This thesis transports you to a wonderful and fascinating small-scale world and tells you the origin of several new phenomena. The investigative tool is the improved discrete dislocation-based multi-scale approaches, bridging the continuum modeling and atomistic simulation. Mechanism-based theoretical models are put forward to conveniently predict the mechanical responses and defect evolution. The findings presented in this thesis yield valuable new guidelines for microdevice design, reliability analysis and defect tuning.
Dislocation Based Crystal Plasticity: Theory and Computation at Micron and Submicron Scale provides a comprehensive introduction to the continuum and discreteness dislocation mechanism-based theories and computational methods of crystal plasticity at the micron and submicron scale. Sections cover the fundamental concept of conventional crystal plasticity theory at the macro-scale without size effect, strain gradient crystal plasticity theory based on Taylar law dislocation, mechanism at the mesoscale, phase-field theory of crystal plasticity, computation at the submicron scale, including single crystal plasticity theory, and the discrete-continuous model of crystal plasticity with three-dimensional discrete dislocation dynamics coupling finite element method (DDD-FEM). Three kinds of plastic deformation mechanisms for submicron pillars are systematically presented. Further sections discuss dislocation nucleation and starvation at high strain rate and temperature effect for dislocation annihilation mechanism. - Covers dislocation mechanism-based crystal plasticity theory and computation at the micron and submicron scale - Presents crystal plasticity theory without size effect - Deals with the 3D discrete-continuous (3D DCM) theoretic and computational model of crystal plasticity with 3D discrete dislocation dynamics (3D DDD) coupling finite element method (FEM) - Includes discrete dislocation mechanism-based theory and computation at the submicron scale with single arm source, coating micropillar, lower cyclic loading pillars, and dislocation starvation at the submicron scale
Machine Learning for Low-Latency Communications presents the principles and practice of various deep learning methodologies for mitigating three critical latency components: access latency, transmission latency, and processing latency. In particular, the book develops learning to estimate methods via algorithm unrolling and multiarmed bandit for reducing access latency by enlarging the number of concurrent transmissions with the same pilot length. Task-oriented learning to compress methods based on information bottleneck are given to reduce the transmission latency via avoiding unnecessary data transmission. Lastly, three learning to optimize methods for processing latency reduction are given which leverage graph neural networks, multi-agent reinforcement learning, and domain knowledge. Low-latency communications attracts considerable attention from both academia and industry, given its potential to support various emerging applications such as industry automation, autonomous vehicles, augmented reality and telesurgery. Despite the great promise, achieving low-latency communications is critically challenging. Supporting massive connectivity incurs long access latency, while transmitting high-volume data leads to substantial transmission latency. - Presents the challenges and opportunities of leveraging data and model-driven machine learning methodologies for achieving low-latency communications - Explains the principles and practices of modern machine learning algorithms (e.g., algorithm unrolling, multiarmed bandit, graph neural network, and multi-agent reinforcement learning) for achieving low-latency communications - Gives design, modeling, and optimization methods for low-latency communications that apply appropriate learning methods to solve longstanding problems - Provides full details of the simulation setup and benchmarking algorithms, with downloadable code - Outlines future research challenges and directions
Dislocation Based Crystal Plasticity: Theory and Computation at Micron and Submicron Scale provides a comprehensive introduction to the continuum and discreteness dislocation mechanism-based theories and computational methods of crystal plasticity at the micron and submicron scale. Sections cover the fundamental concept of conventional crystal plasticity theory at the macro-scale without size effect, strain gradient crystal plasticity theory based on Taylar law dislocation, mechanism at the mesoscale, phase-field theory of crystal plasticity, computation at the submicron scale, including single crystal plasticity theory, and the discrete-continuous model of crystal plasticity with three-dimensional discrete dislocation dynamics coupling finite element method (DDD-FEM). Three kinds of plastic deformation mechanisms for submicron pillars are systematically presented. Further sections discuss dislocation nucleation and starvation at high strain rate and temperature effect for dislocation annihilation mechanism. - Covers dislocation mechanism-based crystal plasticity theory and computation at the micron and submicron scale - Presents crystal plasticity theory without size effect - Deals with the 3D discrete-continuous (3D DCM) theoretic and computational model of crystal plasticity with 3D discrete dislocation dynamics (3D DDD) coupling finite element method (FEM) - Includes discrete dislocation mechanism-based theory and computation at the submicron scale with single arm source, coating micropillar, lower cyclic loading pillars, and dislocation starvation at the submicron scale
This thesis transports you to a wonderful and fascinating small-scale world and tells you the origin of several new phenomena. The investigative tool is the improved discrete dislocation-based multi-scale approaches, bridging the continuum modeling and atomistic simulation. Mechanism-based theoretical models are put forward to conveniently predict the mechanical responses and defect evolution. The findings presented in this thesis yield valuable new guidelines for microdevice design, reliability analysis and defect tuning.
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