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Showing posts from August, 2022

BEST SEMICONDUCTOR MATERIAL EVER FOUND?

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Talking about semiconductors the first and most widely used semiconductor that comes to our mind is silicon, but is silicon the best semiconductor? A team of researchers has discovered what the Massachusetts Institute of Technology calls the “best semiconductor material ever found,” even better than silicon, the material used in just about every computer chip on earth Let's know a little about semiconductors. A semiconductor is a solid substance that has a conductivity between that of an insulator and that of most metals, either due to the addition of an impurity or because of temperature effects. Silicon is one of the most abundant elements on Earth, and in its pure form, the material has become the foundation of much of modern technology, from solar cells to computer chips. But silicon’s properties as a semiconductor are far from ideal. For a thought, is there any other Semiconductor that is better than Silicon? Well, a recent study done by an MIT professor has proved that cubic

Material Informatics

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Welcome to today's Meta Monday Blog. As you have seen in the title, we will be talking about Material Informatics. At the first glance one may wonder what these terms mean together. Because we seem to know the meaning of both the terms individually. Material is nothing but the matter that is around us, and informatics is the handling and systematic study of information.  Like any other field combined with the field of information, Material informatics attempts to extensively use computational principles to minimise the time required to design a new material, to manage data related to materials with similar properties  Even though the topic deals with materials and the various aspects of data related to it and its synthesis, it does not keep itself limited to that and explores the domains of combinatorial chemistry, Process Modelling, materials property databases, materials data management and product life cycle management. The benefits of combining material sciences with data scien