Large data-assisted materials science

New materials feed and invent. Gorilla Glass has been widely used in smartphones; Kevlar began to enter consumer-grade products while saving lives; lithium-ion battery technology provides a power source for high energy consumption facilities. However, the development of new materials is an extremely time-consuming and laborious task.

Creating a new breakthrough material is an extremely time-consuming process – especially compared to the development cycle of products that rely on these materials. The Boeing 787 Dreamliner took less than 9 years from concept to commercial sailing, and Apple began designing iphone,2007 years from 2005. In contrast, the birth of new materials may take up to 20 years of research and experimentation.

Two years ago, http://www.aliyun.com/zixun/aggregation/10075.html "> The U.S. government to break through this technology bottleneck as the goal, set up a materials genome Initiative (MGI) project. MGI's goal is to drastically reduce the time and financial input needed to develop new materials. and the Human Genome Project is similar to the task of mapping our genes, and scientists want to use MGI to find out the broad effects of the interactions between elements on the type and nature of the material. Based on this knowledge, scientists and engineers will have the hope of "customizing" the corresponding materials for different applications in shorter cycles.

The number of permutations and combinations among elements is numerous, and most of them are meaningless to us. Trying to exhaust these permutations and combinations in the lab is completely impractical. So, some of MGI's teams have started to use the power of large data to simulate all the possibilities, and then analyze the data to explore the potential direction.

Since its establishment, MGI has facilitated the cooperation of a number of third-party projects. Among them are materials project from MIT and Clean Energy Project at Harvard. These two plans seek different answers with similar theoretical foundations. The former is concentrated on inorganic solids, especially battery material, while the latter's clean Energy Program centers on molecular materials that can be used in solar cells. Both of them use the density functional theory (density functional germ) to predict the actual properties of the simulated material model.

Material Project, MIT, was founded about 8 years ago with the help of Professor Gerbrand Ceder. As a consultant to many companies, Ceder has accumulated a lot of results. But cooperation with a handful of companies has kept the valuable data closed. "If we provide this data to everyone, people will create a lot of amazing results, and that's materials Project," he said. Currently, the MIT database holds about 100,000 known or theoretical material information. In order to give full play to the role of these data in the development of new materials, MIT scholars use manual screening and machine learning to explore the various chemical laws.

Similarly, the Harvard Clean Energy Program uses a combination of manual and machine to explore its database. The program begins with a validation experiment on the concept of organic solar cell materials. Scholars have calculated the performance of about 15 new mixtures in the real world in a completely virtual scenario. The final result of the simulation is a new material with super electrical properties. This is only a graduate student through a number of experiments to draw the results, imagine if from a volunteer army to borrow their computing power, the results will be magnified?

This is the strategy now adopted by the Clean Energy Program: Anyone can use a computer to download a degree to calculate and return the results. With this discretionary resource, academics have calculated millions of potential combinations – this is just the beginning. "The project has entered a very interesting phase," Dr. Hachmann said, "and it is almost time for us to reap the fruits of our hard work." "At the moment, Harvard has published 2.3 million combinations of mixtures on the web for everyone to study." Although the data are designed to help with solar cell development, scientists can also use any valuable information to assist other research. MIT also has a web portal for people to read materials Project data.

Ceder hopes that the great MGI plan will fulfill its mission. In fact, Ceder has seen some results, and he is applying for a patent for a new battery material, which is a good result for the growth of MGI and battery technology development. Ceder that the Internet and big data can bring unpredictable progress and discovery into the program, "When you have this combination, you can't predict what people will bring you." "(Internet enthusiasts)

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