Fast and reliable probabilistic reflectometry inversion with prior-amortized neural posterior estimation.

Reconstructing the structure of thin films and multilayers from measurements of scattered x-rays or neutrons is key to progress in physics, chemistry, and biology. However, finding all structures compatible with reflectometry data is computationally prohibitive for standard algorithms, which typically results in unreliable analysis with only a single potential solution identified. We address this lack of reliability with a probabilistic deep learning method that identifies all realistic structures in seconds, redefining standards in reflectometry.

Aryl-Acetylene Layered Hybrid Perovskites in Photovoltaics.

Metal halide perovskites have shown exceptional potential in converting solar energy to electric power in photovoltaics, yet their application is hampered by limited operational stability. This stimulated the development of hybrid layered (two-dimensional, 2D) halide perovskites based on hydrophobic organic spacers, templating perovskite slabs, as a more stable alternative. However, conventional organic spacer cations are electronically insulating, resulting in charge confinement within the inorganic slabs, thus limiting their functionality.

From Chalcogen Bonding to S-π Interactions in Hybrid Perovskite Photovoltaics.

The stability of hybrid organic-inorganic halide perovskite semiconductors remains a significant obstacle to their application in photovoltaics. To this end, the use of low-dimensional (LD) perovskites, which incorporate hydrophobic organic moieties, provides an effective strategy to improve their stability, yet often at the expense of their performance. To address this limitation, supramolecular engineering of noncovalent interactions between organic and inorganic components has shown potential by relying on hydrogen bonding and conventional van der Waals interactions.

Helical interfacial modulation for perovskite photovoltaics.

Hybrid metal halide perovskites have demonstrated remarkable performances in modern photovoltaics, although their stabilities remain limited. We assess the capacity to advance their properties by relying on interfacial modulators featuring helical chirality based on ,-(1-methylene-3-methyl-imidazolium)[6]helicene iodides. We investigate their characteristics, demonstrating comparable charge injection for enantiomers and the racemic mixture.

Resistive switching memories with enhanced durability enabled by mixed-dimensional perfluoroarene perovskite heterostructures.

Hybrid halide perovskites are attractive candidates for resistive switching memories in neuromorphic computing applications due to their mixed ionic-electronic conductivity. Moreover, their exceptional optoelectronic characteristics make them effective as semiconductors in photovoltaics, opening perspectives for self-powered memory elements. These devices, however, remain unexploited, which is related to the variability in their switching characteristics, weak endurance, and retention, which limit their performance and practical use.

Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge.

Due to the ambiguity related to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This ambiguity poses limitations on standard neural networks, constraining the range and number of considered parameters in previous machine learning solutions. To overcome this challenge, a novel training procedure has been designed which incorporates dynamic prior boundaries for each physical parameter as additional inputs to the neural network.

Halide Segregated Crystallization of Mixed-Halide Perovskites Revealed by In Situ GIWAXS.

Mixed-halide perovskites of the composition MAPb(BrI), which seem to exhibit a random and uniform distribution of halide ions in the absence of light, segregate into bromide- and iodide-rich phases under illumination. This phenomenon of halide segregation has been widely investigated in the photovoltaics context since it is detrimental for the material properties and ultimately the device performance of these otherwise very attractive materials. A full understanding of the mechanisms and driving forces has remained elusive.

Compact sample environment for in situ X-ray scattering during spin-coating.

We demonstrate a compact sample environment for the in situ study of crystallization kinetics of thin films on synchrotron beamlines, featuring atmospheric control, automated deposition, spin-coating, and annealing stages. The setup is suitable for studying thin film growth in real time using grazing-incidence X-ray diffraction techniques. Humidity and oxygen levels are being detected by sensors.

Closing the loop: autonomous experiments enabled by machine-learning-based online data analysis in synchrotron beamline environments.

Recently, there has been significant interest in applying machine-learning (ML) techniques to the automated analysis of X-ray scattering experiments, due to the increasing speed and size at which datasets are generated. ML-based analysis presents an important opportunity to establish a closed-loop feedback system, enabling monitoring and real-time decision-making based on online data analysis. In this study, the incorporation of a combined one-dimensional convolutional neural network (CNN) and multilayer perceptron that is trained to extract physical thin-film parameters (thickness, density, roughness) and capable of taking into account prior knowledge is described.

Elucidating Structure Formation in Highly Oriented Triple Cation Perovskite Films.

Metal halide perovskites are an emerging class of crystalline semiconductors of great interest for application in optoelectronics. Their properties are dictated not only by their composition, but also by their crystalline structure and microstructure. While significant efforts are dedicated to the development of strategies for microstructural control, significantly less is known about the processes that govern the formation of their crystalline structure in thin films, in particular in the context of crystalline orientation.

Machine learning for scattering data: strategies, perspectives and applications to surface scattering.

Machine learning (ML) has received enormous attention in science and beyond. Discussed here are the status, opportunities, challenges and limitations of ML as applied to X-ray and neutron scattering techniques, with an emphasis on surface scattering. Typical strategies are outlined, as well as possible pitfalls.

Optical Properties of Perovskite-Organic Multiple Quantum Wells.

A comprehensive study of the optical properties of CsPbBr perovskite multiple quantum wells (MQW) with organic barrier layers is presented. Quantum confinement is observed by a blue-shift in absorption and emission spectra with decreasing well width and agrees well with simulations of the confinement energies. A large increase of emission intensity with thinner layers is observed, with a photoluminescence quantum yield up to 32 times higher than that of bulk layers.

Erratum: Lattice gas study of thin-film growth scenarios and transitions between them: Role of substrate [Phys. Rev. E 103, 023302 (2021)].

This corrects the article DOI: 10.1103/PhysRevE.103.

Neural network analysis of neutron and X-ray reflectivity data: automated analysis using , experimental errors and feature engineering.

The Python package is demonstrated, which implements an optimized pipeline for the automated analysis of reflectometry data using machine learning. The package combines several training and data treatment techniques discussed in previous publications. The predictions made by the neural network are accurate and robust enough to serve as good starting parameters for an optional subsequent least-mean-squares (LMS) fit of the data.

Perovskite-organic tandem solar cells with indium oxide interconnect.

Multijunction solar cells can overcome the fundamental efficiency limits of single-junction devices. The bandgap tunability of metal halide perovskite solar cells renders them attractive for multijunction architectures. Combinations with silicon and copper indium gallium selenide (CIGS), as well as all-perovskite tandem cells, have been reported.

The Role of Alkyl Chain Length and Halide Counter Ion in Layered Dion-Jacobson Perovskites with Aromatic Spacers.

Layered hybrid perovskites based on Dion-Jacobson phases are of interest to various optoelectronic applications. However, the understanding of their structure-property relationships remains limited. Here, we present a systematic study of Dion-Jacobson perovskites based on (S)PbX ( = 1) compositions incorporating phenylene-derived aromatic spacers (S) with different anchoring alkylammonium groups and halides (X = I, Br).

Multimodal host-guest complexation for efficient and stable perovskite photovoltaics.

Formamidinium lead iodide perovskites are promising light-harvesting materials, yet stabilizing them under operating conditions without compromising optimal optoelectronic properties remains challenging. We report a multimodal host-guest complexation strategy to overcome this challenge using a crown ether, dibenzo-21-crown-7, which acts as a vehicle that assembles at the interface and delivers Cs ions into the interior while modulating the material. This provides a local gradient of doping at the nanoscale that assists in photoinduced charge separation while passivating surface and bulk defects, stabilizing the perovskite phase through a synergistic effect of the host, guest, and host-guest complex.

A combined molecular dynamics and experimental study of two-step process enabling low-temperature formation of phase-pure α-FAPbI.

It is well established that the lack of understanding the crystallization process in a two-step sequential deposition has a direct impact on efficiency, stability, and reproducibility of perovskite solar cells. Here, we try to understand the solid-solid phase transition occurring during the two-step sequential deposition of methylammonium lead iodide and formamidinium lead iodide. Using metadynamics, x-ray diffraction, and Raman spectroscopy, we reveal the microscopic details of this process.

Polymorphism and structure formation in copper phthalocyanine thin films.

Many polymorphic crystal structures of copper phthalocyanine (CuPc) have been reported over the past few decades, but despite its manifold applicability, the structure of the frequently mentioned α polymorph remained unclear. The base-centered unit cell (space group 2/) suggested in 1966 was ruled out in 2003 and was replaced by a primitive triclinic unit cell (space group 1). This study proves unequivocally that both α structures coexist in vacuum-deposited CuPc thin films on native silicon oxide by reciprocal space mapping using synchrotron radiation in grazing incidence.

Lattice gas study of thin-film growth scenarios and transitions between them: Role of substrate.

Thin-film growth is investigated in two types of lattice gas models where substrate and film particles are different, expressed by unequal interaction energy parameters. The first is of solid-on-solid type, whereas the second additionally incorporates desorption, diffusion in the gas phase above the film and readsorption at the film (appropriate for growth in colloidal systems). In both models, the difference between particle-substrate and particle-particle interactions plays a central role for the evolution of the film morphology at intermediate times.

Nanoscale Phase Segregation in Supramolecular π-Templating for Hybrid Perovskite Photovoltaics from NMR Crystallography.

The use of layered perovskites is an important strategy to improve the stability of hybrid perovskite materials and their optoelectronic devices. However, tailoring their properties requires accurate structure determination at the atomic scale, which is a challenge for conventional diffraction-based techniques. We demonstrate the use of nuclear magnetic resonance (NMR) crystallography in determining the structure of layered hybrid perovskites for a mixed-spacer model composed of 2-phenylethylammonium (PEA) and 2-(perfluorophenyl)ethylammonium (FEA) moieties, revealing nanoscale phase segregation.

Roughness evolution in strongly interacting donor:acceptor mixtures of molecular semiconductors. An in situ, real-time growth study using x-ray reflectivity.

The evolution of surface roughness in binary mixtures of the two molecular organic semiconductors (OSCs) diindenoperylene (DIP) as electron-donor and 1, 3, 4, 5, 7, 8-hexafluoro-tetracyano naphthoquinodimethane (F6TCNNQ) as electron-acceptor is studied. We co-deposit DIP and F6TCNNQ in vacuum with varying relative molar content while keeping a molar excess of DIP in order to produce phase-heterogeneous mixtures. The excess DIP phase segregates in pristine crystallites, whereas the remaining mixed phase is constituted by DIP:F6TCNNQ co-crystallites.

Minimizing the Trade-Off between Photocurrent and Photovoltage in Triple-Cation Mixed-Halide Perovskite Solar Cells.

Its lower bandgap makes formamidinium lead iodide (FAPbI) a more suitable candidate for single-junction solar cells than pure methylammonium lead iodide (MAPbI). However, its structural and thermodynamic stability is improved by introducing a significant amount of MA and bromide, both of which increase the bandgap and amplify trade-off between the photocurrent and photovoltage. Here, we simultaneously stabilized FAPbI into a cubic lattice and minimized the formation of photoinactive phases such as hexagonal FAPbI and PbI by introducing 5% MAPbBr, as revealed by synchrotron X-ray scattering.

Enhanced protein adsorption upon bulk phase separation.

In all areas related to protein adsorption, from medicine to biotechnology to heterogeneous nucleation, the question about its dominant forces and control arises. In this study, we used ellipsometry and quartz-crystal microbalance with dissipation (QCM-D), as well as density-functional theory (DFT) to obtain insight into the mechanism behind a wetting transition of a protein solution. We established that using multivalent ions in a net negatively charged globular protein solution (BSA) can either cause simple adsorption on a negatively charged interface, or a (diverging) wetting layer when approaching liquid-liquid phase separation (LLPS) by changing protein concentration (c) or temperature (T).