TD-DFT: An Exploration of the Energies and Structures of Crystal Violet and a Variety of Cr(III) Complex Ions
Spectroscopy is the science of utilising light in order to divine information about a molecule or system of molecules. Specifically, the absorption, emission, and scattering of different wavelengths of light can provide data about bond strength, bond order, vibrational frequency, and excitation energy [1, 2]. As the wavelength and therefore energy of the incident photons can be set by the instrument, the exact energies of absorbance or emission of the molecule can be measured. This data can be gathered experimentally using specialised equipment however some molecules resist synthesis, and so a wealth of data about many theoretically possible species eludes us. We may also want to isolate the molecule in “empty space” whereas “gas phase” measurements are not always possible. This is one place where computational chemistry comes to the fore. Using an appropriate computational method such as density functional theory (DFT), data can be theoretically derived and calculated for many interesting areas of chemistry. DFT is a computational method based on the findings of Hohenberg and Kohn in 1964 that the ground state electronic energy of a system can be determined completely by the electron density [3-6]. This means that it has a considerably higher efficiency as a computational method compared to the wave function approach, where the number of variables increases exponentially as your system increases in size, as the electron density has the same number of variables regardless of the size of the system [7]. The use of an appropriate functional to map the electron density and the energy is one of the vital choices in utilising this method, but if chosen well can provide good results with a much lower computational cost than other methods, while still accounting for electron correlation effects [8]. It has become a very popular method due to its versatility and generally good accuracy with relatively low computational expense when compared to ab initio methods [9].