Ein Mikroverfahren zur Stickstoffbestimmung nach Kjeldahl

Ohne Zusammenfassung     

Effect of metal chelates on the ignition and early flaming behaviour of intumescent fire-retarded polyethylene systems

Polyethylene (PE) was treated with various formulations containing an intumescent fire retardant, which consists of melamine phosphate (MP), pentaerythritol (PER) and ammonium polyphosphate (APP), and one or none of following metal chelates: CuSAO, CoSAO and NiSAO. The behaviour of this intumescent system can be enhanced significantly by the addition of small amounts (0.2%) of metal chelate (CuSAO, CoSAO and NiSAO). The thermal stabilization, burning behaviour and char formation of the fire retardant PE system have been investigated by TGA, LOI, UL-94 test, SEM and cone calorimetry. All formulations studied provide good fire retardant behaviour, with LOI ≥ 27.4 and UL-94 V-0 rating. TGA results present more complicated thermal decomposition behaviour after the addition of small amounts (0.2%) of metal chelate when compared to that of PE-IFR. Cone calorimetry of PE-IFR–metal chelate (PE-IFR–CuSAO, PE-IFR–CoSAO and PE-IFR–NiSAO) shows a very significant decrease in HRR, PHRR, ML, THR and a very significant improvement of TTI compared to samples without metal chelate. Furthermore, SEM and photographs of the char layer show that the char layer from PE-IFR–metal chelate has a compact and tough char structure compared to the open porous char layer produced by sample without metal chelate.     

Pareto memetic algorithm for multiple objective optimization with an industrial application

Multiple objective combinatorial optimization problems are difficult to solve and often, exact algorithms are unable to produce optimal solutions. The development of multiple objective heuristics was inspired by the need to quickly produce acceptable solutions. In this paper, we present a new multiple objective Pareto memetic algorithm called PMS^MO. The PMS^MO algorithm incorporates an enhanced fine-grained fitness assignment, a double level archiving process and a local search procedure to improve performance. The performance of PMS^MO is benchmarked against state-of-the-art algorithms using 0–1 multi-dimensional multiple objective knapsack problem from the literature and an industrial scheduling problem from the aluminum industry.