Computational methods, which solves the Schrödinger’s equation for molecules, have become an indispensable tool in last decades. And Density Functional Theory is one of the most used, and most effective computational method.
Transition Metal complexes, on the other hand, have been being used extensively in many important applications in many fields, such as chemical catalysts, atomic thin films, and pharmaceutical industry. Applying computational methods to transition metal complexes has become inevitable to understand better, to control and to design these compounds.
As it is known, it is very difficult to handle transition metals computationally, mostly due to near degeneracy in their electronic states. The computational algorithms usually cannot achieve as successive result as they can do for other typical elements, like carbon or nitrogen for instance. Computational methods are needed to be improved for properly deal with transition metal complexes. To find computationally cheaper but still effective methods to deal with these complexes is a major challenge.
Unlike the analogue calculations, computational methods solve all equations iteratively, so there are major differences between these two calculation types. The starting point in state space (the assumed initial conformation of molecule) is could have a stronger effect then the expected, on the flow of the iterative solving algorithm of the computational approach.
Here we present a comparative study for a Ruthenium complex. We have optimised the molecule several times. Each of the optimisations started from different initial molecular conformations. Then we have compared the result in different ways, like calculation times and minimum energy that had reached, to see effect of starting configurations on the calculation.
It is showed that, starting configuration is an important parameter for computational calculations of transition metal complexes, and it is needed to be carefully chosen to improve success of calculations.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Articles |
Authors | |
Publication Date | October 31, 2019 |
Published in Issue | Year 2019 Special Issue 2019 |