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Several studies have been shown that the electron beam can be used to create nanomaterials from microparticle targets in situ in a transmission electron microscope (TEM). Here, we show how this method has to be modified in order to synthesize plasmonic gold nanoparticles (NPs) on insulating silicon oxide substrate by employing a scanning electron microscope with a comparatively low acceleration voltage of 30 kV. The synthesized NPs exhibit a random distribution around the initial microparticle target: Their average size reduces from 150 nm to 3 nm with growing distance to the initial Au microparticle target. Similarly, their average distance increases. The synthesized NP assemblies therefore show distinctly different plasmonic behaviour with growing distance to the target, which allows to study consequences of random hybridization of surface plasmon in disordered system, such as Anderson localization. To reveal the surface plasmons and their localization behaviour we apply electron energy loss spectroscopy in the TEM.
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.
This is the stable version of the full-notch creep test ontology (OntoFNCT) that ontologically represents the full-notch creep test. OntoFNCT has been developed in accordance with the corresponding test standard ISO 16770:2019-09 Plastics - Determination of environmental stress cracking (ESC) of polyethylene - Full-notch creep test (FNCT).
The OntoFNCT provides conceptualizations that are supposed to be valid for the description of full-notch creep tests and associated data in accordance with the corresponding test standard. By using OntoFNCT for storing full-notch creep test data, all data will be well structured and based on a common vocabulary agreed on by an expert group (generation of FAIR data) which is meant to lead to enhanced data interoperability. This comprises several data categories such as primary data, secondary data and metadata. Data will be human and machine readable. The usage of OntoFNCT facilitates data retrieval and downstream usage. Due to a close connection to the mid-level PMD core ontology (PMDco), the interoperability of full-notch creep test data is enhanced and querying in combination with other aspects and data within the broad field of materials science and engineering (MSE) is facilitated.
The class structure of OntoFNCT forms a comprehensible and semantic layer for unified storage of data generated in a full-notch creep test including the possibility to record data from analysis and re-evaluation. Furthermore, extensive metadata allows to assess data quality and reliability. Following the open world assumption, object properties are deliberately low restrictive and sparse.
Unlike conventional alloys, which typically consist of one main element, high-entropy alloys (HEAs) contain five or more principal elements, which broaden chemical complexity and with it a realm of synergistic mechanisms. The AlMo0.5NbTa0.5TiZr HEA initiated a subclass of Al-containing refractory (r)HEAs that has recently drawn attention [2]. The alloy has a superalloy-resembling B2/bcc nanostructure, which inspired its name refractory high entropy superalloy (RSA). With high-temperature (HT) compressive strengths beyond conventional Ni-based superalloys, this nanostructure could be used for improved HT structural applications. However, in the application-relevant HT regime the Al-Zr-rich B2 phase decomposes to form a hexagonal Al-Zr-based intermetallic (Al4-xZr5; x: 0..1) [3,4]. This work explores the fascinating yet fatal micromechanisms associated to this phase transformation, in the context of creep, annealing and oxidation experiments performed between 800 and 1200 °C.
The material was produced by arc-melting and heat treatment in argon, which lead to grain boundaries decorated with up to 7%. Interrupted constant-load creep tests were performed under vacuum (at 10-4 Pa), at 900–1100 °C with external tensile stresses of 30–120 MPa. Oxidation experiments were separately conducted for 24 hours at 800 and 1000 °C in both dry (21% O2 + 79% N2) and humid (8% O2 + 74% N2 + 18% H2O) air. After the experiments, the samples were characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy to reveal degradation mechanisms. Crystallographic texture, orientation relationships and stabilization of an oxygen-containing iso structure (Al4-xZr5(Ox-y); y: 0..x) of the Al-Zr-rich intermetallic are found and discussed.
In the past two decades, numerous relaxation or physical aging experiments of metallic glasses have revealed signatures of intermittent atomic-scale processes. Revealed via intensity cross-correlations from coherent scattering using X-ray photon correlation spectroscopy (XPCS), the observed abrupt changes in the time-domain of atomic motion does not fit the picture of gradual slowing down of relaxation times and their origin continues to remain unclear. Using a binary Lennard-Jones model glass subjected to microsecond-long isotherms, we show here that temporally and spatially heterogeneous atomic-cluster activity at different length-scales drive the emergence of highly non-monotonous intensity cross-correlations. The simulated XPCS experiments reveal a variety of time-dependent intensity-cross correlations that, depending on both the structural evolution and the 𝑞-space sampling, give detailed insights into the possible structural origins of intermittent aging measured with XPCS.
Additive manufacturing (AM) offers significantly greater freedom of design compared to conventional manufacturing processes since the final parts are built layer by layer. This enables metal AM, also known as metal 3D printing, to be utilized for improving efficiency and functionality, for the production of parts with very complex geometries, and rapid prototyping. However, despite many technological advancements made in recent years, several challenges hinder the mass adoption of metal AM. One of these challenges is mechanical anisotropy which describes the dependency of material properties on the material orientation. Therefore, in this work, stainless steel 316L parts produced by laser-based powder bed fusion are used to isolate and understand the root cause of anisotropy in AM parts. Furthermore, an efficient and accurate multiscale numerical framework is presented for predicting the deformation behavior of actual AM parts on the macroscale undergoing large plastic deformations. Finally, a novel constitutive model for the plastic spin is formulated to capture the influence of the microstructure evolution on the material behavior on the macroscale.
Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer–Emmet–Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.
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.
This study investigates the sintering and crystallization behavior and kinetic of the bioactive glass (BG) 13–93 with nominal composition (in mol%): 54.6 SiO2 - 1.7 P2O3 - 22.1 CaO - 6.0 Na2O - 7.9 K2O - 7.7 MgO. Sintering and crystallization were investigated non-isothermally for various particle size fractions smaller than 315 μm as well as for bulk samples. Densification was not hindered by the presence of crystalline phases across all particle size fractions. Afterwards, wollastonite was found as the dominant crystal phase at higher temperature which resorb primary surface precipitation-like quartz crystallites. The growth direction shifts into volume when the sample surface is nearly covered. The crystal growth rate of wollastonite was calculated from the crystalline surface layer thickness measured during heating. The findings of this study are relevant for the high temperature processing of BG 13–93.