Datei für die Öffentlichkeit verfügbar ("Open Access")
Filtern
Erscheinungsjahr
Dokumenttyp
- Zeitschriftenartikel (1616)
- Forschungsbericht (372)
- Beitrag zu einem Tagungsband (369)
- Dissertation (203)
- Zeitschriftenheft (Herausgeberschaft für das komplette Heft) (148)
- Sonstiges (64)
- Forschungsdatensatz (61)
- Posterpräsentation (48)
- Vortrag (40)
- Jahresbericht (19)
Sprache
- Englisch (2098)
- Deutsch (875)
- Mehrsprachig (23)
Schlagworte
- SAXS (54)
- Additive manufacturing (53)
- Nanoparticles (51)
- Fluorescence (44)
- Concrete (41)
- Zerstörungsfreie Prüfung (41)
- Corrosion (37)
- Ultrasound (35)
- Non-destructive testing (31)
- Simulation (31)
Organisationseinheit der BAM
- 8 Zerstörungsfreie Prüfung (431)
- 6 Materialchemie (429)
- 1 Analytische Chemie; Referenzmaterialien (356)
- 4 Material und Umwelt (217)
- 7 Bauwerkssicherheit (191)
- 9 Komponentensicherheit (186)
- 5 Werkstofftechnik (172)
- 6.3 Strukturanalytik (141)
- 8.5 Mikro-ZfP (117)
- 6.1 Oberflächenanalytik und Grenzflächenchemie (104)
Paper des Monats
- ja (15)
Air-coupled ultrasound sensors have advantages over contact ultrasound sensors when a sample should not become contaminated or influenced by the couplant or the measurement has to be a fast and automated inline process. Thereby, air-coupled transducers must emit high-energy pulses due to the low air-to-solid power transmission ratios (10−3 to 10−8). Currently used resonant transducers trade bandwidth—a prerequisite for material parameter analysis—against pulse energy. Here we show that a combination of a non-resonant ultrasound emitter and a non-resonant detector enables the generation and detection of pulses that are both high in amplitude (130 dB) and bandwidth (2 µs pulse width). We further show an initial application: the detection of reflections inside of a carbon fiber reinforced plastic plate with thicknesses between 1.7 mm and 10 mm. As the sensors work contact-free, the time of flight and the period of the in-plate reflections are independent parameters. Hence, a variation of ultrasound velocity is distinguishable from a variation of plate thickness and both properties are determined simultaneously. The sensor combination is likely to find numerous industrial applications necessitating high automation capacity and opens possibilities for air-coupled, single-side ultrasonic inspection.
We present how mesoporosity can be engineered in transition metal phosphate (TMPs) materials in a template-free manner. The method involves a transformation of a precursor metal phosphate phase, called M-struvite (NH4MPO4·6H2O, M = Mg2+, Ni2+, Co2+, NixCo1-x2+). It relies on the thermal decomposition of crystalline M-struvite precursors to an amorphous and simultaneously mesoporous phase, which forms while degassing of NH3 and H2O. The temporal evolution of mesoporous frameworks and the response of the metal coordination environment were followed with in-situ and ex-situ scattering and diffraction, as well as X -ray spectroscopy. Despite sharing the same precursor struvite structure, different amorphous and mesoporous structures were obtained depending on the involved transition metal. We highlight the systematic differences in absolute surface area, pore shape, pore size, and phase transitions depending on a metal cation present in the analogous M-struvites. The amorphous structures of thermally decomposed Mg-, Ni- and NixCo1-x-struvites exhibit high surface areas and pore volumes (240 m²g-1 and 0.32 cm-3 g-1 for Mg and 90 m²g-1 and 0.13 cm-3 g-1 for Ni). We propose that the low-cost, environmentally friendly M-struvites could be obtained as recycling products from industrial and agricultural wastewaters. These waste products could be then upcycled into mesoporous TMPs through a simple thermal treatment for further applications, for instance, in (electro)catalysis.
Cryoadsorption on the inner surface of porous materials is a promising solution for safe, fast, and reversible hydrogen storage. Within the class of highly porous metal−organic frameworks, zeolitic imidazolate frameworks (ZIFs) show high thermal, chemical, and mechanical stability. In this study, we selected ZIF-8 synthesized mechanochemically by twin-screw extrusion as powder and pellets. The hydrogen storage capacity at 77 K and up to 100 bar has been analyzed in two laboratories applying three different measurement setups showing a high reproducibility. Pelletizing ZIF-8 increases the packing density close to the corresponding value for a single crystal without loss of porosity, resulting in an improved volumetric hydrogen storage capacity close to the upper limit for a single crystal. The high volumetric uptake combined with a low and constant heat of adsorption provides ca. 31 g of usable hydrogen per liter of pellet assuming a temperature−pressure swing adsorption process between 77 K − 100 bar and 117 K − 5 bar. Cycling experiments do not indicate any degradation in storage capacity. The excellent stability during preparation, handling, and operation of ZIF-8 pellets demonstrates its potential as a robust adsorbent material for technical application in pilot- and full-scale adsorption vessel prototypes.
Data science (digitalisation and artificial intelligence) became more than an important facilitator for many domains in fundamental and applied sciences as well as industry and is disrupting the way of research already to a large extent. Originally, data sciences were viewed to be well-suited, especially, for data-intensive applications such as image processing, pattern recognition, etc. In the recent past, particularly, data-driven and physics-inspired machine learning methods have been developed to an extent that they accelerate numerical simulations and became directly usable for applications related to the nuclear waste management cycle. In addition to process-based approaches for creating surrogate models, other disciplines such as virtual reality methods and high-performance computing are leveraging the potential of data sciences more and more. The present challenge is utilising the best models, input data and monitoring information to integrate multi-chemical-physical, coupled processes, multi-scale and probabilistic simulations in Digital Twins (DTw) able to mirror or predict the performance of its corresponding physical twins. Therefore, the main target of the Topical Collection is exploring how the development of DTw can benefit the development of safe, efficient solutions for the pre-disposal and disposal of radioactive waste. A particular challenge for DTw in radioactive waste management is the combination of concepts from geological modelling and underground construction which will be addressed by linking structural and multi-physics/chemistry process models to building or tunnel information models. As for technical systems, engineered structures a variety of DTw approaches already exist, the development of DTw concepts for geological systems poses a particular challenge when taking the complexities (structures and processes) and uncertainties at extremely varying time and spatial scales of subsurface environments into account.
Das Ziel des Verbundforschungsvorhabens KKS-Gründung war die Entwicklung eines Monitoringsystems zur Erfassung von Korrosion an Gründungsstrukturen im Labormaßstab. Dafür war eine umfassende Bewertung und Beschreibung korrosionsbeeinflussender Faktoren und der Korrosionssysteme notwendig. Im Vorhaben KKS-Gründung wurde die Gründungsstruktur unterhalb der Wasserlinie betrachtet bis hin zum anaeroben Bereich im Sediment. Insbesondere der Sedimentbereich wurde bisher nur unzureichend betrachtet. Da die komplexen Mechanismen in der Sedimentzone noch nicht ausreichend wissenschaftlich untersucht wurden, mussten Möglichkeiten entwickelt werden, um diese zu bewerten.
Im Verbundforschungsvorhaben KKS-Gründung agierte die Bundesanstalt für Materialforschung und -prüfung (BAM) als Forschungsstelle. Die Hauptziele des Teilvorhabens der BAM waren die Bereitstellung einer Messumgebung für das von den Partnern entwickelte Monitoringsystem, die umfassende wissenschaftliche Beschreibung der Korrosionssysteme im Unterwasserbereich und Sediment sowie die Gewinnung von Messdaten zur Verifizierung und Überführung in die Simulation. Als Forschungsstelle war die BAM der Ansprechpartner für die Verbundpartner bei wissenschaftlichen Fragestellungen.
Die Hauptziele des Vorhabens wurden erreicht und es wurden grundlegende Erkenntnisse zum Korrosionsverhalten von Offshore-Stahl im Unterwasser und Sedimentbereich gewonnen. Darüber hinaus wurden wichtige Erkenntnisse zum Betrieb eines Laborcontainers und zur Nachstellung von Korrosionssystemen in Meerwasserbecken bei Verwendung von künstlichem Meerwasser und Sand als Sediment gewonnen. Eine Beschreibung und Bewertung der Korrosivität und ablaufender Reaktionen in den einzelnen Belastungszonen wurde mittels elektrochemischer und gravimetrischer Verfahren vorgenommen.
The 18O/16O ratio of cherts (δ18Ochert) increases nearly monotonically by ~15‰ from the Archean to present. Two end-member explanations have emerged: cooling seawater temperature (TSW) and increasing seawater δ18O (δ18Osw). Yet despite decades of work, there is no consensus, leading some to view the δ18Ochert record as pervasively altered.
Here, we demonstrate that cherts are a robust archive of diagenetic temperatures, despite metamorphism and exposure to meteoric fluids, and show that the timing and temperature of quartz precipitation and thus δ18Ochert are determined by the kinetics of silica diagenesis. A diagenetic model shows that δ18Ochert is influenced by heat flow through the sediment column. Heat flow has decreased over time as planetary heat is dissipated, and reasonable Archean-modern heat flow changes account for ~5‰ of the increase in δ18Ochert, obviating the need for extreme TSW or δ18Osw reconstructions. The seawater oxygen isotope budget is also influenced by solid Earth cooling, with a recent reconstruction placing Archean δ18OSW 5 to 10‰ lower than today. Together, this provides an internally consistent view of the δ18Ochert record as driven by solid Earth cooling over billion-year timescales that is compatible with Precambrian glaciations and biological.
The reliable identification and quantitation of phosphorylated amino acids, peptides and proteins is one of the key challenges in contemporary bioanalytical research, an area of particular interest when attempting to diagnose and treat diseases at an early stage. We have developed a synthetic probe for targeting phosphorylated amino acids, based on core–shell submicron-sized particles consisting of a silica core, coated with a molecularly imprinted polymer (MIP) shell. The MIP layer contains a fluorescent probe crosslinker which binds selectively to phosphorylated tyrosine (pY) moieties with a significant imprinting factor (IF) and responds with a "light-up” fluorescence signal. The bead-based ratiometric detection scheme has been successfully transferred to a microfluidic chip format and its applicability to rapid assays has been exemplarily shown by discriminating a pY-terminating oligopeptide against its nonphosphorylated counterpart. Such miniaturised devices could lead to an automated pY or pY N-terminated peptide measurement system in the future. The setup combines a modular microfluidic system for amino acid derivatisation, extraction (by micropillar co-flow) and selective adsorption and detection with the fluorescent MIP core–shell particle probes. A miniaturised optical assembly for low-light fluorescence measurements was also developed, based on miniaturised opto-electronic parts and optical fibres. The emission from the MIP particles upon binding of pY or pY N-terminated peptides could be monitored in real-time.
Ratiometric green–red fluorescent nanosensors for fluorometrically monitoring pH in the acidic range were designed from 80 nm-sized polystyrene (PS) and silica (SiO2) nanoparticles (NPs), red emissive reference dyes, and a green emissive naphthalimide pH probe, analytically and spectroscopically characterized, and compared regarding their sensing performance in aqueous dispersion and in cellular uptake studies. Preparation of these optical probes, which are excitable by 405 nm laser or LED light sources, involved the encapsulation of the pH-inert red-fuorescent dye Nile Red (NR) in the core of self-made carboxylated PSNPs by a simple swelling procedure and the fabrication of rhodamine B (RhB)-stained SiO2-NPs from a silane derivative of pH-insensitive RhB. Subsequently, the custom-made naphthalimide pH probe, that utilizes a protonation-controlled photoinduced electron transfer process, was covalently attached to the carboxylic acid groups at the surface of both types of NPs. Fluorescence microscopy studies with the molecular and nanoscale optical probes and A549 lung cancer cells confirmed the cellular uptake of all probes and their penetration into acidic cell compartments, i.e., the lysosomes, indicated by the switching ON of the green naphthalimide fluorescence. This underlines their suitability for intracellular pH sensing, with the SiO2-based nanosensor revealing the best performance regarding uptake speed and stability.
We report, to our knowledge for the first time on simultaneous distributed temperature and strain sensing in a standard telecom optical fiber using a machine learning assisted Brillouin frequency domain analysis (BOFDA) system. The well-known temperature and strain cross-sensitivity problem is addressed by developing a BOFDA system with a high signal-to-noise ratio and applying machine learning. The spectrum consists of four highly resolved peaks, whose Brillouin frequency shifts are extracted and serve as features for the machine learning algorithms. The spectra result from a 450-m standard SMF-28 optical fiber, and particularly from a segment of 30 m. This fiber segment is coiled around a stretcher and placed in a climate chamber. The applied temperature and strain values range from 20 °C to 40 °C and from 0 µɛ to 1380 µɛ, respectively. The total measurement time to achieve a high SNR and resolve four peaks with a spatial resolution of 6 m is 16 min. To discriminate temperature and strain effects, simple frequentist and more sophisticated Bayesian-based algorithms are employed with the powerful Gaussian process regression (GPR) delivering the best performance in terms of temperature and strain errors, which are found to be 2 °C and 45 µɛ, respectively. These errors are calculated using leave-one-out cross-validation, so that an unbiased estimation of the sensor’s performance is provided.