A Multi-scale Model for Copper Dishing in Chemical-Mechanical Polishing

The present success in the manufacture of multi-layer interconnects in ultra-large-scale integration is largely due to the acceptable planarization capabilities of the chemical-mechanical polishing (CMP) process. In the past decade, copper has emerged as the preferred interconnect material. The greatest challenge in Cu CMP at present is the control of wafer surface non-uniformity at various scales. As the size of a wafer has increased to 300 mm, the wafer-level non-uniformity has assumed critical importance. Moreover, the pattern geometry in each die has become quite complex due to a wide range of feature sizes and multi-level structures. Therefore, it is important to develop a non-uniformity model that integrates wafer-, die- and feature-level variations into a unified, multi-scale dielectric erosion and Cu dishing model. In this paper, a systematic way of characterizing and modeling dishing in the single-step Cu CMP process is presented. The possible causes of dishing at each scale are identified in terms of several geometric and process parameters. The feature-scale pressure calculation based on the step-height at each polishing stage is introduced. The dishing model is based on pad elastic deformation and the evolving pattern geometry, and is integrated with the wafer- and die-level variations. Experimental and analytical means of determining the model parameters are outlined and the model is validated by polishing experiments on patterned wafers. Finally, practical approaches for minimizing Cu dishing are suggested.

A Multi-scale Model for Copper Dishing in Chemical-Mechanical Polishing

The present success in the manufacture of multi-layer interconnects in ultra-large-scale integration is largely due to the acceptable planarization capabilities of the chemical-mechanical polishing (CMP) process. In the past decade, copper has emerged as the preferred interconnect material. The greatest challenge in Cu CMP at present is the control of wafer surface non-uniformity at various scales. As the size of a wafer has increased to 300 mm, the wafer-level non-uniformity has assumed critical importance. Moreover, the pattern geometry in each die has become quite complex due to a wide range of feature sizes and multi-level structures. Therefore, it is important to develop a non-uniformity model that integrates wafer-, die- and feature-level variations into a unified, multi-scale dielectric erosion and Cu dishing model. In this paper, a systematic way of characterizing and modeling dishing in the single-step Cu CMP process is presented. The possible causes of dishing at each scale are identified in terms of several geometric and process parameters. The feature-scale pressure calculation based on the step-height at each polishing stage is introduced. The dishing model is based on pad elastic deformation and the evolving pattern geometry, and is integrated with the wafer- and die-level variations. Experimental and analytical means of determining the model parameters are outlined and the model is validated by polishing experiments on patterned wafers. Finally, practical approaches for minimizing Cu dishing are suggested.

Psychometric Properties of the Inventário Dimensional Clínico da Personalidade (IDCP) using the Rating Scale Model

The aim of this study was to evaluate the performance of the Dimensional Clinical Personality Inventory (DCPI) using Rasch-based person and item analysis. 1281 participants were recruited, between 18 and 90 years of age (M=26.64; SD=8.94), 431 men (33.6%) and 127 (9.9%) patients diagnosed with axis I disorders and/or axis II according to DSM-IV-TR. Results indicated the IDCP scales performed reasonably well, and the usefulness of the analyses presented, demonstrate the Rasch model’s applicability for clinical applications. Among the important tools offered by the Rasch model, we explore the use of the person-item map, which visually presents the intuitively understandable psychological construct along the dimensional scale of the instrument.

Nest Boxes Facilitate Local-Scale Conservation of Common Goldeneye (Bucephala clangula) and Bufflehead (Bucephala albeola) in Alberta, Canada

We tested the general predictions of increased use of nest boxes and positive trends in local populations of Common Goldeneye (Bucephala clangula) and Bufflehead (Bucephala albeola) following the large-scale provision of nest boxes in a study area of central Alberta over a 16-year period. Nest boxes were rapidly occupied, primarily by Common Goldeneye and Bufflehead, but also by European Starling (Sturnus vulgaris). After 5 years of deployment, occupancy of large boxes by Common Goldeneye was 82% to 90% and occupancy of small boxes by Bufflehead was 37% to 58%. Based on a single-stage cluster design, experimental closure of nest boxes resulted in significant reductions in numbers of broods and brood sizes produced by Common Goldeneye and Bufflehead. Occurrence and densities of Common Goldeneye and Bufflehead increased significantly across years following nest box deployment at the local scale, but not at the larger regional scale. Provision of nest boxes may represent a viable strategy for increasing breeding populations of these two waterfowl species on landscapes where large trees and natural cavities are uncommon but wetland density is high.

Distribution of stream macroalgal communities from the mid-western region of Paraná state, southern Brazil: importance of local scale variation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Local scale finite element modelling of stack pollutant emissions

Congresos y conferencias

Stochastic local volatility model for fx markets

Questa tesi verte sullo studio di un modello a volatilità stocastica e locale, utilizzato per valutare opzioni esotiche nei mercati dei cambio. La difficoltà nell'implementare un modello di tal tipo risiede nella calibrazione della leverage surface e uno degli scopi principali di questo lavoro è quello di mostrarne la procedura.

MODELING DYNAMICS OF OZONE AND NITROGEN OXIDES AT SUMMIT, GREENLAND WITH A 1-D PROCESS-SCALE MODEL

This work presents a 1-D process scale model used to investigate the chemical dynamics and temporal variability of nitrogen oxides (NOx) and ozone (O3) within and above snowpack at Summit, Greenland for March-May 2009 and estimates surface exchange of NOx between the snowpack and surface layer in April-May 2009. The model assumes the surface of snowflakes have a Liquid Like Layer (LLL) where aqueous chemistry occurs and interacts with the interstitial air of the snowpack. Model parameters and initialization are physically and chemically representative of snowpack at Summit, Greenland and model results are compared to measurements of NOx and O3 collected by our group at Summit, Greenland from 2008-2010. The model paired with measurements confirmed the main hypothesis in literature that photolysis of nitrate on the surface of snowflakes is responsible for nitrogen dioxide (NO2) production in the top ~50 cm of the snowpack at solar noon for March – May time periods in 2009. Nighttime peaks of NO2 in the snowpack for April and May were reproduced with aqueous formation of peroxynitric acid (HNO4) in the top ~50 cm of the snowpack with subsequent mass transfer to the gas phase, decomposition to form NO2 at nighttime, and transportation of the NO2 to depths of 2 meters. Modeled production of HNO4 was hindered in March 2009 due to the low production of its precursor, hydroperoxy radical, resulting in underestimation of nighttime NO2 in the snowpack for March 2009. The aqueous reaction of O3 with formic acid was the major sync of O3 in the snowpack for March-May, 2009. Nitrogen monoxide (NO) production in the top ~50 cm of the snowpack is related to the photolysis of NO2, which underrepresents NO in May of 2009. Modeled surface exchange of NOx in April and May are on the order of 1011 molecules m-2 s-1. Removal of measured downward fluxes of NO and NO2 in measured fluxes resulted in agreement between measured NOx fluxes and modeled surface exchange in April and an order of magnitude deviation in May. Modeled transport of NOx above the snowpack in May shows an order of magnitude increase of NOx fluxes in the first 50 cm of the snowpack and is attributed to the production of NO2 during the day from the thermal decomposition and photolysis of peroxynitric acid with minor contributions of NO from HONO photolysis in the early morning.

Regulation of Phytoplankton Carbon to Chlorophyll Ratio By Light, Nutrients and Temperature in the Equatorial Pacific Ocean: A Basin-Scale Model

The complex effects of light, nutrients and temperature lead to a variable carbon to chlorophyll (C:Chl) ratio in phytoplankton cells. Using field data collected in the Equatorial Pacific, we derived a new dynamic model with a non-steady C:Chl ratio as a function of irradiance, nitrate, iron, and temperature. The dynamic model is implemented into a basin-scale ocean circulation-biogeochemistry model and tested in the Equatorial Pacific Ocean. The model reproduces well the general features of phytoplankton dynamics in this region. For instance, the simulated deep chlorophyll maximum (DCM) is much deeper in the western warm pool (similar to 100 m) than in the Eastern Equatorial Pacific (similar to 50 m). The model also shows the ability to reproduce chlorophyll, including not only the zonal, meridional and vertical variations, but also the interannual variability. This modeling study demonstrates that combination of nitrate and iron regulates the spatial and temporal variations in the phytoplankton C:Chl ratio in the Equatorial Pacific. Sensitivity simulations suggest that nitrate is mainly responsible for the high C:Chl ratio in the western warm pool while iron is responsible for the frontal features in the C:Chl ratio between the warm pool and the upwelling region. In addition, iron plays a dominant role in regulating the spatial and temporal variations of the C:Chl ratio in the Central and Eastern Equatorial Pacific. While temperature has a relatively small effect on the C:Chl ratio, light is primarily responsible for the vertical decrease of phytoplankton C:Chl ratio in the euphotic zone.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

Decoding urban landscapes through the analysis of place names and imaginaries at a local scale.

Toponomastics is increasingly interested in the subjective role of place names in quotidian life. In the frame of Urban Geography, the interest in this matter is currently growing, as the recently change in modes of habitation has urged our discipline to find new ways of exploring the cities. In this context, the study of how name's significance is connected to a urban society constitutes a very interesting approach. We believe in the importance of place names as tools for decoding urban areas and societies at a local-scale. This consideration has been frequently taken into account in the analysis of exonyms, although in their case they are not exempt of political and practical implications that prevail over the tool function. The study of toponomastic processes helps us understanding how the city works, by analyzing the liaison between urban landscape, imaginaries and toponyms which is reflected in the scarcity of some names, in the biased creation of new toponyms and in the pressure exercised over every place name by tourists, residents and local government for changing, maintaining or eliminating them. Our study-case, Toledo, is one of the oldest cities in Spain, full of myths, stories and histories that can only be understood combined with processes of internal evolution of the city linked to the arrival of new residents and the more and more notorious change of its historical landscape. At a local scale, we are willing to decode the information which is contained in its toponyms about its landscape and its society.