Optimization by genetic algorithm of H2 production from aluminum water reaction in alkaline solution

Abstract

An experimental laboratory setup was designed to produce gaseous H 2 from aluminum particles obtained by melting and spraying recycled material. To evaluate process performance, a design of experiments was conducted with the following four factors: particle size of recycled aluminum, concentration of potassium hydroxide in the solution, speed of mechanical stirring in the solution, and solution temperature; for each factor, two levels were considered. The solid products of the reactions were characterized by scanning electron microscopy and X-ray diffraction, and the gaseous H 2 produced was characterized by gas chromatography (GC). Two genetic algorithms were built: one to model H 2 production and another to maximize it. Results show that the solid reaction products are aluminum hydroxides, and that the gas produced is high-purity H 2 ; the maximum H 2 production rate was 3983 μL/s. The aluminum particle size has the greatest impact on H 2 generation, indicating that the effective surface area is a decisive factor in H 2 production.