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Chemical Vapour Deposition (CVD) is an essential technique for growing metallic films, and it has been around for over a century. Today, the range of applications for CVD has expanded to include electrical, optoelectronic, optical, mechanical, and chemical materials, among others. To understand the growth processes and improve product characteristics, researchers rely on quantum mechanical calculations, particularly density functional theory (DFT).

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Explore how to use BIOVIA Pipeline Pilot to analyze the Titanic dataset, available on Kaggle.com Pipeline Pilot allows users to manage and analyze complex scientific data by integrating data from multiple sources and creating customized scientific workflows.

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Learn how missing data can affect the accuracy of machine learning models and how to enhance the data by imputing missing values using Pipeline Pilot.

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By investing in the future of the workforce, Dassault Systèmes drives innovation, growth, and development and positions itself as a leader in the software industry.

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Access to healthy, unpolluted water is a fundamental human right. Unfortunately, there are many water quality problems, and technological progress often creates new ones.

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Discover how advancements in battery materials can improve the efficiency and performance of the batteries that power our modern world.

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Recycling plastic is a crucial aspect of sustainability, but it remains a challenging task. While mechanical recycling is the most common form, it leads to products with degraded properties.

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Plastic films used in food packaging are made of multiple layers of polymers, each with its unique properties. As a result, up to 40% of pristine film is discarded as industrial waste during the manufacturing process. However, researchers from the University of Wisconsin-Madison, Department of Energy, and Amcor Flexibles have developed a process called STRAP, which uses different solvent washes to dissolve and recover the pure polymers from the discarded film.

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At Dassault Systèmes, we believe that Virtual Twins hold enormous potential in leveraging machine learning to tackle complex technical problems. Our focus on models has been a key aspect of our technology for many years.

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To keep up with the growing demand in the wake of diminishing arable land, exacerbated further by a changing climate, providing sustainable solutions in the agriculture sector behooves novel approaches. A successful second green revolution will entail technologies such as Artificial Intelligence (AI), Machine learning (ML) and Internet of Things (IoTs).

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