Machine learning (ML) algorithms are becoming increasingly important in nanotechnology. They can analyze vast datasets generated from experiments and simulations to identify patterns and make predictions. For instance, ML can be used to predict the properties of new nanomaterials, optimize the synthesis process, or even design new nanostructures with desired properties. By leveraging data-driven approaches, ML accelerates the discovery and development of innovative nanotechnologies.
