微纳米-γ-Al2O3烧结吸附剂对石脑油馏分中有机氯化物的去除效果

IF 1 Q4 ENGINEERING, CHEMICAL
Behnam Hosseingholilou, Samad Arjang, Majid Saidi
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引用次数: 0

摘要

摘要本研究考察了微纳米烧结γ-Al 2o3在30℃恒温条件下对污染原油(CO)石脑油馏分中有机氯化物(OC)的去除效果。通过BET、SEM-EDS和XRD对吸附剂进行了表征。当微吸附剂对初始污染物浓度为105和8.5 mg/L的石脑油馏分样品的OC组分进行去除时,最大去除率分别只有28%和56%。相比之下,使用纳米吸附剂的吸附率明显更高,对相同的两个样品分别超过45%和96%。平衡研究表明,Freundlich等温线模型对纳米吸附剂的吸附平衡数据有较好的匹配,而Langmuir模型对微吸附剂的吸附平衡数据有较好的描述。动力学数据分析表明,纳米吸附剂的吸附动力学服从准二级模型,而微吸附剂的吸附动力学服从颗粒内扩散机制。总的来说,这些发现表明,烧结γ-Al - 2o3纳米颗粒(NPs)比微颗粒(MPs)更有效地吸附去除原油石脑油馏出物中的有机氯化物(OCs)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Removal efficiency of organic chloride from naphtha fraction using micro and nano-γ-Al2O3 sintered adsorbents
Abstract This research examines the removal efficiency of organic chloride (OC) compounds from the naphtha fraction of polluted crude oil (CO) using sintered micro and nano γ-Al 2 O 3 at a consistent temperature of 30 °C. The adsorbents were characterized through BET, SEM-EDS, and XRD analyses. When utilizing micro-adsorbents to eliminate OC components from naphtha fraction samples containing initial contaminant concentrations of 105 and 8.5 mg/L, the maximum removal efficiency reached only 28 % and 56 %, respectively. In contrast, the use of nano-based adsorbents resulted in significantly higher adsorption percentages, exceeding 45 % and 96 % for the same two samples, respectively. Equilibrium investigations revealed that the Freundlich isotherm model yielded a superior match for the adsorption equilibrium data for the nano-adsorbents case, while the Langmuir model accurately characterized the data for the micro-adsorbents. Kinetic data analysis indicated that the adsorption kinetics for nano-adsorbents followed the pseudo-second-order model, while the micro-adsorbents obeyed the intra-particle diffusion mechanism. Overall, these findings suggest that sintered γ-Al 2 O 3 nanoparticles (NPs) are more effective than microparticles (MPs) for the adsorptive removal of organic chlorides (OCs) from crude oil’s naphtha distillate.
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来源期刊
Chemical Product and Process Modeling
Chemical Product and Process Modeling ENGINEERING, CHEMICAL-
CiteScore
2.10
自引率
11.10%
发文量
27
期刊介绍: Chemical Product and Process Modeling (CPPM) is a quarterly journal that publishes theoretical and applied research on product and process design modeling, simulation and optimization. Thanks to its international editorial board, the journal assembles the best papers from around the world on to cover the gap between product and process. The journal brings together chemical and process engineering researchers, practitioners, and software developers in a new forum for the international modeling and simulation community. Topics: equation oriented and modular simulation optimization technology for process and materials design, new modeling techniques shortcut modeling and design approaches performance of commercial and in-house simulation and optimization tools challenges faced in industrial product and process simulation and optimization computational fluid dynamics environmental process, food and pharmaceutical modeling topics drawn from the substantial areas of overlap between modeling and mathematics applied to chemical products and processes.
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