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A large strain collection comprising antagonistic bacteria was screened for novel detergent proteases. Several strains displayed protease activity on agar plates containing skim milk but were inactive in liquid media. Encapsulation of cells in alginate beads induced protease production. Stenotrophomonas maltophilia emerged as best performer under washing conditions. For identification of wash-active proteases, four extracellular serine proteases called StmPr1, StmPr2, StmPr3 and StmPr4 were cloned. StmPr2 and StmPr4 were sufficiently overexpressed in E. coli. Expression of StmPr1 and StmPr3 resulted in unprocessed, insoluble protein. Truncation of most of the C-terminal domain which has been identified by enzyme modeling succeeded in expression of soluble, active StmPr1 but failed in case of StmPr3.
From laundry application tests StmPr2 turned out to be a highly wash-active protease at 45 °C. Specific activity of StmPr2 determined with suc-l-Ala-l-Ala-l-Pro-l-Phe-p-nitroanilide as the substrate was 17 ± 2 U/mg. In addition we determined the kinetic parameters and cleavage preferences of protease StmPr2.
In this research work, a statistical analysis of the CO2 laser beam welding of dual phase (DP600)/transformation induced plasticity (TRIP700) steel sheets was done using response surface methodology. The analysis considered the effect of laser power (2–2.2 kW), welding speed (40–50 mm/s) and focus position (−1 to 0 mm) on the heat input, the weld bead geometry, uniaxial tensile strength, formability limited dome height and welding operation cost. The experimental design was based on Box–Behnken design using linear and quadratic polynomial equations for predicting the mathematical models. The results indicate that the proposed models predict the responses adequately within the limits of welding parameters being used and the welding speed is the most significant parameter during the welding process.
Generally, the quality of a weld joint is directly influenced by the welding input parameter settings. Selection of proper process parameters is important to obtain the desired weld bead profile and quality. In this research work, numerical and graphical optimization techniques of the CO2 laser beam welding of dual phase (DP600)/transformation induced plasticity (TRIP700) steel sheets were carried out using response surface methodology (RSM) based on Box–Behnken design. The procedure was established to improve the weld quality, increase the productivity and minimize the total operation cost by considering the welding parameters range of laser power (2–2.2 kW), welding speed (40–50 mm/s) and focus position (−1 to 0 mm). It was found that, RSM can be considered as a powerful tool in experimental welding optimization, even when the experimenter does not have a model for the process. Strong, efficient and low cost weld joints could be achieved using the optimum welding conditions.