HomeEducationGraduate and Undergraduate ProgramsResearch Experience for Undergraduates (REU)REU 2017 ProjectsComputer Optimization and 3D Printing of Quantum Dot

Computer Optimization and 3D Printing of Quantum Dot

Professor: Tobias Hanrath

Tobias HanrathProject Description
: This proposed research will first apply this dual approach to the field of Quantum Dot (QD) assemblies for photovoltaics. Quantum dots hold tremendous potential for efficient solar energy conversion, which has broad impacts for our transition towards a sustainable energy portfolio.iii Despite impressive recent progress, one of the largest challenges in thin film QD solar cells is the poor extraction of photo-generated charges due to lack of continuous charge collection pathways. Therefore, even if exciton generation in QDs is record breaking, until there is sufficient control over QD assemblies that allows for collection of electrons at one of the electrodes, QD photovoltaic devices will not reach their full potential.v The problem of inefficient charge collection is not specific to QD solar cells, and this research will enable more efficient overall solar cell design. I initiated this research project because I saw the potential for computer optimization methods and 3D printing to vastly improve QD assemblies and their resultant photovoltaic performance. I sought out experts in these two very different fields and brought them together to collaborate on and solve this interdisciplinary problem. Both at Cornell University, Professor Hod Lipson in the Mechanical Engineering dept. is an expert in computational optimization and 3D printing, and Professor Tobias Hanrath in the Chemical Engineering dept. is an expert in QD assemblies. I will conduct my research jointly between their labs, gaining the best of both worlds. I will use computational techniques to obtain optimized 3D structures for both the solar cell electrodes and for the QD assemblies. The best structures will be 3D printed and tested to verify the optimization methods. In the end, the optimization of structure by a combination of computer optimization and 3D printing will be broadly applicable to many technologies. Aim 1: To understand the mechanism by which electrons are transferred between QDs. Experimental Design: I will determine how the QDs are spatially arranged by examining self-assembled PbSe QD films using scanning electron microscopy (SEM) (Fig.A). My research will leverage access to unique world-class materials characterization facilities at Cornell, including high-resolution electron microscopy and synchrotron-based Xray scattering. I will use scanning tunneling electron microscopy (STEM) in combination with electron energy loss spectroscopy (EELS) to obtain elemental mapping on an atomic scale to help map and understand the pathways in which electrons can move between QDs. Impact: The QD arrangements and hopping mechanisms I measured while completing Aim 1 will directly inform the computer models that I will develop in Aim 2 and 3. Aim 2: To accurately represent electron transport mechanisms and the resultant solar cell efficiency using computer models. Experimental Design: I will begin by generating several computer models that describe various hypothesized electron transport mechanisms through 2D QD monolayers (Fig. B). The computer model will predict the efficiency of a solar cell with a monolayer of QDs. I will compare the results of my several computer models to measurements of the photovoltaic properties of a monolayer

QD solar cell. I can then determine which transport mechanisms best describe electron movement through a monolayer. I can extend these computer models to include stacks of monolayers, and can compare the computer-modelled efficiency of stacked 2D layers to the experimentallymeasured efficiency of multi-layer QD solar cells. Impact: My computer models will generate quantitative solar cell efficiencies for given a specific physical structure of QDs, which will be essential when optimizing 3D structures in Aim 3. Aim 3: To predict 3D electrode architectures for QD solar cells with maximum efficiency, using computer optimization methods. Experimental Design: I will apply computational optimization methods to the physically accurate models developed during Aim 2 in order to discover 3D electrode structures that can optimize the charge collection pathways in the QD solar cell (Fig. C). In order to 3D print the predicted electrode designs, I have begun a partnership with the Laser-Assisted Nano-Engineering Lab at the University of Nebraska-Lincoln, where they employ high-resolution photonic laser lithography to create nanoscale 3D structures (Fig D).viii I will build solar cells by filling the empty spaces between the 3D printed electrodes with QDs and will measure their photovoltaic efficiency. These measurements will then be used to validate the effectiveness of my model to predict complex 3D structures that have enhanced photovoltaic efficiencies. Impact: This project will drastically improve the efficiency of many types of solar cells by combining computer optimization with advanced 3D printing. Additionally, the dual approach can be used to tackle other open research questions such as optimal battery electrode geometry or optimal energetic material arrangements. Both Professor Lipson and Hanrath have entrusted me with the opportunity to mentor a group of five undergraduate and Masters students to help build a 3D printer with micron-scale resolution. In recruiting students, I put an emphasis on recruiting female and underrepresented minority students with diverse international backgrounds. For all of this group, two male and three female students, this was their first time doing an independent research project, so above all I wanted to enable them to independently and creatively think of solutions to problems that I presented them. After working together for a summer, four of these five students decided to continue conducting independent research during the academic year. I found the process of mentoring extremely rewarding and am proud to have played a small part in the start of their future careers as scientists and engineers. In my future career as a professor, I will continue mentoring the next-generation of diverse scientists. I intend to keep conducting interdisciplinary research that brings together experts from different fields to face future challenges in science.

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