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Big Data Technique Reveals Previously Unknown Capabilities of Common Materials

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Australia's synchrotron.

Researchers at Rensselaer Polytechnic Institute used a synchrotron to gather diffraction data as a means of unlocking the properties of common materials that could enable a range of new applications.


Researchers at Rensselaer Polytechnic Institute have found a new way to optimize nickel by unlocking properties that could enable a range of applications, from quantum computing to biosensors.

The researchers made this discovery using a technique called lensless microscopy, in which a synchrotron is used to gather diffraction data. The data is then plugged into computer algorithms to produce 3D images of electronic density and atomic displacement.

Using a big data approach, the team used this technique to produce better images than traditional microscopes, providing more information for scientists; the method combines computational and experimental physics with materials science.

The researchers used the same technique to show that barium hexaferrite—a universal and abundant material often used in tapes, CDs, and computer components—has spontaneous magnetic and electric polarization simultaneously, a property that is useful for fast writing, power saving, and data storage.

From Rensselaer Polytechnic Institute 
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Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA


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