt pool has been tracked by the Volume of Fluid (VOF) method. Surface tension was modeled by taking the Continuum Surface Force (CSF) model combined with a force-balance flow algorithm. Laser-powder interaction was modeled to account for the effects of laser power attenuation and powder temperature rise during the laser metal deposition process. Temperature-dependent thermal-physical material properties were considered in the numerical implementation. The calculation domain is logically partitioned into smaller cells in 3D space. This makes the numerical implementation consume large amounts of computational resources as each cell is considered at each step of the implementation. This challenge has been addressed through the use of parallel computing by way of message passing interface. Simulations were performed and a comparison between the sequential and parallel implementations was also made"--Abstract, page iv.

Download or read book Real Time Control of Polysilicon Deposition in Single Wafer Rapid Thermal Chemical Vapor Deposition Furnaces written by and published by . This book was released on 1910 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis describes the development of a real-time control system for depositing polysilicon films on silicon wafers by means of rapid thermal chemical vapor deposition. Results are presented which characterize the ability of the control system to deposit films of an average desired thickness and predict the film's spatial thickness distribution. A rapid thermal chemical vapor deposition system was used to individually process wafers. During processing, a mass spectrometer monitored the chemical species present in the exhaust gases to determine the total volume of material deposited. Simultaneously, optical probes resolved the spatial temperature distribution of the wafer. The mass spectrometry and optical temperature data were combined with an Arrhenius equation to model the deposition process. Validation of the model was exsitu. After processing, film thickness measurements were made on each wafer and compared to the computer model's predictions. Experimental results identified hydrogen, a by-product of the deposition reaction, as the metric for determining the total volume of polysilicon deposited. Process recipe control (today's standard control technique) produced films varying over a range of 280 Å when repeatedly employed to deposit film's of 900 Å. Application of the real-time control system produced films varying a maximum of 74 Å when attempting to deposit films of average thickness ranging from 800 to 1200 Å. Modeling results predicted the thickness of the deposited film to within 20 Å at the center of the wafer. Predictions at the wafers edge were off by a maximum of 160 Å. From the experience gained during this project, the following two recommendations are made to guide future efforts. First, the mass spectrometer's reaction time to an event occurring in the furnace was found to be one second. Employing an optical sensor could improve control by reducing the time lag of the system. Second, designing the furnace with the n.

Download or read book Rapid Thermal and Other Short time Processing Technologies written by Fred Roozeboom and published by The Electrochemical Society. This book was released on 2000 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings from this May 2000 symposium illustrate the range of applications in Rapid Thermal Processing (RTP). The refereed papers cover a variety of issues, such as ultra-shallow junctions; contacts for nanoscale CMOS; gate stacks; new applications of RTP, such as for the enhanced crystalization of amorphous silicon thin films; and advances on RTP systems and process monitoring, including optimizing and controlling gas flows in an RTCVD reactor. Most presentations are supported by charts and other graphical data. c. Book News Inc.