Optimization and activation of renewable durian husk for biosorption of lead (II) from a aqueous medium

Background: Biosorption of lead Pb(II) by durian husk activated carbon (DHAC) was investigated. The main aim of this work is to explore the effect of operating variables such as pH, biosorbent dose, temperature, initial metal ion concentration and contact time on the removal of Pb(II) from synthesized aqueous medium using a response surface methodology (RSM) technique. The experimentation was performed in two sets, namely set 1 and set 2. Results: For experimental set 1, pH was set to 7.0. The optimum conditions for the remaining parameters were determined to be 0.39 g DHAC dose, 60 min contact time and 100 mg L−1 of initial metal ion concentration, which yielded maximum biosorption capacity of 14.6 mg g−1. For experimental set 2, 41.27 °C, 8.95 and 99.96 mg L−1 were the optimum conditions determined for temperature, pH and initial Pb(II) concentration, respectively; which revealed a maximum adsorption capacity of 9.67 mg g−1. Characterization of the adsorbent revealed active functional groups such as hydroxyl, carboxylic, alcohol and hemicellulose. The equilibrium adsorption data obeyed the Langmuir isotherm and pseudo‐second‐order kinetic models with maximum Langmuir uptake of 36.1 mg g−1. Conclusions: The biosorbent was capable of reuse, so that the abundant durian husk could be utilized effectively for the removal of Pb(II) from polluted water

Computational Identification and Analysis of the Key Biosorbent Characteristics for the Biosorption Process of Reactive Black 5 onto Fungal Biomass

The performances of nine biosorbents derived from dead fungal biomass were investigated for their ability to remove Reactive Black 5 from aqueous solution. The biosorption data for removal of Reactive Black 5 were readily modeled using the Langmuir adsorption isotherm. Kinetic analysis based on both pseudo-second-order and Weber-Morris models indicated intraparticle diffusion was the rate limiting step for biosorption of Reactive Black 5 on to the biosorbents. Sorption capacities of the biosorbents were not correlated with the initial biosorption rates. Sensitivity analysis of the factors affecting biosorption examined by an artificial neural network model showed that pH was the most important parameter, explaining 22%, followed by nitrogen content of biosorbents (16%), initial dye concentration (15%) and carbon content of biosorbents (10%). The biosorption capacities were not proportional to surface areas of the sorbents, but were instead influenced by their chemical element composition. The main functional groups contributing to dye sorption were amine, carboxylic, and alcohol moieties. The data further suggest that differences in carbon and nitrogen contents of biosorbents may be used as a selection index for identifying effective biosorbents from dead fungal biomass