Condensed-matter physics and materials science have a silo problem. Although researchers in these fields have access to vast amounts of data – from experimental records of crystal structures and ...
When scientists study how materials behave under extreme conditions, they typically examine what happens under compression. But what occurs when you pull matter apart in all directions simultaneously?
A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of ...
The new method can determine crystal structures underlying experimental data thus far difficult to analyze. A joint research team led by Yuuki Kubo and Shiji Tsuneyuki of the University of Tokyo has ...
Driven by these challenges, researchers at New York University, in collaboration with scientists at the biopharmaceutical company AbbVie, have developed a new computational tool that can quickly and ...
Crystals -- from sugar and table salt to snowflakes and diamonds -- don't always grow in a straightforward way. Researchers have now captured this journey from amorphous blob to orderly structures. In ...
A team of researchers has developed a novel method for using cholesteric liquid crystals in optical microcavities. The platform created by the researchers enables the formation and dynamic tuning of ...
Duplicates of crystal structures are flooding databases, implicating repositories hosting organic, inorganic, and computer-generated crystals. The issue raises questions about curation practices at ...
Hosted on MSN
Crystallography-informed AI achieves high performance in predicting novel crystal structures
A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results