Chloride ion sequestration by vetiver root biosorption: isotherm, kinetic, and thermodynamic analyses and ANN prediction

Water Supply Pub Date : 2024-03-15 DOI:10.2166/ws.2024.049
R. Dhumal, P. Sadgir
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Abstract

The present research investigates the potential of activated vetiver root powder as a bioadsorbent for removing chloride ions from saline aqueous environments, especially relevant for addressing agricultural water scarcity. Factors such as pH, biomass dosage, contact duration, and initial salt ion concentration were examined. Thermodynamic analysis provided insights into the adsorption process, demonstrating the feasibility, non-spontaneous behavior, and exothermic nature of chloride ion adsorption onto activated vetiver root powder. The batch adsorption of chlorides adhered to the Langmuir equation and a pseudo-second-order kinetic model, demonstrating a monolayer adsorption capacity of 17.58 mg/g for activated vetiver powder. An artificial neural network (ANN) was used to develop a predictive model for estimating the percentage removal of chloride ions. The values of R2 and mean squared error were used to determine the predictive performance of the ANN. In the near term, prospective commercial uses of activated vetiver powder merit further investigation through in-depth research using real wastewater containing salinity-inducing ion.
香根草根部的生物吸附作用对氯离子的螯合作用:等温线、动力学和热力学分析及 ANN 预测
本研究调查了活性香根草根粉作为生物吸附剂从盐水环境中去除氯离子的潜力,特别是与解决农业缺水问题相关的潜力。研究考察了 pH 值、生物量用量、接触时间和初始盐离子浓度等因素。热力学分析深入揭示了吸附过程,证明了氯离子在活性香根草根粉上吸附的可行性、非自发行为和放热性质。氯离子的批量吸附符合朗穆尔方程和伪二阶动力学模型,活性香根草粉末的单层吸附容量为 17.58 毫克/克。利用人工神经网络(ANN)建立了一个预测模型,用于估算氯离子的去除率。R2 和均方误差值用于确定人工神经网络的预测性能。从近期来看,活化香根草粉的商业用途值得通过使用含盐诱导离子的实际废水进行深入研究来进一步调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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