Interfacial Engineering for Controlled Crystal Mosaicity in Single-Crystalline Perovskite Films.

Organic-inorganic hybrid perovskites have attracted significant attention for optoelectronic applications due to their efficient photoconversion properties. However, grain boundaries and irregular crystal orientations in polycrystalline films remain issues. This study presents a method for producing crystalline-orientation-controlled perovskite single-crystal films using retarded solvent evaporation. It is shown that single-crystal films, grown via inverse temperature crystallization within a confined space, exhibit enhanced optoelectronic property. Using interfacial polymer layer, this method produces high-quality perovskite single-crystalline films with varying crystal orientations. Density functional theory calculations confirm favorable adsorption energies for (110) surfaces with methylammonium iodide and PbI2 terminations on poly(3-hexylthiophene), and stronger adsorption for (224) surfaces with I and methylammonium terminations on polystyrene, influenced by repulsive forces between the thiophene group and the perovskite surface. The correlation between charge transport characteristics and perovskite single-crystalline properties highlights potential advancements in perovskite optoelectronics, improving device performance and reliability.

Utilizing Machine Learning and Diode Physics to Investigate the Effects of Stoichiometry on Photovoltaic Performance in Sequentially Processed Perovskite Solar Cells.

Organic-inorganic metal halide perovskite solar cells are renowned for their extensive solution processability, although the production of uniformly crystalline perovskite films can necessitate intricate deposition methods. In our study, we harmonized Shockley diode-based numerical analysis with machine learning techniques to extract the device characteristics of perovskite solar cells and optimize their photovoltaic performance in light of the experimental variables. The application of the Shockley diode equation facilitated the extraction of photovoltaic parameters and the prediction of power conversion efficiencies, thus aiding the understanding of device physics and charge recombination. Through machine learning, specifically Gaussian process regression, we trained models on current-voltage curves sensitive to variations in fabrication conditions, thereby pinpointing the optimal settings for enhanced device performance. Our multifaceted approach not only clarifies the interplay between experimental conditions and device performance but also streamlines the optimization process, diminishing the need for exhaustive trial-and-error experiments. This methodology holds substantial promise for advancing the development and fine-tuning of next-generation perovskite solar cells.

Correction: Optical humidity sensors based on lead-free Cu-based perovskite nanomaterials.

[This corrects the article DOI: 10.1039/D2NA00168C.].

Optical humidity sensors based on lead-free Cu-based perovskite nanomaterials.

Organometallic halide perovskite materials possess unique and tunable optical properties with a wide range of optoelectronic applications. However, these materials suffer from humidity-driven degradation in ambient atmospheres. In this paper we investigate stable copper-based perovskite nanocrystals for potential use in humidity sensors, specifically examining their unique humidity-dependent optical properties and reversibility. We controlled stoichiometric ratios of Cu-based perovskites and demonstrated that (methylammonium)2CuBr4 nanocrystals showed excellent reversible physisorption of water molecules. These perovskite nanocrystals exhibited reversible hydro-optical properties, including transparency changes in response to variations in relative humidity under ambient conditions. The perovskite nanomaterial humidity sensor was highly reliable and stable, with a linear correlation in a relative humidity range of 7% to 98%. Accordingly, the lead-free Cu-based perovskite materials developed herein have the potential to be employed as real-time, self-consistent humidity sensors.