基于酸的地聚合物泡活性碳复合物用于甲基蓝色吸附:异温,动力学,热力学和机器学习研究
Muhammad Irfan Khan1,2, Suriati Sufian1,2, Farrukh Hassan3
1Department of Chemical Engineering, Universiti Teknologi PETRONAS Bandar Sri Iskandar Perak 32610 Malaysia.
RSC advances
|January 23, 2025
概括
一种新的活性碳和酸地质聚合物泡 (ACP) 复合物有效地去除甲蓝色染料. 优化的ACP吸附剂显示出高吸附能力和效率,由机器学习模型验证.
科学领域:
- 材料科学 材料科学 材料科学
- 环境化学环境化学
- 吸附科学 吸附科学
背景情况:
- 废水处理需要有效的吸附剂来去除染料.
- 地质聚合物复合材料为污染物修复提供了一个可持续的替代方案.
- 活性炭是一种成熟的吸附剂,但可以通过复合材料来增强.
研究的目的:
- 从活性炭和酸地质聚合物泡中合成和表征一种二元复合吸附剂 (ACP).
- 为了评估从水溶液中去除甲蓝 (MB) 染料的ACP吸附剂的效率.
- 通过机器学习模型研究吸附机制并优化参数.
主要方法:
- 通过将酸地质聚合物 (PAGP) 与从飞灰和甲中提取的活性炭 (AC) 结合起来,制备ACP吸附剂.
- 使用SEM,FTIR,XRD,SAP和TGA对非洲和非洲的描述.
- 批量吸附实验以确定最佳pH值,剂量,度,接触时间和温度;使用异热,动力和热力学模型分析数据;用于预测的机器学习模型 (ANN,SVR,RFR,DTR,GPR).
主要成果:
- 最佳的ACP成分是70%的PAGP和30%的AC,其表面积为47.36 m2/g,孔径为5.6 nm.
- 在0.2g的吸附剂剂量,25°C,pH10和240分钟的接触时间下,达到204.8mg/g的最大MB吸附能力.
- 吸附遵循兰格穆尔等温和和伪二次动力学,化学吸附被确定为主要机制;ANN模型显示高预测准确度 (R2=0.873吸附容量).
结论:
- 开发的ACP复合物是一种高效的吸附剂,用于去除甲蓝.
- 该研究阐明了吸附机制,并为高效的染料去除提供了最佳条件.
- 机器学习模型,特别是ANN,准确地预测吸附性能,为流程优化提供了有价值的工具.
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