ABSTRACT
Nanoscale materials characterization often uses highly energetic probes which can rapidly damage beam-sensitive materials, such as hybrid organic-inorganic compounds. Reducing the probe dose minimizes the damage, but often at the cost of lower signal-to-noise ratio (SNR) in the acquired data. This work reports the optimization and validation of principal component analysis (PCA) and nonnegative matrix factorization for the postprocessing of low-dose nanoscale characterization data. PCA is found to be the best approach for data denoising. However, the popular scree plot-based method for separation of principal and noise components results in inaccurate or excessively noisy models of the heterogeneous original data, even after Poissonian noise weighting. Manual separation of principal and noise components produces a denoised model which more accurately reproduces physical features present in the raw data while improving SNR by an order of magnitude. However, manual selection is time-consuming and potentially subjective. To suppress these disadvantages, a deep learning-based component classification method is proposed. The neural network model can examine PCA components and automatically classify them with an accuracy of >99% and a rate of â¼2 component/s. Together, multivariate analysis and deep learning enable a deeper analysis of nanoscale materials' characterization, allowing as much information as possible to be extracted.
ABSTRACT
Halide perovskite materials offer an ideal playground for easily tuning their color and, accordingly, the spectral range of their emitted light. In contrast to common procedures, this work demonstrates that halide substitution in Ruddlesden-Popper perovskites not only progressively modulates the bandgap, but it can also be a powerful tool to control the nanoscale phase segregation-by adjusting the halide ratio and therefore the spatial distribution of recombination centers. As a result, thin films of chloride-rich perovskite are engineered-which appear transparent to the human eye-with controlled tunable emission in the green. This is due to a rational halide substitution with iodide or bromide leading to a spatial distribution of phases where the minor component is responsible for the tunable emission, as identified by combined hyperspectral photoluminescence imaging and elemental mapping. This work paves the way for the next generation of highly tunable transparent emissive materials, which can be used as light-emitting pixels in advanced and low-cost optoelectronics.
ABSTRACT
Quantitative chemical analysis on the nanoscale provides valuable information on materials and devices which can be used to guide further improvements to their performance. In particular, emerging families of technologically relevant composite materials such as organic-inorganic hybrid halide perovskites and metal-organic frameworks stand to benefit greatly from such characterization. However, these nanocomposites are also vulnerable to damage induced by analytical probes such as electron, X-ray, or neutron beams. Here the effect of electrons on a model hybrid halide perovskite is investigated, focusing on the acquisition parameters appropriate for energy-dispersive X-ray spectroscopy in a scanning transmission electron microscope (STEM-EDX). The acquisition parameters are systematically varied to examine the relationship between electron dose, data quality, and beam damage. Five metrics are outlined to assess the quality of STEM-EDX data and severity of beam damage, further validated by dark field STEM imaging. Loss of iodine through vacancy creation is found to be the primary manifestation of electron beam damage in the perovskite specimen, and iodine content is seen to decrease exponentially with electron dose. This work demonstrates data acquisition and analysis strategies that can be used for studying electron beam damage and for achieving reliable quantification for a broad range of beam-sensitive materials.
ABSTRACT
Although perovskite light-emitting diodes (PeLEDs) have recently experienced significant progress, there are only scattered reports of PeLEDs with both high efficiency and long operational stability, calling for additional strategies to address this challenge. Here, we develop perovskite-molecule composite thin films for efficient and stable PeLEDs. The perovskite-molecule composite thin films consist of in-situ formed high-quality perovskite nanocrystals embedded in the electron-transport molecular matrix, which controls nucleation process of perovskites, leading to PeLEDs with a peak external quantum efficiency of 17.3% and half-lifetime of approximately 100 h. In addition, we find that the device degradation mechanism at high driving voltages is different from that at low driving voltages. This work provides an effective strategy and deep understanding for achieving efficient and stable PeLEDs from both material and device perspectives.
ABSTRACT
Halide perovskites are emerging as valid alternatives to conventional photovoltaic active materials owing to their low cost and high device performances. This material family also shows exceptional tunability of properties by varying chemical components, crystal structure, and dimensionality, providing a unique set of building blocks for new structures. Here, highly stable self-assembled lead-tin perovskite heterostructures formed between low-bandgap 3D and higher-bandgap 2D components are demonstrated. A combination of surface-sensitive X-ray diffraction, spatially resolved photoluminescence, and electron microscopy measurements is used to reveal that microstructural heterojunctions form between high-bandgap 2D surface crystallites and lower-bandgap 3D domains. Furthermore, in situ X-ray diffraction measurements are used during film formation to show that an ammonium thiocyanate additive delays formation of the 3D component and thus provides a tunable lever to substantially increase the fraction of 2D surface crystallites. These novel heterostructures will find use in bottom cells for stable tandem photovoltaics with a surface 2D layer passivating the 3D material, or in energy-transfer devices requiring controlled energy flow from localized surface crystallites to the bulk.
ABSTRACT
Hybrid metal halide perovskites have emerged as a potential photovoltaic material for low-cost thin film solar cells due to their excellent optoelectronic properties. However, high efficiencies obtained with lab-scale cells are difficult to replicate in large modules. The upscaling process requires careful optimization of multiple steps, such as laser scribing, which divides a module into serially connected cells using a pulsed laser beam. In this work, we characterize the effect of laser scribing on the perovskite layer adjacent to a P3 scribe line using analytical scanning and cross-sectional transmission electron microscopy techniques. We demonstrate that lateral flow of residual thermal energy from picosecond laser pulses decomposes the perovskite layer over extended length scales. We propose that the exact nature of the change in perovskite composition is determined by the presence of preexisting PbI2 grains and hence by the original perovskite formation reaction. Furthermore, we show that along the P3 lines, the indium tin oxide contact is also damaged by high-fluence pulses. Our results provide a deeper understanding on the interaction between laser pulses and perovskite solar modules, highlighting the need to minimize material damage by careful tuning of both laser parameters and the device fabrication procedure.
ABSTRACT
Organo-metal halide perovskite demonstrates a large potential for achieving highly efficient photovoltaic devices. The scaling-up process represents one of the major challenges to exploit this technology at the industrial level. Here, the scaling-up of perovskite solar modules from 5 × 5 to 10 × 10 cm2 substrate area is reported by blade coating both the CH3NH3PbI3 perovskite and spiro-OMeTAD layers. The sequential deposition approach is used in which both lead iodide (PbI2) deposition and the conversion step are optimized by using additives. The PbI2 solution is modified by adding methylammonium iodide (MAI) which improves perovskite crystallinity and pore filling of the mesoporous TiO2 scaffold. Optimization of the conversion step is achieved by adding a small concentration of water into the MAI-based solution, producing large cubic CH3NH3PbI3 grains. The combination of the two modifications leads to a power conversion efficiency of 14.7% on a perovskite solar module with an active area of 47 cm2.
ABSTRACT
The power conversion efficiency of organic-inorganic hybrid perovskite solar cells has soared over the past ten years and currently rivals those of crystalline silicon and other thin-film solar cells. Most of the research effort so far has been focused on three-dimensional (3 D) perovskite crystals, producing devices with very high efficiency but poor operational and environmental stability. Two-dimensional (2 D) Ruddlesden-Popper perovskite has recently shown its potential as a highly stable light absorber, albeit with low efficiency. This work reviews the current progress in attaining both high efficiency and stability in solar cells by using 2 D perovskite. In particular, the focus is on multidimensional perovskite as a way to combine the best characteristics of 3 D and 2 D perovskites. Future challenges and potential methods to boost the performance of multidimensional perovskite solar cells further are briefly presented.
