Unlocking Atomic Geometry: Machine Learning Reveals New Insights
In a groundbreaking new study, a research team has developed a machine learning algorithm that is capable of predicting the atomic geometry of molecules. The algorithm, developed by scientists from the University of California, Berkeley and the Lawrence Berkeley National Laboratory, uses a technique known as “machine learning” to analyze the properties of molecules and predict their atomic geometry. This breakthrough could lead to a better understanding of the structure of molecules and the discovery of new materials with unique properties. The team’s findings have been published in the journal Nature Communications.
source: Phys.org