Cleaner Chemical Engineering最新文献

{"title":"Synergistic integration of PCM-filled coil fins and smart water depth control in solar stills: A comprehensive energy, exergy, and environmental analysis","authors":"Lailatul Nehar ,&nbsp;Tanvir Rahman ,&nbsp;Md Shahiduzzaman Shahed ,&nbsp;Md Yeamin Prodhan ,&nbsp;Md Sazan Rahman ,&nbsp;S.S. Tuly","doi":"10.1016/j.clce.2025.100189","DOIUrl":"10.1016/j.clce.2025.100189","url":null,"abstract":"<div><div>Freshwater scarcity remains a critical global challenge, necessitating sustainable desalination solutions. This study investigates the performance enhancement of a double-slope solar still (SS) through the integration of hollow copper coil fins (HCCFs), phase change material (PCM), and an Arduino-based water depth control system. Three configurations were tested: conventional (Case I), fin-modified (Case II), and PCM-fin with smart control (Case III). Experimental results demonstrated that Case III achieved the highest productivity, yielding 1.81 L/m²/day, a 166 % improvement over the conventional still (0.68 L/m²/day) and 14 % higher than Case II (1.59 L/m²/day). Thermal analysis revealed peak energy and exergy efficiencies of 38.9 % and 4.31 %, respectively, for Case III, significantly surpassing Cases I (23.1 %, 1.45 %) and II (28.3 %, 3.45 %). The intelligent water depth modulation (20–35 mm) optimized heat transfer, while PCM extended post-sunset distillation. Economic and environmental assessments showed a payback period of 295 days and 4.8 tons of CO₂ mitigation over the system’s lifetime, with potential carbon credits of $190. This work establishes a novel, scalable approach for sustainable solar desalination.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100189"},"PeriodicalIF":0.0,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced biofuels research: A Scopus database-driven bibliometric evaluation and future directions forecast via machine learning and deep learning","authors":"Md. Saiful Islam ,&nbsp;Mridha Md. Nafis Fuad ,&nbsp;Sadit Bihongo Malitha ,&nbsp;Md. Zahangir Alam","doi":"10.1016/j.clce.2025.100188","DOIUrl":"10.1016/j.clce.2025.100188","url":null,"abstract":"<div><div>Renewable energy is a research hotspot in the present day to promote sustainability. Biofuel, an alternative to conventional fossil fuels, can contribute to environmental sustainability through being a renewable energy source and having a zero carbon footprint. However, traditional biofuels are generated from edible biomass, which raises questions about the use of traditional biofuels in the long run due to global food scarcity. Advanced biofuels are now being developed from non-edible biomass and waste sources, which are expected to be a colossal renewable energy source. This study conducted a complete bibliometric analysis to get an overview of research progress on advanced biofuels. A bibliographic dataset has been collected from the Scopus database. The dataset has been investigated based on articles, authors, journals, institutions, and countries to get a complete overview of current research trends on advanced biofuels. Burst keywords have also been analysed to identify the research hotspots. In addition to bibliometric analysis, machine learning and deep learning algorithms have been used to perform natural language processing (NLP), execute topic modelling, and carry out the research evolution forecast. This study will uncover the current research trend on advanced biofuels, identify the research gaps, and predict future research direction. The significance of the identified research gaps lies in their potential to guide future researchers towards areas that need further exploration, thereby contributing to advancing knowledge in this field.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100188"},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable SHAP-based machine learning-assisted design for selecting ultrafiltration membranes in protein-laden phosphate wastewater","authors":"Lukka Thuyavan Yogarathinam ,&nbsp;Sani I. Abba ,&nbsp;Jamilu Usman ,&nbsp;Muthumareeswaran Ramamoorthy ,&nbsp;Isam H. Aljundi","doi":"10.1016/j.clce.2025.100187","DOIUrl":"10.1016/j.clce.2025.100187","url":null,"abstract":"<div><div>Industrial wastewater contaminated with proteins and phosphates poses a significant challenge for producing clean water. This study innovatively employed regression-based machine learning (ML) algorithms to predict the separation performance of proteins with varying molecular weights from synthetic phosphate-laden wastewater using commercially available membranes with different pore sizes. The chosen ML tools are bi-layered neural network (BNN), linear regression (LR), least squares support vector machine (LSSVM), and Gaussian process regression (GPR). Correlation was employed to select the most pertinent variables for constructing an effective model combination while safeguarding against data leakage within the frugal dataset. Among the ML tools, the BNN and GPR algorithms demonstrated effective predictive capabilities for protein rejection. The collaborative integration of all input variable combinations resulted in superior predictive accuracy (R²=0.99) for protein rejection, showcasing minimal error rates for both the BNN and GPR algorithms. Interpretable SHapley Additive exPlanations (SHAP) analysis indicated that the molecular weight cutoff (MWCO), protein molecular weight (PMw), and isoelectric point (IEP) were the most influential factors affecting protein separation performance, with mean SHAP values of approximately 25, 12, and 15, respectively. The ML tools revealed that the input variables of MWCO, PMw, and IEP exerted a more substantial impact compared to hydro-dynamic variables. This study provides insights into advancing the development of ML tools tailored to sparse datasets, particularly for accurately predicting protein separation from phosphate-laden wastewater.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100187"},"PeriodicalIF":0.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phyto-mediated synthesis of polymetallic nanoparticles (Cu/Ag/Ru/Gd/Te) using abutilon indicum filtrate: Antimicrobial, antioxidant, antidiabetic and photocatalytic potentials","authors":"R Rathika,&nbsp;S Srinivasan,&nbsp;M Sindhu Devi","doi":"10.1016/j.clce.2025.100185","DOIUrl":"10.1016/j.clce.2025.100185","url":null,"abstract":"<div><div>This research delves into the creation of polymetallic nanoparticles composed of Cu/Ag/Ru/Gd/Te (PNS), utilizing the seed filtrate from the medicinal plant <em>Abutilon indicum</em>. A variety of characterization techniques have demonstrated a robust surface plasmon resonance in the range of 200 to 400 nm. Furthermore, the study examined the morphology, shape, composition, oxidation states, particle size, and thermal properties of the nanoparticles through SEM, EDX, XPS, AFM, and DTA/TG methods. The crystalline sizes were found to be 18.3 nm for Cu, 17.2 nm for Ag, 17.9 nm for Ru, 18.1 nm for Gd, and 17.9 nm for Te. The study also explored antibacterial and photocatalytic properties, revealing significant in vitro antidiabetic activity, with IC₅₀ values of 326 µg/ml for the α-amylase inhibition assay and 303 µg/ml for α-glucosidase inhibition. Additionally, the antioxidant activity of PNS was measured, yielding an IC₅₀ value of 127 µg/ml and an R² value of 0.9172.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100185"},"PeriodicalIF":0.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of methane emissions reduction methods in the oil and natural gas operations using a decision support system under quartic fuzzy DEAMEIM-MARCOS model","authors":"Abdolvahhab Fetanat ,&nbsp;Mohsen Tayebi ,&nbsp;Elham Gholampour","doi":"10.1016/j.clce.2025.100186","DOIUrl":"10.1016/j.clce.2025.100186","url":null,"abstract":"<div><div>Methane is an important greenhouse gas that has been linked to climate change impacts and the industry of oil and natural gas (O&amp;G) energy is a major source of methane emissions. These emissions arise from leaks and regular venting that occurs throughout O&amp;G operations. Mitigating these emissions from the operations of the studied industry has advantages for air quality and health. There are several policy options that are considered as solutions available to mitigate the emissions of methane from O&amp;G operations. Choosing the appropriate policy option is a complex multi-criteria decision-making (MCDM) problem that needs to use an intelligent and robust decision support system (DSS) to employ a smart and resilient model to decrease uncertainty in the decision-making process. The proposed DSS of this work incorporates the Delphi method and Method based on the Removal Effects of Criteria (MEREC) integration method (DEAMEIM) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) model under the quartic fuzzy set (QFS). Moreover, a hybrid criteria system, which involves 19 criteria has been used to evaluate policy options for methane emissions reduction. The criteria are selected according to the integration of 1) sustainability pillars and 2) health, safety, and environmental (HSE) aspects. The results of evaluations exhibit that the Regulation of methane leak detection and repair (LDAR) programs, is the most suitable scenario for methane emissions reduction from the operations. Computational analysis confirms the practicality and applicability of the DSS in determining the best possible scenario.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100186"},"PeriodicalIF":0.0,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144239768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Cr(VI) removal by nanoscale zerovalent iron through biogenic sulfidation:Comparison against corresponding chemical sulfidation","authors":"Yanni Xi ,&nbsp;Zheng Peng ,&nbsp;Zhuang Zhang ,&nbsp;Zhu Su ,&nbsp;Yicai Huang ,&nbsp;Xin Li ,&nbsp;Xingzhong Yuan","doi":"10.1016/j.clce.2025.100184","DOIUrl":"10.1016/j.clce.2025.100184","url":null,"abstract":"<div><div>This study examines the effects of biogenic sulfidation and chemical sulfidation on the reactivity of nanoscale zerovalent iron (nZVI) for the removal of carcinogenic hexavalent chromium (Cr(VI)). Biogenic sulfidated nanoscale zerovalent iron (BS-nZVI) was synthesised by culturing nZVI with sulphate-reducing bacteria (SRB), while chemically synthesised sulfidated nanoscale zerovalent iron (CS-nZVI) was produced using a Na₂S solution. Characterisation results indicated that both BS-nZVI and CS-nZVI were coated with FeS_x, with BS-nZVI additionally covered by extracellular polymeric substances (EPS) secreted by the SRB. Both BS-nZVI and CS-nZVI exhibited significantly higher Cr(VI) removal efficiencies compared to nZVI, with values of 18.91 mg/g and 18.80 mg/g, respectively, versus 0.095 mg/g for nZVI. These improvements are attributed to the enhanced electron transfer properties of FeS_x. In cyclic “sulfidation-Cr(VI) removal” experiments, biogenic sulfidation was found to be more effective than chemical sulfidation in enhancing and reactivating the Cr(VI) removal capacity of nZVI. The EPS associated with S-nZVI provided additional binding sites for co-precipitation of Cr(III)-Fe(III) during Cr(VI) removal, resulting in the formation of a loosely structured Cr(III)-Fe(III)-EPS co-precipitate. This co-precipitate mitigated the hindering caused by dense Cr(III)-Fe(III) passivation layers on electron transfer during Cr(VI) removal and cyclic sulfidation, in contrast to CS-nZVI. This study elucidates the synergistic effects of the coupled SRB-ZVI system for Cr(VI) remediation.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100184"},"PeriodicalIF":0.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of photocatalytic degradation of amoxicillin by ZnO-TiO2 heterojunction under UV-Visible irradiation","authors":"Samira Charafi ,&nbsp;Fatima Zahra Janani ,&nbsp;Alaâeddine Elhalil ,&nbsp;Mohamed Abdennouri ,&nbsp;Mhamed Sadiq ,&nbsp;Noureddine Barka","doi":"10.1016/j.clce.2025.100183","DOIUrl":"10.1016/j.clce.2025.100183","url":null,"abstract":"<div><div>This study aims to evaluate the efficiency of the ZnO/TiO₂ heterojunction in a photocatalytic process under UV-Visible irradiation for the degradation of amoxicillin (AMX), an antibiotic commonly detected as a pharmaceutical contaminant in water. The photocatalyst was synthesized by sol-gel method and characterized by various techniques such as XRD, FT-IR, SEM/EDX, MET and UV-vis DRS, in order to evaluate its physicochemical properties. Optimization of several experimental parameters, such as the initial concentration of AMX, the nature of the photocatalyst, the catalyst dose and the initial pH of the solution, was carried out to maximize photocatalytic performance. XRD revealed the presence of the wurtzite phase for ZnO, while TiO₂ showed the rutile and anatase phases, finely dispersed in the ZnO matrix. FT-IR analysis confirmed the presence of the characteristic ZnO and TiO₂ bands, and UV-vis DRS analysis also confirmed significant energy absorption in the UV-vis range. In addition, evaluation of photocatalytic efficiency under different experimental conditions showed that alkaline conditions were more conducive to degradation due to the significantly higher hydroxyl ion content. Under optimal experimental conditions (AMX concentration of 40 mg/L, pH of approx. 10, catalyst dose of 100 mg/L and Zn²⁺/Ti⁴⁺=4 molar ratio), the ZnO-TiO₂ heterojunction reached 94% after 210 minutes of exposure to UV-vis irradiation, guaranteeing an optimum balance between light penetration and photocatalytic activity. In addition, the photocatalyst demonstrated high regeneration capacity and photostability, maintaining high regeneration capacity after five cycles. These results underline the strong potential of the ZnO-TiO₂ heterojunction for concrete applications in the treatment of polluted water.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100183"},"PeriodicalIF":0.0,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calcium oxide nanoparticles from eggshell waste: A green nanotechnological strategy for microwave-assisted environmental clean up","authors":"Jannatun Zia ,&nbsp;Amit Kumar Shringi ,&nbsp;Ufana Riaz","doi":"10.1016/j.clce.2025.100182","DOIUrl":"10.1016/j.clce.2025.100182","url":null,"abstract":"<div><div>This study presents a sustainable and innovative strategy for waste reutilization and environmental remediation through the green synthesis of calcium oxide (CaO) nanoparticles (NPs) derived from waste eggshells, predominantly composed of calcium carbonate. The CaO NPs were synthesized via a straight forward calcination process and characterized using X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDX), Fourier-transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), thermogravimetric analysis (TGA), and UV–visible diffuse reflectance spectroscopy (UV–Vis DRS). XRD confirmed high crystallinity with an average crystallite size of 32 nm, while TEM revealed cubic nanoparticles in the range of 30–50 nm. TGA analysis demonstrated notable thermal stability up to 800 °C.The catalytic performance of the synthesized CaO NPs was evaluated via microwave-assisted degradation of Malachite Green (MG), a model organic pollutant. Under microwave irradiation, CaO NPs achieved 86 % degradation within 30 min, significantly outperforming raw eggshells (72 %). The degradation followed pseudo-first-order kinetics. Optimization studies revealed enhanced degradation efficiency (up to 93.40 %) at 900 W microwave powers and 94.59 % efficiency with a catalyst dose of 250 mg/L. However, increasing MG concentration from 20 to 50 mg/L resulted in a decline in degradation efficiency from 86 % to 60.2 %. Recyclability assessments showed 77 % degradation efficiency after four consecutive cycles, indicating the catalyst’s stability and reusability. Scavenger experiments identified the involvement of reactive species, including hydroxyl radicals (•OH), superoxide anions (•O₂⁻), and photo-generated holes (h⁺), in the degradation mechanism. Furthermore, LC-MS analysis proposed a plausible degradation pathway based on intermediate <em>m/z</em> values. Compared to conventional thermal or chemical degradation methods, the microwave-assisted catalytic process using CaO NPs demonstrated superior efficiency, rapid reaction kinetics, and reduced energy consumption. This work highlights the potential of converting bio-waste into high-value nanomaterials for scalable, eco-friendly, and cost-effective wastewater treatment applications.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100182"},"PeriodicalIF":0.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of industrial carbon capture process using gradient, weight-based, and lexicographic approach","authors":"Swaprabha P. Patel,&nbsp;Ashish M. Gujarathi,&nbsp;Sara Al Khamisi","doi":"10.1016/j.clce.2025.100181","DOIUrl":"10.1016/j.clce.2025.100181","url":null,"abstract":"<div><div>Natural gas (NG) is a fossil energy source and a crucial petrochemical feedstock. Raw NG contains impurities that must be removed before it can be commercially used. Carbon capture (CC) is considered a crucial step in the NG treatment process. The removal of acid gases like hydrogen sulphide (H₂S) and carbon dioxide (CO₂) from NG is of great importance. Optimization of the industrial CC process is carried out using environment, process, and energy-based objectives, five decision variables, and two constraints. Six different optimization algorithms are utilized for each of the objective functions, and their detailed convergence-specific comparison is carried out using the corresponding objective and the decision variable's values. In a gradient optimization study, the minimum energy value of 13.35 MMBtu/h is achieved by the Interior Point-Central difference algorithm. In a weight-based study, as weight increases from 0 to 0.4, the CO₂ in sweet NG decreases and remains nearly constant at an average of 8038 ppm, and the hydrocarbon recovery first decreases and remains constant at the value of 92.4 %. In a lexicographic optimization study, the total energy optimum value increases with an increase in compromise percentage, with a maximum of 8.1 % with 10 % compromise, whereas the CO₂ content in sweet NG objective values decreases by up to 7 %. This optimization study gives insight into the complex natural gas CC process using traditional optimization algorithms.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100181"},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization and comparison of multi-beds PSA technology for separation of carbon dioxide mixtures by processes simulations","authors":"Qiwei Yang ,&nbsp;Jingjing Chai ,&nbsp;Li Yang,&nbsp;Zhen Chen,&nbsp;Yuanhang Qin,&nbsp;Tielin Wang,&nbsp;Wei Sun,&nbsp;Cunwen Wang","doi":"10.1016/j.clce.2025.100180","DOIUrl":"10.1016/j.clce.2025.100180","url":null,"abstract":"<div><div>Pressure Swing Adsorption (PSA) demonstrates significant potential for post-combustion CO₂ capture from coal-fired flue gas (15 % CO₂/85 % N₂). This study systematically investigates two-bed, four-bed, and six-bed structural configurations of pressure swing adsorption (PSA) systems to elucidate the purity-recovery trade-off relationship. The six-bed process, incorporating triple pressure equalization steps, achieves the breakthrough performance of 92.7 % CO₂ purity and 92.4 % recovery under industrially feasible conditions (10 bar adsorption pressure, 40 s cycle time), surpassing conventional two-bed systems where neither metric exceeds 90 %. While the four-bed configuration attains ultra-high purity (∼99 % CO₂), its scalability in recovery remains constrained. Rigorous optimization of operational parameters (adsorption pressure, cycle time, bed aspect ratio) balances energy efficiency and separation performance. Results highlight multi-bed PSA, particularly the six-bed system, as a scalable solution for industrial CO₂ capture, effectively bridging the gap between high-purity benchmarks and practical recovery targets.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100180"},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}