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The current lack of quantitative knowledge on processing-microstructure–property relationships is one of the major bottlenecks in today’s rapidly expanding field of additive manufacturing. This is centrally rooted in the nature of the processing, leading to complex microstructural features. Experimentally-guided modeling can offer reliable solutions for the safe application of additively manufactured materials. In this work, we combine a set of systematic experiments and modeling to address creep anisotropy and its correlation with microstructural characteristics in laser-based powder bed fusion (PBF-LB/M) additively manufactured Inconel-738LC (IN738LC). Three sample orientations (with the tensile axis parallel, perpendicular, and 45° tilted, relative to the building direction) are crept at 850 °C, accompanied by electron backscatter secondary diffraction (EBSD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) investigations. A crystal plasticity (CP) model for Ni-base superalloys, capable of modeling different types of slip systems, is developed and combined with various polycrystalline representative volume elements (RVEs) built on the experimental measurements. Besides our experiments, we verify our modeling framework on electron beam powder bed fusion (PBF-EB/M) additively manufactured Inconel-738LC. The results of our simulations show that while the crystallographic texture alone cannot explain the observed creep anisotropy, the superlattice extrinsic stacking faults (SESF) and related microtwinning slip systems play major roles as active deformation mechanisms. We confirm this using TEM investigations, revealing evidence of SESFs in crept specimens. We also show that the elongated grain morphology can result in higher creep rates, especially in the specimens with a tilted tensile axis.
Estimating the frequency and magnitude of natural hazards largely hinges on stationary models, which do not account for changes in the climatological, hydrological, and geophysical baseline conditions. Using five diverse case studies encompassing various natural hazard types, we present advanced statistical and machine learning methods to analyze and model transient states from long‐term inventory data. A novel storminess metric reveals increasing European winter windstorm severity from 1950 to 2010. Non‐stationary extreme value models quantify trends, seasonal shifts, and regional differences in extreme precipitation for Germany between 1941 and 2021. Utilizing quantile sampling and empirical mode decomposition on 148 years of daily weather and discharge data in the European Alps, we assess the impacts of changing snow cover, precipitation, and anthropogenic river network modifications on river runoff. Moreover, a probabilistic framework estimates return periods of glacier lake outburst floods in the Himalayas, demonstrating large differences in 100‐year flood levels. Utilizing a Bayesian change point algorithm, we track the onset of increased seismicity in the southern central United States and find correlation with wastewater injections into deep wells. In conclusion, data science reveals transient states for very different natural hazard types, characterized by diverse forms of change, ranging from gradual trends to sudden change points and from altered seasonality to overall intensity variations. In synergy with the physical understanding of Earth science, we gain important new insights into the dynamics of the studied hazards and their possible mechanisms.
For a deep process understanding of the laser powder bed fusion process (PBF-LB/M), recording of the occurring surface temperatures is of utmost interest and would help to pave the way for reliable process monitoring and quality assurance. A notable number of approaches for in-process monitoring of the PBF-LB/M process focus on the monitoring of thermal process signatures. However, due to the elaborate calibration effort and the lack of knowledge about the occurring spectral directional emissivity, only a few approaches attempt to measure real temperatures. In this study, to gain initial insights into occurring in the PBF-LB/M process, measurements on PBF-LB/M specimens and metal powder specimens were performed for higher temperatures up to T = 1290 °C by means of the emissivity measurement apparatus (EMMA) of the Center for Applied Energy Research (CAE, Wuerzburg, Germany). Also, measurements at ambient temperatures were performed with a suitable measurement setup. Two different materials—stainless steel 316L and aluminum AlSi10Mg—were examined. The investigated wavelength λ ranges from the visible range (λ-VIS= 0.40–0.75 µm) up to the infrared, λ = 20 µm. The influence of the following factors were investigated: azimuth angle φ, specimen temperature TS, surface texture as for PBF-LB/M surfaces with different scan angles α, and powder surfaces with different layer thicknesses t.
On-line coupled high performance liquid chromatography-gas chromatography-flame ionisation detection (HPLC-GC-FID) was used to compare the effect of hydrogen, helium and nitrogen as carrier gases on the chromatographic characteristics for the quantification of mineral oil hydrocarbon (MOH) traces in food related matrices. After optimisation of chromatographic parameters nitrogen carrier gas exhibited characteristics equivalent to hydrogen and helium regarding requirements set by current guidelines and standardisation such as linear range, quantification limit and carry over. Though nitrogen expectedly led to greater peak widths, all required separations of standard compounds were sufficient and humps of saturated mineral oil hydrocarbons (MOSH) and aromatic mineral oil hydrocarbons (MOAH) were appropriate to enable quantitation similar to situations where hydrogen or helium had been used. Slightly increased peak widths of individual hump components did not affect shapes and widths of the MOSH and MOAH humps were not significantly affected by the use of nitrogen as carrier gas. Notably, nitrogen carrier gas led to less solvent peak tailing and smaller baseline offset. Overall, nitrogen may be regarded as viable alternative to hydrogen or helium and may even extend the range of quantifiable compounds to highly volatile hydrocarbon eluting directly after the solvent peak.
Abstract. In power electronics, compound semiconductors with large bandgaps, like silicon carbide (SiC), are increasingly being used as material instead of silicon. They have a lot of advantages over silicon but are also intolerant of nanoscale material defects, so that a defect inspection with high accuracy is needed. The different defect types on SiC samples are measured with various measurement methods, including optical and tactile methods. The defect types investigated include carrots, particles, polytype inclusions and threading dislocations, and they are analysed with imaging ellipsometry, coherent Fourier scatterometry (CFS), white light interference microscopy (WLIM) and atomic force microscopy (AFM). These different measurement methods are used to investigate which method is most sensitive for which type of defect to be able to use the measurement methods more effectively. It is important to be able to identify the defects to classify them as critical or non-critical for the functionality of the end product. Once these investigations have been completed, the measurement systems can be optimally distributed to the relevant defects in further work to realize a hybrid analysis of the defects. In addition to the identification and classification of defects, such a future hybrid analysis could also include characterizations, e.g. further evaluation of ellipsometric data by using numerical simulations.
AbstractPowder Bed Fusion with Laser Beam of Metals (PBF-LB/M) has gained more industrial relevance and already demonstrated applications at a small series scale. However, its widespread adoption in various use cases faces challenges due to the absence of interfaces to established Manufacturing Execution Systems (MES) that support customers in the predominantly data-driven quality assurance. Current state-of-the-art PBF-LB/M machines utilize communication architectures, such as OPC Unified Architecture (OPC UA), Message Queuing Telemetry Transport (MQTT) and Representational State Transfer Application Programming Interface (REST API). In the context of the Reference Architecture Model Industry 4.0 (RAMI 4.0) and the Internet of Things (IoT), the assets, particularly the physical PBF-LB/M machines, already have an integration layer implemented to communicate data such as process states or sensor values. Missing is an MES component acting as a communication and information layer. To address this gap, the proposed Extract Transform Load (ETL) pipeline aims to extract relevant data from the fabrication of each build cycle down to the level of scan vectors and additionally to register process signals. The suggested data schema for archiving each build cycle adheres to all terms defined by ISO/TC 261—Additive Manufacturing (AM). In relation to the measurement frequency, all data are reorganized into entities, such as the AM machine, build cycle, part, layer, and scan vector. These scan vectors are stored in a runtime-independent format, including all metadata, to be valid and traceable. The resulting machine log represents a comprehensive documentation of each build cycle, enabling data-driven quality assurance at process level.
Scattering luminescent materials dispersed in liquid and solid matrices and luminescent powders are increasingly relevant for fundamental research and industry. Examples are luminescent nano- and microparticles and phosphors of different compositions in various matrices or incorporated into ceramics with applications in energy conversion, solid-state lighting, medical diagnostics, and security barcoding. The key parameter to characterize the performance of these materials is the photoluminescence/fluorescence quantum yield (Φf), i.e., the number of emitted photons per number of absorbed photons. To identify and quantify the sources of uncertainty of absolute measurements of Φf of scattering samples, the first interlaboratory comparison (ILC) of three laboratories from academia and industry was performed by following identical measurement protocols. Thereby, two types ofcommercial stand-alone integrating sphere setups with different illumination and detection geometries were utilized for measuring the Φf of transparent and scattering dye solutions and solid phosphors, namely, YAG:Ce optoceramics of varying surface roughness, used as converter materials for blue light emitting diodes. Special emphasis was dedicated to the influence of the measurement geometry, the optical properties of the blank utilized to determine the number of photons of the incident excitation light absorbed by the sample, and the sample-specific surface roughness. While the Φf values of the liquid samples matched between instruments, Φf measurements of the optoceramics with different blanks revealed substantial differences. The ILC results underline the importance of the measurement geometry, sample position, and blank for reliable Φf data of scattering the YAG:Ce optoceramics, with the blank’s optical properties accounting for uncertainties exceeding 20%.
In this contribution, we present a physically motivated heat source model for the numerical modeling of laser beam welding processes. Since the calibration of existing heat source models, such as the conic or Goldak model, is difficult, the representation of the heat source using so-called Lamé curves has been established, relying on prior Computational Fluid Dynamics (CFD) simulations.
Lamé curves, which describe the melting isotherm, are used in a subsequent finite-element (FE) simulation to define a moving Dirichlet boundary condition, which prescribes a constant temperature in the melt pool. As an alternative to this approach, we developed a physically motivated heat source model, which prescribes the heat input as a body load directly. The new model also relies on prior CFD simulations to identify the melting isotherm. We demonstrate numerical results of the new heat source model on boundary-value problems from the field of laser beam welding and compare it with the prior CFD simulation and the results of the Lamé curve model and experimental data.
Microbially induced carbonate precipitation (MICP), a widespread phenomenon in nature, is gaining attention as a low-carbon alternative to ordinary Portland cement (OPC) in geotechnical engineering and the construction industry for sustainable development. In the Philippines, however, very few works have been conducted to isolate and identify indigenous, urease-producing (ureolytic) bacteria suitable for MICP. In this study, we isolated seven, ureolytic and potentially useful bacteria for MICP from marine sediments in Iligan City. DNA barcoding using 16s rDNA identified six of them as Pseudomonas stutzeri, Pseudomonas pseudoalcaligenes, Bacillus paralicheniformis, Bacillus altitudinis, Bacillus aryabhattai, and Stutzerimonas stutzeri but the seventh was not identified since it was a bacterial consortium. Bio-cementation assay experiments showed negligible precipitation in the control (without bacteria) at pH 7, 8, and 9. However, precipitates were formed in all seven bacterial isolates, especially between pH 7 and 8 (0.7–4 g). Among the six identified bacterial species, more extensive precipitation (2.3–4 g) and higher final pH were observed in S. stutzeri, and B. aryabhattai, which indicate better urease production and decomposition, higher CO2 generation, and more favorable CaCO3 formation. Characterization of the precipitates by scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS) and attenuated total reflectance Fourier transform spectroscopy (ATR-FTIR) confirmed the formation of three carbonate minerals: calcite, aragonite, and vaterite. Based on these results, all six identified indigenous, ureolytic bacterial species from Iligan City are suitable for MICP provided that the pH is controlled between 7 and 8. To the best of our knowledge, this is the first report of the urease-producing ability and potential for MICP of P. stutzeri, P. pseudoalcaligenes, S. stutzeri, and B. aryabhattai.