Development of tools for evolutionary de novo design of molecules with improved properties
Doctoral thesis
Permanent lenke
http://hdl.handle.net/11250/2396893Utgivelsesdato
2016Metadata
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- Institutt for kjemi [1402]
Sammendrag
Design and discovery of molecules using computers and particularly de novo based
design has been in practice for many years. In such schemes, the algorithm to
design the molecules and precise estimates their properties are relevant for the
discovery of structures with desired features. This thesis presents methods and
software tools for the design of synthetically realistic structures, di erent approaches
to perform necessary computations in a more e cient manner and ways
to improve the accuracies of the property estimates.
The de novo design method was implemented to discover azobenzene dyes using
evolutionary algorithms. The property chosen to be optimised was, the energy
of excitation, which is an important property in the eld of molecular electronics
and dye-sensitised solar cell (DSSCs) applications. The excitation energies of
the molecules from the design program were computed using time-dependent density
functional theory (TD-DFT) calculations. Novel derivatives of the dye were
discovered with signi cantly lower excitation energies.
The property estimates by density functional theory (DFT) and TD-DFT methods
greatly vary with the exchange-correlation functional used. With many density
functionals and basis-sets available in the literature, it is not practical to perform
DFT and TD-DFT computations using all density functionals to identify the
most appropriate functional. To address this, an algorithm is presented that
helps determine the best functional suitable to compute a certain property of a
molecular system.
There are many methods available in the literature to compute the properties
of molecules with increasing levels of accuracy and computational cost. Starting
from less accurate methods based on molecular mechanics to more accurate
methods in quantum chemical such as DFT and ab-initio methods. Generally,
with increasing accuracy of the method, the computational costs required also
increases rapidly. As a way to address this challenge, a software is presented that
is designed speci cally to manage high-throughput quantum chemical calculations
on massively parallel computing systems.
Evolutionary de novo design was applied to discover Coumarin derivatives with
improved properties for use in Gr atzel solar cells. Quantitative structure and
property relationship models were used to predict relevant properties of the dye.
The top structures identi ed from the design scheme were further analysed using
DFT computations to support the evidence of their potential use in DSSCs.