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 sciences helps us acquire something we may call as ‘MetaData’. This data can help us accelerate material property prediction, conduct systematic searches through the space of possible materials to discover compounds with optimized properties, and even design new materials based on the properties we want.


The field of machine learning can be used extensively to collaborate with material sciences. Various real life applications of material informatics have helped us reach milestones where we could conduct Accelerated Discovery of the Polymer Blends for Cartilage Repair through Data-Mining Tools and Machine-Learning Algorithm which is a great leap for medical technologies as well. A lot of fields like architecture, civil engineering and manufacturing are benefitted from the research related to material informatics like A case study in biomimetic roofing: Moisture dissipation from leaf-shaped shingles.


A simple real life example of how we could retrieve information from materials for our own benefit is collecting data about a building’s moisture absorption. We all know how the buildings that we build suffer severe moisture problems in the rainy season. To minimize this problem the right composition of raw material in the building elements can be found out by cross matching a lot of data acquired from actual buildings that suffer from this problem. Although, to make this possible one would have to design an ultra-futuristic mechanism to accurately capture data of materials. 

In the same way various fields and domains of Biochemistry, Infrastructure, Textile Industries can benefit a lot based on material informatics.  










 The field of material informatics is not yet developed to a level of scientific certainty. A lot of aspects remain untapped and unexplored such as, Construction of material big data, implementation of machine learning, and platform design for materials. But active research in these fields is going to lead us towards a more systematic and clear view of how materials will be perceived in the future. The remaining tension between traditional materials development methodologies and the use of more computationally, machine learning, and analytics approaches will likely exist for some time as the materials industry overcomes some of the cultural barriers necessary to fully embrace such a futuristic technology.




Reference Links

https://pubs.rsc.org/en/content/articlelanding/2016/dt/c6dt01501h

https://towardsdatascience.com/getting-started-in-materials-informatics-41ee34d5ccfe

https://en.wikipedia.org/wiki/Materials_informatics

https://www.nature.com/articles/s41524-017-0056-5


NOTE:-

This blog is meant for Educational Purpose only .We do not own any Copyrights related to images and information , all the rights goes to their respective owners . The sole purpose of this blog is to Educate, Inspire, Empower and to create awareness in the viewers. The usage is non-commercial(Not For Profit) and we do not make any money from it.

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