8 research outputs found

    DÉVELOPPEMENT, INTÉGRATION ET MODÉLISATION DE COMPOSANTS PASSIFS INTÉGRÉS EN COUCHES MINCES DANS UNE FILIÈRE CMOS

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    Ces travaux ont été réalisés dans le cadre d'une CIFRE avec MHS (Nantes)In this thesis we present the development of a high density integrated passive technology. The aim is to integrate thin film passive components in the Back End of Line of an industrial CMOS technology by introducing limited additional steps. We propose to report all the electrical performance constraints of the components on the material characteristics. The three main steps to develop the integrated passives in 0.5µ-CMOS technology are presented. The first level of our study is focused closer to the material, and is applied in the case of MIM capacitors. The electrical characterization of TixTayO dielectrics thin film is performed from MOS capacitors to validate the material electrical performances before starting its process integration to realize the MIM capacitors. Secondly, the interface between the material and the component is studied. Based on the thin film resistors, we propose an integration schema for TiNxOy resistive thin film in the metallization layers of the CMOS technology. The electrical characteristics of the resistors are measured and validated via experiments. The last step of the study is focused on the integrated component level and its electrical modeling. a new scalable, physical and analytical enhanced simple-π model of spiral inductors in CMOS technology is proposed. The entire model elements are determined under quasi-static approximations to obtain a fully scalable model from the geometrical and technological properties of the inductors. In this thesis, the bases for the development of integrated passive component in a CMOS technology are presented.Nous proposons dans cette thèse de développer une technologie de composants passifs dans les niveaux de métallisation d’une filière industrielle en effectuant un report des contraintes en performances sur les propriétés des matériaux utilisés en couches minces. Nous présentons la démarche adoptée à travers trois étapes clés du développement des composants passifs intégrés dans une technologie CMOS 0.5µm. Les résultats de chacun de ces niveaux sont présentés et illustrés ici à travers un type de composant passif donné. Le premier niveau se place au plus proche du matériau, et est appliqué au cas des condensateurs MIM. La caractérisation électrique de couches minces diélectriques de TixTayO est effectuée à partir de capacités MOS pour valider les performances du diélectrique avant son intégration dans la filière pour réaliser les condensateurs MIM. Dans un second temps, l’analyse est portée à l’interface entre le matériau et le composant, et nous nous intéressons alors aux résistances intégrées. Un schéma d’intégration des couches minces résistives de TiNxOy dans les niveaux d’interconnexions de la filière CMOS est proposé et testé afin d’évaluer les caractéristiques électriques des résistances. Enfin, le dernier niveau d’analyse met l’accent sur le composant intégré et en particulier sur sa représentation électrique. Dans cette dernière étape, nous développons un modèle d’échelle d’inductances spirales basé sur un circuit localisé, et dont les éléments peuvent-être évalués analytiquement à partir des paramètres géométriques et des caractéristiques de la technologie. Ce travail de recherche cherche donc à fournir une vue d’ensemble sur le développement d’une technologie de composants passifs en CMOS

    A unified analytical and scalable lumped model of RF CMOS spiral inductors based on electromagnetic effects and circuit analysis

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    International audienceAn enhanced scalable compact model for on-chip RF CMOS spiral inductors is presented. By considering layout and technology parameters, under quasi-static approximation, the model elements are all expressed analytically and based on electromagnetic effects. Frequency dependent behavior of CMOS spiral such as skin and proximity effects, and decrease of equivalent series resistance due to substrate coupling is considered. The model is suitable to be easily implemented in design kits by foundry and provides interesting accuracy to be used by CMOS Radio Frequency Integrated Circuits designers

    A deep learning-based framework for predicting survival-associated groups in colon cancer by integrating multi-omics and clinical data

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    Precise prognostic classification of patients and identifying survival subgroups and their associated genes can be important clinical references when designing treatment strategies for cancer patients. Multi-omics and data integration techniques are powerful tools to achieve this goal. This study aimed to introduce a machine learning method to integrate three types of biological data, and investigate the performance of two other methods, in identifying the survival dependency of patients. The data included TCGA RNA-seq gene expression, DNA methylation, and clinical data from 368 patients with colon cancer also we use an independent external validation data set, containing 232 samples. Three methods including, hyper-parameter optimized autoencoders (HPOAE), normal autoencoder, and penalized principal component analysis (PPCA) were used for simultaneous data integration and estimation under a COX hazards model. The HPOAE was thought to outperform other methods. The HPOAE had the Log Rank Mantel-Cox value of 14.27 ± 2, and a Breslow-Generalized Wilcoxon value of 13.13 ± 1. Ten miRNA, 11 methylated genes, and 28 mRNA all by (importance of marginal cutoff > 0.95) were identified. The study demonstrated that hsa-miR-485-5p targets both ZMYM1 and tp53, the latter of which has been previously associated with cancer in numerous studies. Furthermore, compared to other methods, the HPOAE exhibited a greater capacity for identifying survival subgroups and the genes associated with them in patients with colon cancer. However, all of the results were obtained by computational methods, and clinical and experimental studies are needed to validate these results
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