(681b) Comparing Molecules and Solids Across Structural and Alchemical Space
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Computational Molecular Science and Engineering Forum
Data-Driven Screening of Chemical and Materials Space
Thursday, November 17, 2016 - 12:42pm to 12:54pm
compounds is a critical step in the development of algorithms to classify
structures, search chemical space for better compounds and materials,
and drive the next generation of machine-learning algorithms for pre-
dicting the stability and properties of atomic systems. In recent years
several strategies have been designed [1-3] to compare atomic coor-
dination environments. In particular, the Smooth Overlap of Atomic
Positions has emerged as a natural framework to obtain translation, ro-
tation and permutation-invariant descriptors of atomic environments,
driven by the design of various classes of machine-learned inter-atomic
potentials. Here we will present few examples showcasing how one can
construct a Sketchmap[4-6] representation of databases of both molec-
ular and bulk structures, using (dis)similarity definitions based on such
local descriptors that can treat alchemical and structural complexity
within a unified framework.
[1] A. P. Bart ok, et al, Phys. Rev. B88, 054104(2013) [2] Ali Sadeghi
et al, J. Chem. Phys. 139, 184118 (2013) [3] Sandip De et al, Phys.
Rev. Lett. 112, 083401(2014) [4] G. A. Tribello et al,Proc. Acad. Natl.
Sci. U.S.A. 109 5196 (2012) [5] M. Ceriotti et al, Proc. Acad. Natl.
Sci. U.S.A. 108 13023 (2011) [6] M. Ceriotti et al, J. Chem. Theory
Comput. 9 1521 (2013)