Development of low temperature oxidation for crystalline silicon thin film transistor applications

Development of thin-film transistor (TFT) backplane technologies has traditionally been limited by the substrate materials used; amorphous (a-Si) or polycrystalline (p-Si) silicon on glass. These materials have lower carrier mobility as compared to traditional crystalline silicon CMOS technologies, resulting in performance limitations. In addition, thermal oxidation is not a viable option for two reasons: oxidation on non-crystalline silicon is non-uniform, and the temperature limitations of the glass, 600 °C, prevents any appreciable SiO2 growth. This constrains the potential for a high-quality Si-SiO2 interface necessary for aggressive scaling. Corning Incorporated has developed a new Silicon-on-Glass (SiOG) substrate material addressing some of these limitations. The crystalline silicon layer allows for high carrier mobility and a uniform surface for thermal oxidation; however the glass substrate remains incompatible with process temperatures above 600°C for traditional oxidation processes. Development of a fluorine-assisted thermal oxidation process enabling substantially higher growth rates is explored. Both NF3 and Ar/F2 additives have been shown to provide significant enhancement in growth rate, resulting in 10\u27s of nanometers of oxide at temperatures compatible with the SiOG substrate. The oxidation process has been optimized for applications such as a sacrificial layer for ion implantation screening, or a gate dielectric in TFT devices

Ai in the european manufacturing industry - a management guide

Artificial intelligence will have significant influence upon the manufacturing industry. Rapid disruption of existing processes will lead to a clear distinction between those who were able to adapt quickly enough and those that fall behind. There are several challenges e.g. data availability and IT-security that come along with AI,that managers must addressin advance to be prepared. The opportunities lie mainly in enhancing efficiency as well as fault detection and error recognition. Defininga framework and following certain success factors such as the definition of KPIs and developing a minimum viable product,increases the chances of success massivel

Thermal SiO2 Growth Rate Enhancement at Low Temperature Using an NF3 Additive

Thermally grown silicon oxide growth enhancement using small amounts of NF3 was investigated, examining both growth rate and interface quality. Low temperature results showed noted growth rate enhancement at temperatures above 7000 C. Interface quality showed significant improvement. Further enhancement is expected through modified chamber and equipment design

Redução do desmatamento na Amazônia por meio da intensificação da pecuária em assentamentos de reforma agrária

Dissertação (mestrado)—Universidade de Brasília, Centro de Desenvolvimento Sustentável, 2013.O presente trabalho analisa a contribuição da intensificação da pecuária em assentamen¬tos de reforma agrária para a redução do desmatamento na Amazônia. Parte do pressuposto de que a redução do desmatamento só será efetiva com geração de renda às populações que vivem na região. Para isso, a pecuária é uma atividade fundamental, pois é uma realidade inexorável em todos os tipos de propriedades na Amazônia, ocupando a maior parte da área já desmatada e ainda com baixos índices de produtividade. Ao mesmo tempo, observa-se nos últimos anos uma mudança no perfil do desmatamento na Amazônia, que apresenta ín¬dices crescentes de pequenos desmatamentos (pulverização do desmatamento), esgotando a efetividade da fiscalização isolada e urgindo a necessidade de políticas de fomento às ativi¬dades produtivas. Nesse sentido, é essencial priorizar a agricultura familiar, pois o segmento é fundamental para a produção de alimentos no Brasil e ações de fomento podem significar resultados efetivos também na agenda de redução da pobreza. Assim, o estudo centra sua análise nos assentamentos de reforma agrária do Território da Cidadania da Transamazônica e Xingu, estado do Pará. Propõe um modelo de intensificação pecuária factível para a região e compara a projeção da redução do desmatamento e de custos e benefícios entre a manu¬tenção do modelo de produção atual com o sistema de intensificação produtiva, no período de 2013 a 2020. Conclui-se que a intensificação pecuária nos assentamentos da região teria alto impacto na redução do desmatamento, com baixo custo por tonelada de carbono evitada (R 5,64 / tCO2eq). No entanto, para que os produtores adotem sistemas intensificados de produção, seria necessário uma intervenção governamental, através de créditos subsidiados ou compensações por serviços ambientais, como o mecanismo de REDD, uma vez que a manutenção do sistema extensivo e abertura de novas áreas para produção tem baixo custo. _______________________________________________________________________________________ ABSTRACTThis study analyzes the contribution of intensification of livestock in agrarian reform set¬tlements in reducing deforestation in the Amazon. It assumes that the reduction of defores¬tation will only be effective when it generates income for people living in the region. For this, cattle ranching is fundamental because it is an inexorable reality in all kinds of properties in the Amazon, occupying most of the deforested area and with low levels of productivity. At the same time, in recent years there has been a change in the profile of deforestation in the Ama¬zon, which has increasing rates of small deforestation, depleting the effectiveness of isolated supervision and urging the need for policies that promotes productive activities. Therefore, it is essential to prioritize the family farm because this segment is essential for food production in Brazil and fostering actions can mean effective results also on the agenda of poverty re¬duction. Thus, this study focuses its analysis on land reform settlements in the Transamazon and Xingu Territory, Pará State. It proposes a model of livestock intensification, feasible for the region and compares the projected deforestation reduction and costs and benefits between maintaining the current production model with the intensified production system in the period of 2013 to 2020.The conclusion is that the increased livestock settlements in the region would have high impact on reducing deforestation with low cost per ton of avoided carbon (U.S. 2.82 / tCO2eq). However, for producers to adopt intensified production systems, it would be neces¬sary a government intervention through subsidized credit or compensation for environmental services such as REDD mechanism, since the maintenance of the extensive system and the opening of new areas for production have low cost

Investigation of Material Supply Strategies to Increase Resilience in Matrix Production Systems

In order to design a resilient production system, individual system elements have to be flexible and adapt towards changing requirements. In contrast to the prevailing paradigm that complexity in production systems is reduced by standardisation or cycle production, complexity in resilient production systems offers great potential in terms of adaptiveness, robustness and anticipation. Within production control, matrix production is seen as a resilient and versatile system. Flexible routing between work-stations makes it possible to compensate for failures more quickly in the event of a malfunction, flexible logistics and control processes allow the workstations to be controlled and used in a job-specific manner. In this paper, challenges and operating principles of material supply strategies are investigated that have the biggest influence on the design of resilient processes in matrix production. Using a simulation model and scenarios from the automotive sector, the potentials, requirements and parameters for describing resilience are specified

The Journal of Microelectronic Research 2008

https://scholarworks.rit.edu/meec_archive/1016/thumbnail.jp

Development of a patient-specific atrial phantom model for planning and training of inter-atrial interventions

Article is accepted for publicationBackgroundSeveral authors have presented cardiac phantoms to mimic the particularities of the heart, making it suitable for medical training and surgical planning. Although the initial models were mainly focused on the ventricles, personalized phantoms of the atria were recently presented. However, such models are typically rigid, the atrial wall is not realistic and they are not compatible with ultrasound (US), being sub-optimal for planning/training of several interventions. MethodsIn this work, we propose a strategy to construct a patient-specific atrial model. Specifically, the target anatomy is generated using a computed tomography (CT) dataset and then constructed using a mold-cast approach. An accurate representation of the inter-atrial wall (IAS) was ensured during the model generation, allowing its application for IAS interventions. Two phantoms were constructed using different flexible materials (silicone and polyvinyl alcohol cryogel, PVA-C), which were then compared to assess their appropriateness for US acquisition and for the generation of complex anatomies. ResultsTwo experiments were set up to validate the proposed methodology. First, the accuracy of the manufacturing approach was assessed through the comparison between a post-production CT and the virtual references. The results proved that the silicone-based model was more accurate than the PVA-C-based one, with an error of 1.680.79, 1.36 +/- 0.94, 1.45 +/- 0.77mm for the left (LA) and right atria (RA) and IAS, respectively. Second, an US acquisition of each model was performed and the obtained images quantitatively and qualitatively assessed. Both models showed a similar performance in terms of visual evaluation, with an easy detection of the LA, RA, and the IAS. Furthermore, a moderate accuracy was obtained between the atrial surfaces extracted from the US and the ideal reference, and again a superior performance of the silicone-based model against the PVA-C phantom was observed. ConclusionsThe proposed strategy proved to be accurate and feasible for the correct generation of complex personalized atrial models.The authors acknowledge "Fundacao para a Ciencia e a Tecnologia" (FCT), in Portugal, and the European Social Found, European Union, for funding support through the "Programa Operacional Capital Humano" (POCH) in the scope of the PhD grants SFRH/BD/95438/2013 (P. Morais) and SFRH/BD/93443/2013 (S. Queiros).Authors gratefully acknowledge the funding of Projects NORTE-01-0145-FEDER-000013 and NORTE-01-0145-FEDER-000022, cofinanced by "Programa Operacional Regional do Norte" (NORTE2020), through "Fundo Europeu de Desenvolvimento Regional" (FEDER).info:eu-repo/semantics/publishedVersio

Labeling lateral prefrontal sulci using spherical data augmentation and context-aware training

The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due to the scarcity of manual/well-defined annotations and their large neuroanatomical variability. In this paper, we present an automated framework for regional labeling of both primary/secondary and tertiary sulci of the dorsal portion of lateral prefrontal cortex (LPFC) using spherical convolutional neural networks. We propose two core components that enhance the inference of sulcal labels to overcome such large neuroanatomical variability: (1) surface data augmentation and (2) context-aware training. (1) To take into account neuroanatomical variability, we synthesize training data from the proposed feature space that embeds intermediate deformation trajectories of spherical data in a rigid to non-rigid fashion, which bridges an augmentation gap in conventional rotation data augmentation. (2) Moreover, we design a two-stage training process to improve labeling accuracy of tertiary sulci by informing the biological associations in neuroanatomy: inference of primary/secondary sulci and then their spatial likelihood to guide the definition of tertiary sulci. In the experiments, we evaluate our method on 13 deep and shallow sulci of human LPFC in two independent data sets with different age ranges: pediatric (N=60) and adult (N=36) cohorts. We compare the proposed method with a conventional multi-atlas approach and spherical convolutional neural networks without/with rotation data augmentation. In both cohorts, the proposed data augmentation improves labeling accuracy of deep and shallow sulci over the baselines, and the proposed context-aware training offers further improvement in the labeling of shallow sulci over the proposed data augmentation. We share our tools with the field and discuss applications of our results for understanding neuroanatomical-functional organization of LPFC and the rest of cortex (https://github.com/ilwoolyu/SphericalLabeling). ?? 2021 The Author(s