Montanuniversität Leoben

High-entropy ceramics have been studied as potential candidates for applications in extreme environments, such as nuclear fusion reactors. Their beneficial properties and increased radiation tolerance are often attributed to their compositional complexity achieved through equimolarity. A near-equimolar (CrNbTaTiW)C carbide, obtained by magnetron sputtering, was investigated using in situ TEM whilst being exposed to 300-keV Xe heavy ion irradiation at 573 K. The material did not show structural changes or amorphisation after irradiation to 8.5 dpa. The pristine material showed partial elemental segregation of Cr and Ti and after irradiation redistribution and homogenisation of the solid solution was observed. Furthermore, the coating showed signs of erosion damage near the surface and along some of the grain boundaries, likely due to sputtering during the energetic particle bombardment. This work suggests the response to irradiation in these novel multicomponent ceramics to be multifaceted—determined by an interplay of composition, microstructure, and constituent elements’ chemistry—going beyond simply equimolarity.

The relevance of reducing resource consumption in the manufacturing industry is increasing due to the scarcity of natural resources and EU directives. This paper analyzes the current literature on resource efficiency measures in the manufacturing industry, focusing on the circular economy. The focus paper presents the results of a systematic literature review aimed at reducing resource consumption in the manufacturing industry. The authors analyze 50 peer-reviewed articles and identified 22 measures, grouped into ten categories and two clusters. The categories were divided into two clusters: ”strategic” and ”operational”. Most of the identified measures were found in the ”resource-efficient production” category, which is assigned to the operational cluster. The objective of this work is to utilize the developed framework to provide measures for resource-efficient production for the manufacturing industry. This allows the industry to implement measures to reduce resource consumption in production.

Low-melting metal alloys have gained renewed attention for additive manufacturing, energy storage and microelectronics. However, micro- and nanostructure characterisation demands highly sophisticated sample preparation. Here, we optimise the Ga-FIB preparation of atom probe tomography (APT) specimens for low melting SAC305 solder materials utilising different FESEM/FIB stage temperatures. We study the effects of FESEM/FIB stage temperature on the specimen milling behaviour during Ga-FIB preparation and compare the extent of Ga implantation and precipitate coarsening during the preparation utilising energy dispersive X-ray spectroscopy and APT. We show that cooling the sample to −60 °C during FIB milling utilising a Peltier cooling stage improves the behaviour of the specimen during the final low-keV milling step significantly. We conclude that performing all Ga-FIB-sample interactions at −60 °C with a Pt-protection layer allows for effective and reproducible APT specimen preparation for low-melting alloys, such as SAC305.

Metal matrix composites (MMCs) offer asignificant boost to achieve a wide range of advanced mechanical properties and improved performance for a variety of demanding applications. The addition of metal particles as reinforcement in MMCs is an exciting alternative to conventional ceramic reinforcements, which suffer from numerous shortcomings. Over the last two decades, various categories of metal particles, i.e., intermetallics, bulk metallic glasses, high-entropy alloys, and shape memory alloys, have become popular as reinforcement choices for MMCs. These groups of metal particles offer a combination of outstanding physico-mechanical properties leading to unprecedented performances; moreover, they are significantly more compatible with the metal matrices compared to traditional ceramic reinforcements. In this review paper, the recent developments in MMCs are investigated. The importance of understanding the active mechanisms at the interface of the matrix and the reinforcement is highlighted. Moreover, the processing techniques required to manufacture high-performance MMCs are explored identifying the potential structural and functional applications. Finally, the potential advantages and current challenges associated with the use of each reinforcement category and the future developments are critically discussed. Based on the reported results, the use of metal particles as reinforcement in MMCs offers a promising avenue for the development of advanced materials with novel mechanical properties. Further progress requires more in-depth fundamental research to realize the active reinforcing mechanisms at the atomic level to precisely identify, understand, and tailor the properties of the integrated composite materials.

Phase-separated metallic glasses (MGs) have attracted a lot of interest recently because they offer a unique opportunity to design composites or alloys with hierarchical microstructure at various length scales. Phase-separated MGs differ from other MGs in terms of their structure and physical properties. Though a lot of theoretical work has been done, there is still a lack of understanding regarding the mechanism underlying phase separation in MGs. In general, phase separation in many MG systems is explained on the basis of nucleation and growth or spinodal decomposition mechanisms. On the other hand, the phase separation in Ce-based MGs is examined based on changes in the electronic structure of Ce atoms. This opens up a new direction of research for delineating issues pertaining to phase separation in amorphous systems. The present brief review aims to provide a comprehensive overview of the phase separation phenomenon in Ce- and Zr-based MG systems. It is broadly divided into two sections: the first section gives a brief introduction into the phase separation in MG systems, mechanisms of phase separation, micro-structural and thermal characteristics, and advantages of phase separation. The second section discusses some of the recent work on Ce- and Zr-based phase-separated MGs with respect to their design and properties. Graphical Abstract

Vibrating screens are crucial in the waste and mineral processing industries. However, they often lack comprehensive digital monitoring, which necessitates subjective condition assessments. This study introduces a system developed in cooperation with IFE Aufbereitungstechnik GmbH that provides an objective machine state evaluation using permanently installed acceleration sensors, developed by eSensial Data Science GmbH. Unlike previous research, data for this project was collected from a linear vibrating screen, which is operating in a waste processing plant, introducing uncertainties and occasionally missing data due to sensor damage to the analysis. The study focuses on applying supervised machine learning algorithms to predict the machine’s operating condition. In particular, decision trees, multi-layer perceptron networks, and long-short-term memory networks were evaluated using classical performance metrics like the MSE and the R2-Score. The models were also tested with respect to missing input data. The multilayer perceptron network achieved a prediction accuracy of over 90%. Further, it displayed the ability to determine previously unlabeled intermediate states. Additionally, the main cause of prediction errors was identified, and a method of handling missing input data was developed.

Zr‐based conversion coatings represent an environmentally conscious alternative to traditional phosphating and chromating in the automotive industry. In this study, we employ XPS and LEIS to investigate the formation of Zr‐conversion layers on Zn–Mg–Al alloy after alkaline and acidic model pretreatments. On alkaline pretreated surfaces, a Zr‐oxide/oxyfluoride layer and an underlying Mg–Al–fluoride layer are formed, whereas acidic pretreatment results in only an oxidic layer. The thickness of the Zr‐layer depends on pretreatment pH and immersion time. Acidic treatment achieves an approximately 23 nm‐thick Zr‐oxide/oxyfluoride layer after 1 min, while prolonged treatment increases the thickness of the oxidic layer for strong alkaline and acidic conditions. Mild alkaline pretreatments, however, do not benefit from extended immersion. F‐induced corrosion pits are observed after mild alkaline treatment. The strong alkaline pretreatment proved to be the most efficient in creating a double‐layered Zr‐conversion coating with increased oxidic layer thickness over time.

Graphene oxide (GO) possesses specific properties that are revolutionizing materials science, with applications extending from flexible electronics to advanced nanotechnology. A key method for harnessing GO’s potential is its laser-induced reduction, yet the exact mechanisms — photothermal versus photochemical effects — remain unclear. Herein, we discover the dominant role of photochemical reactions in the laser reduction of GO under visible light, challenging the prevailing assumption that photothermal effects are dominant. Employing a combination of Raman thermometry, X-ray photoelectron and photoluminescence spectroscopies, and electrical atomic force microscopy, we quantify the temperature and map the reduction process across micro and nano scales. Our findings demonstrate that the photochemical cleavage of oxygen-containing groups below a reduction threshold temperature is a decisive factor in GO reduction, leading to distinct characteristics that cannot be replicated by heating alone. This work clarifies the fundamental mechanisms of GO transformation under visible laser irradiation, highlighting the dominant role of photochemical processes. Distinguishing these subtleties enables the development of laser-reduced GO platforms for graphene-based applications compatible with industrial scales. We illustrate this potential by encoding information on GO surfaces as optical storage, allowing us to write binary sequences in long-term memory encoding invisible even through an optical microscope.

In the present paper, we obtain an explicit product formula for products of multiple integrals w.r.t. a random measure associated with a Lévy process. As a building block, we use a representation formula for products of martingales from a compensated-covariation stable family. This enables us to consider Lévy processes with both jump and Gaussian part. It is well known that for multiple integrals w.r.t. the Brownian motion such product formulas exist without further integrability conditions on the kernels. However, if a jump part is present, this is, in general, false. Therefore, we provide here sufficient conditions on the kernels which allow us to establish product formulas. As an application, we obtain explicit expressions for the expectation of products of iterated integrals, as well as for the moments and the cumulants for stochastic integrals w.r.t. the random measure. Based on these expressions, we show a central limit theorem for the long time behaviour of a class of stochastic integrals. Finally, we provide methods to calculate the number of summands in the product formula.

Ti-6Al-4V has a wide range of applications, but long lead times and low-efficiency processing of the material leads to limitations. Through additive manufacturing, such as wire-arc directed energy deposition, higher processing efficiency, and lower lead times are possible. To fully realize the benefits, an important parameter for application is the fatigue performance, which needs to be better documented and performance shortcomings improved. Currently, available results on fatigue performance of wire-arc directed energy deposition of Ti-6Al-4V are limited. Therefore, wire-arc directed energy deposition of Ti-6Al-4V was used with the following approach. Samples were characterized using scanning electron microscopy and optical light microscopy, and mechanically tested for tensile and fatigue performance. Minimal pore density and a fine α microstructure within coarsened epitaxial columnar β-grains was observed. Additionally, elemental burn-off and oxygen contamination was assessed, showing a loss of 0.2 wt.% aluminum during processing and no oxygen pick-up. Compared to other cold metal transfer-based wire-arc directed energy deposition results available in the literature, the results present significant improvements. Fractography indicated mixed fracture modes, which are likely due to the macro-zones of α having varying orientations. Our work provides an advancement in fatigue performance and processing, further showing the potential of the technology.

This review article provides a comprehensive examination of sustainable extraction and recycling methods for non-ferrous metals, which are critical to a wide range of industries including electronics, construction and renewable energy. Focusing on metals such as aluminium, copper and silicon, the study highlights the importance of recycling in conserving resources and minimizing environmental impact. It discusses the challenges posed by material diversity in recycling processes and the advances in recycling technologies that have emerged in response. Special emphasis is placed on the importance of a circular economy in maintaining a sustainable balance between consumption and conservation of metal resources. Through detailed analysis, it advocates innovative recycling practices and improved design for recyclability and highlights the role of policy, industry and consumer behaviour in achieving sustainability goals. The findings contribute to the discourse on strategic self-sufficiency in Europe through recycling, providing insights into how to improve efficiency and manage the complexity of the global material cycle. This work calls for a collaborative effort towards sustainable metallurgy and underlines the critical need for advances in recycling infrastructure and technology to ensure the long-term availability and environmental stewardship of non-ferrous metals. This article is part of the discussion meeting issue ‘Sustainable metals: science and systems’.

It is demonstrated in this work that a four parameter Debye–Einstein integral is an excellent fitting function for heat capacity values of pure elements from zero Kelvin to room temperature provided that there are no phase transformations in this temperature range. The standard errors of the four parameters of the Debye–Einstein approach are provided. As examples the temperature dependent molar heat capacities of Fe, Al, Ag and Au are calculated in the temperature range from 0 to 300 K. Standard molar entropies, enthalpies and values of a molar Gibbs energy related function are derived from the molar heat capacities and the values are compared to literature data. The next goal focuses on a seamless transition of these low temperature heat capacities to SGTE (Scientific Group Thermodata Europe) unary data. This can be achieved by penalyzing deviations in the heat capacity values and in their temperature derivatives at the transition point. Whereas the constrained heat capacities of Fe and Al mimic the experimental data, the calculated values deviate considerably in case of Ag and Au. As an alternative a smooth transition in the heat capacities and the temperature derivative is achieved by a switch function employed close to the transition region.

The transition to a low-carbon future necessitates the exploration of alternative energy carriers, and hydrogen has emerged as a promising solution. However, establishing a fully functional hydrogen economy is a complex undertaking full of challenges. One significant obstacle to achieving the European Union’s sustainability goals is the limited infrastructure, particularly regarding storage capacity and integration into the anticipated hydrogen network. Merely relying on underground storage is insufficient – instead, the development of hydrogen transmission and distribution networks is crucial for effective transportation and utilization of hydrogen. Thermal turbomachinery, including compressors and turbines, is a key component in hydrogen distribution networks. These components are responsible for compressing hydrogen for efficient transmission and play a critical role in maintaining the pressure and flow of hydrogen within the network, ensuring its safe and reliable transport. Therefore, investigating the performance and efficiency of integrated systems that combine underground hydrogen storage with thermal turbomachinery is essential. This study aims to address the technological challenge of designing and optimizing hydrogen distribution networks to enhance efficiency and sustainability. The research examines the integration of underground hydrogen storage and thermal turbomachinery within hydrogen networks to gain valuable insights into system performance.

The significant occurrence of bearing faults in electrical machines necessitates continuous online monitoring of the machine’s operating data with the main objective of ensuring both high reliability and efficiency and therefore minimising the chance of unwanted breakdowns. This work focuses on the simulation of (defective) bearings, utilising a dedicated model with five degrees of freedom (DOF) (translational motion) in conjunction with an induction motor model. The primary objective is to gain a comprehensive understanding of how faulty bearings influence both the entire bearing itself and the machine, mainly concerning vibration signals and additional frictional torque. Additionally, various shapes of spalls on the raceway(s) are described, analysed and compared. This work is an extended version of the conference paper ‘Simulating Rolling Element Bearing Defects in Induction Machines’, presenting additional information on how to simulate spalls (with different shapes and sizes) on the inner ring of the bearing. Furthermore, the so-obtained vibration signal is examined and a method is proposed aiming to verify the simulation results and to predict the location of the spall (raceway of the inner or outer ring).

Ordinary refractory ceramics are multi-phase materials, and their inhomogeneous microstructures induce the scatter of properties. The definition of a reasonable number of samples is important to obtain representative results from experiments and simulations, and this reasonable number might be property or microstructure relevant. Stochastic discrete element (DE) simulations of cold crushing tests with homogeneous interface properties were performed. Three minimum DE size ranges were used to represent matrix variation at different levels. Statistical methods, i.e., Kolmogorov–Smirnov (K–S) test, t-test, and correlation analysis, were utilized to study the influences of minimal number of samples on mechanical properties and crack density. It revealed that a relatively small number of samples are sufficient to obtain representative cold crushing strength (CCS) and Young’s modulus, whilst a large number of samples are favourable when the fracture energy and crack density under cold crushing conditions are of interest. The analysis also showed that the fracture energy under cold crushing condition generally correlates positively with CCS, and the static Young’s moduli determined from the stress–piston displacement curves with different definitions are divergent, caused by contact compliance and premature cracking. The data from the stress–strain curves recorded directly on the sample are required for the accurate static Young’s modulus calculation.

The accuracy of the current models for the calculation of the melting temperature of the mold flux shows that there is still room for improvement, given that their accuracy could not be satisfactory enough to keep up with the current industrial needs. In this work the use of artificial neural networks for data prediction is explored. The network acts as a "black box" capable to predict the melting temperature determined by complex physical interaction among the involved chemical species composing the flux. The network is trained by learning from real experimental data provided by different research groups through hot stage microscopy. The data was tested first within its respective batches and then tested as a single aggregate data batch. After testing and optimization of the networks' parameters, an acceptable level of accuracy was reached because the estimated melting temperatures point out an average error lower than 30 K if compared to measured data. This opens the possibility for the development of a standalone application that can be used for reference. In order to open the possibility for further improvements of this study the paper shares and makes public the values contained in the matrixes connecting the nodes of neural networks.

The invisible-gold deposits known as Carlin-type are becoming more important as easier to find deposits are progressively depleted. The combination of the invisible nature of the Au in these deposits, as well as the limited surface indicators of these deposits, makes exploration to find new Carlin-type deposits extremely difficult. Comprehensive mineralization models are essential to find new Carlin-type deposits in similar geologic settings. The Nadaleen Trend of Yukon, Canada, is one such district where an improved understanding of this deposit type has led to new discoveries. Previous studies compared and contrasted the tectonic setting, host rock depositional setting, structural preparation, and mineralization style of the Nadaleen Trend with those in Carlin-type localities, Nevada. However, the comparisons at an atomic scale, between Carlin-type Au deposits in the Nadaleen Trend and those in Nevada, has yet to be investigated. This study fills this knowledge gap by combining high resolution microanalytical techniques with atom probe tomography to examine the distribution of Au and other trace elements in the Nadaleen Trend, compare them to a representative Carlin-type deposit in Nevada (Turquoise Ridge), and determine how widespread the mineralization model is. Our findings show that in the Nadaleen Trend, as in Nevada, Au is generally directly linked with As at the macro to atomic scale, and is incorporated into As/Au rich overgrowths on sedimentary/diagenetic pyrite. Gold-rich pyrite rims in the Nadaleen Trend are generally smaller than those found in Nevada (0.5–2 µm vs > 10 µm), although the ore grades appear comparable. We find that the Au in the pyrite of the Nadaleen Trend is homogenously distributed (i.e. lattice bound) at the atomic scale, but that there is a notable enrichment of As surrounding individual Au atoms. These findings are in agreement with those from previous work on a representative deposit in Nevada, and support the assertation that As is the key ingredient in facilitating the incorporation of Au into the pyrite lattice. Arsenic as an essential component in the trapping mechanisms of Au in CTG deposits, is something that has been as to yet underappreciated in the current models of CTG deposit formation.

The layered character of transition metal diborides (TMB2:s)---with three structure polymorphs representing different stackings of the metallic sublattice---evokes the possibility of activating phase-transformation plasticity via mechanical shear strain. This is critical to overcome the most severe limitation of TMB2:s: their brittleness. To understand finite-temperature mechanical response of the α, ω, and γ polymorphs at the atomic scale, we train machine-learning interatomic potentials (MLIPs) for TMB2:s, TM=(Ti, Ta, W, Re). Validation against ab initio data set supports the MLIPs' capability to predict structural and elastic properties, as well as shear-induced slipping and phase transformations. Nanoscale molecular dynamics simulations (>104 atoms; ≈53 nm3) allow minimizing size effects, thus evaluating theoretical shear strengths attainable in single-crystal TMB2:s and their temperature evolution from 300 up to 1200 K. Quantitative structural analysis via angular and bond-order parameter descriptors shows that xz and yz shearing activates transformations between the (energetically) metastable and the preferred phase of TiB2, TaB2, and WB2. These transformations can be promoted by additional tensile or compressive strain along the [0001] axis. The preferred phase of ReB2 shows negative thermal expansion and an unprecedented shear-induced plasticity mechanism: metallic/boron layer interpenetration and uniform lattice rotation.

Highly porous bioceramic scaffolds are widely used as bone substitutes in many applications. However, the use of bioceramics is often limited to hard tissues due to the risk of potential soft tissue calcification. A further limitation of highly porous bioceramic scaffolds is their poor mechanical stability, manifested by their tendency to break under stress. In our study, highly porous CaP-based scaffolds were prepared via freeze-casting with longitudinal and oriented pores ranging from 10 to 20 μm and a relative porosity of ∼70%. The resulting scaffolds achieved a flexural strength of 10.6 ± 2.7 MPa, which, in conjunction with their favorable bioactivity, made them suitable for in vivo testing. The prepared scaffolds were subcutaneously implanted in rats for two distinct periods: 6 weeks and 6 months, respectively. The subsequent development of fibrous tissue and involvement of myofibroblasts, newly formed vessels, and macrophages were observed, with notable changes in spatial and temporal distributions within the implantation. The absence of calcification in the surrounding soft tissue, as a result of the narrow pore geometry, indicates the opportunity to tailor the scaffold behavior for soft tissue regeneration.

In this study, we propose a practical approach for producing a heterobimetallic Ni(II)–Ce(III) diimine complex from an extended salen-type ligand (H2L) to serve as an electrocatalyst for CO2 reduction and demonstrate an outstanding overall efficiency of 99.6% of the cerium–nickel complex and integrate it into applicable cell assemblies. We optimize not only the catalyst, but the operational conditions enabling successful CO2 electrolysis over extended periods at different current densities. A comparison of electrochemical behavior in H-cell and zero-gap cell electrolyzers suggests potential applications for industrial scale-up. In the H-cell electrolyzer configuration, the most elevated efficiency in CO production was achieved with a selectivity of 56.96% at −1.01 V vs RHE, while HCOO– formation exhibited a selectivity of 32.24% at −1.11 V vs RHE. The highest TON was determined to be 14657.0 for CO formation, followed by HCOO– with a TON of 927.8 at −1.11 V vs RHE. In the zero-gap electrolyzer configuration, the most efficient setup toward CO production was identified at a current density (CD) of 75 mA cm–2, a flow rate of 10 mL min–1, operating at 60 °C and utilizing a low KOH concentration of 0.1 M to yield a maximum faradaic efficiency (FECO) of 82.1% during 24 h of stable electrocatalysis.