Data-driven enhancement of cubic phase stability in mixed-cation perovskites

Phase Transitions and Dynamics in Mixed Three- and Low-Dimensional Lead Halide Perovskites

Lead halide perovskites are extensively investigated as efficient solution-processable materials for photovoltaic applications. The greatest stability and performance of these compounds are achieved by mixing different ions at all three sites of the APbX3 structure. Despite the extensive use of mixed lead halide perovskites in photovoltaic devices, a detailed and systematic understanding of the mixing-induced effects on the structural and dynamic aspects of these materials is still lacking. The goal of this review is to summarize the current state of knowledge on mixing effects on the structural phase transitions, crystal symmetry, cation and lattice dynamics, and phase diagrams of three- and low-dimensional lead halide perovskites. This review analyzes different mixing recipes and ingredients providing a comprehensive picture of mixing effects and their relation to the attractive properties of these materials.

Composition-Property Relations for GAx FAy MA1- x - y PbI3 Perovskites

Halide perovskites are materials for diverse optoelectronic applications owing to a combination of factors, including their compositional flexibility. A major source of this diversity of compositions comes from the use of mixed organic cations in the A-site of such compounds to form solid solutions. Many organic cations are possible for this purpose. Although significant progress is made over years of intensive research, the determination of systematic relationships between the compositions and properties of halide perovskites is not exploited accordingly. Using the MAPbI3 prototype, a wide range of compositions substituted by formamidinium (FA+ ) and guanidinium (GA+ ) cations are studied. From a detailed collection of experimental data and results reported in the literature, heat maps correlating the composition of GAx FAy MA1- x - y PbI3 solid solutions with phase transition temperatures, dielectric permittivity, and activation energies are constructed. Considering the characteristics of organic cations, namely their sizes, dipole moments, and the number of N─H bonds, it is possible to interpret the heat maps as consequences of these characteristics. This work brings a systematization of how obtaining specific properties of halide perovskites might be possible by customizing the characteristics of the A-site organic cations.

The Development of New Perovskite-Type Oxygen Transport Membranes Using Machine Learning

The aim of this work is to predict suitable chemical compositions for the development of new ceramic oxygen gas separation membranes, avoiding doping with toxic cobalt or expensive rare earths. For this purpose, we have chosen the system Sr1−xBax(Ti1−y−zVyFez)O3−δ (cubic perovskite-type phases). We have evaluated available experimental data, determined missing crystallographic information using bond-valence modeling and programmed a Python code to be able to generate training data sets for property predictions using machine learning. Indeed, suitable compositions of cubic perovskite-type phases can be predicted in this way, allowing for larger electronic conductivities of up to σe = 1.6 S/cm and oxygen conductivities of up to σi = 0.008 S/cm at T = 1173 K and an oxygen partial pressure pO2 = 10−15 bar, thus enabling practical applications.

Structure, optoelectronic properties and thermal stability of the triple organic cation GAxFAxMA1-2xPbI3 system prepared by mechanochemical synthesis

Halide perovskites are a well-known class of materials with many interesting applications. Great attention has been devoted to investigating halide perovskites containing triple methylammonium (MA⁺), formamidinium (FA⁺), and guanidinium (GA⁺) cations. Despite presenting very good applied perspectives so far, the lack of fundamental information for this system, such as its structural, thermal, and optoelectronic characteristics, prompts a step back before any technological leap forward. In the present work, we investigate the physical properties of mechanochemically solvent-free synthesized GA_xFA_xMA_1-2xPbI₃ halide perovskite powders with compositions of 0.00 ≤ x ≤ 0.15. We demonstrate that the synthesis of the powders can be performed by a simple manual mechanical grinding of the precursors for about 40 minutes, leading to solid solutions with an only minor content of unreacted precursors. X-ray diffraction, differential scanning calorimetry, and infrared spectroscopy techniques were used to investigate the structure, tetragonal-to-cubic phase transition, and vibrational characteristics of the organic cations with increasing GA⁺ and FA⁺ contents, respectively. The band gap and Urbach energies, obtained from ultraviolet-visible spectroscopy analyses, ranged from 1.58 to 1.65 eV and 23 to 36 meV, respectively, depending on the composition. These parameters demonstrate a non-random variation with x composition, which offers the possibility of a rational composition design for a given set of desired properties, demonstrating potential for optoelectronic applications. Finally, the system appears to have adequately tolerated heating for 12 hours at 120 °C in an ambient atmosphere, indicating high thermal stability and low ionic conductivity, which are desirable characteristics for solar cell applications.

Bertoleti E, Reis SP, Carvalho J, Araújo EB. Guanidinium substitution-dependent phase transitions, ionic conductivity and dielectric properties of MAPbI3

Over the past few years of boosting studies in halide perovskites, the formulation of guanidinium (GA+)-containing compounds has been proven to be an excellent strategy. A system in particular, namely...

Design Principles of Large Cation Incorporation in Halide Perovskites

Perovskites have stood out as excellent photoactive materials with high efficiencies and stabilities, achieved via cation mixing techniques. Overcoming challenges to the stabilization of Perovskite solar cells calls for the development of design principles of large cation incorporation in halide perovskite to accelerate the discovery of optimal stable compositions. Large fluorinated organic cations incorporation is an attractive method for enhancing the intrinsic stability of halide perovskites due to their high dipole moment and moisture-resistant nature. However, a fluorinated cation has a larger ionic size than its non-fluorinated counterpart, falling within the upper boundary of the mixed-cation incorporation. Here, we report on the intrinsic stability of mixed Methylammonium (MA) lead halides at different concentrations of large cation incorporation, namely, ehtylammonium (EA; [CH₃CH₂NH₃]⁺) and 2-fluoroethylammonium (FEA; [CH₂FCH₂NH₃]⁺). Density functional theory (DFT) calculations of the enthalpy of the mixing and analysis of the perovskite structural features enable us to narrow down the compositional search domain for EA and FEA cations around concentrations that preserve the perovskite structure while pointing towards the maximal stability. This work paves the way to developing design principles of a large cation mixture guided by data analysis of DFT data. Finally, we present the automated search of the minimum enthalpy of mixing by implementing Bayesian optimization over the compositional search domain. We introduce and validate an automated workflow designed to accelerate the compositional search, enabling researchers to cut down the computational expense and bias to search for optimal compositions.

Investigation of Opto-Electronic Properties and Stability of Mixed-Cation Mixed-Halide Perovskite Materials with Machine-Learning Implementation

The feasibility of mixed-cation mixed-halogen perovskites of formula AxA’1−xPbXyX’zX”3−y−z is analyzed from the perspective of structural stability, opto-electronic properties and possible degradation mechanisms. Using density functional theory (DFT) calculations aided by machine-learning (ML) methods, the structurally stable compositions are further evaluated for the highest absorption and optimal stability. Here, the role of the halogen mixtures is demonstrated in tuning the contrasting trends of optical absorption and stability. Similarly, binary organic cation mixtures are found to significantly influence the degradation, while they have a lesser, but still visible effect on the opto-electronic properties. The combined framework of high-throughput calculations and ML techniques such as the linear regression methods, random forests and artificial neural networks offers the necessary grounds for an efficient exploration of multi-dimensional compositional spaces.