HC Plastics News: Generally speaking, when scientists search for new materials for a specific purpose, they must rely on the experimental results of the selected materials. Now, they know that there are better solutions besides this. For example, can semiconductors provide higher efficiency for solar modules, are they more flexible than silicon wafers, what are the best catalysts for special chemical reactions, or how to coat surfaces for optimal thermal protection?
To make it easier to find answers to the typical questions that material scientists face in the future, eleven researchers from the Max Planck Institute hope to make better use of the opportunities offered by analyzing large amounts of data. To this end, they work with MaxNet through big data drives in materials science or simply BigMax.
If one day, it is possible to obtain material properties through theory, then you can save some time and money spent on experiments. The cooperation of MPG facilities is moving in this direction. (©Mopic/shutterstock)
Matthias Scheffler, director of the Fritz Haber Institute at the Max Planck Institute in Berlin, said: "So far, there are about 240,000 inorganic materials known as inorganic materials, but we know that the properties of the materials are less than 100. "Scheffler is co-founder of MaxNet, a cross-institutional alliance of materials science across the Max Planck Society. BigMax's goal is to make creative use of most of the already existing data and then make it the basis of research materials. In addition to the Fritz Haber Institute, there are 11 other MPG facilities under cooperation.
Big data model reveals new information
Peter Benner of the Max Planck Institute for Complex Technology System Dynamics in Magdeburg, Germany, explains: "Programs such as x-ray structural analysis or atom probe tomography provide millions of data per minute; For example, researchers can obtain data on the atomic configuration of solids. Although the amount of data in quantum mechanical analysis in solid state physics is huge, researchers can now draw conclusions from these data."
However, the new alliance aims to gain more insight from these data. Therefore, new methods will be developed and existing methods will be improved. Benner and Matthias Scheffler are working together on a new collaboration. He said: "The data on materials research poses a very specific challenge to computer algorithms." One of the central goals is to investigate data for specific structures or patterns, in addition to known content. We will also extract new information.
Therefore, he and Max Planck scientists hope that in the future, material researchers can gain new insights from existing data. The team aims to focus joint activities on five different topics. The goal is to be able to theoretically predict the properties of metals and alloys, determine the causal relationship between material properties and data structures, develop data diagnostic methods, convert experimental data into image information more quickly, and facilitate the design of polymer materials. Has a specific desired property. On the fifth topic, the team aims to continue to improve the material encyclopedia that has already begun. The New Materials Discovery Lab (NOMAD Center of Excellence) used the theoretical calculations as an entry in the encyclopedia.
The experimental data will now also be part of BigMax.
Before you can complete the dream of multidimensional material maps, simply look for the best materials. Although there is still a long way to go, Matthias Scheffler does not doubt that big data can help achieve this goal. Here, he saw a new paradigm in materials science, Scheffler said: “In the past, researchers have been able to research and develop models based on general theoretical understanding. I believe that the task of future big data analysis It is bound to search for structures and patterns in large amounts of data. Once we develop equations to describe them, we can apply them to materials we don't even analyze."
PS: In addition to the Fritz Haber Institute, there are 11 MPGs that are working together: Max Planck Institute for Complex Technology System Dynamics (Magdeburg), colloids and interfaces (Potsdam Gorm) , Microstructure Physics (Halle), Polymer Research (Mainz), Endocrine Research Institute (Düsseldorf), Biogeochemistry (Jena), Complex Systems Physics (Dresden), Material Structure With Dynamics (Hamburg), Intelligent Systems (Tubingen University) and Informatics (Saarbrücken) as well as Max Planck Computing and Data Facilities (Garching). 
Editor in charge: Wang Ning 12
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