All chapters

Chapter 3

Applications of Machine Learning for Representing Interatomic Interactions

Machine learning focuses on prediction, based on known properties learned from training data. In computational materials science, this powerful technique is often used for constructing new interatomic potentials. These approaches are illustrated in this chapter, and the improvements over the empirical force fields are discussed.

Publication details

Print publication date
02 Nov 2018
Copyright year
2019
Print ISBN
978-1-78262-961-0
PDF eISBN
978-1-78801-012-2
ePub eISBN
978-1-78801-562-2