Bridging the Computational-Experimental Divide to Design Transparent Contact Materials for Solar Energy

This dissertation addresses several divides that must be bridged in materials science in order to transition to a renewable energy society. Despite our increasing demand for renewable energy materials over the past decade, as well as recent advances in photovoltaics (PV), solar energy still accounts for less than 1% of global energy generation. Additionally, real-world efficiencies of solar cells still lag behind theoretical limits, despite high-quality solar absorbers. These lags are in part from energetic losses due to suboptimal solar cell contacts; specifically, in contacts that have both p-type conductivity and optical transparency, which are the focus of this dissertation. A high performance p-type transparent conductor (TC) could enable advances in a wide range of PV applications, for example as a junction partner to new thin film absorbers, as part of a hole-selective top contact stack, as a semi-transparent hole-selective back contact, or as a window layer in tandem PV devices./nHowever, such a material with properties comparable to n-type transparent conducting oxides (TCOs) such as Sn-doped In2O3 (ITO) have not yet been found, and nearly all TCs used in industry are still n-type. The contradictory properties of transparency and conductivity are already difficult to achieve, but p-type TCs suffer from two additional physical challenges: (1) localized valence bands and (2) doping difficulties in wide-gap oxides. Although TCs are conventionally oxides, chalcogenide (S, Se, Te), pnictide (N, P, As), and mixed anion semiconductors show promise of higher hole transport and greater p-type doping propensity. High-throughput computational materials screenings offer a pathway to discover such materials, but so far no computationally predicted p-type TC has high enough performance for solar devices, which can be attributed to a disconnect between theory and experiment. How can we transform computational design principles to yield experimentally-realizable p-type TC materials?/nThis dissertation research combines high-throughput computation, combinatorial experimental methodologies, and PV device integration to discover and optimize new p-type TCs. My work addresses various aspects of this combined "p-type TC materials discovery pipeline," depicted graphically here and introduced in Chapter 1. Chapter 2 reviews the theoretical background and describes the computational and experimental methods that are used in conjunction throughout my research. In Chapter 3, before applying these methods to search for new p-type TCs, I define my search space in the context of computational material databases, as well as strategies to predict new materials not present in these databases. I also introduce and explore a database of new potential semiconductor alloys./nThe first phase of my research focuses on computational approaches to materials discovery. In Chapter 4, I define and evaluate descriptors currently used in computational screenings, which I show to have a remarkably high degree of false negatives and positives. Subsequently, I introduce new experimentally-guided metrics to assess high performance such as widening of a transparency window due to forbidden optical transitions. By performing various tiered computational searches in Chapter 5, I identify a set of promising p-type TC compounds such as BaSnS2, ZnZrN2, and BeSiP2 that were not previously grown as thin films, and CaMg2P2 and spinel MgAl2S4 which are not yet in databases and have not yet been synthesized. Screening for alloy endpoints also reveals a variety of new candidates to examine./nThe second phase of this dissertation involves synthesizing these predicted semiconductors as thin films. My approach uses combinatorial sputter deposition, which allows for varying stoichiometry, synthesis temperature, and thickness within a single sample in order to probe a wide array of phase space. I then perform a variety of structural, optical, and electronic characterization, first using combinatorial characterization and then zooming into a region of interest using more targeted analysis techniques. In Chapter 6, I introduce this methodology and focus on a few ternary case studies: CuxZn1-xS, BaSnS2, and ZnZrN2. I discuss some successes, such as an unexpected phase change and a high p-type TC figure of merit in CuxZn1-xS, and I also discuss challenges encountered in the laboratory such as difficulty crystallizing targeted ZnZrN2 and BaSnS2. I also investigate how to assess whether a predicted material is actually synthesizable as a thin film, using a descriptor-based approach I develope based on "disorder tolerance" in Chapter 8./nThe next step after synthesis and characterization is incorporating these new p-type TC materials into solar cell devices. I fabricate both silicon heterojunction (SHJ) and cadmium telluride (CdTe) solar cells, each using a novel p-type contact, to explore the challenges of bringing designed materials to actual highly-optimized device stacks; these two case studies are discussed in Chapter 7. This understanding, alongside simulations I perform, then leads to the development of new computational descriptors and screening criteria, discussed in Chapter 7 and Chapter 4. Thus, each phase of this process continues to inform subsequent phases. With this combined theoretical and experimental framework, I have discovered new p-type TC materials and have developed infrastructure and insight to inform future strategies for discovery of new solar cell materials./nI summarize my findings and lessons learned in Chapter 9, and conclude in Chapter 10 by discussing some of the environmental and human impacts of materials research. Renewable materials can lead to positive impacts, such as increased PV efficiency enabled by discovery of a high-performing p-type TC, but also materials can and have caused harm, and have led to climate catastrophe. I first propose a thought experiment to estimate the carbon cost of delaying PV deployment until solar cells are more efficient and show that our research cannot come at the cost of delaying PV installations. I also estimate my CO2 footprint during my PhD, demonstrating a significantly higher footprint than the average American and highlighting a specific cost of doing research. Finally, I reflect upon the ethical responsibility of scientists in the modern world: we have to change the way we do science to truly work towards a more equitable and sustainable future.

Advisor: Persson, Kristin A