Applied X-ray spectroscopy

Aromatic Acids and ALL the molecules

Just before the holidays the second paper on our work on amino acids was accepted for publication in Electronic Structure (you can find it here). This is the second part of our exploration of amino acids in collaboration with Dr Laura Ratcliff at Imperial College London, who is the theory mastermind of the operation. Marta Wolinska, a talented Masters student at Imperial, laid the groundwork for the theoretical work and Nathalie Fernando, a PhD student in the AXS group, performed much of the experimental work.

Our interest in amino acids came from the search for a systematic group of molecules, which were readily available and which we could use to study changes in XPS core level binding energies with both theory and experiment. We started off exploring the simple amino acids glycine (Gly), alanine (Ala) and serine (Ser) and managed to show that using our theoretical approach, using ∆SCF implemented in a systematic basis set, we could reliably predict relative core level binding energies of amino acids both in the gas (multiwavelets) and solid, crystalline phase (plane waves). Due to the radiation sensitivity of amino acids we also had to employ a rastering approach to collect experimental spectra not influenced by radiation induced artefacts. This work was published in J. Phys. Chem. Lett. previously.

Encouraged by these initial results, we then decided to test the approach further by tackling the aromatic amino acids phenylalanine (Phe), tyrosine (Tyr), tryptophan (Trp), and histidine (His). It turned out to be a rather formidable challenge. Computationally the increase in unit cell sizes going from the simple to aromatic amino acids also meant an increase in computational cost, particularly for hybrid functionals. However, the true challenge was how to interpret the complex spectra and how to disentangle differences in binding energies.

It turns out that the chemical intuition and the experience of a spectroscopist is not able to fully explain and justify observed changes in binding energies and usually reflects the results given by calculations based on Koopmans’ theorem. The ∆SCF calculations, which describe the observed spectra much better, are harder to rationalise. To help us disentangle the web of varying contributions and energy changes we ended up calculating more than 20 related molecular species to systematically follow differences in core level binding energies.

The most important take-away message is that it is not only the nearest, but also next-nearest and even further removed neighbouring atoms that influence the final binding energy observed for a specific atom within the amino acids. This work will hopefully aid future interpretation of molecular systems and demonstrates the importance of combining theory and experiment to fully understand a material.

Comments are closed.