How is Machine Learning Transforming Computational Design?
Machine learning (ML) is revolutionizing computational design in nanotechnology. By training ML algorithms on experimental and simulation data, researchers can develop predictive models that outperform traditional methods. ML can rapidly screen vast datasets to identify promising nanomaterials, optimize simulation parameters, and even discover new materials with desired properties. This integration of ML with computational design accelerates the development process and enhances the accuracy of predictions.
