You will work at the Department of Materials Engineering of the KU Leuven (www.mtm.kuleuven.be). The Department is responsible for education, research, and service to industry and society related to materials science and engineering. Both the KU Leuven and the Department of Materials Engineering are strongly positioned in the important rankings related to research, innovation, and education. The candidate will participate as a post-doctoral researcher in the project “Multi-scale alignment of carbon-nanotube-encapsulated molecular arrays for nonlinear optics.” funded by the research Foundation Flanders (FWO). The project will be carried out at the Department of Materials Engineering, under the scientific supervision of prof. David Seveno (https://www.kuleuven.be/wieiswie/en/person/00089681) and Dr. Ali Khodayari (https://www.kuleuven.be/wieiswie/nl/person/00122783).
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Responsibilities
OVERALL PROJECT DESCRIPTION
Organic dipolar molecules have attracted much interest over the past decades because of their very large nonlinear optical (NLO) response, holding promise for applications in photonics. Yet, a long standing issue is that to achieve a macroscopic NLO response, the asymmetry intrinsic to dipolar molecules needs to be extended from the molecular scale, over the supramolecular mesoscale, all the way to the macroscopic scale – yet dipole-dipole interactions tend to favor a pairwise anti-parallel orientation in a bulk material, thus cancelling the molecular NLO responses. In this project, three groups will join forces to combine two novel experimental concepts with multiscale modelling to tackle this alignment problem at the nano-, meso- and macro-scales simultaneously: As recently demonstrated for the first time at UAntwerp, dipolar NLO molecules spontaneously adopt an ideal head-to-tail alignment when confined as one-dimensional arrays inside carbon nanotubes. This concept will be elaborated to form highly dipolar NLO nanohybrids and combined with the technique of electrospinning, core expertise of the UGent group, to align the nanohybrids also at the mesoscale in nanofibers. Then, these nanofibers will be aligned in turn on the macroscopic scale to form NLO films. The whole process will be modelled at the KU Leuven group in a multiscale approach, from atomistic simulations of the molecular alignment to large scale coarse grained calculations of the alignment of the nanohybrids.
RESEARCH OBJECTIVE
Model the process of molecular head-to-tail alignment inside CNTs and of the polar alignment of the filled CNTs during the electrospinning.
The modelling activities focus on a hierarchical modelling approach by adopting a parameter passing protocol from the nano- to the mesoscale. At the nanoscale, a simulation of the filling and interaction of individual CNTs with NLO molecules as a function of the CNTs diameter and length is targeted. Then, at the mesoscale, the interactions between the coarse-grained nanohybrids and their environment (surfactant, polymer matrix and electric force) will be scrutinized. This approach will benefit from the use of efficient pre-processing codes, processing, and post-processing tools so that the core activities will focus on the development of an innovative and novel modelling methodology able to model nanocomposites over multiple scales. Special attention will be paid to the transferability of the modelling approach such that not only CNTs but other nanoparticles e.g. BN nanotubes or graphene can be modelled in follow-up projects.
RESEARCH METHODOLOGY
Objective 1: Modelling of the supramolecular ordering inside a CNT
Although the polar alignment of dipolar molecules in CNTs has been experimentally demonstrated, the mechanism of the aligned filling process is not understood in detail and limited to a pair of molecules. In particular, it is still unclear whether the filling is a cooperative process where arrays of molecules align before/while entering the nanotube, or rather it is an equilibrium process, where individual molecules enter and exit multiple times (“wrongly” oriented molecules re-exiting more easily due to the electrostatic repulsion between oppositely oriented dipoles). The filling process will be modelled using full atomistic MD simulations. Thus an in-depth understanding of the dynamics of the filling process, including the way the polar molecules orient themselves will be acquired. The tensile and bending stiffness as well as adhesion between both un-filled and filled CNTs will also be calculated and transferred to the coarse-grained scale as they are key to model the alignment of the nanohybrids.
Objective 2: Modelling of the nanohybrid alignment during electrospinning
During electrospinning, the behaviour of individual nanohybrids and their alignment in the polymer under the effect of a strong electric field cannot be characterized in-situ. Any proposed mechanisms controlling this alignment may remain uncertain if not purely hypothetic. This task aims to unravel the driving mechanisms by performing electrostatic augmented Dissipative Particle Dynamics (eDPD). The preferred polymer (PVA or pullulan) will be first modelled at the atomistic scale, the Flory-Huggins parameter calculated and converted into the repulsive parameter. At the same time, the polymer viscosity will be used to calibrate the friction parameter and finally the random parameter adjusted to thermalize the simulation. Last but not least, a long-range coulombic potential will be implemented. This multiscale modelling approach of CNT nanohybrids embedded in a polymer matrix in the presence of a strong electric field goes far beyond the state-of-the-art both in terms of materials being modelled and development of a method that can transfer atomistic details into a larger simulation framework.
Profile
● Candidates should have recently obtained a PhD in Physics, Chemistry, Materials Science or Materials Engineering with outstanding results.
● Candidates should have a strong theoretical background in at least one of the following topics: molecular modelling, nanomaterials, chemistry, materials science, materials engineering.
● Desirable: programming experience e.g. Python, Matlab, or other coding languages. Good command of Materials Studio, LAMMPS, or/and GROMACS is a plus.
● Language skills: ENGLISH: Excellent; DUTCH: of advantage for the interaction within the University, however not required.
● Candidates have to be hard working, enthusiastic and intelligent with a strong interest in understanding the fundamentals of materials behavior, as well as its implications for engineering applications.
● You have a talent for conceiving, analyzing, and interpretating advanced numerical simulations and can manage them in a target-oriented manner.
Offer
This vacancy offers a 2-year post-doctoral position in the KU Leuven, an international environment, guidance by leading scientists, and competitive fellowship, social security, and other benefits. The successful candidate will be part of a team of 1 PhD student, 2 post-doc, and 3 professors (from 3 different Flemish universities), work with state-of-the-art equipment, and receive an attractive salary in accordance with the KU Leuven regulations.
Interested?
For more information please contact Prof. dr. ir. David Seveno, mail: [emailprotected] and Dr. Ali Khodayari, mail: [emailprotected]
Applications must contain:
• An up-to-date CV, detailing work experience and research and academic achievements
• A cover letter exposing the candidate motivation for the position
• At least two reference letters from a (former) supervisor, professor or manager with contact information.
• Scanned copy of the degree (usually the PhD degree) which would formally entitle the candidate to embark on a post-doctoral position. If the degree has not been obtained yet, the applicant will have to ensure that the date of graduation will be earlier than the start date of the contract.
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Belgium
KU Leuven
On Campus (Full Time)
See Position Description
Postdoc Salary or Fellowship
Expired
On Campus (Full Time)