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The COVID-19 pandemic increased the pollution of water resources by some contaminants, e.g., chloroquine (CQN), due to its probable benefit in the treatment of the virus. Thus, is necessary the removal of CQN from water through advanced techniques. Black soybeans have been widely used due to their benefits to human health, and as a result, there was an increase in soybean husk residue, the main by-product of the soybean processing industry. Given the current scenario and the need to develop new uses for this agricultural residue, this study aimed to establish an economical and environmental biotechnology by the CQN adsorption process onto black soybean hulls (BSH) for the first time. BSH was characterized by physicochemical and spectroscopic techniques that demonstrated porosity, organic functional groups and negative surface charges. The pH study did not affect CQN adsorption pronouncedly, indicating that π-interactions and hydrogen bonds are the main mechanisms of the adsorption process. The maximum adsorption capacity was 75.06 ± 2.24 mg g−1 with 240 min of contact time at 288 K. In order to verify the biosorbent applicability, the safranin orange dye and triclosan adsorption were also evaluated onto BSH. The absorption peaks of the contaminants used in the synthetic mixture demonstrated a removal rate of 90.81 ± 0.80% for safranin orange, 66.79 ± 1.12% for triclosan and 70.62 ± 0.67% for CQN. The satisfactory removal of other contaminants indicates that BSH is a promising, affordable and environmentally friendly biosorbent with applicability potential for alternative treatment of contaminated water. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate both the temperature and the initial moisture content of the material in mathematical models of drying. For this, empirical lumped parameter models were fitted based on experimental data of moisture over time. Furthermore, a new semi‐empirical drying kinetics model was applied. This model was developed using the generalization of arbitrary order of the Lewis equation obtained through the Laplace transform. After performing the fit, the fractional order model for drying wheat seeds as a temperature function was generalized. Distributed parameter models were also fitted to evaluate the influence of initial moisture content on drying kinetics and to estimate the moisture profile along the position inside the seed. It was verified that the fractional order model presented statistical results similar to models with a higher number of constants, being used to generalize the kinetic drying model for the three wheat cultivars. Generalized models showed better fits for the 3 cultivars with first‐degree function, and the maximum global deviation was 10%, 15%, and 20% for the cultivars BRS–Atobá, BRS–Jacana, and BRS–Sanhaço, respectively. In addition, the distribution of moisture content inside the seed was verified by the distributed parameter model, which predicted the experimental data with an overall deviation of around 10%. [ABSTRACT FROM AUTHOR]

Fractional calculus is a method to predict processes mathematically. This study uses fractional order models to determine whether starch hydration is governed by Fickian or anomalous diffusion. Native and modified starches are compared and classified based on their diffusive characteristics and the type of diffusion observed. The study aims to adjust the equation of the analytical solution of the diffusion model to study the hydration of both native and modified starches. The fractional order diffusion model is generalized to compare the two models and identify whether anomalous mechanisms exist in native and modified starches. The results show that water absorption by native and modified starch granules is characterized by anomalous diffusion. This is due to the temperature conditions and differences in the chemical potential of the starches. It is verified that the diffusive characteristics of native and modified starches differ under the same hydration conditions. [ABSTRACT FROM AUTHOR]

In this article is introduced a new kinetic semi‐empirical model for drying. The model was developed by arbitrary‐order generalization of Lewis's kinetic equation that was obtained using the Laplace transform and Laplace's Inverse Transform. Kinetic data on soybean drying at 50, 60, 70, and 80 °C were retrieved to test the model which was compared to first‐order Lewis's model and to Page's model by quantitative criteria. Results show that the process is best described by the fractional‐order model and that arbitrary‐order equation may be employed to adjust experimental data on drying, with better results among other models analyzed. Practical applications: Drying is one of the most complex and energy‐consuming chemical unit operations. The modeling of drying kinetics can be applied in the project of drying equipment and to reduce costs of energy consumption. In general, the approach used in drying kinetics modeling is based on differential balances to represent the temporal variability of moisture content. In some cases, the Mathematical models cannot fit good the experimental data by to the fact that the models obtained by differential balances are exponential and the experimental data nonexponential. The fractional calculus can be an alternative to generalize the order of differential equations and fit process. The modeling procedure presented in this article presents the use of fractional calculus to generalize the order of a classic differential model. The model obtained by the fractional calculus approach provides best fits and more reliable adjusts than the classic model, the results indicate an anomalous diffusion. [ABSTRACT FROM AUTHOR]