Researchers used machine learning interatomic potential (MLIP) calculations to narrow down the search for candidate dopants for a new type of photocatalytic tin oxide.
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results