A team of researchers at the Indian Institute of Technology (IIT) Kharagpur in collaboration with the Indo-Korea Science and Technology Cente (IKST) have come up with a deep-learning framework, CrysXPP, that will allow the rapid and accurate prediction of electronic, magnetic, and elastic properties of a wide range of materials.
A team of researchers at the Indian Institute of Technology (IIT) Kharagpur in collaboration with the Indo-Korea Science and Technology Cente (IKST) have come up with a deep-learning framework, CrysXPP, that will allow the rapid and accurate prediction of electronic, magnetic, and elastic properties of a wide range of materials.
In a recently published paper in NPJ Computational Materials (a journal of the Nature Publishing Group), the researchers said that CrysXPP “lowers the need for large property tagged datasets by intelligently designing an autoencoder, CrysAE, the press release stated.
The paper added that "the crucial structural and chemical properties captured by CrysAE from a large amount of available crystal graphs data helped in achieving low prediction errors. The researchers have also designed a feature selector that helps to interpret the model’s prediction. When given a small amount of experimental data, CrysXPP is consistently able to outperform conventional DFT."
Meanwhile, IIT Kharagpur has announced that it will resume offline classes for all courses from August 2. IIT Kharagpur had earlier also issued the academic calendar 2022-23. As per the calendar, the examinations this year will also be conducted in offline mode.
In the previous semester, students had protested against the institute's decision to hold end-semester exams in offline mode as the classes were conducted in online mode. While speaking to the telegraphIndia, an IIT Kharagpur official said that the students have been informed that this year the classes will be held offline so that they don't have any objection to appearing for the exam in physical mode.
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