scholarly journals Machine Learning Force Field Parameters from Ab Initio Data

2017 ◽  
Vol 13 (9) ◽  
pp. 4492-4503 ◽  
Author(s):  
Ying Li ◽  
Hui Li ◽  
Frank C. Pickard ◽  
Badri Narayanan ◽  
Fatih G. Sen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Force Field ◽  
Ab Initio ◽  
Force Field Parameters

Tuning force field parameters of ionic liquids using machine learning techniques

2021 ◽  
Vol 200 ◽  
pp. 110759
Author(s):  
Rafikul Islam ◽  
Md Fauzul Kabir ◽  
Saugato Rahman Dhruba ◽  
Khurshida Afroz
Keyword(s):  
Machine Learning ◽  
Ionic Liquids ◽  
Force Field ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Force Field Parameters

Development of a computer program for the determination of force field parameters derived from ab initio pes

1995 ◽  
Author(s):  
Ugo Cosentino ◽  
Giorgio Moro ◽  
Demetrio Pitea ◽  
Mercedes Procopio ◽  
Pier Carlo Fantucci
Keyword(s):  
Computer Program ◽  
Force Field ◽  
Ab Initio ◽  
Force Field Parameters

Intermolecular Force-Field Parameters for Boron Hydrides

1998 ◽  
Vol 54 (1) ◽  
pp. 41-49 ◽  
Author(s):  
D. E. Williams ◽  
D. Gao
Keyword(s):  
Force Field ◽  
Ab Initio ◽  
Crystal Structures ◽  
Weighted Least Squares ◽  
Minimum Energy ◽  
Structural Parameter ◽  
Exponential Dependence ◽  
Monoclinic Space Group ◽  
Boron Hydrides ◽  
Force Field Parameters

Intermolecular atom–atom force-field parameters of the (exp-6-1) type for B and H atoms in boron hydrides were determined. They were obtained by full-weighted least-squares minimization of 116 forces in 15 observed crystal structures of boranes, the heat of sublimation of B10H14 and data from ab initio wavefunction calculations for diborane. Net atomic charges were obtained by fitting them to molecular electric potentials calculated from ab initio wavefunctions. Charges of terminal hydrogens were usually negative and those of bridging hydrogens usually positive. Repulsion-energy calculations for the B2H6 dimer provided the exponential dependence of H...H repulsion. Using the resulting force field, minimum-energy crystal structures were found with structural parameter values close to those of the observed structures. For diborane, energy minimization beginning with randomly oriented molecules placed initially in an 8 × 8 × 8 body-centered orthogonal cell led to the observed crystal structure and monoclinic space group.

Derivation of MM2 force-field parameters for polychlorophosphazenes (NPCl2)n from ab initio data

1994 ◽  
Vol 311 ◽  
pp. 101-110 ◽  
Author(s):  
Antonio Grassi ◽  
Giuseppe M. Lombardo ◽  
Giuseppe C. Pappalardo
Keyword(s):  
Force Field ◽  
Ab Initio ◽  
Force Field Parameters

All-Atom MD Simulation of DNA Condensation Using Ab Initio Derived Force Field Parameters of Cobalt(III)-Hexammine

2017 ◽  
Vol 121 (33) ◽  
pp. 7761-7770 ◽  
Author(s):  
Tiedong Sun ◽  
Alexander Mirzoev ◽  
Nikolay Korolev ◽  
Alexander P. Lyubartsev ◽  
Lars Nordenskiöld
Keyword(s):  
Force Field ◽  
Ab Initio ◽  
Md Simulation ◽  
Dna Condensation ◽  
Force Field Parameters

Derivation of MM2 force-field parameters for polychlorophosphazenes (NPCl2)n from ab initio data

1994 ◽  
Vol 311 ◽  
pp. 101-110
Author(s):  
Antonio Grassi ◽  
Giuseppe M. Lombardo ◽  
Giuseppe C. Pappalardo
Keyword(s):  
Force Field ◽  
Ab Initio ◽  
Force Field Parameters

scholarly journals Automatic Assignment of Bonded Force Field Parameters for Small Molecules Using Machine Learning

2019 ◽  
Vol 116 (3) ◽  
pp. 289a-290a ◽  
Author(s):  
Praveer Narwelkar ◽  
Hui Sun Lee ◽  
Sihong Xie ◽  
Wonpil Im
Keyword(s):  
Machine Learning ◽  
Force Field ◽  
Small Molecules ◽  
Automatic Assignment ◽  
Force Field Parameters
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