Investigation of gold adsorption by ironbark biochar using response surface methodology and artificial neural network modelling

Abstract

Due to the importance and economic value of gold in various applications, recovering gold from waste streams like tailings and industrial wastewater is essential. Biochar with a high surface area and porosity is considered a potential low-cost adsorbent for gold reclaiming from aqueous media. Therefore, this study aims to develop a high-quality biochar with excellent physicochemical properties to efficiently remove gold from aqueous media. To accomplish this, biochar was obtained from pyrolysis of ironbark (IB) biomass at 500 °C which has a surface area of 493.79 m2/g. Subsequently, the biochar was investigated for adsorption of gold from aqueous media, which exhibited a maximum adsorption capacity of 858 mg/g. Isotherm results showed that the adsorption of gold by biochar followed the Langmuir model, indicating monolayer adsorption. Further, response surface methodology (RSM) and an artificial neural network (ANN) combined with the Salp Swarm Algorithm (SSA) were used to analyze the generated results (ANN-SSA). The RSM prediction model fit was adequate (R2 = 0.99). However, comparing the statistical data revealed that ANN-SSA outperformed RSM in predicting experimental results. Overall, this study suggested that biochar derived from IB biomass could be used as a potential adsorbent to recover gold from an aqueous solution. This article presents a unique and innovative study on the utilization of ironbark biochar for the purpose of gold adsorption.