{"title":"Solid waste utilization: a comprehensive review of strategic metal extraction technologies from coal fly ash","authors":"Zhenghong Xie, Wentao Zhou","doi":"10.1515/revce-2026-0032","DOIUrl":"https://doi.org/10.1515/revce-2026-0032","url":null,"abstract":"Coal fly ash, an industrial solid waste from coal-fired power plants, contains abundant strategic metals such as lithium, gallium, and rare earth elements. Efficient recovery of these metals is critical for resource security, circular economy advancement, and green industrial transformation. This review systematically evaluates technical approaches developed over the past decade for extracting strategic metals from fly ash. Key physicochemical properties influencing extraction are analyzed, and pretreatment methods including mechanochemical and calcination activation are assessed in terms of principles, progress, and limitations. Conventional leaching techniques (acid, alkali, and bioleaching) are compared with emerging methods (subcritical water and ionic liquids) regarding efficiency, selectivity, and environmental compatibility. Despite notable improvements in metal recovery and process optimization, existing technologies still confront persistent challenges: high energy consumption, poor selectivity, secondary pollution. Future research should prioritize deeper mechanistic understanding of metal occurrence and reaction pathways, design of highly selective coordination-based leaching systems, development of low-energy coupled activation–leaching processes, and comprehensive technical–economic–environmental assessments. These advances will drive strategic metal extraction from fly ash toward precision, low-carbon footprint, and industrial viability.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"168 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148428888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Frontmatter","authors":"","doi":"10.1515/revce-2026-frontmatter5","DOIUrl":"https://doi.org/10.1515/revce-2026-frontmatter5","url":null,"abstract":"","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"38 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148379740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jack M. I’Anson, Mark J.H. Simmons, Estefania Lopez-Quiroga, E. Hugh Stitt, Robert W. Gallen
{"title":"A review of the use of machine learning to predict the properties of porous media","authors":"Jack M. I’Anson, Mark J.H. Simmons, Estefania Lopez-Quiroga, E. Hugh Stitt, Robert W. Gallen","doi":"10.1515/revce-2025-0056","DOIUrl":"https://doi.org/10.1515/revce-2025-0056","url":null,"abstract":"Understanding the properties of porous media is important in a wide range of applications. However, they are often difficult to determine using experimental techniques or fluid simulations. In light of this, methods for predicting properties using machine learning have become popular. A wide range of machine learning techniques have been commonly used for porous media property prediction including the convolutional neural network (CNN) and the graph neural network (GNN). Many early studies represent porous media with 2D images, however, this is often an over-simplification that does not translate well to the properties of 3D porous media. Building 3D models, such as the 3D CNN can lead to more accurate results, but scalability issues are introduced for porous media at the representative elementary volume (REV) scale. In this review, the current state of the art in deep learning for predicting porous media properties, such as permeability of thermal conductivity, is accessed, focusing on both the accuracy and scalability of the models, when considering porous structures of a representative scale. Finally, future areas of research are suggested to achieve more accurate, robust and scalable models, such as couplings of GNNs and CNNs to produce models that exhibit the benefits of both techniques.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"31 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148299662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A review of recent advances in solvent-based technologies for postcombustion CO 2 capture","authors":"Somayeh Mirzaei, Chin-Yu Hsu, Ruei-Hao Shie, Akshansha Chauhan","doi":"10.1515/revce-2025-0082","DOIUrl":"https://doi.org/10.1515/revce-2025-0082","url":null,"abstract":"As a result of recent advances, solvent-based postcombustion CO <jats:sub>2</jats:sub> capture (PCC) systems have shown markedly improved absorption capacity, regeneration efficiency, and solvent stability compared with conventional monoethanolamine systems. This review provides a comparative assessment of seven major solvent classes, namely, amine blends and promoters, amino acid-based solvents, phase-change solvents, water-lean and nonaqueous systems, ionic liquids (ILs), deep eutectic solvents (DESs), and nanofluids. Among these solvent classes, amine blends remain the most practical short-term solution, achieving 33–60 % reductions in regeneration energy with proven scalability. Phase-change and biphasic solvents deliver the lowest regeneration energies (0.74–1.3 GJ t <jats:sup>−1</jats:sup> CO <jats:sub>2</jats:sub> ) among solvent classes, whereas water-lean systems balance energy savings with corrosion resistance and reduced water use. DESs and ILs offer long-term potential through molecular tunability and environmental compatibility. However, their viscosity and recyclability remain key challenges. Nanofluids expand the research frontier by coupling chemical reactivity with enhanced mass transfer. Progress in solvent-based PCC depends on integrating molecular design, process optimization, and pilot-scale validation to achieve low-energy, stable, and scalable CO <jats:sub>2</jats:sub> capture technologies.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"19 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147739214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Frontmatter","authors":"","doi":"10.1515/revce-2026-frontmatter3","DOIUrl":"https://doi.org/10.1515/revce-2026-frontmatter3","url":null,"abstract":"","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"21 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147655941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seyed Taha Hosseini, Reza Azin, Shahriar Osfouri, Erfan Mohammadian
{"title":"A comprehensive review on bentonite and its applications in petroleum industry","authors":"Seyed Taha Hosseini, Reza Azin, Shahriar Osfouri, Erfan Mohammadian","doi":"10.1515/revce-2025-0046","DOIUrl":"https://doi.org/10.1515/revce-2025-0046","url":null,"abstract":"Bentonite, a smectite clay mineral, is essential in petroleum operations for its swelling capacity, thixotropy, and cation exchange properties. However, its effectiveness in high-salinity and high-temperature environments remains a significant challenge. This review synthesizes advanced engineering strategies to enhance bentonite’s performance for modern petroleum applications. It examines activation methods, including acid, thermal, alkaline, and nanomaterial treatments, and their effects on colloidal stability and rheological properties. The review highlights bentonite’s role in enhanced oil recovery, showing that polymer-clay nanocomposites improve thermal stability and conformance control. Data indicate that adding bentonite can extend polyacrylamide gel lifespan from 37 to 120 days at 100 °C and increase elastic modulus by 40 %. The review also evaluates Iranian bentonite reserves as a case study, analyzing their mineralogy and activation needs. By linking fundamental properties with targeted engineering, this review offers a strategic framework for developing advanced bentonite technologies to support more sustainable and efficient hydrocarbon recovery.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"5 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147649034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lyudmila Slobodkina, Roksana Muzyka, Marcin Sajdak, Szymon Sobek, Sebastian Werle
{"title":"Recent trends in textile waste recycling: an overview","authors":"Lyudmila Slobodkina, Roksana Muzyka, Marcin Sajdak, Szymon Sobek, Sebastian Werle","doi":"10.1515/revce-2025-0027","DOIUrl":"https://doi.org/10.1515/revce-2025-0027","url":null,"abstract":"The global textile industry is an important economic driver, but at the same time it generates serious environmental challenges. These challenges are twofold: the vast amounts of textile waste generated each year and the substantial climate impacts caused mainly during the production phase. According to the European Environment Agency, about 80 % of the total climate impact of textiles derives from production, 14 % from the use phase (washing, drying, ironing), 3 % from distribution and retail, and 3 % from end-of-life stage, which includes collection, sorting, recycling, incineration, and landfilling. By 2030, global apparel (clothing + footwear) consumption is projected to rise from around 70 million tons today to approximately 105 million tons. Despite this growth, less than half of textile items are collected for reuse or recycling after use, and only a very small fraction – under 1 % – are recycled into new garments. This gap is primarily due to technical barriers: the processing of mixed fibers, chemical finishing and additives, as well as the lack of scalable and cost-competitive processing systems. This review examines current work on textile waste processing, taking into account technological, regulatory, economic, and environmental factors. It also identifies innovations and strategies for developing a circular economy.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"84 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147471105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Eco-friendly production technologies for poly(vinyl acetate) wood adhesives: recent progress and challenges – a short review","authors":"Michał Frycholc, Marcin Libera, Marcin Sajdak","doi":"10.1515/revce-2025-0051","DOIUrl":"https://doi.org/10.1515/revce-2025-0051","url":null,"abstract":"Wood adhesives have come a long way from urea-formaldehyde (UF) resins to waterborne poly(vinyl acetate) (PVAc) latex polymerized by emulsion polymerization. Nevertheless, while modern adhesives are more environmentally friendly, they still contain low concentrations of substances considered to be toxic or carcinogenic. Increasing social awareness about the environmental friendliness and toxicity of chemical compounds has pressured producers of wood-based materials and furniture to develop new green technologies and eliminate potentially dangerous chemical compounds. The crucial parameter for wood adhesives is the durability class of water resistance according to the EN204:2016 standard. To achieve a higher class, i.e., D3 or D4, it is necessary to use a crosslinked polymer. Crosslinking is usually performed using N-(hydroxymethyl)acrylamide monomer (NMA), UF resins, or glutaraldehyde. NMA contains and emits formaldehyde, which is poisonous and carcinogenic, so the chemical industry is trying to replace this substance with greener, formaldehyde-free, and eco-friendly substitutes, such as silanes, bio vinyl and acrylate monomers, or 2,5-diformylfuran. In this short review, we focus on demonstrating updated green approaches to developing wood adhesives and methods to eliminate the presence of unwanted substances such as formaldehyde. We present the technologies for producing PVAc step by step and the stages that need to be further investigated or improved.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"24 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147319463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahdi Alibeigi, Mehdi Mehrpooya, Prodip K. Das, Tohid N. Borhani
{"title":"A critical review of modeling hydrogen production using water electrolyzer","authors":"Mahdi Alibeigi, Mehdi Mehrpooya, Prodip K. Das, Tohid N. Borhani","doi":"10.1515/revce-2025-0049","DOIUrl":"https://doi.org/10.1515/revce-2025-0049","url":null,"abstract":"The quest for effective hydrogen production through water electrolysis depends on the performance. Yet, making good models for performance improvement is naturally difficult because operation of an electrolyzer is both a multi-physics and multi-scale problem. Interaction of such complex phenomena across disparate spatial and temporal scales makes system design and optimization an extremely difficult task that indeed calls for advanced computational approaches. This review explores the application of recently developed computational methods to address such problems. Key methods examined include the lattice Boltzmann method (LBM), computational fluid dynamics (CFD), response surface methodology (RSM), and artificial intelligence (AI) methods. Water electrolyzer simulations are dominated by two-phase liquid–gas models; the LBM is particularly effective for microscale flows and interfacial phenomena where surface effects are important, while Eulerian volume of fluid approaches are the most effective for treating bubble behavior. Briefly, optimal surrogate models for integrated systems are provided by empirical correlations and experiment design techniques (such as RSM). AI and hybrid AI-CFD techniques are making modeling and optimization easier and faster. For instance, DeepONet has predicted current density, oxygen mole fraction, and cell temperature with a root-mean-squared error of less than 1 %. This review concludes that LBM is a valuable tool for microscale multiphase dynamics and that AI-augmented CFD has proven capable of supplementing, and in certain situations, even replace conventional CFD workflows for the design and optimization of electrolyzers.","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"244 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Frontmatter","authors":"","doi":"10.1515/revce-2026-frontmatter2","DOIUrl":"https://doi.org/10.1515/revce-2026-frontmatter2","url":null,"abstract":"","PeriodicalId":54485,"journal":{"name":"Reviews in Chemical Engineering","volume":"147 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146101792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}