Iron oxide Permeated Mesoporous rice-husk nanobiochar (IPMN) mediated removal of dissolved arsenic (As): Chemometric modelling and adsorption dynamics

Abstract Adsorption based technologies are most widely used to mitigate the global predominance of heavy-metal groundwater contaminants like Arsenic (As), owing to their high efficiency and economic operation. The current study involves the optimization of Iron oxide Permeated Mesoporous rice-husk nanobiochars (IPMN) for As removal, which were synthesized through a chemically amended pyrolytic approach. The IPMN variants were screened based on preliminary OVAT (one-variable-at-a-time) studies for As removal. Chemometric investigations employing a central composite design matrix of Response surface methodology was further used to understand the influence of the process parameters on the adsorption of As on the most efficient IPMN variant. A Multi-Layered-Perceptron based artificial neural network was further used to confirm the veracity of the experimental and predictive conditions, to derive the optimal condition for the best adsorption efficiency. In addition, the dynamics of As adsorption by the optimal IPMN variant was modelled using pseudo-first-order (Lagergren) and pseudo-second-order (Ho) rate kinetic equations followed by isotherm studies using non-linear regression of Langmuir, Freundlich and Sips adsorption isotherms. The IPMNs have an appreciably higher uptake capacity (>90%) for dissolved As, as compared to the native milled rice husk (∼20%), alongside a substantial recyclability, thereby establishing their potential as a highly efficient, economical and sustainable nanobiochar for As removal.