Doctoral position in theoretical modeling of nanocrystal growth

The doctoral student will develop theoretical and computational descriptions of the nucleation and growth of semiconductor nanocrystals. The initial focus will be on combining existing models for CdSe nanoplatelets and magic-sized nanocrystals. The work will subsequently be expanded to include conventional, continuously growing quantum dots and other semiconductor materials, including InP. The project will combine three complementary modeling approaches: First, the student will use density functional theory (DFT) to calculate the energies of surfactant-terminated nanocrystal surfaces, edges, steps, and vertices. These calculations will provide physically meaningful parameters for the growth models. They will also be used to identify surfactant molecules that may stabilize particular nanocrystal shapes. Second, the student will construct mass-balance models describing the coupled growth and dissolution of nanocrystal populations. These models will examine the competitive growth of nanoplatelets and magic-sized nanocrystals by solving systems of coupled rate equations. The results will be compared directly with experimental stability measurements. The models will then be extended to include quantum dots, with the goal of explaining the transition between discrete and continuous nanocrystal growth. Third, the student will use kinetic Monte Carlo simulations to investigate the early stages of nanocrystal growth. Such calculations will examine how initially small crystallites develop into competing morphologies and how growth conditions influence the selection of nanoplatelets, magic-sized nanocrystals, or quantum dots. The doctoral student will work closely with experimentalists responsible for nanocrystal synthesis and growth studies. This interaction between theory and experiment is central to the project: experimental results will provide input for the models, while simulations will guide the design of new experiments. The calculations will be performed using ETH Zurich’s high-performance computing infrastructure. In addition to research, the doctoral candidate will contribute to general laboratory activities and will have opportunities to participate in teaching and the supervision of bachelor and master’s students.

The Optical Materials Engineering Laboratory (Prof. David J. Norris) in the Department of Mechanical and Process Engineering (D-MAVT) at ETH Zurich investigates the synthesis, growth, structure, and optical properties of semiconductor nanomaterials. Our interdisciplinary and international team combines materials chemistry, optical spectroscopy, electron microscopy, theoretical modeling, and numerical simulation to understand and control materials at the nanoscale.

• A strong background in thermodynamics, kinetics, statistical mechanics, solid-state physics, physical chemistry, or materials modeling is expected.

• Applicants must hold, or be close to completing, an MSc degree in chemistry, chemical engineering, mechanical engineering, materials science, physics, computational science, or a closely related discipline.

• Experience in one or more of the following areas would be advantageous: Density functional theory and electronic-structure calculations, Kinetic Monte Carlo or other stochastic simulation methods, Numerical solution of coupled differential or rate equations, Atomistic or mesoscale modeling of materials, Semiconductor nanocrystals, surfaces, or colloidal growth, Scientific programming, High-performance computing.

• Prior experience with every method used in the project is not required. The successful candidate should, however, have a strong quantitative foundation and an enthusiasm for learning new computational techniques.

• Academic excellence, a professional approach to research, and the ability to work independently are expected.

• The candidate must be able to communicate fluently in English, both orally and in writing, and should enjoy working in a collaborative and international research environment.