Intramolecular polarisable multipolar electrostatics from the machine learning method Kriging

By Matthew J. L. Mills, Paul L. A. Popelier. 2011

63 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. ST John
2. Gábor Csányi
3. K. Müller
4. Frank No'e
5. Cecilia Clementi
6. Alexandre Tkatchenko

In Materials Chemistry

1. ST John
2. Gábor Csányi
3. Alexander V. Shapeev
4. Evgeny V. Podryabinkin
5. K. Müller
6. Alexandre Tkatchenko
7. James R. Kermode
8. Frank No'e

In Molecular Biology

1. ST John
2. Gábor Csányi

Citations in the corpus

• Many-Body Coarse-Grained Interactions Using Gaussian Approximation Potentials. (2016, background): “This is already an approximation in all-atom simulations [24], where ongoing research is studying extensions such as polarisable force fields [111, 112] and more general many-body approaches [30, 113].”