Investigation of Severe Plastic Deformation Effects on Magnesium RZ5 Alloy Sheets Using a Modified Multi-Pass Equal Channel Angular Pressing (ECAP) Technique.

The present study investigates the effects of multiple passes of equal channel angular pressing (ECAP) on magnesium alloy sheets with the assistance of an Inconel plunger along with a die setup having a channel angle of 120° and corner angle of 10° operating at a temperature of 200 °C followed by the required heat treatment processes. The microstructural analysis of the sheet samples at various stages of the multi-pass hot ECAP has shown evidence of ultrafine grain refinement (UFG) due to the occurrence of severe plastic deformation. X-ray diffraction analysis has also exhibited the presence of phases like MgZn and CeZn3 which is supposedly responsible for the enhancement of the mechanical properties. As a result, the room temperature tensile and compressive strengths have improved by 6.12% and 6.63%, respectively, after the second pass, and 11.56% and 15.64%, respectively, after the fourth pass of ECAP. Additionally, the hardness of the sheets has increased by 6.49% and 16.64% after the second and fourth pass of hot ECAP, respectively, mainly attributed to the drastic decrease in grain size from 164 µm to 12 µm within four ECAP passes, all these with a negligible change in ductility. This success in the thermomechanical processing of Mg-RZ5 alloy sheets using a die channel angle of 120° with a minimal number of passes of hot ECAP under a controlled equivalent strain, further opens doors for incorporating optimizations and/or additional aspects so as to achieve even better grain refinements, and consequently, mechanical strength improvements thereby catering to the industrial needs of aerospace and construction areas.

Invasive weed optimization coupled biomass and product dynamics of tuning soybean husk towards lipolytic enzyme.

Waste to the product approach was proposed for tuning environ-threat soybean husk towards lipolytic enzyme by integrating the invasive weed optimization with biomass and product dynamics study. The invasive weed optimization constitutes based on the non-linear regression model results in a 47 % enhancement in lipolytic enzyme using the optimization parameters of 7% Sigma Final, 9% exponent; Smax of 5 with a population size of 35 and Max. generations of 99. The biomass dynamic study showcases the dynamic parameters of 0.0239 µmax, 8.17 XLimst and 0.852 RFin values. The product dynamic studies reveal the kinetic parameters of kst, kdiv, PFin, which seem to be equal to -0.0338, 0.0896 and 68.1, respectively. Overall, the present study put forth the zero-waste (soybean husk) to the product (lipolytic enzyme) approach by introducing the novel "Invasive Weed Optimization" coupled with "Biomass and product dynamics" to the bioprocessing field.

Enhanced lipase recovery through RSM integrated differential evolutionary approach from the fermented biomass

The aim of this work was to apply a modeling integrated optimisation approach for a complex, highly nonlinear system for an extracellular lipase extraction process. The model was developed using mutation, crossover and selection variables of Differential Evolution (DE) based on central composite design of Response Surface Methodology. The experimentally validated model was optimized by DE, a robust evolutionary optimization tool. A maximum lipase activity of 134.13 U/gds (more than 36.28 U/gds compared to one variable at a time approach) was observed with the DE-stated optimum values of 25.01% dimethyl sulfoxide concentration, 40 mM buffer, 128.52 min soaking time and 35ºC with the DE control parameters, namely number of population, generations, crossover operator and scaling factor as 20, 50, 0.5 and 0.25, respectively. The use of DE approach improved the optimization capability and decision speed, resulting in an improved yield of 36.28 U/gds compared to the one variable at a time approach for the extracellular lipase activity under the non-optimized conditions. The developed mathematical model and optimization were generic in nature, which seemed to be useful for the scale-up studies of maximum recovery of lipase from the fermented biomass.

Evaluation of lipase production by genetic algorithm and particle swarm optimization and their comparative study.

This paper presents the nature-inspired genetic algorithm (GA) and particle swarm optimization (PSO) approaches for optimization of fermentation conditions of lipase production for enhanced lipase activity. The central composite non-linear regression model of lipase production served as the optimization problem for PSO and GA approaches. The overall optimized fermentation conditions obtained thereby, when verified experimentally, have brought about a significant improvement (more than 15 U/gds (gram dry substrate)) in the lipase titer value. The performance of both optimization approaches in terms of computational time and convergence rate has been compared. The results show that the PSO approach (96.18 U/gds in 46 generations) has slightly better performance and possesses better convergence and computational efficiency than the GA approach (95.34 U/gds in 337 generations). Hence, the proposed PSO approach with the minimal parameter tuning is a viable tool for optimization of fermentation conditions of enzyme production.