PostDoc Position for “Multi-scale simulations of graphene formation on liquid metal catalysts”

Deadline: until the position is filled

Start date: 1^st January 2021

Duration: 2 years

Salary: ~ 50k EUR per year (according to German TVÖD E13 pay scale)

Dear all,

A fully funded PostDoc research position is available at the Theory Department of Prof. Dr. Karsten Reuter at the Fritz-Haber-Institute of the Max-Planck Society in Berlin, Germany. The position is part of an EU-funded project (DirectSepa) which is carried out within a consortium of international experimental collaborators. The project is a continuation of a foregoing project (LMCat) where liquid metal catalyzed graphene synthesis has been studied as a viable and economic process.

The overarching goal of the DirectSepa project (and LMCat previously) is the elaboration of a novel synthesis procedure which allows for a cheaper, high-quality production of graphene (and other 2D-materials). The usage of liquid metal catalysts for graphene formation has been shown to occur rapidly and yield a near defect-free product. In contrast, the current state-of-the-art synthesis methods are slow by nature and yield a defective and contaminated product which impedes the promising material’s properties sought after in many future applications. The liquid metal catalyzed process is thus highly desirable for commercial mass production. Current challenges of this procedure are, however, still found in the separation of the as-produced graphene from the liquid metal catalyst. The imminent goal of DirectSepa is the elaboration of an efficient separation process. Integrated into the efforts of our experimental collaborators, the theoretical part of this project will tend to the atomic interaction of the forming graphene flakes on the metal catalyst and their evolution over different length and time scales. Insight gained hereof will allow for the formulation and refinement of macroscopic models to optimize a continuous synthesis process.

The candidate will study mesoscopic graphene flakes on liquid metal catalysts using Molecular Dynamics (MD) simulations. Involved atomistic models require large system sizes and will necessary rely on a multi-scale methodology to extrapolate from ab initio, density-functional theory (DFT) calculations to either DFT-B, empirical or machine-learning potentials. Further, by using advanced sampling methods and statistical mechanics, macroscopic properties of the graphene/liquid metal system are to be obtained. This work will be integrated into the current development efforts for atomistic potentials for mesoscale applications within the Reuter group. The candidate will thereby benefit from the experience held and continuously build in the group.

Essential requirements:

• PhD in either Physics, Chemistry or related fields
• Basic knowledge of DFT and electronic structure theory
• Experience with molecular dynamics simulations
• Python scripting and programming knowledge
• Experience with DFT-B, empirical or machine learning potentials is an advantage

How to apply:
Interested candidates should submit a cover letter, CV, and 2-3 references to [email protected]. Eventual questions can also be directed to this email address.