As global energy demands escalate, the need for technological advancements in alternative energy sources becomes crucial to counter climate change. Hybrid organic-inorganic perovskites (HOIPs) have demonstrated great promise for optoelectronics, owing to their tunable bandgap, cost-effectiveness, and simplicity in fabrication. Despite their rapidly growing efficiency and popularity among the scientific community, they suffer from sensitivity to exposure to different environmental stressors (humidity, temperature, oxygen, light, and bias). To quantify the effects of similar surface treatments on perovskites, nanoscale spatial resolution with scanning probe microscopy (SPM) methods are required. Leveraging the ability to resolve electrical characteristics of grains and grain boundaries with Kelvin probe force microscopy (KPFM), we investigate HOIP material systems, exploring the ion migration and charge trapping in grain boundaries in response to varying humidity conditions, and the effect of treatment with additives on humidity stability. Our results elucidate the transience of surface voltage distribution at various humidity exposure durations, due to a complex interaction between the mobile ions and water and the role of grain boundaries in this process. We see improvement in surface voltage and better resistance to humidity with additive treatment. Understanding the exact mechanism of interaction of water with photovoltaic materials is essential to harness the full potential of these materials for their application in commercial solar technologies. Overall, we anticipate the environmental, in situ and ex situ microscopy developed in this thesis to be extended for interrogating other halide perovskite families, including Pb-free options.

As anthropogenic global warming and climate change continues to intensify, it is more important than ever to curb our use of fossil fuels for heat and electricity. The clean energy transition requires investment in photovoltaic (PV) technology to replace unsustainable generation sources and to meet increasing electrification demand. Most currently available PV modules use Si as the light absorber material. Advancements in the manufacturing process of Si solar cells has led to a reduction in cost over the past decade, yet there are still inherent difficulties in the refinement process. Next-generation PV must improve upon Si by maintaining or increasing device efficiency while simplifying manufacturing. Metal halide perovskite solar cells (PSC) have proven to meet these criteria, with >25% efficiency and cost-effective fabrication options such as blade coating and ink jet printing. However, degradation in perovskite materials under several environmental stressors (light, humidity, temperature, bias, and oxygen) precludes commercial adoption. Stability testing of PSC is time-consuming, particularly due to the large compositional space available. As a result, methods to quickly vet the stability of various perovskite compositions are critically needed. My thesis addresses this open problem by applying automated, in situ characterization and machine learning (ML) forecasting to PSC degradation studies.

First, I present a generalized ML roadmap for perovskite PV. I delineate three levels of PSC design and provide examples of ML projects which could accelerate the development process. Next, I design and build a high-throughput setup for in situ, environmental photoluminescence (PL) spectroscopy, a technique which requires <2 seconds to acquire data. The system uses a custom chamber containing up to 14 samples and an x-y translation stage to automatically move from one sample to the next. We select ten CsyFA1-yPb(BrxI1-x)3 perovskite thin films of varied composition and track changes in radiative recombination under repeated 6-hour temperature and rH cycles. Using the high-throughput setup, I obtain 240 PL spectra every hour and 14,000 spectra over the course of a single experiment. The temperature cycling results show increased non-radiative carrier recombination as samples are heated above 23°C. We show that FA-rich perovskites with 10-30% Cs+ have minimal lattice strain which promotes high structural and thermal stability. During rH cycling, all compositions displayed a PL enhancement with increasing rH as H2O passivates band gap trap states and suppresses non-radiative recombination. FA-rich films show the greatest PL increases over the course of the rH cycling while Cs-rich films reach a plateau in maximum PL value after 5-10 cycles. Finally, I apply ML models to the datasets and generate forecasts of environment-dependent PL responses. I use linear regression, Echo State Network (ESN), and Auto-Regressive Integrated Moving Average with eXogenous regressors (ARIMAX) algorithms. For the temperature cycling, I attain an average normalized root mean square error (NRMSE) over all compositions of 24.4% (linear regression), 16.6% (ESN), and 7.3% (ARIMAX) for prediction windows extending 70 hours into the future. For the rH cycling, NRMSE values of 72.5% (linear regression) and 44.0% (ESN) indicate difficulty in tracking long-term changes over a 50-hour window. Using ARIMAX with seasonality components, I achieve an error of only 10.3%, demonstrating the algorithm’s capability to model complex, non-linear data from varied perovskite compositions. My high-throughput characterization results and accurate time series forecasts illustrate the potential of data-centric approaches for perovskite stability investigations and showcase the promise of automation, data science, and ML as tools to drive PSC commercialization.

The study of optical materials for extreme environments is a rapidly growing field, with a number of possible applications from space science to energy efficiency to defense. In order to meet the growing demand for optical devices which can operate at very high temperatures and in different environments, we must first characterize the optical properties of different materials which might be used in the design of such devices at these elevated temperatures. Given their high-temperature stability, this makes refractory materials the ideal candidates for such a study. Refractory materials have previously been analyzed in great detail for their high-temperature structural and chemical stability. However, their usage as optical materials has been comparably limited.

In this thesis, I begin to analyze the optical properties of multiple classes of refractory materials: refractory metals and their oxides, refractory nitrides, and refractory carbides. In addition to analyzing their optical and chemical responses to high-temperature treatment, I present in situ high-temperature data up to 1,500°C, which are used to analyze their stability–or lack thereof–at very high temperatures. This thesis will also study multiple possible applications of each structure, including structural color, superabsorption, and thermophotovoltaics.

Structural color is used in a variety of applications, from conformal coatings for spacecraft, to sensing, to anticounterfeit technology. However, in many cases, the structural color systems proposed are either too complicated to fabricate making them difficult to scale for large-scale production, or would not be able to survive in the extreme environments required by some of these applications. We propose a simple multi- layer structure composed of a refractory metal and its oxide on silicon, in which the oxide is grown via high-temperature treatment in an oxygen-rich environment. During this high-temperature treatment (up to 600C) we measure the samples’ optical properties in situ using ellipsometry, which can give us very precise control over the thickness of the generated oxide layer and thus the generated color of the structure. In addition to our experimental results for three refractory metals (Ru, Ta, and W), we present simulated results demonstrating the full range of possible colors achievable with these metals and their oxides.

Many technological applications in photonics require devices to function reliably under extreme conditions, including high temperatures. To this end, materials and structures with thermally stable optical properties are indispensable. State-of-the-art thermal photonic devices based on nanostructures suffer from severe surface diffusion-induced degradation, and the operational temperatures are often restricted. Here we report on a thermo-optically stable superabsorber composed of bilayer refractory dielectric materials. The device features an average absorptivity 90% over >500 nm bandwidth in the near-infrared (NIR) regime, with minimal temperature dependence up to 1,500°C. Our results demonstrate an alternative pathway to achieve high-temperature thermo-optically stable photonic devices.

As the impacts of extended fossil fuel use are felt by our environment, economy, and public health, it becomes increasingly crucial to minimize our dependence on fossil fuels in favor of reusable, clean energy generation techniques. This requires the optimization of efficiency for each technique, thus requiring the minimization of waste heat. One method through which we can recover this waste heat is using thermophotovoltaics (TPV): converting the waste heat into usable electricity utilizing a thermal emitter and a photovoltaic cell. We propose a simple bi-layer SiC/AlN structure as a broadband thermal emitter for thermophotovoltaic applications, demonstrating ex situ and in situ its optical stability in temperatures up to 1,200°C in air and 1,500°C in inert environments. Our results demonstrate a scalable, broadband thermal emitter which can be applied for waste heat recovery across a myriad of high-temperature energy generation processes.