Mouhtady Omar, Obeid Emil, Abu-Samha Mahmoud, Younes Khaled, Murshid Nimer
College of Engineering and Technology, American University of the Middle East, Kuwait.
Gels. 2022 Jul 18;8(7):447. doi: 10.3390/gels8070447.
Industrial dye wastewater is one of the major water pollution problems. Adsorbent materials are promising strategies for the removal of water dye contaminants. Herein, we provide a statistical and artificial intelligence study to evaluate the adsorption efficiency of graphene oxide-based hydrogels in wastewater dye removal by applying Principal Component Analysis (PCA). This study aims to assess the adsorption quality of 35 different hydrogels. We adopted different approaches and showed the pros and cons of each one of them. PCA showed that alginate graphene oxide-based hydrogel (without polyvinyl alcohol) had better tolerance in a basic medium and provided higher adsorption capacity. Polyvinyl alcohol sulfonated graphene oxide-based hydrogels are suitable when higher adsorbent doses are required. In conclusion, PCA represents a robust way to delineate factors affecting hydrogel selection for pollutant removal from aqueous solutions.
工业染料废水是主要的水污染问题之一。吸附材料是去除水中染料污染物的有前景的策略。在此，我们通过应用主成分分析（PCA）提供一项统计和人工智能研究，以评估氧化石墨烯基水凝胶在废水染料去除中的吸附效率。本研究旨在评估35种不同水凝胶的吸附质量。我们采用了不同方法并展示了每种方法的优缺点。PCA表明，基于藻酸盐的氧化石墨烯水凝胶（不含聚乙烯醇）在碱性介质中具有更好的耐受性，并具有更高的吸附容量。当需要更高的吸附剂剂量时，基于聚乙烯醇的磺化氧化石墨烯水凝胶是合适的。总之，PCA是一种强有力的方法，可用于描绘影响从水溶液中去除污染物的水凝胶选择的因素。
