The corner effect is known as a leakage current enhancement at the edges of the active areas in the shallow trench isolated CMOS transistors. It usually deterio rates the transistor performance. In this work, the corner effect for FinFET tra nsistors with the minimum feature size of 50 nm is investigated by coupled three -dimensional process and device simulation. In contrast to earlier CMOS generati ons, the corner effect in small size FinFETs for typical device parameters does not lead to an additional leakage current and therefore does not deteriorate the FinFET transistor performance. This holds for both double and triple gate Fin FETs

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Abstract-Process variations increasingly challenge the manufacturability of advanced devices and the yield of integrated circuits. Technology computer-aided design (TCAD) has the potential to make key contributions to minimize this problem, by assessing the impact of certain variations on the device, circuit, and system. In this way, TCAD can provide the information necessary to decide on investments in the processing level or the adoption of a more variation tolerant process flow, device architecture, or design on circuit or chip level. In this first of two consecutive papers, sources of process variations and the state of the art of related simulation tools are reviewed. An approach for hierarchical simulation of process variations including their correlations is presented. The second paper, also published in this issue, presents examples of simulation results obtained with this methodology.

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Neck shrivel is a physiological disorder of european plum (Prunus ·domestica L.) fruit, characterized by a shriveled pedicel end and a turgescent stylar end. Affected fruit are perceived as of poor quality. Little is known of the mechanistic basis of neck shrivel, but microcracking of the cuticle has been implicated. The objective of our study was to quantify transpiration through the skin surfaces of european plums with and without symptoms of neck shrivel. Cumulative transpiration increased linearly with time and was greater in the susceptible european plum cultivar Hauszwetsche Wolff with neck shrivel, compared with fruit of the same cultivar but without neck shrivel and compared with fruit of the nonsusceptible unnamed clone P5-112. Cumulative transpiration of epidermal skin segments (ES) excised from symptomatic 'Hauszwetsche Wolff' from near the pedicel end exceeded that from ES excised from near the stylar end. The permeance of ES from near the pedicel end of 'Hauszwetsche Wolff' with neck shrivel (12.4 ± 2.6 · 10 L4 mÁs L1 ) exceeded that of ES from near the stylar end (2.9 ± 0.4 · 10 L4 mÁs L1 ) 4.3-fold. However, in the clone P5-112, the same difference was only 1.6-fold (1.3 ± 0.8 · 10 L4 mÁs L1 vs. 0.8 ± 0.3 · 10 L4 mÁs L1 ). Microscopy revealed numerous microcracks near the pedicel end of symptomatic 'Hauszwetsche Wolff' fruit but markedly fewer microcracks near the stylar end. The microcracks near the pedicel end were oriented parallel to the pedicel/style axis, whereas those near the stylar end were randomly oriented. Juices extracted from near the pedicel end of susceptible cultivars had consistently more negative osmotic potentials [c S (e.g., for Doppelte Hauszwetsche L5.1 ± 0.1 MPa)] than those from near the stylar end (e.g., for Doppelte Hauszwetsche L4.0 ± 0.1 MPa) or that from fruit without symptoms of neck shrivel (e.g., for pedicel end and stylar scar regions of Doppelte Hauszwetsche L3.8 ± 0.1 vs. L3.3 ± 0.1 MPa, respectively). Our results indicate that increased transpiration through microcracks near the pedicel end may contribute to neck shrivel but that the causes of neck shrivel are likely more complex.

A numerically efficient model for the simulation of ion implantation doping profiles in silicon after pulsed plasma immersion ion implantation is suggested. The model is based on an analytical formula for the energy distribution of the ions extracted from the plasma and on the application of this energy distribution in a Monte-Carlo simulator for conventional ion implantation. The model is verified using examples of BF 3 and AsH 3 plasmas for p-type and n-type doping in silicon, respectively

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Advanced CMOS devices are increasingly affected by various kinds of process variations. Whereas the impact of statistical process variations such as Random Dopant Fluctuations has for several years been discussed in numerous publications, the effect of systematic process variations which result from non-idealities of the equipment used or from various layout issues has got much less attention. Therefore, in the first part of this paper, an overview of the sources of process variability is given. In order to assess and minimize the impact of variations on device and circuit performance, relevant systematic and statistical variations must be simulated in parallel, from equipment through process to device and circuit level. Correlations must be traced from their source to the final result. In this paper the approach implemented in the cooperative European project SUPERAID7 to reach these goals is presented.