This study deals with the optimization of energetic and exergetic parameters of a hybrid-solar dryer to dry basil leaves under determined experimental conditions at three air temperatures (40 °C, 55 °C, and 70 °C) and three bed thickness levels (2, 4, and 6 cm). The optimization of the thermodynamic parameters was performed using the response surface method (RSM) based on the central composite design (CCD) and the desirability function (DF) to maximize the drying rate, exergy efficiency, improvement potential rate and the sustainability index, and to minimize the energy utilization, energy utilization ratio and exergy loss rate. These parameters were calculated on the basis of the first and second laws of thermodynamics as the response variables. Based on the results obtained, it was determined that the optimal conditions for basil drying were at a drying air temperature of 63.8 °C and a bed thickness of 2 cm. At this point, the parameters of the drying rate, energy utilization, energy utilization ratio, exergy efficiency, exergy loss rate, improvement potential rate and sustainability index were obtained with the maximum utility function (D = 0.548) as 0.27, 0.019 (kJ/s), 0.23, 65.75%, 0.016 (kJ/s), 1.10 (kJ/s) and 0.015, respectively.

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The current exploration manifests the progress of a one-dimensional reactor for the production of methyl ethyl ketone (MEK) as a commercial-industrial solvent with a relatively rapid evaporation rate and high solvation ability. MEK has been extensively utilized in colorings, printing, artificial leather, and base oils. One of the methods for the production of MEK is catalytic dehydrogenation of 2-butyl alcohol in the temperature range of 650–750 K utilizing spherical ZnO catalyst. Considering the high cost of fossil fuels to achieve optimal energy consumption, thermal coupling with the Fischer–Tropsch reaction was employed. Eventually, an evolutionary genetic algorithm was adopted to optimize the reactor to maximize MEK production. MATLAB software was utilized for the modeling and optimization. The modeling results were verified by industrial data. Moreover, they indicated a 37 and 55.4% increase in the production rate of thermal coupling and optimal thermal coupling reactors, respectively.