Suppr超能文献

废生物炭对磷酸氯喹的间歇式和固定床吸附:使用人工神经网络进行功效验证

Waste Biochar in Batch and Fixed-Bed Adsorption of Chloroquine Phosphate: Efficacy Validation Using Artificial Neural Networks.

作者信息

Inyinbor Adejumoke Abosede, Bankole Deborah Temitope, Oluyori Abimbola Peter

机构信息

Department of Physical Sciences, Landmark University, P.M.B 1001, Omu Aran 251101, Nigeria.

Clean water and Sanitation Sustainable Development Goal, Landmark University, P.M.B 1001, Omu Aran 251101, Nigeria.

出版信息

ACS Omega. 2024 Mar 6;9(11):12564-12574. doi: 10.1021/acsomega.3c05008. eCollection 2024 Mar 19.

Abstract

The present study investigated the potency of biochar prepared from seedpods (BSSPs) in the uptake of chloroquine phosphate (CQP) from single-component batch and multicomponent fixed-bed adsorption systems. BSSPs presented a highly porous structure with a BET surface area of 1122.05 m/g, to which adsorption efficiency correlated. The Dubinin-Radushkevich isotherm energy was obtained as 129.09 kJ/mol, confirming the chemisorption nature of the BSSP-CQP adsorption system. The efficiency of the artificial neural network (ANN) was evaluated using the lowest mean square error (MSE = 7.27) and highest correlation coefficient ( = 0.9910). A good agreement between the experimental results and the ANN-predicted data indicated the efficiency of the model. The percentage removal of 95.78% obtained for the column adsorption studies indicated the effectiveness of BSSPs in a multicomponent system. The mechanism of the interaction proceeded via hydrogen bonding and electrostatic attraction. This was confirmed by the high desorption efficiency (69.11%) with a HCl eluent. The degree of reversibility was found to be 2.95, indicating the reusability potential of BSSPs. BSSPs are therefore considered multilayered adsorbents with potential applications in pharmaceutical wastewater treatment.

摘要

本研究考察了由豆荚制备的生物炭(BSSPs)在单组分间歇吸附系统和多组分固定床吸附系统中对磷酸氯喹(CQP)的吸附能力。BSSPs呈现出高度多孔的结构,BET表面积为1122.05 m²/g,吸附效率与之相关。Dubinin-Radushkevich等温线能量为129.09 kJ/mol,证实了BSSP-CQP吸附系统的化学吸附性质。使用最低均方误差(MSE = 7.27)和最高相关系数( = 0.9910)评估了人工神经网络(ANN)的效率。实验结果与ANN预测数据之间的良好一致性表明了该模型的有效性。柱吸附研究获得的95.78%的去除率表明BSSPs在多组分系统中的有效性。相互作用机制通过氢键和静电吸引进行。这通过HCl洗脱液的高解吸效率(69.11%)得到证实。发现可逆程度为2.95,表明BSSPs具有潜在的可重复使用性。因此,BSSPs被认为是多层吸附剂,在制药废水处理中具有潜在应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/08fd/10955583/23d208daf2f8/ao3c05008_0001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验