An efficient modeling approach for substrate noise coupling analysis with multiple contacts in heavily doped CMOS processes

A computationally efficient and accurate substrate noise coupling model for multiple contacts in heavily doped CMOS processes is presented and validated with simulations and experimental data. The model is based on Z parameters that are scalable with contact separation and size. This results in fast extraction of substrate resistances for large circuit examples. The Z-parameter model can be readily extracted from three dimensional simulations or measured data. Extensions of the model to lightly doped substrates are also presented. Several examples demonstrate that this approach can be orders of magnitude faster than currently available techniques for substrate resistance extraction. The computed substrate resistances are in close agreement with the numerical simulations, with a maximum error less than 10%

Robust and Efficient Uncertainty Quantification and Validation of RFIC Isolation

Modern communication and identification products impose demanding constraints on reliability of components. Due to this statistical constraints more and more enter optimization formulations of electronic products. Yield constraints often require efficient sampling techniques to obtain uncertainty quantification also at the tails of the distributions. These sampling techniques should outperform standard Monte Carlo techniques, since these latter ones are normally not efficient enough to deal with tail probabilities. One such a technique, Importance Sampling, has successfully been applied to optimize Static Random Access Memories (SRAMs) while guaranteeing very small failure probabilities, even going beyond 6-sigma variations of parameters involved. Apart from this, emerging uncertainty quantifications techniques offer expansions of the solution that serve as a response surface facility when doing statistics and optimization. To efficiently derive the coefficients in the expansions one either has to solve a large number of problems or a huge combined problem. Here parameterized Model Order Reduction (MOR) techniques can be used to reduce the work load. To also reduce the amount of parameters we identify those that only affect the variance in a minor way. These parameters can simply be set to a fixed value. The remaining parameters can be viewed as dominant. Preservation of the variation also allows to make statements about the approximation accuracy obtained by the parameter-reduced problem. This is illustrated on an RLC circuit. Additionally, the MOR technique used should not affect the variance significantly. Finally we consider a methodology for reliable RFIC isolation using floor-plan modeling and isolation grounding. Simulations show good comparison with measurements

Phase-field-crystal models for condensed matter dynamics on atomic length and diffusive time scales: an overview

Here, we review the basic concepts and applications of the phase-field-crystal (PFC) method, which is one of the latest simulation methodologies in materials science for problems, where atomic- and microscales are tightly coupled. The PFC method operates on atomic length and diffusive time scales, and thus constitutes a computationally efficient alternative to molecular simulation methods. Its intense development in materials science started fairly recently following the work by Elder et al. [Phys. Rev. Lett. 88 (2002), p. 245701]. Since these initial studies, dynamical density functional theory and thermodynamic concepts have been linked to the PFC approach to serve as further theoretical fundaments for the latter. In this review, we summarize these methodological development steps as well as the most important applications of the PFC method with a special focus on the interaction of development steps taken in hard and soft matter physics, respectively. Doing so, we hope to present today's state of the art in PFC modelling as well as the potential, which might still arise from this method in physics and materials science in the nearby future.Comment: 95 pages, 48 figure

Accurate a priori signal integrity estimation using a multilevel dynamic interconnect model for deep submicron VLSI design.

A multilevel dynamic interconnect model was derived for accurate a priori signal integrity estimates. Cross-talk and delay estimations over interconnects in deep submicron technology were analyzed systematically using this model. Good accuracy and excellent time-efficiency were found compared with electromagnetic simulations. We aim to build a dynamic interconnect library with this model to facilitate the interconnect issues for future VLSI design

Charge-based silicon quantum computer architectures using controlled single-ion implantation

We report a nanofabrication, control and measurement scheme for charge-based silicon quantum computing which utilises a new technique of controlled single ion implantation. Each qubit consists of two phosphorus dopant atoms ~50 nm apart, one of which is singly ionized. The lowest two energy states of the remaining electron form the logical states. Surface electrodes control the qubit using voltage pulses and dual single electron transistors operating near the quantum limit provide fast readout with spurious signal rejection. A low energy (keV) ion beam is used to implant the phosphorus atoms in high-purity Si. Single atom control during the implantation is achieved by monitoring on-chip detector electrodes, integrated within the device structure, while positional accuracy is provided by a nanomachined resist mask. We describe a construction process for implanted single atom and atom cluster devices with all components registered to better than 20 nm, together with electrical characterisation of the readout circuitry. We also discuss universal one- and two-qubit gate operations for this architecture, providing a possible path towards quantum computing in silicon.Comment: 9 pages, 5 figure