To cite this paper use one of the standards below:
Positron binding to atoms and molecules: Machine learning studies
PAULO AMARAL
Universidade de São Paulo
Now you could share with me your questions, observations and congratulations
Create a topicAb inition calculations of bound states of a apositron with atoms ans molecules are very difficult and expensive.
Machine-learning techniques permit to unveil the physics of the bonding in terms of properties of the targets, by handle existing data of binding energies.
As output, new predictions and insights come out, as the fundamental role of the ionization potential of the target.
With nearly 200,000 papers published, Galoá empowers scholars to share and discover cutting-edge research through our streamlined and accessible academic publishing platform.
Learn more about our products:
This proceedings is identified by a DOI , for use in citations or bibliographic references. Attention: this is not a DOI for the paper and as such cannot be used in Lattes to identify a particular work.
Check the link "How to cite" in the paper's page, to see how to properly cite the paper