Defects and charge-carrier lifetime in early-stage photovoltaic materials : relating experiment to theory

Abstract

To minimize risks associated with climate change, we must rapidly reduce greenhouse gas emissions worldwide by shifting reliance away from fossil fuels. Solar photovoltaic (PV) modules are well suited for reducing emissions; however, manufacturing and capital costs must continue to decline for rapid, worldwide PV adoption. Low-cost and Earth-abundant "thin film" materials offer potential in spurring PV growth, but their development is often hampered by the presence of defects, which degrade solar cell efficiency due to short charge-carrier lifetimes. In this thesis, such defects and their impact on lifetime in early-stage PV materials are investigated, focusing on experimental methods to assess lifetime connected to theoretical concepts about both defects and lifetime measurements themselves. First, time-resolved photoluminescence is performed, and both analytical and numerical modeling are used to determine lifetimes exceeding 1 nanosecond in six materials predicted to be "defect tolerant." Two-photon spectroscopy is then employed to decrease the effect of surface recombination, enabling more representative estimates of "bulk" lifetime. Second, the role of impurities is explored by intentionally contaminating lead halide perovskites with iron. Synchrotron-based X-ray techniques are also utilized to investigate the distribution and charge state of incorporated iron, and perovskite solar cells are found to tolerate approximately 100 times more iron in the feedstock than comparable p-type silicon solar cells. In addition, improved methods for extracting lifetime from solar cell devices are explored. Quantum efficiency measurements are performed and modeled on tin monosulfide solar cells to verify that very short lifetimes (30-100 picoseconds) limit device performance. Furthermore, temperature- and illumination-dependent current-voltage measurements are performed and modeled in iron-contaminated silicon solar cells- and analyzed with the help of a Bayesian inference algorithm-to estimate the defect parameters that directly relate to lifetime. Collectively, these studies serve to provide a more robust framework for assessing and mitigating the presence of defects in early-stage PV materials, streamlining efforts to better optimize their photovoltaic performance.