Lecturer in Materials Science

Charlotte Lynch

  • I studied for my undergraduate degree in Materials Science at Trinity, and then stayed on to study for a DPhil, also in Materials Science.

  • My research areas involve computational modelling techniques based on quantum and classical mechanics, and machine learning.

  • I am currently carrying out postdoctoral research in the Nuffield Department of Medicine, where I am using machine learning to predict antibiotic resistance in Mycobacterium tuberculosis.

Charlotte Lynch

Teaching

I give tutorials to the first- and second-year Materials Science undergraduates, and revision classes to the third-year undergraduates. I primarily teach the first-year courses on random processes and statistical physics, and wave mechanics and quantum theory, and the second-year courses on electronic structure, electrical and optical properties, and statistical mechanics and thermal properties. I also teach mathematics to the first-year Materials Science undergraduates at Corpus Christi College.

Research

My research interests lie in applying computational methodologies to a broad range of applications, from predicting the properties of materials, to the behaviour of biomimetic nanopores and biological ion channels, and most recently to antimicrobial resistance.

My DPhil in Materials Science involved using quantum mechanics to simulate the nuclear magnetic resonance (NMR) parameters for a variety of materials, in order to aid with the interpretation of experimental NMR spectra, provide insight on the interactions within the material and to guide future experiments. My postdoctoral research in the Biochemistry Department involved using classical mechanics to model and understand the interactions of water in ion channels and biomimetic nanopores. My current postdoctoral research is in the Nuffield Department of Medicine, where I am using machine learning to predict antibiotic resistance in Mycobacterium tuberculosis (which causes the disease tuberculosis). 

Selected Publications

‘Influence of Effective Polarization on Ion and Water Interactions within a Biomimetic Nanopore’, L. X. Phan, C. I. Lynch, J. Crain, M. S. P. Sansom, S. J. Tucker, Biophys. J. (2022), 121, 2014-2026.

‘Water Nanoconfined in a Hydrophobic Pore: Molecular Dynamics Simulations of Transmembrane Protein 175 and the Influence of Water Models’, C. I. Lynch, G. Klesse, S. Rao, S. J. Tucker, M. S. P. Sansom, ACS Nano (2021), 15, 19098-19108.

‘Influence of Water Models on Water Movement through AQP1’, M. A. Gonzalez, A. Zaragoza, C. I. Lynch, M. S. P. Sansom, C. Valeriani, J. Chem. Phys. (2021), 155, 154502.

‘Effect of Water Models on Transmembrane Self-Assembled Cyclic Peptide Nanotubes’, M. Calvelo, C. I. Lynch, J. R. Granja, M. S. P. Sansom, R. Garcia- Fandiño, ACS Nano (2021), 15, 7053-7064.

‘Molecular Simulations of Hydrophobic Gating of Pentameric Ligand Gated Ion Channels: Insights into Water and Ions’, S. Rao, G. Klesse, C. I. Lynch, S. J. Tucker, M. S. P. Sansom, J. Phys. Chem. B (2021), 125, 981-994.

‘Water in Nanopores and Biological Channels: A Molecular Simulation Perspective’, C. I. Lynch, S. Rao, M. S. P. Sansom, Chem. Rev. (2020), 120, 10298-10335.

‘Water and Hydrophobic Gates in Ion Channels and Nanopores’, S. Rao, C. I. Lynch, G. Klesse, G. E. Oakley, P. J. Stansfeld, S. J. Tucker and M. S. P. Sansom, Faraday Discuss. (2018), 209, 231-247.