Beyond potentials: integrated machine learning models for materials

HIGHLIGHTS

• who: Michele Ceriotti from the (UNIVERSITY) have published the paper: Beyond potentials: Integrated machine learning models for materials, in the Journal: (JOURNAL)
• what: The atomic nuclei, that is an important contributor to the fluctuations of light atoms such as hydrogen, has a substantial effect on many observables (Figure 5).
• future: Thanks to the extension of symmetry-adapted models to vectorial and tensorial quantities other microscopic properties that can be computed by solving the electronicstructure problem can also be predicted by ML. An important practical issue that may slow down the adoption of this . . .
  

   

  

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