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. ML-based online analysis results are processed in a closed-loop workflow for X-ray reflectometry (XRR), using the growth of organic thin films as an example. Our focus lies on the beamline integration of ML-based online data analysis and closed-loop feedback. Our data demonstrate the accuracy and robustness of ML methods for analyzing XRR curves and Bragg reflections and its autonomous control over a vacuum deposition setup.

Investigating the Conformation of Surface-Adsorbed Proteins with Standing-Wave X-ray Fluorescence.

Protein adsorption to surfaces is at the heart of numerous technological and bioanalytical applications, but sometimes, it is also associated with medical risks. To deepen our insights into processes involving layers of surface-adsorbed proteins, high-resolution structural information is essential. Here, we use standing-wave X-ray fluorescence (SWXF) in combination with an optimized liquid-cell setup to investigate the underwater conformation of the random-coiled phosphoprotein ß-casein adsorbed to hydrophilic and hydrophobized solid surfaces. The orientation of the protein, as determined through the distributions of sulfur and phosphorus, is found to be sensitive to the chemical nature of the substrate. While no preferred orientations are observed on hydrophobized surfaces, on hydrophilic Al oxide, ß-casein is adsorbed as a diblock copolymer with the phosphorylated domain I attached to the surface. Our results demonstrate that targeting biologically relevant chemical elements with SWXF enables a detailed investigation of biomolecular layers under near-physiological conditions.

Molecular structure of the substrate-induced thin-film phase of tetracene.

We present a combined experimental and theoretical study to solve the unit-cell and molecular arrangement of the tetracene thin film (TF) phase. TF phases, also known as substrate induced phases (SIPs), are polymorphs that exist at interfaces and decisively impact the functionality of organic thin films, e.g., in a transistor channel, but also change the optical spectra due to the different molecular packing. As SIPs only exist in textured ultrathin films, their structure determination remains challenging compared to bulk materials. Here, we use grazing incidence X-ray diffraction and atomistic simulations to extract the TF unit-cell parameters of tetracene together with the atomic positions within the unit-cell.

Diffusion and nucleation in multilayer growth of PTCDI-C8 studied with in situ X-ray growth oscillations and real-time small angle X-ray scattering.

We study nucleation and multilayer growth of the perylene derivative PTCDI-C8 and find a persistent layer-by-layer growth, transformation of island shapes, and an enhancement of molecular diffusivity in upper monolayers (MLs). These findings result from the evaluation of the ML-dependent island densities, obtained by in situ real-time grazing incidence small angle X-ray scattering measurements and simultaneous X-ray growth oscillations. Complementary ex situ atomic force microscopy snapshots of different growth stages agree quantitatively with both X-ray techniques. The rate and temperature-dependent island density is analyzed using different mean-field nucleation models. Both a diffusion limited aggregation and an attachment limited aggregation model yield in the first two MLs the same critical nucleus size i, similar surface diffusion attempt frequencies in the 1019-1020 s-1 range, and a decrease of the diffusion barrier Ed in the 2nd ML by 140 meV.

Polymorphism in α-sexithiophene crystals: relative stability and transition path.

We present a joint theoretical and experimental study to investigate polymorphism in α-sexithiophene (6T) crystals. By means of density-functional theory calculations, we clarify that the low-temperature phase is favorable over the high-temperature one, with higher relative stability up to 50 meV per molecule. This result is in agreement with our thermal desorption measurements. We also propose a transition path between the high- and low-temperature 6T polymorphs, estimating an upper bound for the energy barrier of about 1 eV per molecule. The analysis of the electronic properties of the investigated 6T crystal structures complements our study.

Thermally driven smoothening of molecular thin films: Structural transitions in n-alkane layers studied in real-time.

We use thermal annealing to improve smoothness and to increase the lateral size of crystalline islands of n-tetratetracontane (TTC, C44H90) films. With in situ x-ray diffraction, we find an optimum temperature range leading to improved texture and crystallinity while avoiding an irreversible phase transition that reduces crystallinity again. We employ real-time optical phase contrast microscopy with sub-nm height resolution to track the diffusion of TTC across monomolecular step edges which causes the unusual smoothing of a molecular thin film during annealing. We show that the lateral island sizes increase by more than one order of magnitude from 0.5 µm to 10 µm. This desirable behavior of 2d-Ostwald ripening and smoothing is in contrast to many other organic molecular films where annealing leads to dewetting, roughening, and a pronounced 3d morphology. We rationalize the smoothing behavior with the highly anisotropic attachment energies and low surface energies for TTC. The results are technically relevant for the use of TTC as passivation layer and as gate dielectric in organic field effect transistors.

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. In this manner, the neural network can be trained simultaneously on all well-posed subintervals of a larger parameter space in which the inverse problem is underdetermined. During inference, users can flexibly input their own prior knowledge about the physical system to constrain the neural network prediction to distinct target subintervals in the parameter space. The effectiveness of the method is demonstrated in various scenarios, including multilayer structures with a box model parameterization and a physics-inspired special parameterization of the scattering length density profile for a multilayer structure. In contrast to previous methods, this approach scales favourably when increasing the complexity of the inverse problem, working properly even for a five-layer multilayer model and a periodic multilayer model with up to 17 open parameters.

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. Applications to reflectometry and grazing-incidence scattering are critically discussed. Comment is also given on the availability of training and test data for ML applications, such as neural networks, and a large reflectivity data set is provided as reference data for the community.

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. The spinning stage exhibits low vertical oscillation amplitude (∼3µm at speeds up to 10 000 rpm) and can optionally be employed for antisolvent application or gas quenching to investigate the impact of these techniques, which are often used to assist thin film growth. Differential reflectance spectroscopy is implemented in the spin-coater environment for inspecting thin film thickness and optical properties. The infrared radiation-based annealing system consists of a halogen lamp and a holder with an adjustable lamp-to-sample distance, while the sample surface temperature is monitored by a pyrometer. All features of the sample environment can be controlled remotely by the control software at synchrotron beamlines. In order to test and demonstrate the performance, the crystallization pathway of the antisolvent-assisted MAPbI3 (MA = methylammonium) perovskite thin film during the spinning and annealing stages is monitored and discussed.

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 C2/c) suggested in 1966 was ruled out in 2003 and was replaced by a primitive triclinic unit cell (space group P 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. The unit-cell parameters and the space group were determined by kinematic scattering theory and provide possible molecular arrangements within the unit cell of the C2/c structure by excluded-volume considerations. In situ X-ray diffraction experiments and ex situ atomic force microscopy complement the experimental data further and provide insight into the formation of a smooth thin film by a temperature-driven downward diffusion of CuPc molecules during growth.

Effect of the Organic Semiconductor Side Groups on the Structural and Electronic Properties of Their Interface with Dopants.

Two derivatives of [1]benzothieno[3,2-b][1]benzothiophene (BTBT), namely, 2,7-dioctyl-BTBT (C8-BTBT) and 2,7-diphenyl-BTBT (DPh-BTBT), belonging to one of the best performing organic semiconductor (OSC) families, have been employed to investigate the influence of the substitutional side groups on the properties of the interface created when they are in contact with dopant molecules. As a molecular p-dopant, the fluorinated fullerene C60F48 is used because of its adequate electronic levels and its bulky molecular structure. Despite the dissimilarity introduced by the OSC film termination, dopant thin films grown on top adopt the same (111)-oriented FCC crystalline structure in the two cases. However, the early stage distribution of the dopant on each OSC film surface is dramatically influenced by the group side, leading to distinct host-dopant interfacial morphologies that strongly affect the nanoscale local work function. In this context, Kelvin probe force microscopy and photoelectron emission spectroscopy provide a comprehensive picture of the interfacial electronic properties. The extent of charge transfer and energy level alignment between OSCs and dopant are debated in light of the differences in the ionization potential of the OSC in the films, the interface nanomorphology, and the electronic coupling with the substrate.

Fast fitting of reflectivity data of growing thin films using neural networks.

X-ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. This study shows how a simple artificial neural network model can be used to determine the thickness, roughness and density of thin films of different organic semiconductors [diindenoperylene, copper(II) phthalocyanine and α-sexithiophene] on silica from their XRR data with millisecond computation time and with minimal user input or a priori knowledge. For a large experimental data set of 372 XRR curves, it is shown that a simple fully connected model can provide good results with a mean absolute percentage error of 8-18% when compared with the results obtained by a genetic least mean squares fit using the classical Parratt formalism. Furthermore, current drawbacks and prospects for improvement are discussed.

Template-Free Orientation Selection of Rod-Like Molecular Semiconductors in Polycrystalline Films.

Many organic semiconductors (OSCs) feature strong optical anisotropy that can be exploited to increase the efficiency of optoelectronic devices. We demonstrate that for the technologically relevant, rod-like OSCs diindenoperylene (DIP), pentacene (PEN), and α-sexithiophene (6T) deposited on silicon oxide surfaces it is possible to prepare polycrystalline thin films in which the long molecular axis is oriented parallel to the substrate plane in a template-free fashion. In films grown by organic molecular beam deposition at room temperature or higher, the molecules are oriented upright standing (σ-orientation). Instead, the here-presented growth at low temperatures followed by slow annealing up to a temperature near molecular desorption has the effect of "freezing" the molecules with their long axis oriented parallel to the substrate plane (λ-orientation) while conferring them crystalline long-range order. We discuss the huge impact on the optical anisotropy of the films observed as a consequence of the orientation transition. Finally, we propose a mechanism for explaining the achieved λ-orientation, which is stable under environmental conditions.

Direct Photoalignment and Optical Patterning of Molecular Thin Films.

A novel strategy for direct photoalignment of molecular materials using optothermal re-orientation is introduced. Photoalignment for molecular materials such as the organic semiconductor tetracene is shown, without relying on additional photoreactive dopants or alignment layers. Patterning and polarized light emission, e.g., for polarized organic light emitting diodes is demonstrated.

Cooperative Switching in Nanofibers of Azobenzene Oligomers.

Next-generation molecular devices and machines demand the integration of molecular switches into hierarchical assemblies to amplify the response of the system from the molecular level to the meso- or macro-scale. Here, we demonstrate that multi-azobenzene oligomers can assemble to form robust supramolecular nanofibers in which they can be switched repeatedly between the E- and Z-configuration. While in isolated oligomers the azobenzene units undergo reversible photoisomerization independently, in the nanofibers they are coupled via intermolecular interactions and switch cooperatively as evidenced by unusual thermal and kinetic behavior. We find that the photoisomerization rate from the Z-isomer to the E-isomer depends on the fraction of Z-azobenzene in the nanofibers, and is increased by more than a factor of 4 in Z-rich fibers when compared to E-rich fibers. This demonstrates the great potential of coupling individual photochromic units for increasing their quantum efficiency in the solid state with potential relevance for actuation and sensing.