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AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
Knowledge representation in the Materials Science and Engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant (consistent) and variant (context-specific) knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. In this paper, an approach how to maintain a comprehensive MSE-centric terminology composing a mid-level ontology–the Platform MaterialDigital Core Ontology (PMDco)–via MSE community-based curation procedures is presented. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics. Additionally, it demonstrates how the PMDco lowers development and integration thresholds. Moreover, the research highlights how to fuel it with real-world data sources ranging from manually conducted experiments and simulations with continuously automated industrial applications.
Due to the extremely high specific surface area of nanoparticles and corresponding potential for adsorption, the results of surface analysis can be highly dependent on the history of the particles, particularly regarding sample preparation and storage. The sample preparation method has, therefore, the potential to have a significant influence on the results. This report describes an interlaboratory comparison (ILC) with the aim of assessing which sample preparation methods for ToF-SIMS analysis of nanoparticles provided the most intra- and interlaboratory consistency and the least amount of sample contamination. The BAM reference material BAM-P110 (TiO2 nanoparticles with a mean Feret diameter of 19 nm) was used as a sample representing typical nanoparticles. A total of 11 participants returned ToF-SIMS data,in positive and (optionally) negative polarity, using sample preparation methods of “stick-and-go” as well as optionally “drop-dry” and “spin-coat.” The results showed that the largest sources of variation within the entire data set were caused by adventitious hydrocarbon contamination or insufficient sample coverage, with the spin-coating protocol applied in this ILC showing a tendency toward insufficient sample coverage; the sample preparation method or the participant had a lesser influence on results.
Lanthanide-based, spectrally shifting, and multi-color luminescent upconverting nanoparticles (UCNPs) have received much attention in the last decades because of their applicability as reporter for bioimaging, super-resolution microscopy, and sensing as well as barcoding and anti-counterfeiting tags. A prerequisite for the broad application of UCNPs in areas such as sensing and encoding are simple, robust, and easily upscalable synthesis protocols that yield large quantities of UCNPs with sizes of 20 nm or more with precisely controlled and tunable physicochemical properties from lowcost reagents with a high reproducibility. In this context, we studied the reproducibility, robustness, and upscalability of the synthesis of β-NaYF4:Yb, Er UCNPs via thermal decomposition. Reaction parameters included solvent, precursor chemical compositions, ratio, and concentration. The resulting UCNPs were then examined regarding their application-relevant physicochemical properties such as size, size distribution, morphology, crystal phase, chemical composition, and photoluminescence.
Based on these screening studies, we propose a small volume and high-concentration synthesis approach that can provide UCNPs with different, yet controlled size, an excellent phase purity and tunable morphology in batch sizes of up to at least 5 g which are well suited for the fabrication of sensors, printable barcodes or authentication and recycling tags.
The round robin test investigated the reliability users can expect for AlSi10Mg additive manufactured specimens by laser powder bed fusion through examining powder quality, process parameter, microstructure defects, strength and fatigue. Besides for one outlier, expected static material properties could be found. Optical microstructure inspection was beneficial to determine true porosity and porosity types to explain the occurring scatter in properties. Fractographic analyses reveal that the fatigue crack propagation starts at the rough as-built surface for all specimens. Statistical analysis of the scatter in fatigue using statistical derived safety factors concludes that at a stress of 36.87 MPa the fatigue limit of 107 cycles could be reached for all specimen with a survival probability of 99.999 %.
The status of standardization related to x-ray photoelectron spectroscopy (XPS, ESCA) at ASTM International (Subcommittee E42.03) and ISO (TC 201) is presented and commented upon in a structured manner. The survey also identifies other active bodies, here VAMAS Technical Working Area 2 and the Surface Analysis Working Group at the International Meter Convention, contributing to prestandardization Research and metrology of XPS and reports their specific activities. It is concluded that existing standardization is delivering good practices in the use of XPS and has a high potential to avoid the recently observed erroneous use, misapplications, and misinterpretation by new and inexperienced users of the method—which seems to be the main reason for the “reproducibility crisis” in the field of XPS applications. A need for a more proactive publicizing of international documentary standards by experienced XPS users, specifically those who are involved in standardization, is identified. Because the existing portfolio of standards addressing the use of XPS is not complete, future standardization projects planned or already ongoing are mentioned. The way the standardization bodies are identifying future needs is shortly explained.
This chapter provides an overview of what standards are, why they are important, and how they are developed. There is a focus on the work of standards committees relevant to nanotechnology measurement and characterization with tables detailing the standards that are currently available for a large number of different techniques, materials, and applications at the nanoscale.