Fine grain thermal modeling and experimental validation of 3D-ICs

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Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends where predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure-properties relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to "simply" support experimental work. This is illustrated by examples from several application areas on structural materials. This manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.Comment: 25 pages, 11 figures, review article accepted for publication in J. Mater. Sc

Steady state and transient thermal analysis of hot spots in 3D stacked ICs using dedicated test chips

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Heat conductivity of DNA double helix

Thermal conductivity of isolated single molecule DNA fragments is of importance for nanotechnology, but has not yet been measured experimentally. Theoretical estimates based on simplified (1D) models predict anomalously high thermal conductivity. To investigate thermal properties of single molecule DNA we have developed a 3D coarse-grained (CG) model that retains the realism of the full all-atom description, but is significantly more efficient. Within the proposed model each nucleotide is represented by 6 particles or grains; the grains interact via effective potentials inferred from classical molecular dynamics (MD) trajectories based on a well-established all-atom potential function. Comparisons of 10 ns long MD trajectories between the CG and the corresponding all-atom model show similar root-mean-square deviations from the canonical B-form DNA, and similar structural fluctuations. At the same time, the CG model is 10 to 100 times faster depending on the length of the DNA fragment in the simulation. Analysis of dispersion curves derived from the CG model yields longitudinal sound velocity and torsional stiffness in close agreement with existing experiments. The computational efficiency of the CG model makes it possible to calculate thermal conductivity of a single DNA molecule not yet available experimentally. For a uniform (polyG-polyC) DNA, the estimated conductivity coefficient is 0.3 W/mK which is half the value of thermal conductivity for water. This result is in stark contrast with estimates of thermal conductivity for simplified, effectively 1D chains ("beads on a spring") that predict anomalous (infinite) thermal conductivity. Thus, full 3D character of DNA double-helix retained in the proposed model appears to be essential for describing its thermal properties at a single molecule level.Comment: 16 pages, 12 figure

Development of the constitutive model of an Al–Mg alloy during the solidification and hot tearing prediction using FEM thermal stress analysis

早大学位記番号:新7486早稲田大

Fatigue modeling of nano-structured chip-to-package interconnections

Driven by the need for increase in system¡¯s functionality and decrease in the feature size, International Technology Roadmap for Semi-conductors has predicted that integrated chip packages will have interconnections with I/O pitch of 90 nm by the year 2018. Lead-based solder materials that have been used for many decades will not be able to satisfy the thermal mechanical requirements of these fines pitch packages. Of all the known interconnect technologies, nanostructured copper interconnects are the most promising for meeting the high performance requirements of next generation devices. However, there is a need to understand their material properties, deformation mechanisms and microstructural stability. The goal of this research is to study the mechanical strength and fatigue behavior of nanocrystalline copper using atomistic simulations and to evaluate their performance as nanostructured interconnect materials. The results from the crack growth analysis indicate that nanocrystalline copper is a suitable candidate for ultra-fine pitch interconnects applications. This study has also predicts that crack growth is a relatively small portion of the total fatigue life of interconnects under LCF conditions. The simulations result conducted on the single crystal copper nano-rods show that its main deformation mechanism is the nucleation of dislocations. In the case of nanocrystalline copper, material properties such as elastic modulus and yield strength have been found to be dependent on the grain size. Furthermore, it has been shown that there is competition between the dislocation activity and grain boundary sliding as the main deformation mode This research has shown that stress induced grain coarsening is the main reason for loss of mechanical performance of nanocrystalline copper during cyclic loading. Further, the simulation results have also shown that grain growth during fatigue loading is assisted by the dislocation activity and grain boundary migration. A fatigue model for nanostructured interconnects has been developed in this research using the above observations Lastly, simulations results have shown that addition of the antimony into nanocrystalline copper will not only increase the microstructure stability, it will also increase its strength.Ph.D.Committee Chair: Rao R. Tummala; Committee Co-Chair: Ashok Saxena; Committee Member: Karl Jacob; Committee Member: Suresh Sitaraman; Committee Member: Thomas H. Sanders, J

Modeling, Characterizing and Reconstructing Mesoscale Microstructural Evolution in Particulate Processing and Solid-State Sintering

abstract: In material science, microstructure plays a key role in determining properties, which further determine utility of the material. However, effectively measuring microstructure evolution in real time remains an challenge. To date, a wide range of advanced experimental techniques have been developed and applied to characterize material microstructure and structural evolution on different length and time scales. Most of these methods can only resolve 2D structural features within a narrow range of length scale and for a single or a series of snapshots. The currently available 3D microstructure characterization techniques are usually destructive and require slicing and polishing the samples each time a picture is taken. Simulation methods, on the other hand, are cheap, sample-free and versatile without the special necessity of taking care of the physical limitations, such as extreme temperature or pressure, which are prominent issues for experimental methods. Yet the majority of simulation methods are limited to specific circumstances, for example, first principle computation can only handle several thousands of atoms, molecular dynamics can only efficiently simulate a few seconds of evolution of a system with several millions particles, and finite element method can only be used in continuous medium, etc. Such limitations make these individual methods far from satisfaction to simulate macroscopic processes that a material sample undergoes up to experimental level accuracy. Therefore, it is highly desirable to develop a framework that integrate different simulation schemes from various scales to model complicated microstructure evolution and corresponding properties. Guided by such an objective, we have made our efforts towards incorporating a collection of simulation methods, including finite element method (FEM), cellular automata (CA), kinetic Monte Carlo (kMC), stochastic reconstruction method, Discrete Element Method (DEM), etc, to generate an integrated computational material engineering platform (ICMEP), which could enable us to effectively model microstructure evolution and use the simulated microstructure to do subsequent performance analysis. In this thesis, we will introduce some cases of building coupled modeling schemes and present the preliminary results in solid-state sintering. For example, we use coupled DEM and kinetic Monte Carlo method to simulate solid state sintering, and use coupled FEM and cellular automata method to model microstrucutre evolution during selective laser sintering of titanium alloy. Current results indicate that joining models from different length and time scales is fruitful in terms of understanding and describing microstructure evolution of a macroscopic physical process from various perspectives.Dissertation/ThesisDoctoral Dissertation Materials Science and Engineering 201

Skybridge: A New Nanoscale 3-D Computing Framework for Future Integrated Circuits

Continuous scaling of CMOS has been the major catalyst in miniaturization of integrated circuits (ICs) and crucial for global socio-economic progress. However, continuing the traditional way of scaling to sub-20nm technologies is proving to be very difficult as MOSFETs are reaching their fundamental performance limits [1] and interconnection bottleneck is dominating IC operational power and performance [2]. Migrating to 3-D, as a way to advance scaling, has been elusive due to inherent customization and manufacturing requirements in CMOS architecture that are incompatible with 3-D organization. Partial attempts with die-die [3] and layer-layer [4] stacking have their own limitations [5]. We propose a new 3-D IC fabric technology, Skybridge [6], which offers paradigm shift in technology scaling as well as design. We co-architect Skybridge’s core aspects, from device to circuit style, connectivity, thermal management, and manufacturing pathway in a 3-D fabric-centric manner, building on a uniform 3-D template. Our extensive bottom-up simulations, accounting for detailed material system structures, manufacturing process, device, and circuit parasitics, carried through for several designs including a designed microprocessor, reveal a 30-60x density, 3.5x performance/watt benefits, and 10x reduction in interconnect lengths vs. scaled 16-nm CMOS [6]. Fabric-level heat extraction features are found to be effective in managing IC thermal profiles in 3-D. This 3-D integrated fabric proposal overcomes the current impasse of CMOS in a manner that can be immediately adopted, and offers unique solution to continue technology scaling in the 21st century