Responsibilities and tasks
This PhD scholarship is part of the Inorganic Phosphosulfides for Optoelectronics (IDOL) project funded by the European Research Council. The overarching goal of the project is to address a crucial scientific and technological challenge: How can we find the absolute best material for a desired application out of the enormous space of all possible materials, including the ones we haven’t yet discovered (trillions at least)?
Answering this question would advance all areas of technology, including renewable energy, electronics, transport, etc. It would also help us find alternatives to the metals that are rapidly depleting (e.g., In), slowly mined (Li), or irresponsibly sourced (Co).
We will approach this question by working on a smaller-scale case study where we limit ourselves to one intriguing class of materials (phosphosulfides) and one important application (solar cells). Our team’s task then becomes: among all possible phosphosulfides, which one will convert light most efficiently into electricity?
You will be responsible for computational work as part of a diverse team of materials scientists, chemists, and physicists working on either experiment of computation. You will be supervised by Assistant Prof. Andrea Crovetto, Senior Researcher Eugen Stamate, and Associate Professor Ivano Castelli (at DTU Energy).
Your background could be Materials Science, Physics (emphasis on solid state physics is a plus), Chemistry (emphasis on inorganic/solid state chemistry is a plus), or related Engineering disciplines. You should have an interest in programming (Python experience is a plus). Hands-on experience with either data science and/or computational methods for materials modelling (e.g., density functional theory, molecular dynamics, quantum chemical methods) is an advantage, but not a requirement. Most importantly, you should be motivated to learn new things, push the boundaries of science, and be able to work both individually and as part of a team.
Your tasks:
- Perform atomistic simulations of phosphosulfide semiconductors, mainly by density functional theory. Simulations will include thermodynamic stability, band structure, interactions with light, intrinsic defects, bonding analysis, etc. We anticipate using VASP as the main code for these calculations, but other codes can be used according to the specific needs.
- Develop a two-way collaboration with an experimental PhD student, who will supply you with experimentally measured properties to assist your work, and who will rely on your computational predictions to decide which new phosphosulfides to synthesize.
- Take advantage of our unique mix of experimental and computational data to develop models for establishing composition-structure-property-performance relationships for phosphosulfides. You will consider both classical models and machine learning models.
- Apply on-the-fly artificial intelligence methods (active learning) to help us decide which experiment or which calculation it makes sense to do next.
- Acquire leadership experience by supervising BSc and MSc students in smaller projects related to your PhD work.
Further information
Further information may be obtained from Assistant Professor Andrea Crovetto, email: ancro@dtu.dk, phone +4581915317
You can read more about DTU Nanolab at www.nanolab.dtu.dk