scholarly journals Deep Learning Based Optimization of Lennard-Jones Parameters for the Drude General Force Field (DGenFF)

2021 ◽  
Vol 120 (3) ◽  
pp. 77a
Author(s):  
Payal Chatterjee ◽  
Mert Y. Sengul ◽  
Alexander D. MacKerell
2019 ◽  
Author(s):  
Samuel Kantonen ◽  
Hari S. Muddana ◽  
Niel M. Henriksen ◽  
Lee-Ping Wang ◽  
Michael Gilson

We utilize a previously described Minimal Basis Iterative Stockholder (MBIS) method to carry out an atoms-in-molecules partitioning of electron densities. Information from these atomic densities is then mapped to Lennard-Jones parameters using a set of mapping parameters much smaller than the typical number of atom types in a force field. This approach is advantageous in two ways: it eliminates atom types by allowing each atom to have unique Lennard-Jones parameters, and it greatly reduces the number of parameters to be optimized. We show that this approach yields results comparable to those obtained with the typed GAFF force field, even when trained on a relatively small amount of experimental data.


2020 ◽  
Vol 16 (2) ◽  
pp. 1115-1127 ◽  
Author(s):  
Sophie M. Kantonen ◽  
Hari S. Muddana ◽  
Michael Schauperl ◽  
Niel M. Henriksen ◽  
Lee-Ping Wang ◽  
...  

Author(s):  
Samuel Kantonen ◽  
Hari S. Muddana ◽  
Niel M. Henriksen ◽  
Lee-Ping Wang ◽  
Michael Gilson

We utilize a previously described Minimal Basis Iterative Stockholder (MBIS) method to carry out an atoms-in-molecules partitioning of electron densities. Information from these atomic densities is then mapped to Lennard-Jones parameters using a set of mapping parameters much smaller than the typical number of atom types in a force field. This approach is advantageous in two ways: it eliminates atom types by allowing each atom to have unique Lennard-Jones parameters, and it greatly reduces the number of parameters to be optimized. We show that this approach yields results comparable to those obtained with the typed GAFF force field, even when trained on a relatively small amount of experimental data.


2012 ◽  
Vol 33 (31) ◽  
pp. 2451-2468 ◽  
Author(s):  
Wenbo Yu ◽  
Xibing He ◽  
Kenno Vanommeslaeghe ◽  
Alexander D. MacKerell

2010 ◽  
Vol 75 (5) ◽  
pp. 577-591 ◽  
Author(s):  
Ling Zhang ◽  
J. Ilja Siepmann

The transferable potentials for phase equilibria (TraPPE) force field is extended through the development of a non-polarizable five-site ammonia model. In this model, the electrostatic interactions are represented by three positive partial charges placed at the hydrogen position and a compensating partial charge placed on an M site that is located on the C3 molecular axis and displaced from the nitrogen atom toward the hydrogen atoms. The repulsive and dispersive interactions are represented by placing a single Lennard–Jones site at the position of the nitrogen atom. Starting from the five-site model by Impey and Klein (Chem. Phys. Lett. 1984, 104, 579), this work optimizes the Lennard–Jones parameters and the magnitude of the partial charges for three values of the M site displacement. This parameterization is done by fitting to the vapor–liquid coexistence curve of neat ammonia. The accuracy of the three resulting models (differing in the displacement of the M site) is assessed through computation of the binary vapor–liquid equilibria with methane, the structure and the dielectric constant of liquid ammonia. The five-site model with an intermediate displacement of 0.08 Å for the M site yields a much better value for the dielectric constant, whereas differences in the other properties are quite small.


CrystEngComm ◽  
2020 ◽  
Vol 22 (43) ◽  
pp. 7350-7360 ◽  
Author(s):  
Angelo Gavezzotti ◽  
Leonardo Lo Presti ◽  
Silvia Rizzato

A novel, universal Lennard-Jones–Coulomb (LJC) atom–atom force field parametrization reproduces the experimental sublimation enthalpies of 377 molecular crystals drawn from the CSD.


2019 ◽  
Vol 116 (3) ◽  
pp. 142a ◽  
Author(s):  
Payal Chatterjee ◽  
Esther Heid ◽  
Christian Schröder ◽  
Alexander D. MacKerell
Keyword(s):  

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