PhD offer in simulation/computation chemistry in Sorbonne Université, Paris, France

Updated: 3 months ago
Location: Paris 15, LE DE FRANCE
Job Type: FullTime
Deadline: 10 Mar 2024

14 Feb 2024
Job Information
Organisation/Company

Sorbonne Université
Department

Department of chemistry
Research Field

Chemistry » Computational chemistry
Physics » Chemical physics
Researcher Profile

First Stage Researcher (R1)
Country

France
Application Deadline

10 Mar 2024 - 20:00 (Europe/Paris)
Type of Contract

Temporary
Job Status

Full-time
Hours Per Week

35
Offer Starting Date

10 Jan 2024
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Aqueous secondary batteries based on economical, safe and environmentally friendly materials have the potential to impact the stationary energy storage market (> 32Bn$ by 2030).  One direction to improve the performance of such batteries is to develop new high-performance and more stable redox electrolytes. This PhD project has the objective to take a first step in this direction by performing molecular computation on a database of nitroxide molecules that will be used to define some molecular descriptors allowing to select the most promising redox active species for aqueous battery applications. Such descriptors will be subsequently employed by the PhD student to perform a high-throughput analysis of nitroxide derivatives to identify the most promising candidates to synthesize. A first natural descriptor is the redox potential which can be computed using electronic structure methods, such as the electronic density functional theory. However, due to a prohibitive computational time, most studies attempting to perform a systematic study of redox molecules, such as quinones and nitroxides disregard the role of the solvent. Since redox active specie stability is a key parameter the practical design of a competitive redox flow battery, we believe it is essential to keep a faithful description of the solvent. It is also mandatory to keep the computation cost tractable which is why we will resort to molecular density functional theory (MDFT). This method allows to compute the solvation free energy and the solvation structure in water or in organic solvent within a few minutes on a standard laptop.

Considered descriptors are solvation free energy, coordination number which can be used to assess the number of hydrogen bonds, redox potentials and partition coefficient between water and an organic solvent. We will also compute the reorganization free energies of the active species following a procedure we recently published [1]. Reorganization free energies can be related to rate constants through activated complex theory. Calculation of the redox potentials requires a computation of the ground state energies of both oxidation states in the presence of the solvent which can be done using the recently published hybrid quantum mechanics MDFT method [2]. Since it requires performing several quantum calculations, the QM/MDFT approach is more computationally demanding, but it remains several orders of magnitude faster than a full QM description.

MDFT is a flavor of classical DFT designed to study the solvation of chemically complexed solutes in a molecular solvent. The solvent is described by a density field. Due to the presence of the solute molecule, represented by an external potential acting on the solvent, this density is perturbed and become inhomogeneous. The DFT ansatz guarantee the existence of a functional of the solvent density that reaches its minimum for the equilibrium solvent density and that is equal to the solvation free energy at this minimum. This theory has proved to be competitive with respect to state-of-the-art simulation techniques for the description of the solvation of a wide range of solutes into molecular solvent such as water and acetonitrile.

[1] TY. Hsu, R. Berthin, A. Serva, K. Reeves, M. Salanne, and G. Jeanmairet. The Journal of Chemical Physics, 157(9) 2022
[2] G. Jeanmairet, M. Levesque, and D. Borgis. Journal of Chemical Theory and Computation, 16(11) 2020


Requirements
Research Field
Chemistry » Physical chemistry
Education Level
Master Degree or equivalent

Research Field
Physics » Chemical physics
Education Level
Master Degree or equivalent

Skills/Qualifications

The candidate will conduct molecular dynamics simulations and classical density functional theory. Any student with a Master's degree in the field of physical chemistry, physics, or computer science is invited to apply. Previous experience in the field of molecular modeling is a plus.


Languages
ENGLISH
Level
Good

Additional Information
Work Location(s)
Number of offers available
1
Company/Institute
Sorbonne Université
Country
France
City
Paris
Postal Code
75005
Street
4 place Jussieu
Geofield


Where to apply
E-mail

[email protected]

Contact
City

Paris
Website

https://www.sorbonne-universite.fr/
Street

4 place jussieu
Postal Code

75005

STATUS: EXPIRED

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