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Paper des Monats
- ja (2)
In recent years, many protocols in computational materials science have been automated and made available within software packages (primarily Python-based). This ranges from the automation of simple heuristics (oxidation states, coordination environments) to the automation of protocols, including multiple DFT and post-processing tools such as (an)harmonic phonon computations or bonding analysis. Such developments also shorten the time frames of projects after such developments have been made available and open new possibilities. For example, we can now easily make data-driven tests of well-known rules and heuristics or develop quantum chemistry-based materials descriptors for machine learning approaches. These tests and descriptors can have applications related to magnetic ground state predictions of materials relevant for spintronic applications or for predicting thermal properties relevant for thermal management in electronics. Combining high-throughput ab initio computations with fitting, fine-tuning machine learning models and predictions of such models within complex workflows is also possible and promises further acceleration in the field. In this talk, I will show our latest efforts to link automation with data-driven chemistry and materials science.
We introduce a novel adaptive Gaussian Process Regression (GPR) methodology for efficient construction of surrogate models for Bayesian inverse problems with expensive forward model evaluations. An adaptive design strategy focuses on optimizing both the positioning and simulation accuracy of training data in order to reduce the computational cost of simulating training data without compromising the fidelity of the posterior distributions of parameters. The method interleaves a goal-oriented active learning algorithm selecting evaluation points and tolerances based on the expected impact on the Kullback-Leibler divergence of surrogated and true posterior with a Markov Chain Monte Carlo sampling of the posterior. The performance benefit of the adaptive approach is demonstrated for two simple test problems.
This research deals with the development of the Vickers hardness knowledge graph, mapping the example dataset in them, and exporting the data-mapped knowledge graph as a machine-readable Resource Description Framework (RDF). Modeling the knowledge graph according to the standardized test procedure and using the appropriate upper-level ontologies were taken into consideration to develop the highly standardized, incorporable, and industrial applicable models. Furthermore, the Ontopanel approach was utilized for mapping the real experimental data in the developed knowledge graphs and the resulting RDF files were successfully evaluated through the SPARQL queries.
This study aims to represent an approach for transferring the materials testing datasets to the digital schema that meets the prerequisites of the semantic web. As a use case, the tensile stress relaxation testing method was evaluated and the testing datasets for several copper alloys were prepared. The tensile stress relaxation testing ontology (TSRTO) was modeled following the test standard requirements and by utilizing the appropriate upper-level ontologies. Eventually, mapping the testing datasets into the knowledge graph and converting the data-mapped graphs to the machine-readable Resource Description Framework (RDF) schema led to the preparation of the digital version of testing data which can be efficiently queried on the web.
The stress-induced tetragonal to monoclinic (t-m) zirconia phase transformation can provide a certain degree of plasticity to Ceria-stabilized (Ce-TZP) zirconia-based composites. Characterizing and monitoring this phase transition on a millimeter-size range, within the bulk and in-situ remains a challenge. In this work, the mechanical behavior of Ce-TZP based composite was studied in tension, combining microscopy and synchrotron Xray refraction techniques. In contrast with microscopy methods, which only provide surface information, X-ray refraction radiography (SXRR) allowed the visualization of all the transformation bands, over the entire length and thickness of tested specimens, opening up new avenues for in-situ stress-induced t-m transformation studies.
Investigation on the Durability of a Polypropylene Geotextile under Artificial Aging Scenarios
(2024)
Geosynthetics are widely used in various civil engineering applications, such as geotextiles in coastal protection, and display a sustainable alternative to natural mineral materials. However, the full benefits of using geosynthetics can only be gained with a long service lifetime of the products. With the use of added stabilizers to the polymers, service lifetimes can be achieved in the range of 100 years. Therefore, accelerated aging methods are needed for the assessment of the long-term performance of geotextiles. In the present study, the behavior of geosynthetic materials made of polypropylene was investigated under artificial aging conditions involving elevated temperatures ranging from 30 to 80 °C, increased oxygen pressures ranging from 10 to 50 bar in water-filled autoclaves, and UV irradiation under atmospheric conditions. ATR-IR spectroscopy was employed to detect the increase in the carbonyl index over various aging durations, indicating the oxidative degradation of the geotextile. The most pronounced increase was observed in the case of aging through UV irradiation, followed by thermal aging. Elevated pressure, on the other hand, had a lower impact on oxidation. High-temperature size exclusion chromatography was utilized to follow the reduction in molar mass under different degradation conditions, and the results were consistent with those obtained from ATR-IR spectroscopy. In polyolefins such as polypropylene, Hindered Amine Stabilizers (HAS) are used to suppress oxidation caused by UV radiation. The quantitative analysis of HAS was carried out using a UV/Vis method and HPLC. The degradation of UV stabilizers during the aging of geotextiles is responsible for the oxidation and the reduction in the molar mass of polypropylene. From the results, it can be concluded that applications of PP geotextile without soil or sand cover might cause the risk of the formation of microplastic particles. Material selection, design, and maintenance of the construction must follow best practices, including the system’s removal or replacement at end-of-life. Otherwise, a sustainable use of geotextiles in civil engineering is not possible.
The presentation gives an overview of BAM's activities on processing influences and application properties of MPEAs in the form of joined and machined high and medium entropy alloys (CoCrFeMnNi and CoCrNi). In the case of welding, the focus is on defect-free welded joints with sufficient mechanical properties. In the case of machining, the focus is on the possible influence on the surface quality of the materials through adequate milling parameters. In addition, the hydrogen absorption and diffusion properties as well as the electrochemical corrosion behavior are fundamentally examined.
Impact of organic phosphates on the structure and composition of short-range ordered iron nanophases
(2024)
Organic phosphates (OP) are important nutrient components for living cells in natural environments, where they readily interact with ubiquitous iron phases such as hydrous ferric oxide, ferrihydrite (FHY). FHY partakes in many key bio(geo)chemical reactions including iron-mediated carbon storage in soils, or iron-storage in living organisms. However, it is still unknown how OP affects the formation, structure and properties of FHY. Here, we document how β-glycerophosphate (GP), a model OP ligand, affects the structure and properties of GP–FHY nanoparticles synthesized by coprecipitation at variable nominal molar P/Fe ratios (0.01 to 0.5). All GP–FHY precipitates were characterized by a maximum solid P/Fe ratio of 0.22, irrespective of the nominal P/Fe ratio. With increasing nominal P/Fe ratio, the specific surface area of the GP–FHY precipitates decreased sharply from 290 to 3 m2 g−1, accompanied by the collapse of their pore structure. The Fe–P local bonding environment gradually transitioned from a bidentate binuclear geometry at low P/Fe ratios to monodentate mononuclear geometry at high P/Fe ratios. This transition was accompanied by a decrease in coordination number of edge-sharing Fe polyhedra, and the loss of the corner-sharing Fe polyhedra. We show that Fe(III) polymerization is impeded by GP, and that the GP–FHY structure is highly dependent on the P/Fe ratio. We discuss the role that natural OP-bearing Fe(III) nanophases have in biogeochemical reactions between Fe–P and C species in aquatic systems.
The heat-resistant cast iron EN-GJSA-XNiSiCr35-5-2 (Ni-Resist D-5S) was investigated for its fatigue crack growth behavior at room and high temperatures. Force-controlled tests were carried out at constant temperatures (20 °C, 500 °C, 700 °C) without and with hold time and different load ratios. The crack growth behavior was also characterized under TMF loading (Tmin = 400 °C, Tmax = 700 °C) by applying IP and OP conditions and different load ratios. Three different techniques were combined to monitor crack growth: potential drop, thermography, and compliance method. The effect of the different loading conditions on the fatigue crack growth behavior will be presented and discussed.