Download or read book Machine Learning Based Modelling in Atomic Layer Deposition Processes written by Oluwatobi Adeleke and published by CRC Press. This book was released on 2023-12-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications. . .

Download or read book Machine Learning Based Modelling in Atomic Layer Deposition Processes written by Oluwatobi Adeleke and published by CRC Press. This book was released on 2023-12-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications.

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 Machine Learning Based Modeling and Operation of Plasma Enhanced Atomic Layer Deposition of Hafnium Oxide Thin Films written by Ho Yeon Chung and published by . This book was released on 2020 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plasma-enhanced atomic layer deposition (PEALD) has demonstrated its superiority at coatingultra-conformal high dielectric thin-films, which are essential to the fin field-effect transistors (FinFETs) as well as the advanced 3D V-NAND (vertical Not-AND) flash memory cells. Despite the growing research interest, the exploration of the optimal operation policies for PEALD remains a complicated and expensive task. Our previous work has constructed a comprehensive 3D multiscale computational fluid dynamics (CFD) model for the PEALD process and demonstrated its potential to enhance the understanding of the process. Nevertheless, the limitation of computational resources and the relatively long computation time restrict the efficient exploration of the operating space and the optimal operating strategy. Thus, in this work, we apply a 2D axisymmetric reduction of the previous 3D model of PEALD reactors with and without the showerhead design. Furthermore, a data-driven model is derived 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 Analysis and Design of Atomic Layer Deposition Processes written by and published by . This book was released on 2013 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Atomic Layer Deposition written by Tommi Kääriäinen and published by John Wiley & Sons. This book was released on 2013-05-28 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition was published in 2008, Atomic Layer Deposition (ALD) has emerged as a powerful, and sometimes preferred, deposition technology. The new edition of this groundbreaking monograph is the first text to review the subject of ALD comprehensively from a practical perspective. It covers ALD's application to microelectronics (MEMS) and nanotechnology; many important new and emerging applications; thermal processes for ALD growth of nanometer thick films of semiconductors, oxides, metals and nitrides; and the formation of organic and hybrid materials.

Download or read book Atomic Layer Deposition written by David Cameron and published by MDPI. This book was released on 2020-12-28 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Atomic layer deposition (ALD) is a thin film deposition process renowned for its ability to produce layers with unrivaled control of thickness and composition, conformability to extreme three-dimensional structures, and versatility in the materials it can produce. These range from multi-component compounds to elemental metals and structures with compositions that can be adjusted over the thickness of the film. It has expanded from a small-scale batch process to large scale production, also including continuous processing – known as spatial ALD. It has matured into an industrial technology essential for many areas of materials science and engineering from microelectronics to corrosion protection. Its attributes make it a key technology in studying new materials and structures over an enormous range of applications. This Special Issue contains six research articles and one review article that illustrate the breadth of these applications from energy storage in batteries or supercapacitors to catalysis via x-ray, UV, and visible optics.

Download or read book Sensor Based Atomic Layer Deposition for Rapid Process Learning and Enhanced Manufacurability written by Wei Lei and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Atomic Layer Deposition Applications 3 written by Ana Londergan and published by The Electrochemical Society. This book was released on 2007 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The continuously expanding realm of Atomic Layer Deposition (ALD) Applications is the symposium focus. ALD can enable the precise deposition of ultra-thin, highly conformal coatings over complex 3D topography, with controlled composition and properties. Following two successful years, this symposium is well on its way to becoming a forum for the sharing of cutting edge research in the various areas where ALD is used.

Download or read book Atomic Layer Deposition Applications 6 written by J. W. Elam and published by The Electrochemical Society. This book was released on 2010-10 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: The continuously expanding realm of Atomic Layer Deposition (ALD) Applications is the focus of this reoccurring symposium. ALD can enable the precise deposition of ultra-thin, highly conformal coatings over complex 3D topographies with controlled thickness and composition. This issue of ECS Transactions contains peer reviewed papers presented at the symposium. A broad spectrum of ALD applications is featured, including novel nano-composites and nanostructures, dielectrics for state-of-the-art transistors and capacitors, optoelectronics, and a variety of other emerging applications.

Download or read book Atomic Layer Deposition Applications 2 written by Ana Londergan and published by The Electrochemical Society. This book was released on 2007 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue gives an overview of the cutting edge research in the various areas where Atomic Layer Deposition (ALD) can be used, enabling the identification of issues, challenges, and areas where further research is needed. Contributions include: Memory applications, Interconnects and contacts, ALD Productivity enhancement and precursor development, ALD for optical and photonic applications, and Applications in other areas, such as MEMs, nanotechnology, fabrication of sensors and catalysts, etc.

Download or read book Atomic Layer Deposition Applications 7 written by J. W. Elam and published by The Electrochemical Society. This book was released on 2011 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Atomic Layer Deposition for Nanotechnology written by Arthur Sherman and published by . This book was released on 2008 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Thin Films Atomic Layer Deposition and 3D Printing written by Kingsley Ukoba and published by CRC Press. This book was released on 2023-11-29 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thin Films, Atomic Layer Deposition, and 3D Printing explains the concept of thin films, atomic layers deposition, and the Fourth Industrial Revolution (4IR) with an aim to illustrate existing resources and give a broader perspective of the involved processes as well as provide a selection of different types of 3D printing, materials used for 3D printing, emerging trends and applications, and current top-performing 3D printers using different technologies. It covers the concept of the 4IR and its role in current and future human endeavors for both experts/nonexperts. The book includes figures, diagrams, and their applications in real-life situations. Features: Provides comprehensive material on conventional and emerging thin film, atomic layer, and additive technologies. Discusses the concept of Industry 4.0 in thin films technology. Details the preparation and properties of hybrid and scalable (ultra) thin materials for advanced applications. Explores detailed bibliometric analyses on pertinent applications. Interconnects atomic layer deposition and additive manufacturing. This book is aimed at researchers and graduate students in mechanical, materials, and metallurgical engineering.

Download or read book Atomic Layer Deposition for Semiconductors written by Cheol Seong Hwang and published by Springer Science & Business Media. This book was released on 2013-10-18 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering thorough coverage of atomic layer deposition (ALD), this book moves from basic chemistry of ALD and modeling of processes to examine ALD in memory, logic devices and machines. Reviews history, operating principles and ALD processes for each device.

Download or read book Chemistry of Atomic Layer Deposition written by Seán Thomas Barry and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-11-08 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will help chemists and non-chemists alike understand the fundamentals of surface chemistry and precursor design, and how these precursors drive the processes of atomic layer deposition, and how the surface-precursor interaction governs atomic layer deposition processes. The underlying principles in atomic layer deposition rely on the chemistry of a precursor with a surface.

Download or read book A Multiscale Model for an Atomic Layer Deposition Process written by Vivek Hari Dwivedi and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: