arXiv subjects

Alexander Wieczorek

Publications and source records attributed to Alexander Wieczorek.

9 recordsLinked to original sources

arXiv2026

Tuning the optoelectronic properties of wide bandgap perovskites: Data-driven insights from combinatorial synthesis and high-throughput experimentation

The discovery and optimization of wide-bandgap lead halide perovskites (LHPs) is hindered by solution-based workflows with limited scalability. Large compositional parameter spaces present an additional challenge for materials optimization. Here, we establish an integrated, combinatorial workflow based on sequential physical vapor deposition that enables independent tuning of cation (Cs/Pb) and anion (Br/Cl) compositions. Applying automated structural, compositional, and optical characterizations across >500 samples regions of interest are rapidly screened in the quaternary Cs-Pb-Br-Cl space. From the screening, we establish a practical Cs/Pb window of 1.05-1.20 for wide bandgap perovskites, within which elevated PL yields were observed. Through in-depth analysis of the data set, we uncover a high-energy optical transition as a robust determinant for high PL yields. By combining mechanistic insight into the compositional origins of high PL efficiency with a fully integrated, high-throughput screening framework, and by openly releasing the complete multi-modal dataset, this work provides a broadly accessible benchmark to accelerate data-driven discovery of wide-bandgap perovskites.

cond-mat.mtrl-sci↗

arXiv2026

Physics-informed time-series forecasting of perovskite photoluminescence stability

Accelerated ageing using elevated temperatures and illumination is one of the most common methods to rapidly study the stability of novel semiconductor materials. However, as the pace of materials discovery continues to accelerate, even faster stability evaluations are needed. A physics-informed time-series forecasting algorithm designed to predict the long-term photoluminescence stability of metal halide perovskites is presented. A diverse experimental dataset of 167 metal halide perovskites is collected, including different crystallinities and compositions. These are stressed using heat and light, while the photoluminescence (PL) is monitored. The >86k collected PL spectra are featurized using a physics-informed model, and a hybrid CNN-LSTM model is trained to forecast the PL intensity during degradation of samples unseen during model training. Notably, the approach generalizes across the material groups and outperforms baseline benchmarks. Furthermore, the physics-based featurization ensures explainability, enabling analysis to identify critical stability descriptors for given predictions. It is expected that this approach will be adapted to other types of time-series data and enables a pathway to significantly reduce experimental testing times.

cond-mat.mtrl-sci↗

arXiv2026

Autonomous Sampling and SHAP Interpretation of Deposition-Rates in Bipolar HiPIMS

High-power impulse magnetron sputtering (HiPIMS) offers considerable control over ion energy and flux, making it invaluable for tailoring the microstructure and properties of advanced functional coatings. However, compared to conventional sputtering techniques, HiPIMS suffers from reduced deposition rates. Many groups have begun to evaluate complex pulsing schemes to improve upon this, leveraging multi-pulse schemes (e.g. pre-ionization or bipolar pulses). Unfortunately, the increased complexity of these pulsing schemes has led to high-dimensionality parameter spaces that are prohibitive to classic design of experi-ments. In this work we evaluate bipolar HiPIMS pulses for improving deposition rates of Al and Ti sputter tar-gets. Over 3000 process conditions were collected via autonomous Bayesian sampling over a 6-dimensional parameter space. These process conditions were then interpreted using Shapley Additive Explanations (SHAP), to deconvolute complex process influences on deposition rates. This allows us to link observed var-iations in deposition rate to physical mechanisms such as back-attraction and plasma ignition. Insights gained from this approach were then used to target specific processes where the positive pulse components were expected to have the highest impact on deposition rates. However, in practice, only minimal improve-ments in deposition rate were achieved. In most cases, the positive pulse appears to be detrimental when placed immediately after the neg. pulse which we hypothesize relates to quenching of the afterglow plasma. The proposed workflow combining autonomous experimentation and interpretable machine learning is broad-ly applicable to the discovery and optimization of complex plasma processes, paving the way for physics-informed, data-driven advancements in coating technologies.

physics.plasm-ph↗

arXiv2025

Accelerating the development of oxynitride thin films: A combinatorial investigation of the Al-Si-O-N system

Oxynitrides are used in a variety of applications including photocatalysts, high-k dielectrics or wear-resistant coatings and often show intriguing multi-functionality. To accelerate the co-optimization of the relevant material properties of these compositionally complex oxynitride systems, high-throughput synthesis and characterization methods are desirable. In the present work, three approaches were investigated to obtain orthogonal anion and cation gradients on the same substrate by magnetron sputtering. The different approaches included varying positions of the local reactive gas inlets and different combinations of target materials. The best performing approach was applied to screen a large two-dimensional area of the quaternary phase space within the Al-Si-O-N system. This material system is a promising candidate for transparent protective coatings with variable refractive indices. With only five depositions of combinatorial libraries, an anion composition range of 2-46% O/(N+O) and a cation composition range of 4-44% Si/(Al+Si) is covered. For lower oxygen and silicon contents, a region with hardness of up to 25 GPa is observed, where the material exhibits either wurtzite AlN or a composite microstructure. By increasing the deposition temperature to 400 °C, an extension of this region can be achieved. At higher oxygen and silicon contents, the structure of the samples is X-ray amorphous. In this structural region, an intimate correlation between hardness and refractive index is confirmed. The results of this study introduce a practical approach to perform high-throughput development of mixed anion materials, which is transferable to many materials systems and applications.

cond-mat.mtrl-sci↗

arXiv2025

opXRD: Open Experimental Powder X-ray Diffraction Database

Powder X-ray diffraction (pXRD) experiments are a cornerstone for materials structure characterization. Despite their widespread application, analyzing pXRD diffractograms still presents a significant challenge to automation and a bottleneck in high-throughput discovery in self-driving labs. Machine learning promises to resolve this bottleneck by enabling automated powder diffraction analysis. A notable difficulty in applying machine learning to this domain is the lack of sufficiently sized experimental datasets, which has constrained researchers to train primarily on simulated data. However, models trained on simulated pXRD patterns showed limited generalization to experimental patterns, particularly for low-quality experimental patterns with high noise levels and elevated backgrounds. With the Open Experimental Powder X-Ray Diffraction Database (opXRD), we provide an openly available and easily accessible dataset of labeled and unlabeled experimental powder diffractograms. Labeled opXRD data can be used to evaluate the performance of models on experimental data and unlabeled opXRD data can help improve the performance of models on experimental data, e.g. through transfer learning methods. We collected 92552 diffractograms, 2179 of them labeled, from a wide spectrum of materials classes. We hope this ongoing effort can guide machine learning research toward fully automated analysis of pXRD data and thus enable future self-driving materials labs.

cond-mat.mtrl-sci↗

arXiv2023

Advancing High-Throughput Combinatorial Aging Studies of Hybrid Perovskite Thin-Films via Precise Automated Characterization Methods and Machine Learning Assisted Analysis

To optimize materials' stability, automated high-throughput workflows are of increasing interest. However, many of those workflows use processes not suitable for large-area depositions which limits the transferability of results. While combinatorial approaches based on vapour-based depositions are inherently scalable, their potential for controlled stability assessments has yet to be exploited. Based on MAPbI3 thin-films as a prototypical system, we demonstrate a combinatorial inert-gas workflow to study materials degradation based on intrinsic factors only, closely resembling conditions in encapsulated de-vices. Through a comprehensive set of automated X-Ray fluorescence (XRF), X-Ray diffraction (XRD) and UV-Vis characterizations, we aim to obtain a holistic understanding of thin-film properties of pristine and aged thin-films. From phase changes derived from XRD characterizations before and after aging, we observe simi-lar aging behaviours for MAPbI3 thin-films with varying PbI2 residuals. Using a custom-designed in-situ UV-Vis aging setup, the combinatorial libraries are exposed to relevant aging conditions, such as heat or light-bias exposure. Simultaneously, UV-Vis photospectroscopy is performed to gain kinetic insights into the aging process which can be linked to intrinsic degradation processes such as autocatalytic decomposition. Despite scattering effects, which complicate the conventional interpretation of in-situ UV-Vis results, we demonstrate how a machine learning model trained on the comprehensive characterization data before and after the aging process can link optical changes to phase changes during aging. Consequently, this approach does not only enable semi-quantitative comparisons of materials' stability but also provides detailed insights into the underlying degradation processes which are otherwise mostly reported for investigations on single samples.

physics.app-ph↗

arXiv2023

Combinatorial Reactive Sputtering with Auger Parameter Analysis Enables Synthesis of Wurtzite Zn2TaN3

The discovery of new functional materials is one of the key challenges in materials science. Combinatorial high-throughput approaches using reactive sputtering are commonly employed to screen unexplored phase spaces. During reactive combinatorial deposition the process conditions are rarely optimized, which can lead to poor crystallinity of the thin films. In addition, sputtering at shallow deposition angles can lead to off-axis preferential orientation of the grains. This can make the results from a conventional structural phase screening ambiguous. Here we perform a combinatorial screening of the Zn-Ta-N phase space with the aim to synthesize the novel semiconductor Zn2TaN3. While the results of the XRD phase screening are inconclusive, including chemical state analysis mapping in our workflow allows us to see a very clear discontinuity in the evolution of the Ta binding environment. This is indicative of the formation of a new ternary phase. In additional experiments, we isolate the material and perform a detailed characterization confirming the formation of single phase WZ-Zn2TaN3. Besides the formation of the new ternary nitride, we map the functional properties of ZnxTa1-xN and report previously unreported clean chemical state analysis for Zn3N2, TaN and Zn2TaN3. Overall, the results of this study showcase common challenges in high-throughput materials screening and highlight the merit of employing characterization techniques sensitive towards changes in the materials' short-range order and chemical state.

cond-mat.mtrl-sci↗

arXiv2022

Resolving oxidation states and Sn-halide interactions of perovskites through Auger parameter analysis in XPS

Reliable chemical state analysis of Sn semiconductors by XPS is hindered by the marginal observed shift in the Sn 3d region. For hybrid Sn-based perovskites especially, errors associated with charge referencing can easily exceed chemistry-related shifts. Studies based on the modified Auger parameter $α'$ provide a suitable alternative and have been used previously to resolve different chemical states in Sn alloys and oxides. However, the meaningful interpretation of Auger parameter variations on Sn-based perovskite semiconductors requires fundamental studies. In this work, we perform a comprehensive Auger parameter study through systematic compositional variations of Sn halide perovskites. We find that in addition to the oxidation state, $α'$ is highly sensitivity to the composition of the halide-site, inducing shifts of up to $Δα' = 2 eV$ between ASnI$_3$ and ASnBr$_3$ type perovskites. The reported dependencies of $α'$ on the Sn oxidation state, coordination and local chemistry provide a framework that enables reliable tracking of degradation as well as X-site interaction for Sn-based perovskites and related compounds. The higher robustness and sensitivity of such studies not only enables more in-depth surface analysis of Sn-based perovskites than previously performed, but also increases reproducibility across laboratories.

cond-mat.mtrl-sci↗

arXiv2022

High-Performance Flexible All-Perovskite Tandem Solar Cells with Reduced VOC-Deficit in Wide-Bandgap Subcell

Among various types of perovskite-based tandem solar cells (TSCs), all-perovskite TSCs are of particular attractiveness for building- and vehicle-integrated photovoltaics, or space energy areas as they can be fabricated on flexible and lightweight substrates with a very high power-to-weight ratio. However, the efficiency of flexible all-perovskite tandems is lagging far behind their rigid counterparts primarily due to the challenges in developing efficient wide-bandgap (WBG) perovskite solar cells on the flexible substrates as well as the low open-circuit voltage (VOC) in the WBG perovskite subcell. Here, we report that the use of self-assembled monolayers as hole-selective contact effectively suppresses the interfacial recombination and allows the subsequent uniform growth of a 1.77 eV WBG perovskite with superior optoelectronic quality. In addition, we employ a post-deposition treatment with 2-thiopheneethylammonium chloride to further suppress the bulk and interfacial recombination, boosting the VOC of the WBG top cell to 1.29 V. Based on this, we present the first proof-of-concept four-terminal all-perovskite flexible TSC with a PCE of 22.6%. When integrating into two-terminal flexible tandems, we achieved 23.8% flexible all-perovskite TSCs with a superior VOC of 2.1 V, which is on par with the VOC reported on the 28% all-perovskite tandems grown on the rigid substrate.

physics.app-ph↗