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Review Article
Basics of Differentiation of Zeolite Adsorbent with
H-permutite
Issue:
Volume 14, Issue 4, August 2026
Pages:
76-85
Received:
3 April 2026
Accepted:
15 April 2026
Published:
6 August 2026
DOI:
10.11648/j.ajche.20261404.11
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Abstract: Scientific research is being conducted worldwide to purify process and wastewater generated by industrial enterprises to meet established requirements for reuse as circulating process water, to develop low-waste or waste-free technologies, and to comprehensively recycle solid and liquid waste generated during enterprise activities. In this regard, special attention is paid to purifying domestic, process, and industrial wastewater contaminated with various additives to meet established requirements and to use them as circulating water in the process or for watering trees and plants on the enterprise's territory. The scientific significance of the research results is that the effective course of the synthesis process for obtaining H-permutite depends on the type and ratio of components, and the efficiency of wastewater treatment is closely related to the degree of contamination and the environmental pH. The article presents general information on theoretical and practical research regarding methods and technologies for treating industrial, technical, and wastewater, based on published articles and patent literature. Based on the issues raised and a critical analysis of the data obtained, the article defines the research goals and objectives. Currently, there are both natural and artificial zeolites. In this scientific work, an alternative to zeolite, H-permutite, was synthesized from natural raw materials. In this article, the study of the structural properties of the molecular compounds of the samples was conducted on a Nicolet iS50 (Thermo Fisher Scientific, USA) FT-IR spectrometer. Measurements were carried out in the spectral range of 4000–400 cm⁻¹, with a spectral resolution of no more than 0.1 cm⁻¹. The test sample was pressed onto the surface of the mounted assembly with a flat-tip probe.
Abstract: Scientific research is being conducted worldwide to purify process and wastewater generated by industrial enterprises to meet established requirements for reuse as circulating process water, to develop low-waste or waste-free technologies, and to comprehensively recycle solid and liquid waste generated during enterprise activities. In this regard, ...
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Review Article
Advancing Green Chemistry Through Emerging Technologies: A Systematic and Analytical Review of Sustainable Chemical Innovations
Phina Chinelo Ezeagwu
,
Adesegun Nurudeen Osijirin*
Issue:
Volume 14, Issue 4, August 2026
Pages:
86-100
Received:
23 March 2026
Accepted:
20 July 2026
Published:
10 August 2026
DOI:
10.11648/j.ajche.20261404.12
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Abstract: This study presents a systematic and analytical review of the role of emerging technologies in advancing green chemistry and supporting environmental sustainability. Guided by the PRISMA framework, relevant literature was identified from major academic databases, including Scopus, Web of Science, ScienceDirect, SpringerLink, and Google Scholar. A total of 20 studies were selected based on defined inclusion criteria. The review shows that emerging technologies such as artificial intelligence, the Internet of Things, automation, and advanced materials are increasingly integrated into green chemistry practices. These technologies contribute to improved process optimisation, real-time monitoring, and efficient resource utilisation. The findings indicate consistent improvements in environmental outcomes, including reductions in emissions, waste generation, and energy consumption. Evidence further suggests that integrated approaches combining green chemistry and emerging technologies produce better environmental performance than conventional methods. The study is grounded in Pollution Prevention Theory and Circular Economy Theory, which emphasise preventive strategies and efficient resource use. Despite these benefits, challenges related to cost, technical complexity, and infrastructure remain significant. The study highlights the need for supportive policy frameworks, investment in research, and capacity development to facilitate adoption. Overall, the integration of emerging technologies into green chemistry provides a viable pathway for advancing sustainable chemical innovation.
Abstract: This study presents a systematic and analytical review of the role of emerging technologies in advancing green chemistry and supporting environmental sustainability. Guided by the PRISMA framework, relevant literature was identified from major academic databases, including Scopus, Web of Science, ScienceDirect, SpringerLink, and Google Scholar. A t...
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Research Article
Machine Learning-Based Prediction and Optimization of Membrane Fouling in a Hybrid Biochar-Membrane System Treating Real Cafeteria Wastewater
Issue:
Volume 14, Issue 4, August 2026
Pages:
101-118
Received:
11 July 2026
Accepted:
23 July 2026
Published:
10 August 2026
DOI:
10.11648/j.ajche.20261404.13
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Abstract: The main characteristics of cafeteria effluents are the high organic load, varying concentration of fat/oil/grease content and nutrients, thus making them more difficult to treat than traditional domestic sewage. In this study, a combination of biochar-membrane technology was designed to treat real cafeteria wastewater from Akwa Ibom State University in Nigeria and ML for fouling prediction and process optimization. Biochar was prepared by pyrolysis and modified using iron oxide to increase the surface area (185.4 to 312.7 m2g-1) and functional groups, as indicated by FTIR spectroscopy (Fe-O at 580 cm-1), scanning electron microscopy and BET analysis (SEM). Adsorption of the main pollutant (COD) in batch mode followed Langmuir model (qm = 94.3 mg g-1, R2 = 0.986) and first-order kinetics (R2 = 0.978). Removal of COD, oil and grease, phosphate and turbidity were mainly dependent on biochar dosage and contact time. Two-stage Plackett-Burman/Box-Behnken design (45 runs) was used to produce the data set on which four ML models were developed; XGBoost and artificial neural networks exhibited the best results in terms of predictive performance (R2 = 0.91-0.96) for six response variables, surpassing random forest and support vector regression. Combination of the top-performing model with genetic algorithm, particle swarm and Bayesian optimization was used to find the optimal process parameters (14 g L-1 dose, 105 minutes, TMP 1.05 bar), leading to 89-90% COD removal with minimized membrane fouling, confirmed experimentally within ±5% from the predictions. Biochar pretreatment decreased the fouling resistance as compared to membrane-only process, while preliminary techno-economic evaluation suggested the process cost of about $0.258 m-3.
Abstract: The main characteristics of cafeteria effluents are the high organic load, varying concentration of fat/oil/grease content and nutrients, thus making them more difficult to treat than traditional domestic sewage. In this study, a combination of biochar-membrane technology was designed to treat real cafeteria wastewater from Akwa Ibom State Universi...
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