使用金属有机框架和功能化石墨烯从水溶液中吸附diazinon:比较BBD,ANN模型
Mahmood Yousefi1, Hesam Akbari1, Amir Adibzadeh2
1Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Chemosphere
|January 15, 2024
概括
金属有机框架 (MOF) 和氨基石墨碳结构 (ACS-RGO) 有效地去除杀虫剂diazinon. 先进的模型准确地预测了去除效率,为净水策略提供了洞察力.
科学领域:
- 环境化学环境化学
- 材料科学 材料科学 材料科学
- 吸附科学 吸附科学
背景情况:
- 农药污染,特别是迪亚津,对环境构成重大风险.
- 开发高效,具有成本效益的吸附剂对于水资源整治至关重要.
- 金属有机框架 (MOF) 和功能化碳材料显示出对污染物去除的承诺.
研究的目的:
- 为了合成和表征MOF-5和氨基化石墨碳质结构 (ACS-RGO) 用于去除二氧化.
- 使用响应表面方法 (RSM) 来优化吸附条件.
- 评估人工神经网络 (ANN) 和盒式设计 (BBD) 模型的预测能力,以测量其在去除diazinon时的效率.
主要方法:
- 用于合成MOF-5和ACS-RGO的化学沉.
- 使用XRD,FESEM和FTIR进行表征.
- 通过RSM优化pH,吸附剂剂量和接触时间.
- 应用和比较ANN和BBD模型进行预测.
- 异热和运动研究 (兰木尔,伪第一,伪二阶模型).
主要成果:
- 对ACS-RGO的最佳条件:pH 6.6,0.59 g/L剂量,52.15分钟接触时间,达到96.69%的去除.
- 对于MOF-5的最佳条件:pH6.6,0.906g/L剂量,接触时间36.96分钟,达到80.62%的清除.
- 吸附跟随兰格穆尔等温和和伪二阶动力学ACS-RGO,和伪第一阶MOF-5.
- ANN和BBD模型在预测二氧化去除方面显示出高准确度 (R2=0.98).
结论:
- ACS-RGO和MOF-5是有效的吸附剂,可以从水溶液中去除二氧化.
- RSM,ANN和BBD是优化和预测吸附过程的宝贵工具.
- 开发的材料和方法为水处理中的农药修复提供了一个有希望的方法.
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