Research Proposal Abstract:
In the quest of sustainable innovative surface coatings, several challenges need to be addressed: (i) reduce the use of non-sustainable elements as P (ii) use aqueous formulations (iii) ensure high performance in adhesion and corrosion protection. To accelerate this quest, a greater understanding of the complexity governing adhesion is required. The impact of the chemical structure of the functional groups on adhesion performance and the resistance of the resulting composite materials to the environment are key points of interest of this PhD work. They will be investigated using atomistic modeling, benefiting from recent developments done in the Theoretical Chemistry group of the Laboratoire de Chimie of the ENS de Lyon.
The binding of various functional groups was investigated on both hydrated and dry alumina at the ab initio level, identifying carboxylates as promising binding groups.[1,2] We will focus on organic surface coating agents including only carboxylate groups. To start, we will investigate the binding of monomers and small oligomers containing a few carboxylic groups at the DFT level, assessing the binding sites and binding strength. Flexible and polyfunctional molecules will be easily adsorbed on the substrate with the open-source python package DockOnSurf[3] to obtain the optimized low-energy adsorption configurations. Our SolvHybrid scheme[4] will provide a routinely available semiquantitative determination of adsorption energies at the metal/water interface to provide a first assessment of the influence of an aqueous environment. Then, we will parametrize an interfacial force field to describe the carboxylate/alumina interaction using our GLJ approach.[5] This force field is built using a pair-wise approach and showed a high transferability. The force field will be used to explore the substrate hydration, effect of salt (Na+, Cl-), pH, and the presence of multivalent metals, e.g. Al3+ to understand the impact of the environment (air, water, salts) on the adhesion.
Requirements:
1. Obtain a master's degree in computational chemistry, physics, materials science, or a related discipline before July 2024.
2. Experience in applying quantum-chemical (DFT or wavefunction-based) and force-field-based methods to the study of chemical reactivity and
material properties.
3. Fluent in English (both written and spoken). Knowledge of French is a plus, but not mandatory.
4. Chinese citizen.
References:
[1] S. Blanck, S. Loehlé, S. N. Steinmann, C. Michel, Tribology International 2020, 145, 106140
[2] S. Blanck, C. Martí, S. Loehlé, S. N. Steinmann, C. Michel, The Journal of Chemical Physics 2021, 154, 084701
[3] C. Martí, S. Blanck, R. Staub, S. Loehlé, C. Michel, S. N. Steinmann, Journal of Chemical Information and Modeling 2021, 61, 3386-3396
[4] P. Clabaut, B. Schweitzer, A. W. Gotz, C. Michel, S. N. Steinmann, J Chem Theory Comput 2020, 16, 6539-6549.
[5] J. Rey, S. Blanck, P. Clabaut, S. Loehlé, S. N. Steinmann, and C. Michel, The Journal of Physical Chemistry B 125, 10843 (2021); X. Wu, S. N. Steinmann, C. Michel, ChemRxiv 2023.
If you are interested in the program, please send your CV to changru.ma AT syensqo.com. |