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The ubiquity of polymeric materials in daily life Comes with an increased fire risk, and sustained research into efficient flame retardants is key to ensuring the safety of the populace and material goods from accidental fires. Phosphorus, a versatile and effective element for use in flame retardants, has the potential to supersede the halogenated variants that are still widely used today: current formulations employ a variety of modes of action and methods of implementation, as additives or as reactants, to solve the task of developing flameretarding polymeric materials. Phosphorus-based flame retardants can act in both the gas and condensed phase during a fire. This Review investigates how current phosphorus chemistry helps in reducing the flammability of polymers, and addresses the future of sustainable, efficient, and safe phosphorus-based flame-retardants from renewable sources.
The rapid mass calorimeter (RMC) was used as a screening tool based on accelerated fire testing to assess flame-retarded thermoplastic polyurethane (TPU). The reliability of RMC results was proven with the cone calorimeter as reference fire test. The influence of melamine cyanurate (MC) concentration on the fire performance of TPU was investigated, along with some flame-retardant combinations such as MC with aluminium diethylphosphinate (AlPi), aluminium trihydrate (ATH), and melamine polyphosphate (MPP). The two-stage burning behaviour of TPU was investigated in detail; the first stage corresponds mainly to the hard segments' decomposition and has a much lower effective heat of combustion (EHC) than the second stage, in which mainly the soft segments decompose and an intensive liquid pool fire is observed in the cone calorimeter set-up. In addition to fire testing with the cone calorimeter, RMC, and UL 94 flammability tests, the decomposition of the materials was investigated using thermogravimetric analysis coupled with infrared spectrometry (TGeFTIR). TPU/MC/AlPi shows the most promising results, achieving V-0 classification in UL 94 and reducing the extreme peak heat release rate (PHRR) of the liquid pool fire from 3154 kW/m2 to 635 kW/m2. Using MC/AlPi/MPP enhances the latter PHRR reduction further. The decomposition products identified in the gas phase via TGeFTIR reveal specific MCeAlPi eMPP interactions, as they differ from products seen in systems with MC/AlPi or MC/MPP. Correlations between RMC and cone calorimeter results were examined and presented in the final part of the paper. Several characteristics correlate strongly, pointing out that RMC is a reliable high-throughput fire testing method to screen multicomponent flame-retardant solutions in TPU.
The susceptibility of concrete structures due to alkali–silica reaction (ASR) can be assessed by means of ASR concrete prism testing at 60 °C, according to RILEM AAR 4.1. There, expansion of concrete prisms indicates alkali-reactivity of the examined concrete mix. This work applies in situ expansion measurement to accelerated concrete prism testing. Automated measuring facilitates both storage without the usually necessary interruptions for manual measurement and acquisition of quasi-continuousexpansion data. A comparative experimental programme showed that conventional testing resulted in stronger expansion and leaching of alkalis than automated testing. Experimental simulation of interruptions, typically associated with manual measurements in conventional testing, could prove the influence of these cooling–heating cycles. Two phenomenological approaches, frequently used for describing reaction kinetics of ASR by linking it to expansion results from ASR-testing, were validated with continuous expansion data of three types of aggregate. Experimental expansion depicted s-shaped curves similar to them of the modelling approaches. However, strong swelling recorded in the beginning of the test was not covered by the model curves. Auxiliary measurement of acoustic emissions and ultrasonic velocity helped characterising mechanisms such as hydration and cracking, which also influence prism expansion. The proposed modification of the measurement procedure provides an extended basis to analyse expansion mechanisms. Regarding data for validation of ASR-expansion models, continuous expansion results are preferable to conventional test results.
The copper alloyed stainless steel 1.4542 (X5CrNiCuNb16-4) is used in different areas due to its good mechanical properties and corrosion resistance. Strength and corrosion resistance can be adjusted by the heat treatment, which is of importance for the application of this alloy. The mechanical properties (strength and hardness) are attributed to the dispersive precipitation of the copper rich ε–Phase. The additional precipitation of chromium carbides can reduce the corrosion resistance. Different ageing states were produced to investigate the precipitation behaviour with various methods. Furthermore, the influence of cold-rolling on the precipitation behaviour was studied in comparison to a solution annealed state without deformation. The microstructure was studied by SEM and the variations of hardness and magnetic proportion were characterised. The electrochemical potentiodynamic reactivation
(EPR) was used to determine the corrosion resistance and detect chromium depletion in all heattreated states. The results show that a work hardening accelerates the precipitation rate, while ageing at 600 °C reduces the corrosion resistance due to chromium depletion.
In structural parts under vibrational loading fatigue cracks can initiate and grow, which can lead to structural failure. Conventional non-destructive testing methods for crack detection provide just a snapshot of fatigue crack evolution, whereas crack luminescence coating realizes clear visibility of the entire crack formation. Fatigue causing cyclic tensile tests and examinations on special test bodies allowing control of the crack opening width demonstrate a high sensitivity of the coating.
Potentialfeldmessung (PM) ist die beliebteste Methode der Zerstörungsfreien Prüfung (ZfP) zur Lokalisierung von aktiver Betonstahlkorrosion. PM wird durch Parameter wie z. B. Feuchtigkeits- und Chloridgradienten im Bauteil beeinflusst, so dass die Sensitivität gegenüber der räumlich sehr begrenzten, aber gefährlichen Lochkorrosion gering ist. Wir zeigen in dieser Studie, wie zusätzliche Messinformationen mit Multisensor-Datenfusion genutzt werden können, um die Detektionsleistung zu verbessern und die Auswertung zu automatisieren. Die Fusion basiert auf überwachtem maschinellen Lernen (ÜML). ÜML sind Methoden, die Zusammenhänge in (Sensor-) Daten anhand vorgegebener Kennzeichnungen (Label) erkennen. Wir verwenden ÜML um „defekt“ und „intakt“ gelabelte Bereiche in einem Multisensordatensatz zu unterscheiden. Unser Datensatz besteht aus 18 Messkampagnen und enthält jeweils PM-, Bodenradar-, Mikrowellen-Feuchte- und Wenner-Widerstandsdaten. Exakte Label für veränderliche Umweltbedingungen wurden in einer Versuchsanordnung bestimmt, bei der eine Stahlbetonplatte im Labor kontrolliert und beschleunigt verwittert. Der Verwitterungsfortschritt wurde kontinuierlich überwacht und die Korrosion gezielt erzeugt. Die Detektionsergebnisse werden quantifiziert und statistisch ausgewertet. Die Datenfusion zeigt gegenüber dem besten Einzelverfahren (PM) eine deutliche Verbesserung. Wir beschreiben die Herausforderungen datengesteuerter Ansätze in der zerstörungsfreien Prüfung und zeigen mögliche Lösungsansätze.