New Delhi: A section of Indian Scientists have leveraged Machine Learning (ML) to develop a design map of alloys at the nanoscale. This will help in predicting the match of pairs of metals. Thanks to the scientists & researchers at the S N Bose Centre for Basic Sciences, an autonomous institute of the Department of Science and Technology.
The attempt to connect ML with nanoscience was successful in tracing the mixing patterns of metal atoms in nanoclusters and formed a basis for the design map, which can help select the pairs of metals for nanocluster alloys. This design map developed by the scientists will be tested out in the nano laboratories at the Moscow State University and also at the S.N Bose Centre.
In their paper published in the Journal of Physical Chemistry, they investigated the key attributes driving the core−shell morphology using the statistical tool of machine learning applied on this large data set. Core-shell structures with lighter metals having lower atomic numbers in the core were classified as Type 1, and those having the heavier metals in the core were classified as Type 2. A number of attributes were built to characterise each data point in the set. The performance of the ML model was tallied with existing experimental data, and the ML model was proved to be reliable.
