Simulating Reaction networks for prebiotic environments
Lead Supervisor: Alex Thom, Chemistry
Co-supervisor: Alex Archibald, Chemistry
Brief summary
There is huge uncertainty in the chemistry that occurred on early-Earth and other planets, and understanding this is one of the keys to understanding the formation of life from prebiotic conditions and assessing whether potential signatures of life seen on other planets are indeed correct and consistent with the chemistry present.
This project creates an automated framework for building reaction networks of relevant species and can generate data not known experimentally through accurate quantum chemical calculations, propagating any uncertainties in this to predicted outcomes., We will apply this to origin-of-life planetary conditions for the first time.
Importance of the area of research concerned
Atmospheric chemistry for present-day Earth contains well-benchmarked reaction networks allowing simulations of many chemical reactions. The environments on early-Earth and other planets are less well characterised, and for many species which do not readily occur on earth, estimates of thermodynamic and kinetic parameters are used, often off by many orders of magnitude.
This research will build a framework for the automatic creation of reaction networks, calculating the relevant quantities to sufficient accuracy, and including estimates of uncertainties, using quantum chemical methods. For gas phase species, these methods give high accuracy. For condensed-phase species, the lower accuracy of automated methods will be supplemented by state-of-the-art calculations.
We will benchmark this for present-day Earth and experimentally-measured networks used in industrial applications and simulating air quality.
We will then use the networks to simulate early-Earth, Venus, and relevant exo-planet chemistries as these become better established.
What will the student do?
The student will build a python software framework to interface existing quantum chemistry software which calculates thermodynamic and kinetic quantities of relevance. This framework will also include (and mine) any experimental databases for these quantities, and cross-validate them with computed values.
There are already existing networks, and processes for species generation which can be used to generate reaction networks, but the project may also explore filling-in holes and extending uncharacterised regions of such networks.
Initially the framework will focus on gaseous species, but will be extended to solvated or adsorbed species, where the uncertainties and calculations methods are far from automated, and significant work will be needed in designing interfaces, and collaboration with other specialists in chemistry who work in such areas.
With the generated networks and data the student will investigate and evaluate the plausibility of existing and potential hypotheses for planetary prebiotic chemistries.
References
M. Liu, A. Grinberg Dana, M.S. Johnson, M.J. Goldman, A. Jocher, A.M. Payne, C.A. Grambow, K. Han, N.W. Yee, E.J. Mazeau, K. Blondal, R.H. West, C.F. Goldsmith, W.H. Green. Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation, Journal of Chemical Information and Modeling 61, 2686-2696 (2021).
S. Sharma, A. Arya, R. Cruz and H. J. Cleaves II. Automated Exploration of Prebiotic Chemical Reaction Space: Progress and Perspectives, Life 11 1140-1–19 (2021).
A. Pérez-Villa, F. Pietrucci, A. M. Saitta. Prebiotic chemistry and origins of life research with atomistic computer simulations, Phys. Life Rev. 34–35, 105-135 (2020).
Requirements as to the educational background of candidates that would be suitable for the project
Undergraduates in Chemistry, Physics, Earth Sciences, Natural Sciences, and Chemical Engineering would be most suitable, though those some mathematical and programming background from biological sciences could also be suitable.
Applying
You can find out about applying for this project on the Leverhulme Centre for Life in the Universe widening participation PhD Studentships page.