Advanced nanomaterials show a significant improvement in certain physical or functional properties compared to conventional materials. Such advanced materials are, for example, lead halide perovskites (LHP). It is a group of hybrid organic-inorganic materials with a direct bandgap exhibiting unique optical properties. The high quantum efficiency of photoluminescence makes nanocrystals or thin films of LHP suitable candidates for the production of light-emitting diodes, solar cells and LCD displays. Their inexpensive and simple fabrication together with their unique optical properties makes LHP one of the most developed materials of the last decade. This diploma thesis aims to study the optical properties of CsPbBr3 perovskite nanocrystals using high lateral resolution methods. CsPbBr3 perovskite nanocrystals show intense anti-Stokes photoluminescence. These nanocrystals can emit light with a lower wavelength than that of the light that causes their photoluminescence. The nanocrystals are prepared in two different ways: by evaporation or by crystallization of the precursor in a solution of dimethylformamide. The morphology, photoluminescence properties and chemical composition of individual nanocrystals are studied. Each nanocrystal is studied individually and its size, shape, photoluminescence properties and chemical compounds are determined, which leads to a deeper understanding of the anti-Stokes photoluminescence of perovskite nanocrystals.

Metallhalogenid Perowskite sind eine aufkommende Klasse von Halbleitermaterialien, die einige der besten Eigenschaften von organischen und anorganischen Halbleitern vereinen. Die Materialien kombinieren eine hohe Leitfähigkeit und modulierbare Bandlücke mit hohem Absorptionskoeffizienten und Löslichkeit in organischen Lösungsmitteln. Verarbeitungsmethoden wie Tintenstrahldruck ermöglichen somit die Herstellung von kristallinen Halbleitern mit direkter Bandlücke aus Lösung. Zunächst werden in einem kombinatorischen Druckprozess drei Perowskittinten, aus drei separaten Druckköpfen, während des Druckprozesses gemischt. Es resultiert eine Reihe von Perowskitfilmen mit genau definierten Zusammensetzungen. Die Kontrolle über die resultierenden Materialeigenschaften wird durch die Herstellung einer Reihe wellenlängenselektiver Fotodetektoren und Langpassfiltern demonstriert, die zu einem tintenstrahlgedruckten dispersionselementfreien Spektrometer kombiniert werden. Weiterhin wird mit den Möglichkeiten eines Tintenstrahldruckers für großflächige Bearbeitung ein etabliertes Verfahren für Tintenstrahl-gedruckte Perowskit-LEDs (PeLEDs) hochskaliert. Mit dem gleichen Druckverfahren und der gleichen Tintenzusammensetzung wurde die aktiv emittierende Fläche von 4 mm² auf 1600 mm² erhöht. Es konnte ein homogener Perowskit Dünnfilm für PeLEDs gedruckt werden, ohne einen Anstieg des Leckstroms mit steigender Fläche zu verursachen. Zuletzt werden die Strukturierungsmöglichkeiten des Tintenstrahldrucks genutzt um zweifarbige PeLEDs herzustellen. Auf einer primären Perowskitschicht wird eine zweite Perowskit-Vorläufertinte aufgebracht. Während des Betriebs erfährt der gemischte Halogenid-Perowskit eine Phasenseparierung und zeigt nur tiefrote Emission von iodidreichen Domänen vor einem hellgrünen emittierenden Hintergrund, dessen Helligkeit nicht durch den Strukturierungsprozess vermindert wird. / Metal halide perovskites are an emerging semiconductor material class that combines some of the best properties of inorganic and organic semiconductors. The material pairs high conductivity and composition-based bandgap tunability with solution processability and high absorption coefficients. Deposition methods like inkjet printing thus allow for the fabrication of crystalline, direct bandgap semiconductors from solution for various applications. First, in a combinatorial printing approach, three perovskite precursor inks, from three separate printheads, are mixed during the printing process. By controlling the perovskite composition, material properties such as the bandgap can be tuned. This is demonstrated by fabrication of a range of wavelength-selective photodetectors and longpass filters, which are combined to yield an inkjet-printed, dispersion element-free spectrometer. Furthermore, using the large-scale capabilities of an inkjet printer, a previously established procedure for inkjet-printed perovskite LEDs (PeLEDs) is upscaled. The actively emitting area is increased from 4 mm² to 1600 mm² using the same printing procedure and ink formulation. This achieved a homogeneous perovskite film, that showed no increase in leakage current, independent of size. Finally, using the patterning capabilities of inkjet printing, dual coloured red/green PeLEDs are fabricated in a sequential printing process. On a primary perovskite layer, a second perovskite precursor ink is deposited. Under operation in a PeLED, the mixed halide perovskite experiences phase segregation and only shows deep red emission from iodide-rich domains against a bright green emitting background, which still performs as well as a non-patterned device.

<p>  </p> <p>Organic-inorganic halide perovskites are at the brink of commercialization as the next generation of light-absorbing materials for solar energy harvesting devices. Perovskites have large absorption coefficients, long charge-carrier lifetimes and diffusion lengths, and a tunable absorption spectrum. Furthermore, these materials can be low-temperature solution-processed, which transfers to low-cost manufacturing and cost-competitive products. The remarkable material properties of perovskites enable a broad product-market fit, encompassing traditional and new applications for solar technology. Perovskites can be deposited on flexible substrates for flexible solar cells, applied in thermochromic windows for power generation and building cooling, or tuned for tandem solar cell application to include in high-performance solar panels. However, perovskites are intrinsically unstable, which has so far prevented their commercialization. Despite large research efforts, including over two thousand publications per year, perovskite solar cells degrade in under one year of operation. In a saturated research field, new ideas are needed to inspire alternative approaches to solve the perovskite stability problem. In this dissertation, we detail research efforts surrounding the concept of a self-healing perovskite solar cell.</p> <p>     A self-healing perovskite solar cell can be classified with two distinctions: mechanically healing and molecularly healing. First, mechanically self-healing involves the material’s ability to recover its intrinsic properties after mechanical damage such as tares, lacerations, or cracking. This type of healing was unique to the organic polymer community and ultra-rare in semiconducting materials. By combining a self-healing polymer with perovskite material, we developed a self-healing semiconducting perovskite composite material which can heal using synergistic grain growth and solid-state diffusion processes at slightly elevated temperatures. The material is demonstrated in flexible solar cells with improved bending durability and a power conversion efficiency reaching 10%. The addition of fluidic polymer enables macroscopic perovskite material movement, which is otherwise brittle and rigid. The results inspire the use of polymer scaffolds for mechanically self-healing solar cells.</p> <p>     The second type of healing, molecular healing, involves healing defects within the rigid crystal domains resulting from ion migration. The same phenomenon which leads to device degradation, also assists the recovery of the device performance after resting the device in the dark. During device operation, perovskite ions diffuse in the perovskite lattice and accumulate at the device interfaces where they undergo chemical reactions or leave the perovskite layer, ultimately consuming the perovskite precursors. The photovoltaic performance can be recovered if irreversible degradation is limited. Ideally, degradation and recovery can match day and night cycling to dramatically extend the lifetime of perovskite solar cells. In this dissertation, we introduce the application of chalcogenide chemistry in the fabrication of perovskite solar cells to control the thin film crystallization process, ultimately to reduce defects in the perovskite bulk and introduce surface functionality which extends the device stability. This new strategy will help improve molecularly self-healing perovskite solar cell by reducing irreversible degradation. Lastly, we present a few other new ideas to inspire future research in perovskite solar cells and assist in the commercialization of the next generation of photovoltaics.</p>

<p>A wide range of optoelectronic applications demand semiconductors optimized for purpose.</p> <p>My research focused on data-driven identification of ABX3 Halide perovskite compositions for optimum photovoltaic absorption in solar cells.</p> <p>I trained machine learning models on previously reported datasets of halide perovskite band gaps based on first principles computations performed at different fidelities.</p> <p>Using these, I identified mixtures of candidate constituents at the A, B or X sites of the perovskite supercell which leveraged how mixed perovskite band gaps deviate from the linear interpolations predicted by Vegard's law of mixing to obtain a selection of stable perovskites with band gaps in the ideal range of 1 to 2 eV for visible light spectrum absorption.</p> <p>These models predict the perovskite band gap using the composition and inherent elemental properties as descriptors.</p> <p>This enables accurate, high fidelity prediction and screening of the much larger chemical space from which the data samples were drawn.</p> <p><br></p> <p>I utilized a recently published density functional theory (DFT) dataset of more than 1300 perovskite band gaps from four different levels of theory, added to an experimental perovskite band gap dataset of \textasciitilde{}100 points, to train random forest regression (RFR), Gaussian process regression (GPR), and Sure Independence Screening and Sparsifying Operator (SISSO) regression models, with data fidelity added as one-hot encoded features.</p> <p>I found that RFR yields the best model with a band gap root mean square error of 0.12 eV on the total dataset and 0.15 eV on the experimental points.</p> <p>SISSO provided compound features and functions for direct prediction of band gap, but errors were larger than from RFR and GPR.</p> <p>Additional insights gained from Pearson correlation and Shapley additive explanation (SHAP) analysis of learned descriptors suggest the RFR models performed best because of (a) their focus on identifying and capturing relevant feature interactions and (b) their flexibility to represent nonlinear relationships between such interactions and the band gap.</p> <p>The best model was deployed for predicting experimental band gap of 37785 hypothetical compounds.</p> <p>Based on this, we identified 1251 stable compounds with band gap predicted to be between 1 and 2 eV at experimental accuracy, successfully narrowing the candidates to about 3% of the screened compositions.</p>