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The importance of leaching for the carbonation resistance of alkali-activated slag and calcined clay concretes
No full textThis study investigates the impact of leaching on the carbonation resistance of alkali-activated materials with varying calcium content. Six binder compositions were tested, combining ground blast furnace slag and calcined clay, with CaO content ranging from ~0% to ~40%. Samples underwent three conditions: no leaching, two weeks of leaching (2Le), and five leaching-carbonation cycles (5LCC). Carbonation tests were performed under natural conditions and 1% CO2 for reference and 2Le samples, while 5LCC samples were exposed solely to accelerated carbonation. Under natural carbonation, the typical relationship between carbonation resistance and the water/(CaO+MgOeq+Na2Oeq+K2Oeq) ratio was observed for both the reference and 2Le samples, with an increase in carbonation rate in compositions containing more than 40% calcined clay. In accelerated carbonation conditions, 2Le and 5LCC conditions showed slightly improved carbonation resistance compared to the reference samples, except for the mixtures containing only calcined clay (C100) and the mix with 40% calcined clay (C40S60). The poor performance of C100 was attributed to its low reactivity after 28 days, which resulted in significant sodium leaching and reduced activation of the calcined clay. Although C40S60 outperformed non-leached samples, its carbonation resistance slightly decreased in leached and accelerated carbonation samples due to reduced gel phase formation; however, this reduction was significantly less than that of C100. These findings suggest that while leaching can enhance carbonation resistance by reducing excess alkalis, low-reactivity systems, e.g. based solely on calcined clay, are more susceptible to degradation
Machine learning in materials science and engineering – best practice, perspectives and pitfalls
No full textMachine learning (ML) is increasingly utilized to support the data driven analysis of relationships in multidimensional parameter spaces, ideally as an entry point for a more general phenomenological or physics-based model development. Applications include both forward and inverse problems as well as forward problems, for example parameter identification or modeling of structure-property relationships.
The talk will give an overview over a variety of solutions that benefit from the capability of artificial neural networks to approximate and interpolate complex relationships that are represented by a set of sparse data. The reason behind is that numerical simulations as well as experiments do often not allow to generate enough data such that the data set is not sufficient for a deep-learning approach in connection with the complexity of the problem at hand.
After a short introduction to artificial neural networks along with recommendations for data generation and feature engineering, the talk will cover a range of examples from nanoindentation and material parameter identification, the improvement of characterization techniques by ML correction methods towards recent problems in the prediction of structure-property relationships for materials with complex microstructure. All these examples have in common that a successful ML model typically requires a comprehensive understanding of existing knowledge, expertise in translating this knowledge into meaningful input features, a compact ML architecture, and robust validation of the trained model. The talk will conclude with the example of nanoporous metals that demonstrates the importance of high-quality and bias-free data for the applicability and trustworthiness of the trained model, also emphasizing the need for a culture of open data, specifically towards curated data sets for training and validation of ML models
Selective mechanochemical conversion of post-consumer polyethylene terephthalate waste into hcp and fcu UiO-66 metal–organic frameworks
No full textSingle-use plastics strongly contribute to plastic pollution, and less than 10% of plastic waste is recycled globally. Here, we present a selective mechanochemical protocol for converting post-consumer polyethylene terephthalate (PET) transparent bottles and coloured textile waste into the porous metal–organic framework (MOF) UiO-66 materials. We used time-resolved in situ (TRIS) synchrotron powder X-ray diffraction and Raman spectroscopy to monitor the depolymerization of PET during ball milling. To convert disodium terephthalate to UiO-66, we developed base and base-free synthetic routes that lead to fcu and hcp UiO-66 phases, respectively, including the first ever synthesis of hcp UiO-66 by mechanochemistry. Our results demonstrate the potential of mechanochemistry to selectively access fcu and hcp UiO-66 phases using post-consumer PET waste
Atomic spectrometry update: review of advances in environmental analysis
No full textThis review covers advances in the analysis of air, water, plants, soils and geological materials by a range of atomic spectrometric techniques including atomic emission, absorption, fluorescence and mass spectrometry
MINERVA-OS: The Orchestrator of our SDL for Nano and Advanced Materials Synthesis
No full textWe present our SDL "Minerva" and its' Orchestrator "Minerva-OS". We discuss the general architecture of the orchestrator, the problems our orchestration solution solves, associated objectives, and success criteria. We demonstrate how a user would interact with it and give examples of what it has already been used for. We also provide some explanation of the available and planned features, and how workflows/experiments are represented. Lastly, we discuss key technical challenges we faced during development
Emerging electrochemistry of high-concentration colloids: Redox-activity, wide potential window and electrophoretic transport of iron oxide nanoparticles
No full textHigh-concentration, steric stabilizer free colloids and particularly their electrochemical behavior remains almost unexplored. Herein, we report on the electrochemistry (cyclic voltammetry, impedance spectroscopy, etc.) of highly concentrated aqueous colloidal dispersion up to 800 g/L of citrate-capped ∼11 nm Fe3-xO4 nanoparticles (NPs) without background electrolyte on glassy carbon electrodes. X-ray photoelectron spectroscopy was applied to analyze the reaction products. Solid-state Fe(II)/Fe(III) conversion was concluded to determine the cathodic and anodic faradaic reactions of the particles, with the currents depending on approximately square root of the concentration. The electrochemical reactions are coupled with the electrophoretic transfer of the negatively charged NPs on toward the anode, with the ohmic-type behavior in the bulk demonstrated by the nearly linear voltametric cathodic curves and frequency-independent impedance above ∼10–100 Hz. Accumulation and clogging of the NPs retards diffusion near anode. Hydrogen and especially oxygen evolution are arrested, and very large oxidation overpotentials result in extraordinary wide, up to 12 V, electrochemical window of water stability. The findings shed light onto basic features of the electrochemistry of high-concentration colloids without added electrolyte and their potential applications in redox flow batteries, electrophoretic deposition and beyond
Effect of humidity on fiber-optic temperature sensing
No full textThis study investigates the influence of ambient humidity on the temperature sensitivity, measurement accuracy, and uncertainty of optical fibers with different coatings, using a Rayleigh-based distributed sensing technique. Polymer-coated fibers (acrylate and polyimide) and metal-coated fibers (copper and gold) were tested under controlled humidity (30%–90% RH) and temperature (20–60 °C) conditions. Rayleigh-based measurements revealed a slight but consistent decrease in temperature sensitivity with increasing humidity for all polymer-coated fibers, attributed to humidity-induced changes in coating stiffness and strain transfer. In contrast, metal-coated fibers exhibited humidity-independent behavior and superior stability. These findings highlight the non-negligible role of ambient humidity in fiber-optic temperature sensing, particularly in Rayleigh-based systems using hygroscopic coatings. The results provide practical guidance for fiber and coating selection in humid environments and offer broader insight into humidity–strain–temperature coupling mechanisms relevant to other fiber-optic sensing mechanisms
Determination of the oxidation depths of ground granulated blast furnace slag-containing cement pastes using Mn K-edge X-ray absorption near-edge structure spectroscopy
No full textThe redox potential of the pore solution of hardened cements containing ground granulated blast furnace slag (GGBFS) affects reinforcement corrosion and immobilization of radioactive waste. Here, Mn K-edge X-ray absorption near-edge structure (XANES) spectroscopy was applied to determine the depth profile of the oxidation state of manganese in hardened GGBFS-containing cement pastes. Manganese was oxidized in the outer regions of some of the pastes, but the depth to which this occurred was not identical with the ‘blue-green/white color change front’, usually interpreted as indicating oxidation of sulfur species. For CEM III/B, the color change of the material was gradual and thus unsuitable for a precise determination of the oxidation depth, while for the alkali-activated slag, a distinct color change front was found, but full oxidation of manganese and sulfur had not occurred in the brighter region. Mn K-edge XANES spectroscopy is thus a more reliable method than the determination of the visual color change front to follow the ingress of the oxidation front
Project title: Multi-physical simulation of the influence of an auxiliary magnetic field on the process porosity formation during high-power laser beam welding
No full textIn this project, a multiphysically coupled numerical model will be developed to quantitatively describe porosity reduction in high-power laser beam welding of up to 10 mm thick AlMg3 using an oscillating magnetic field. The aim is to gain fundamental insights into the physical dependencies of the introduced electromagnetic forces on the melt pool behavior and the reduction of porosity. With the help of the numerical model, the transient, multi-coupled, three-dimensional problem of heat transfer, liquid flow, free surface deformation, and magnetic induction is to be solved, taking into account temperature-dependent material properties. The numerical modelling of the heat source will integrate all relevant physical mechanisms, for instance, multiple reflections of the laser radiation by an advanced ray tracing model, as well as local Fresnel absorption at the keyhole wall. This allows an analysis of the keyhole fluctuations, which have a dominant influence on the formation of process spores during deep penetration welding, based on physical principles. In addition, further physical factors such as the ablation pressure of the evaporating metal, the Laplace pressure, and Marangoni shear stresses are also to be integrated into the model. To evaluate the pore formation and reduction by means of the electromagnetic forces introduced in the molten pool, suitable models for describing the movement of the pores in the melt are to be developed. For the process pores, their movement can be implemented by tracking their surface under consideration of their internal pressure and temperature. With the help of the simulation model, all key factors for the formation of process pores during laser beam welding of the used aluminum alloy, as well as their avoidance, can be decoupled and analyzed. Accompanying welding tests are planned at BAM on a 20 kW fiber laser and a 16 kW disk laser. The magnetic flux density will be up to 500 mT at a maximum frequency of 5 kHz. The experimental results, in particular temperature measurements, weld cross sections, computer tomography, and X-ray examinations, will be used to verify the multiphysical model and its calibration. Moreover, the models will be validated and quantified by in situ high-speed imaging of the keyhole dynamics in a metal/quartz glass configuration with keyhole illumination by a diode laser coaxial to the processing laser. On the basis of the numerical and experimental results, the dependencies between applied magnetic field, melt pool behavior, and porosity formation will be revealed in this project
Objective, high-throughput regularity quantification of laser-induced periodic surface structures (LIPSS)
No full textThe growing demand for precise surface functionalization through laser-generated periodic surface structures highlights the necessity for efficient, reproducible, and objective evaluation methods to evaluate their structural regularity. We introduce ReguΛarity (v.1.2.7), a freely available, Python-based software with a graphical user interface for the automated, quantitative assessment of the regularity of laser-induced periodic surfaces structures (LIPSS), obtained from optical microscopy, SEM, or AFM. The software integrates image segmentation, one- and two-dimensional Fourier analyses, and gradient-based orientation determination to facilitate a comprehensive regularity analysis of grating-like (quasi-)periodic surface patterns with spatial periods Λ. This is achieved through the proposed regularity tuple R, composed of five key parameters: the normalized spread of the spatial period RΛ,2D (from 2D-FT), the normalized variation of the most frequent spatial period RΛ (from 1D-FT), the Gini coefficient G, the Dispersion of the LIPSS Orientation Angle δθ (DLOA), and the mean phase deviation . To demonstrate its applicability, we compare ideal sinusoidal patterns with SEM images obtained from LIPSS on stainless steel (AISI 316L) and aluminum alloy (AlMg5) surfaces, confirming the software’s ability to objectively distinguish between varying levels of structural regularity. ReguΛarity facilitates high-throughput analysis and data-driven process optimization in surface engineering and laser materials processing