RESUMEN
Ammonia is one of the most produced chemicals around the world due to its various uses. However its traditional production process is associated with high fossil fuel consumption. To avoid this, the production of green ammonia can be done, and one of the considered production methods is water electrolysis, where the hydrogen needed for the manufacturing of ammonia is produced using solar energy. In this work, multi-objective optimization (MOO) is carried out for two ammonia synthesis processes with water electrolysis. One process uses solar energy to generate electricity for the whole process (Green ammonia), while the other uses natural gas for the same purpose (non-green ammonia) on a small production scale. The process is simulated using ProMax 5.0 and MOO is done using Excel-based MOO with I-MODE algorithm. Several MOO cases are solved with different objectives like CO2 emissions and energy (ENG) minimization, and Profit and Purity maximization in two and three objective cases. To conduct the work, several decision variables are selected like the operating temperatures and pressures of different streams in addition to the flow rate of nitrogen and water. Some constraints regarding the purity and reactors temperature are considered as well. The obtained results showed that the profit of green ammonia process (ranges between 0.7 and 80 M$/yr) is lower compared to the non-green process (ranges between 0.8 and 4.4 M$/yr). On the other hand, huge CO2 emissions (up to 38000 tons/yr) are produced in the non-green process compared to almost zero emissions with the green process. In most cases, water and nitrogen flow rates showed a high influence on the results and caused conflict between the objectives.
RESUMEN
The gut wastes of Sardinella longiceps were used as substrate for protease production. The gut waste has 61.6% proteins, 21.8% lipids, 8.5% carbohydrates on dry weight basis and trace elements. The significant factors of protease fermentation were screened by Plackett-Burman design. A protease activity of 68.56 U/ml was predicted at 46.31 °C, incubation time 71.11 h, inoculum 4.86% (v/v) and substrate concentration 2.66% (w/v), using response surface methodology. However, the validation experiment showed 73.52 U/ml activity. The artificial neural network was found as a better tool to predict the experimental results. The partially purified protease showed higher activity at pH 9 and 10 and retained 90% activity after 120 h at pH 9. It showed maximum activity at 50 °C and retained 88% residual activity until 90 min at 50 °C. Zn++ enhanced the protease activity by 40%. The protease retained an activity of 93, 103, 90 and 98% against urea, ß-mercaptoethanol, SDS and tween 80 respectively. The alkaline protease was compatible with all the commercial detergents tested with the residual activity above 90%. The alkaline protease exhibited 22% higher activity on the tryptone soya substrate. The gut waste of S. longiceps is a worthy low cost substrate for the production of industrially important alkaline protease.
