arXiv subjects

Alfred Ludwig

Publications and source records attributed to Alfred Ludwig.

At least 19 recordsLinked to original sources

arXiv2026

A thermally grown SiO2 diffusion barrier enabling high-temperature investigation of Ag-Au-Pd-Pt thin films

Combinatorial processing platforms (CPPs), integrating Si microtip arrays with combinatorial thin film synthesis and atom probe tomography (APT), enable near-atomic-scale characterization of compositionally complex solid solutions (CCSSs) under diverse processing and reaction conditions, including oxidation, thermal phase stability and electrocatalytic reactions. Their application at elevated temperatures, however, can be limited when CCSS constituents such as Pd and Pt react with the Si support to form silicides. Although thermally grown SiO2 has proven effective as a diffusion barrier between pure Pt and Si, its performance for multicomponent CCSS thin films is unclear. Here, using Ag-Au-Pd-Pt as a model system, we compare a 25 nm thermally grown SiO2 barrier with native Si oxide during annealing using APT and transmission electron microscopy. Native Si oxide prevents detectable interfacial reactions up to 300{\deg}C, but at 400{\deg}C Pd and Pt react with Si, causing silicide formation and substantial redistribution of the film constituents. At 600{\deg}C, extensive substrate reactions disrupt the CCSS film and produce a pronounced needle-shaped silicide morphology. In contrast, thermally grown SiO2 suppresses CCSS thin film-substrate reactions up to 600{\deg}C and retains the CCSS composition. The thermally grown SiO2 thus extends the applicable temperature range of Si-based CPPs to at least 600{\deg}C for near-atomic-scale characterization of CCSS thin films.

cond-mat.mtrl-sci↗

arXiv2026

Work Function and High-Coverage Adsorption Energy as Hydrogen-Evolution Descriptors on Ag-Au-Pd-Pt Alloys

Hydrogen-evolution activity is commonly rationalized through hydrogen adsorption energies and the Sabatier principle, yet this descriptor picture becomes ambiguous on multimetallic surfaces, where each composition exposes a distribution of local adsorption environments. Here we investigate whether the bare-surface work function, previously shown to add predictive information for monometallic surfaces, remains an activity descriptor for compositionally complex surfaces. We test this on three combinatorial Ag-Au-Pd-Pt thin-film materials libraries screened for acidic hydrogen evolution by scanning electrochemical cell microscopy. Graph neural networks provide adsorption-energy distributions and work functions for each measured composition. A work-function-only model explained most of the activity variation (mean $R^2_\mathrm{log}$ = 0.903), as did a coverage-corrected adsorption model (mean $R^2_\mathrm{log}$ = 0.955), outperforming dilute adsorption (mean $R^2_\mathrm{log}$ = 0.758). Combining work function and coverage-corrected adsorption yielded the highest fit quality (mean $R^2_\mathrm{log}$ = 0.969), but only a small gain over coverage-corrected adsorption alone. For these four metals the coverage-corrected adsorption energy and work function follow a similar trend, producing similar activity rankings, hence including both adds little beyond either one individually, although both are strong predictors.

cond-mat.mtrl-sci↗

arXiv2026

A hidden low-temperature transformation pathway in compositionally complex materials

Most compositionally complex materials (CCMs, frequently referred to as high entropy alloys) are metastable and their attractive properties often belong to kinetically trapped states. However, pathways towards lower-free-energy phase states governing long-term stability, can remain hidden because diffusion-controlled atomic redistribution is too slow to be revealed at experimentally accessible timescales. This blind spot is acute in CCM design: enormous compositional spaces are screened for performance, yet the low-temperature kinetics and the associated transformation pathways determining whether that performance persists are rarely considered in material selection. Here we use defect-rich nanoscale volumes coupled with atom-probe tomography to access and reconstruct the hidden phase-evolution pathway in a metastable Ag24Au20Pd50Pt6 electrocatalyst, without relying on elevated temperatures to accelerate the transformation. By varying microstructural starting state, annealing temperature and time, we reveal precipitation of a Pt-rich phase within the fcc matrix, its coarsening and re-homogenization. The Pt-rich phase recurs after homogenization with delayed kinetic accessibility, while prolonged annealing extends the pathway to 300{\deg}C. Atomistic simulations independently predict the same Pt-rich phase selection. The transformation is accompanied by a 3.7-fold loss of catalytic activity for hydrogen evolution. These results establish hidden phase-evolution pathways as a materials-design variable: resolving them can guide the selection of metastable CCMs not only for their as-synthesized properties, but also for the phase states and associated functionalities they may access over time.

cond-mat.mtrl-sci↗

arXiv2026

Integrating Semantics into Research Data Management: Modelling and Validating Materials Science Experiment Workflows

The incorporation of Semantic Web technologies within scientific environments is becoming an increasingly popular Research Data Management (RDM) practice. While ontologies offer flexible, reusable and machine-readable vocabularies to describe domain-specific research data, Knowledge Graphs (KGs) facilitate the integration of heterogeneous data sources into an interoperable collection. Furthermore, KGs offer additional advantages, notably the use of expressive SPARQL queries, or the ability to define complex data validation rules with SHACL. This work describes the modelling of a relational RDM system with an ontology, and the subsequent construction of a KG based on it. Enabled by the highly interconnected nature of research data and experiment workflows present in the system, we not only show how we can easily and reliably build an efficient KG from such domain-specific RDM systems, but also how doing so enables more advanced use cases. This is demonstrated by the modelling of ideal counterparts for the experiment workflows logged in the KG, which are then used to programmatically generate SHACL shapes that fully validate the conformance of the latter. By integrating this functionality within a UI, we allow researchers to plan, reuse, share, and track the progress of their daily experiments.

cs.DB↗

arXiv2026

Autonomous scanning electrochemical cell microscopy enables rapid exploration of large compositionally complex material spaces

Alloying is a central strategy in electrocatalysis, enabling fine-tuning of electronic structure. In particular, compositionally complex solid solutions (CCSS) often called high-entropy alloys are of high interest as they allow active site design. However, the "combinatorial explosion" in the number of possible compositions poses a critical bottleneck for the discovery of active CCSS electrocatalysts. We present an autonomous scanning electrochemical cell microscopy (SECCM) system for ultrahigh-throughput and large-scale CCSS activity screening. The platform rapidly establishes composition-electrocatalytic activity relationships for large compositional spaces across multiple thin-film CCSS materials libraries via active learning and automated library exchange. Embedding analytical expressions of voltammetry in the algorithm enables the learning of whole voltammograms rather than a single selected metric. As a demonstration, we investigated hydrogen evolution reaction (HER) activities of Au-Ir-Rh, where Ir and Rh exhibit strong metal-hydrogen binding and Au exhibits relatively weak binding as derived from the HER volcano plot. The composition-activity trend was accurately predicted after measuring only 15% of all 966 measurement areas. Au30Ir20Rh50 and Au10Ir35Rh55 exhibit highest activities with standard rate constants of about 0.012 cm/s, demonstrating positive synergistic contributions from elemental mixing. The autonomous robotic SECCM platform is broadly applicable to a wide range of electrocatalytic reactions, providing a general pathway for accelerating CCSS electrocatalyst discovery and optimization.

cond-mat.mtrl-sci↗

arXiv2026

From Deposition Stress to Surface Reactivity: Strain-Dependent Hydrogen Evolution on Sputtered Platinum Thin Films

Strain has emerged as a promising approach for tuning electrocatalytic properties, yet its role in sputter-deposited thin films remains poorly understood. In this work, magnetron-sputtered platinum (Pt) thin films with different stress states were prepared by varying the sputter pressure. The resulting changes in microstructure, residual strain, and hydrogen evolution reaction (HER) activity were investigated using complementary characterization techniques and density functional theory (DFT) calculations. Structural analysis reveals a transition of (111)-textured Pt thin films from dense and smooth films at low pressures, to more porous microstructures with increased roughness at higher pressures. Electrochemical measurements show that films deposited at low sputter pressure exhibit the highest HER activity, while higher sputter pressures lead to reduced activity despite increased surface area. DFT calculations demonstrate that lattice strain alters hydrogen adsorption energetics and surface coverage on Pt(111), providing a mechanistic explanation for the observed activity trends. Overall, the results highlight that HER activity in sputtered Pt thin films is governed by the interplay of residual strain, microstructure, and hydrogen coverage.

cond-mat.mtrl-sci↗

arXiv2026

Understanding early stages of low-temperature hydrogen-driven direct co-reduction of Fe-Ni mixed oxide thin films at the near atomic scale

Kinetic understanding of hydrogen co-reduction of multinary and multi-phase oxides is of interest for enhancing sustainability of alloy production and transition to a hydrogen-based economy. Benefits include decrease in energy consumption, enhanced kinetics, and conversion of oxides to alloys. Thin films provide a platform to study these processes as reactive co-deposition from multiple elemental, alloy or compound targets and precise oxygen flow control allow atomic mixing into various oxide phases which are well-defined nanoscale precursor structures for the subsequent reduction study at the near atomic scale. The early stages of hydrogen direct reduction of oxide thin films are investigated using a Fe50Ni50Ox thin film consisting of NiFe2O4 and NiO phases. After reduction at 280 C in pure H2 for different times, structural, morphological, and nanoscale changes were examined by different characterisation methods including atom probe tomography (APT). The low-temperature reduction is nucleation-limited marked by grain-boundary nucleation preceded by an incubation time of more than 5 min. APT revealed that the early-stages of the reduction involves phase separation into a Ni-rich FexNiy metallic phase and a transformed remaining oxide (magnetite, Fe3O4). Further reduction induces magnetite reduction and alloying into a nearly equiatomic FeNi alloy. The low-temperature reduction and alloying are facilitated by synergetic effects from the nanostructure of the film, and Ni autocatalytic effects through alloying and hydrogen spillover. The results pave the way for low-temperature formation of Fe-Ni alloy thin films with tunable compositions directly from oxides, and broaden the scope of hydrogen direct reduction of multinary oxides to thin-film platforms.

cond-mat.mtrl-sci↗

arXiv2026

Epitaxial Films as Model Platform for Understanding Compositionally Complex Electrocatalysts

Compositionally complex solid solutions provide a unique route for engineering high-performance electrocatalysts, where the polyelemental surface composition can be seamlessly tuned to optimize activity, selectivity, and stability. However, the mechanistic understanding of these electrocatalysts remains limited by the lack of a model system with a crystallographically-defined surface that is compatible with correlative, multi-scale characterization. Here, we present epitaxial films as a model platform for studying compositionally complex electrocatalysts. Using magnetron sputtering, we realize (111) epitaxial Ir-Pd-Pt-Rh-Ru films on (0001) sapphire substrate via a (111) Pt buffer layer, confirmed by X-ray diffraction and transmission electron microscopy. The growth approach is applicable across a broad composition range and produces smooth surfaces (root mean square roughness < 1 nm) with micrometer-sized grains in the nanoscale films. With these films, we demonstrate direct structure-activity mapping at the nanoscale through precise co-localization using micro-indents and performing correlative atomic force microscopy, electron backscatter diffraction, and scanning electrochemical cell microscopy. Our work establishes a model platform for fundamental scalebridging characterization and paves the way for rational design of compositionally complex electrocatalysts.

cond-mat.mtrl-sci↗

arXiv2026

Synthetic control over marcasite-pyrite polymorph formation in the Fe1-xCoxSe2 series

Transition-metal dichalcogenides of the pyrite-marcasite family are model systems of crystal chemistry. A few of these show polymorphism. The theoretical ground state of CoSe2 is marcasite, but the material is typically synthesized in the pyrite structure. Polymorphism has been observed in nanoparticles and synthetic control of the polymorphs of CoSe2 has not been achieved. We have synthesized material libraries of the Fe1-xCoxSe2 series by combining combinatorial deposition and ex-situ selenization. The approach allows to efficiently explore substitution ranges and crystal structures that form for different synthesis conditions. We find that higher levels of Co content x within the marcasite structure are possible when synthesizing at low temperatures. At a synthesis temperature of only 250{\deg} C, we have successfully synthesized marcasite CoSe2 as the majority phase. Density functional theory simulations reveal that the two isomorphs of CoSe2 are extremely close in energy and that the orthorhombic phase is the energetic ground state. Our experimental and theoretical data show that the marcasite structure is the equilibrium phase of Fe1-xCoxSe2 in the entire composition range.

cond-mat.mtrl-sci↗

arXiv2026

Influence of Ru content on electrocatalytic activity and defect formation of Au-Pd-Pt-Ru compositionally complex solid solution thin films

Compositionally complex solid solutions (CCSSs) consist of a randomly mixed single phase with the potential to enhance electrocatalytic activity through their polyelemental surface atom arrangements. However, microstructural complexity originating from multiple principal elements influences local structure, chemistry, and lattice strain, which might also affect electrocatalytic activity. Here, we investigate the effect of Ru content on electrochemistry and defect formation in Au-Pd-Pt-Ru CCSS thin films. Such defects could provide active sites when terminating at the CCSS surface or modify surface composition through preferential segregation. A thin-film material library covering a wide composition range was fabricated by room-temperature combinatorial co-sputtering. High-throughput compositional, structural and functional characterization, including electron microscopy equipped with energy dispersive X-ray spectroscopy, X-ray diffraction, and electrochemical screening, were used to correlate composition and microstructural features with catalytic activity. Three representative compositions selected from the library - Au68Pd13Pt15Ru4, Au27Pd24Pt23Ru26, and Au9Pd21Pt18Ru52 - were examined in detail. The three samples exhibit face-centered cubic structures, with lattice contraction occurring with increasing Ru content. In addition, with increasing Ru content, a transition from a high density of nanotwins to high-density, atomic-layer stacking faults was observed. Moreover, the hydrogen evolution reaction activity improves with higher Ru content. Atom probe tomography reveals local compositional fluctuations, including element-specific enrichment and depletion at grain boundaries. The findings provide a new insight into surface atom arrangement design in the CCSS electrocatalysts with enhanced performance.

cond-mat.mtrl-sci↗

arXiv2026

Field report from Collaborative Research Center 1625: Heterogeneous research data management using ontology representations

The goal of the Collaborative Research Center 1625 is the establishment of a scientific basis for the atomic-scale understanding and design of multifunctional compositionally complex solid solution surfaces. Next to materials synthesis in form of thin-film materials libraries, various materials characterization and simulations techniques are used to explore the materials data space of the problem. Machine learning and artificial intelligence techniques guide its exploration and navigation. The effective use of the combined heterogeneous data requires more than just a simple research data management plan. Consequently, our research data management system maps different data modalities in different formats and resolutions from different labs to the correct spatial locations on physical samples. Besides a graphical user interface, the system can also be accessed through an application programming interface for reproducible data-driven workflows. It is implemented by a combination of a custom research data management system designed around a relational database, an ontology which builds upon materials science-specific ontologies, and the construction of a Knowledge Graph. Along with the technical solutions of research data management system and lessons learned, first use cases are shown which were not possible (or at least much harder to achieve) without it.

cond-mat.mtrl-sci↗

arXiv2025

Evolve with Your Research -- Stepwise System Evolution from Document-driven to Fact-centric Research Data Management in Materials Science

The digitalisation of research requires data management systems capable of supporting a broad spectrum of usage scenarios, ranging from document-oriented repositories to fully factographic environments. This paper introduces a methodological approach for the stepwise development of such systems, illustrated by the MatInf Research Data Management System (RDMS). The proposed framework combines a graph-based STAR paradigm-emphasising Statefulness, Traceability, Aim, and Result-with the SET methodology, which enables systematic Standardisation, Extraction, and Testing of research data. Together, these principles provide a pathway towards FAIR-compliant data infrastructures, facilitating reproducibility, re-use, and integration of heterogeneous materials science data. By demonstrating the gradual consolidation of research outputs into unified datasets, this study highlights how adaptive RDMS design can support accelerated scientific discovery and enhance collaborative research in large-scale projects.

cs.DL↗

arXiv2025

Structural and Electrocatalytic Properties of La-Co-Ni Oxide Thin Films

La-Co-Ni oxides were fabricated in the form of thin-film materials libraries by combinatorial reactive co-sputtering and analyzed for structural and functional properties over large compositional ranges: normalized to the metals of the film they span about 0 - 70 at.-% for Co, 18 - 81 at.-% for La and 11 - 25 at.-% for Ni. Composition-dependent phase analysis shows formation of three areas with different phase constitutions in dependance of Co-content: In the La-rich region with low Co content, a mixture of the phases La2O3, perovskite, and La(OH)3 is observed. In the Co-rich region, perovskite and spinel phases form. Between the three-phase region and the Co-rich two-phase region, a single-phase perovskite region emerges. Surface microstructure analysis shows formation of additional crystallites on the surface in the two-phase area, which become more numerous with increasing Ni-content. Energy-dispersive X-ray analysis indicates that these crystallites mainly contain Co and Ni, so they could be spinels growing on the surface. The analysis of the oxygen evolution reaction (OER) electrocatalytic activity over all compositions and phase constitutions reveals that the perovskite/spinel two-phase region shows the highest catalytic activity, which increases with higher Ni-content. The highest OER current density was measured as 2.24 mA/cm2 at 1.8 V vs. RHE for the composition La11Co20Ni9O60.

cond-mat.mtrl-sci↗

arXiv2024

A Python-Based Approach to Sputter Deposition Simulations in Combinatorial Materials Science

Magnetron sputtering is an essential technique in combinatorial materials science, enabling the efficient synthesis of thin-film materials libraries with continuous compositional gradients. For exploring multidimensional search spaces, minimizing preliminary experiments is essen-tial, as numerous materials libraries are required to adequately cover the space, making it crucial to fabricate only those libraries that are absolutely necessary. This can be achieved by Monte Carlo particle simulations to model the deposition profile, e.g. by SIMTRA, which is an established package mainly designed for single cathode simulations. A strong enhance-ment of its capabilities is the development of a Python-based wrapper, designed to simulate multi-cathode sputter processes through parallel Monte Carlo simulations. By modeling a sputter chamber and determining the relationship between deposition power and rate for an exemplary quaternary system Ni-Pd-Pt-Ru, we achieve a match between simulated and measured compositions, with a mean Euclidean distance of 3.5%. The object-oriented design of the package allows easy customization and enables the definition of complex sputter sys-tems. Due to parallelization, simulating multiple cathodes results in no additional simulation time. These additions extend the capabilities of SIMTRA making it applicable in combinatorial materials research.

cond-mat.mtrl-sci↗

arXiv2024

Composition-property extrapolation for compositionally complex solid solutions based on word embeddings

Mastering the challenge of predicting properties of unknown materials with multiple principal elements (high entropy alloys/compositionally complex solid solutions) is crucial for the speedup in materials discovery. We show and discuss three models, using property data from two ternary systems (Ag-Pd-Ru; Ag-Pd-Pt), to predict material performance in the shared quaternary system (Ag-Pd-Pt-Ru). First, we apply Gaussian Process Regression (GPR) based on composition, which includes both Ag and Pd, achieving an initial correlation coefficient for the prediction ($r$) of 0.63 and a determination coefficient ($r^2$) of 0.08. Second, we present a version of the GPR model using word embedding-derived materials vectors as representations. Using materials-specific embedding vectors significantly improves the predictive capability, evident from an improved $r^2$ of 0.65. The third model is based on a `standard vector method' which synthesizes weighted vector representations of material properties, then creating a reference vector that results in a very good correlation with the quaternary system's material performance (resulting $r$ of 0.89). Our approach demonstrates that existing experimental data combined with latent knowledge of word embedding-based representations of materials can be used effectively for materials discovery where data is typically sparse.

cond-mat.mtrl-sci↗

arXiv2024

MatInf -- an Extensible Open-Source Solution for Research Digitalisation in Materials Science

Information technology and data science development stimulate transformation in many fields of scientific knowledge. In recent years, a large number of specialized systems for information and knowledge management have been created in materials science. However, the development and deployment of open adaptive systems for research support in materials science based on the acquisition, storage, and processing of different types of information remains unsolved. We propose MatInf - an extensible, open-source solution for research digitalisation in materials science based on an adaptive, flexible information management system for heterogeneous data sources. MatInf can be easily adapted to any materials science laboratory and is especially useful for collaborative projects between several labs. As an example, we demonstrate its application in high-throughput experimentation.

cond-mat.mtrl-sci↗

arXiv2024

On the influence of annealing on the compositional and crystallographic properties of sputtered Li-Al-O thin films

A Li-Al-O thin film materials library, deposited by inert magnetron sputtering and post-deposition annealing in O2 atmosphere, was used to study the effects of different annealing temperatures (300 to 850{\deg}C) and durations (1 min to 7 h) on crystallinity and composition of the films. XPS depth profiling revealed inhomogeneous compositional depth profiles with Li contents increased toward the film surface and Al contents toward the film-substrate interface. These depth profiles were confirmed by a combination of RBS and D-NRA. At annealing temperatures of 550{\deg}C and higher, Li reacted with the Si substrate. At the same time, temperatures of 550{\deg}C and higher enabled the formation of crystalline LiAlO2, whereas at lower temperatures, no crystalline Li-Al-O phases were detected with XRD. In contrast to conventional annealing in a tube furnace (3 to 7 h durations), rapid thermal annealing with fast heating/cooling rates of 10{\deg}C/min and durations of 1 to 10 min resulted in homogeneous depth profiles, while also leading to crystalline LiAlO2.

cond-mat.mtrl-sci↗

arXiv2023

High-throughput study of the phase constitution of the thin film system Mg-Mn-Al-O in relation to Li recovery from slags

The increasing importance of recycling makes the recovery of valuable elements from slags interesting, e.g., by the concept of engineered artificial minerals (EnAMs). In this concept, it is aimed for the formation of EnAMs, meaning phase(s) with a high content of the to-be-recovered element(s) from slags of pyrometallurgical recycling processes. For this, understanding the phase constitution of the slag systems is of high importance. The system Mg-Mn-Al-O is a metal oxide slag subsystem from Li-ion battery recycling, that is critical for the formation of spinel phases, which are competing phases to the possible Li-containing EnAM phase LiAlO2. Here, the phase constitution was investigated using a thin film materials library that covers the composition space (Mg14-69Mn11-38Al14-74)Ox. By means of high-throughput energy-dispersive X-ray spectroscopy and X-ray diffraction, the formation of the spinel solid solution phase was confirmed for a wide composition space. Increasing preferential orientation of the spinel solid solution along (400) with increasing Mg content was identified. X-ray photoelectron spectroscopy was used to measure the near-surface composition of selected areas of the materials library, and detailed peak fitting of the Mn 2p3/2 region revealed the Mn oxidation state to be a mixture of Mn2+ and Mn3+. For one measurement area of the materials library containing equal atomic amounts of Mg, Mn and Al, transmission electron microscopy showed that the approximately 420 nm-thick film consists of columnar spinel grains with Mg, Mn and Al being evenly distributed. Based on these results, we suggest that the shown high likelihood of spinel formation in slags might be influenced by controlling the Mn oxidation state to enable the formation of desirable EnAM phases.

cond-mat.mtrl-sci↗