Shadan Behrad, Jafari Arezou, Gharibshahi Reza
Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran.
Heliyon. 2024 Nov 22;10(24):e40450. doi: 10.1016/j.heliyon.2024.e40450. eCollection 2024 Dec 30.
A magnetic nano-composite coagulant has been designed, originally applied in a specific industrial waste-water treatment, and statistically investigated using Central Composite Design (CCD). The generated polynomial models were utilized to achieve a comprehensive understanding of the impact of each ingredient of PolyAluminum Chloride (PAC), PolyAcrylAmide (PAM), and Iron (III) oxide magnetic nano particles (MNP) regarding optimum limits and conditions. The concentration of each of those components has been considered as the main effective factors, which are found to be significantly correlated, affecting the Total Dissolved Solid (TDS) removal (%), the Total Suspended Solid (TSS) removal (%), and the Turbidity Reduction Rate (TRR) NTU/min. The reliable statistical model for each response underscored the pivotal role of MNP in shaping each response variable. The influence of MNP and PAC, emerged as crucial in enhancing TDS removal, by increasing the kinetic energy of charged ions and the chance of the successful displacement reaction, helping to dissolve with a high surface activity, and the adsorption of magnetic heavy ions. The correlated concentration of MNP also exhibited a significant impact on TSS elimination, and TRR, concurrently, which revealed the importance of controlling the bulk density of generated flocs, to prevent premature and immature settling to optimize pollution removal. The highest recorded results are 72.00 %, 77.01 %, and 23.82 NTU per minute for TDS and TSS removal and TRR, respectively. The experimental records, along with the statistical investigation remarked a promising potential of the achieved Magnetic Nano-composite Coagulant (MNC), and generated practical knowledge of its novel application for drilling waste-water management.
一种磁性纳米复合混凝剂已被设计出来,最初应用于特定的工业废水处理,并使用中心复合设计(CCD)进行了统计研究。所生成的多项式模型被用于全面了解聚合氯化铝(PAC)、聚丙烯酰胺(PAM)和氧化铁磁性纳米颗粒(MNP)的每种成分在最佳限值和条件方面的影响。这些成分各自的浓度被视为主要影响因素,发现它们之间存在显著相关性,影响总溶解固体(TDS)去除率(%)、总悬浮固体(TSS)去除率(%)和浊度降低率(TRR)(NTU/分钟)。每个响应的可靠统计模型强调了MNP在塑造每个响应变量方面的关键作用。MNP和PAC的影响在提高TDS去除率方面至关重要,通过增加带电离子的动能和成功置换反应的机会,有助于以高表面活性溶解以及吸附磁性重金属离子。MNP的相关浓度同时对TSS去除和TRR也有显著影响,这揭示了控制生成絮凝物堆积密度的重要性,以防止过早和不成熟的沉淀,从而优化污染物去除。记录的最高结果分别为TDS去除率72.00%、TSS去除率77.01%和TRR为每分钟23.82 NTU。实验记录以及统计研究表明,所制备的磁性纳米复合混凝剂(MNC)具有广阔的应用前景,并产生了其在钻井废水管理新应用方面的实践知识。