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Computational Design of Efficient Solar Cells

Professor: Paulette Clancy

Paulette ClancyProject Description
: Since their discovery in 2009, perovskite solar cells have shot up the solar efficiency ratings to rival silicon and become the fastest-improving solar material ever. However, due to this rapid rise, a fundamentals-based understanding of these materials is largely missing. This has contributed to technological chokepoints in the scale-up production needed for large-scale manufacturability, revolving around the little-understood mechanisms by which the perovskites grow from a solution of PbX2, methylammonium halides, and an ad hoc set of polar solvents. Cutting through this confusion is a task ideally suited for a computational modeling approach. Using quantum mechanical-based software, we are able to study molecular rearrangements and bonding states as the material is formed in solution. We can calculate both the structural and electronic properties of these systems, yielding a deeper understanding of how processing affects structure and how structure affects key solar properties such as conductivity and band gaps. In this project, students will participate in our group’s effort to study the growth mechanisms of perovskite solar cells using computational and theoretical approaches. Students will gain experience in ab initio Density Functional Theory and molecular-scale Molecular Dynamics approaches, conducting simulations in a variety of open-source software including Orca and LAMMPS. No prior knowledge of these packages is expected; we will teach you from scratch. However, it will be important that the student has a strong computational background and feel comfortable programming in languages like Python, C or C++ (Matlab experience alone will be insufficient).

The key scientific question we seek to answer is: How does chemistry and structure affect the electronic properties of the perovskite semiconductor? We will use a computational approach to optimize ABX3 perovskites, in which we change A (the monovalent organic cation, like methylammonium), B (the metal cation, Pb, Sn, Ge) and X (the halide ion). Our goal is to correlate these combinations of precursors and solvent with stability and electronic performance, ultimately accelerating the manufacturability and deployment of perovskite solar cells..

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