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RR2: Characterisation of adsorption and dielectric and refractive index response of MOFs and zeolites

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RR2: Characterisation of adsorption and dielectric and refractive index response of MOFs and zeolites

Project Title: Characterisation of adsorption and dielectric and refractive index response of MOFs and zeolites (WP1)

Host Institution: Ghent University

Country: Belgium

Supervisors: Prof. V. Van Speybroeck (Ghent University) Prof. L. Vanduyfhuys (Ghent University); Secondary Supervisors: Prof. G. Maurin (CNRS-M), Stan van Gisbergen (SCM)

Objectives:

  • Accurate prediction of adsorption isotherms and selectivity of nanoporous materials towards various VOCs
  • Accurate prediction of the dielectric constants and refractive index of nanoporous materials loaded with VOCs

Short Description of Work & Expected Results:

  • Construction of accurate material specific force fields (FFs) and/or ab initio trained machine learning potentials (MLPs) for 50 of the most promising materials for each VOC as identified by CNRS-Montpellier
  • Use these FFs/MLPs for the simulation of single- and multicomponent isotherms for the most promising 50 materials for each VOC identified by CNRS-Montpellier
  • Calculation of the dielectric constant and refractive index response for the 10 most promising materials for each VOC identified as function of their guest (VOC/water) loading using ab initio techniques such as DFT

Planned secondment(s):

  • Host: CNRS-Montpellier, Prof. G. Maurin, Timing: year 1, Length: 6 months, Topic: High-throughput screening
  • Host: SCM, Stan van Gisbergen, Timing: year 2, Length 2-3 months, Topic: Contributing to simulation software in a non-academic setting

Enrolment in Doctoral degree(s): UGENT & Univ. Montpellier

Candidate requirements: 

  • We are looking for a computational scientist with a good background in atomistic molecular simulations, quantum mechanics, statistical physics and thermodynamics applied to material science.
  • Experience with molecular simulation software (LAMMPS, DLPOLY, RASPA, Gaussian, VASP, CP2K, …) and coding (Python, C, …) is an advantage.
  • You have a pro-active working style, the willingness to look beyond the borders of your own discipline and a strong motivation to work in a multidisciplinary team. You are highly motivated to become an independent researcher.
  • You have excellent communication skills and have a strong motivation to collaborate with other researchers, within the CMM, the SENNET consortium and our networks.
  • You have or will soon obtain a master’s degree of a university or international equivalent in the field of Chemistry, Chemical Engineering, Physics, Physical Engineering or a related field

Recruited researcher: Aparajita Ghosh