Journal of the Taiwan Institute of Chemical Engineers最新文献

{"title":"Green synthesis of carbon dots encapsulated MoO3:La3+ for enhanced photocatalytic degradation, dactyloscopy and real-time FP detection using YOLOv8x","authors":"M. Gagana ,&nbsp;B. R. Radha Krushna ,&nbsp;S.C. Sharma ,&nbsp;S Sharmila ,&nbsp;R. Meenakshi ,&nbsp;A. Devikala ,&nbsp;Samir Sahu ,&nbsp;K. Manjunatha ,&nbsp;Sheng Yun Wu ,&nbsp;R. Arunakumar ,&nbsp;H. Nagabhushana","doi":"10.1016/j.jtice.2025.106032","DOIUrl":"10.1016/j.jtice.2025.106032","url":null,"abstract":"<div><h3>Background</h3><div>Industrial dye pollution poses severe environmental threats, necessitating efficient and sustainable removal strategies. Additionally, forensic and biometric applications require high-resolution fingerprints (FPs) detection for accurate identification. This study develops carbon dots (CDs) integrated MoO₃:1 %La³⁺ nanocomposites (NCs) for photocatalytic dye degradation and forensic applications, offering a multifunctional approach to environmental remediation and FP visualization.</div></div><div><h3>Methods</h3><div>The NCs were synthesized using a green approach with neem leaf extracts and characterized via XRD, FTIR, SEM, TEM, XPS, and UV-Vis spectroscopy. Their photocatalytic efficiency was assessed through methyl orange (MO) degradation, while seed germination tests using <em>Pisum sativum</em> evaluated environmental safety. Additionally, the <em>YOLOv8x</em> deep-learning model was trained for enhanced latent fingerprint (LFP) detection and analysis.</div></div><div><h3>Significant Findings</h3><div>NCs exhibited 99.4 % MO degradation within 70 min, detecting MO at concentrations as low as 0.032 μM. Post-treatment analysis confirmed complete degradation. Seed germination tests showed improved root (6.24 cm), shoot (7.83 cm), and germination energy (84 %), validating detoxification. NCs enhanced FP visualization, while <em>YOLOv8x</em> achieved over 90 % mean average precision (mAP) in minutiae detection, outperforming traditional methods. This work establishes CDs/MoO₃:1 %La³⁺ NCs as a multifunctional solution for environmental remediation, agriculture, and forensic applications.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106032"},"PeriodicalIF":5.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509187","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 novel concentration prediction technique of carbon monoxide (CO) based on beluga whale optimization-extreme gradient boosting (BWO-XGBoost)","authors":"Fan Zhang ,&nbsp;Zhengyang Zhu ,&nbsp;Jiefeng Liu ,&nbsp;Yiyi Zhang ,&nbsp;Min Xu ,&nbsp;Pengfei Jia","doi":"10.1016/j.jtice.2025.106045","DOIUrl":"10.1016/j.jtice.2025.106045","url":null,"abstract":"<div><h3>Background</h3><div>Carbon monoxide (CO), as a toxic gas, poses serious threats to human health and the ecosystem. Monitoring CO concentration is imperative. However, current algorithms used for CO concentration detection suffer from low accuracy due to limitations in data processing and model training. These algorithms fail to adequately consider the complexity and non-linear relationships within CO concentration data, necessitating the search for a more effective and precise approach.</div></div><div><h3>Methods</h3><div>In this study, we first introduce an MI-RF feature selection algorithm combining Mutual Information (MI) with Random Forest (RF) to extract key features. Subsequently, we introduce BWO-XGBoost, which combines Beluga Whale Optimization (BWO) and Extreme Gradient Boosting (XGBoost) to achieve higher prediction accuracy.</div></div><div><h3>Significant Findings</h3><div>We compare it with traditional models such as K-Nearest Neighbors (KNN), Gradient Boosting Decision Tree (GBDT), Support Vector Regression (SVR), and XGBoost. Experimental results demonstrate that the proposed BWO-XGBoost exhibits superior performance in terms of fitting and prediction accuracy.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"171 ","pages":"Article 106045"},"PeriodicalIF":5.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512076","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":"Leveraging ChemBERTa and machine learning for accurate toxicity prediction of ionic liquids","authors":"Safa Sadaghiyanfam ,&nbsp;Hiqmet Kamberaj ,&nbsp;Yalcin Isler","doi":"10.1016/j.jtice.2025.106030","DOIUrl":"10.1016/j.jtice.2025.106030","url":null,"abstract":"<div><h3>Background:</h3><div>Accurately predicting the toxicity of ionic liquids is essential for promoting sustainable chemical applications while mitigating environmental and health risks. The increasing complexity and volume of data inherent in toxicology have stimulated interest in machine learning models because they are attractive approaches that can identify patterns among predictors and responses that may not be obvious through classical statistical methodologies.</div></div><div><h3>Methods:</h3><div>This study introduces a hybrid framework that combines ChemBERTa-based chemical structure embeddings with Convolutional Neural Networks (CNNs), XGBoost, and Support Vector Regression (SVR). ChemBERTa embeddings, derived from SMILES strings, were enriched with molecular descriptors and fingerprints, with dimensionality reduced using Principal Component Analysis (PCA). To further enhance performance, model optimization was conducted through Optuna, ensuring the best configuration of hyperparameters.</div></div><div><h3>Significant Findings:</h3><div>CNNs demonstrated superior performance, achieving an R-squared value of 0.865, a Root Mean Squared Error (RMSE) of 0.390, and a Pearson correlation coefficient of 0.937. XGBoost followed closely with an R-squared value of 0.824, an RMSE of 0.462, and a Pearson correlation of 0.923. SVR also performed competitively, with an R-squared value of 0.797 and an RMSE of 0.496. Notably, the inclusion of ChemBERTa embeddings significantly enhanced model accuracy, as evidenced by the results of ablation studies. This study highlights the potential of hybrid frameworks that combine deep learning with classical machine learning approaches to predict ionic liquid (IL) toxicity. These findings offer valuable insights for safer chemical design, promoting sustainable innovation while supporting regulatory decision-making.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"171 ","pages":"Article 106030"},"PeriodicalIF":5.5,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488660","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":"Synergistically improved electrochemical performance by the assembly of nanosized iron manganese oxide catalyst for the detection of Seleno-L-methionine amino acid","authors":"Yamunadevi Kandeepan ,&nbsp;Tse-Wei Chen ,&nbsp;Sivaprakash Sengodan ,&nbsp;Jaysan Yu ,&nbsp;Shen-Ming Chen","doi":"10.1016/j.jtice.2025.106012","DOIUrl":"10.1016/j.jtice.2025.106012","url":null,"abstract":"<div><h3>Background</h3><div>Seleno-<span>L</span>-methionine (L-Se-Met) is an organic selenium compound that serves as an essential trace element known for its potent antioxidant properties. It provides selenium in dietary supplements to support thyroid health, immune function, and antioxidant defense. However, an excessive consumption of <span>L</span>-Se-Met can lead to selenium toxicity and detrimental side effects on human health. Therefore, the development of a fast and sensitive method is needed for the monitoring of <span>L</span>- Se-Met.</div></div><div><h3>Methods</h3><div>Herein, a simple and cost-effective electrode based on iron manganese oxide (Fe₂O₃/Mn₃O₄) catalyst, which could be actuated by a electrochemical sensing platform has been designed. Fe₂O₃/Mn₃O₄ were successfully prepared by the hydrothermal technique. The proposed Fe₂O₃/Mn₃O₄ catalyst was used to modify the glassy carbon electrode (GCE), and the modified electrode was deployed to sense <span>L</span>- Se-Met. The electrochemical characteristics of the fabricated sensor were then studied through cyclic voltammetry (CV) and differential pulse voltammetry (DPV).</div></div><div><h3>Significant findings</h3><div>The sensor resulted in a oxidation peak current response that covered a broad linear range from 3.92–992.29 ng/L and had a low detection limit (LOD) of 4.59 ng/L, a limit of quantification (LOQ) of 13.92 ng/L and a sensitivity of 0.0031 µA/µM cm² with outstanding performance. The developed sensor determined satisfactory recovery results for detecting <span>L</span>-Se-Met in samples of broccoli, green bean, green gram, mushroom, onion, red gram and human blood serum using the DPV method.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106012"},"PeriodicalIF":5.5,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479674","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":"Potassium titanate-based two-dimensional electrode material for high-current density supercapacitors","authors":"Sankaranarayanan Karthikeyan ,&nbsp;Saravanakumar Balakrishnan ,&nbsp;Ting-Yu Liu ,&nbsp;Anandhakumar Sukeri","doi":"10.1016/j.jtice.2025.106044","DOIUrl":"10.1016/j.jtice.2025.106044","url":null,"abstract":"<div><h3>Background</h3><div>Supercapacitor-based energy storage devices are gaining popularity because of exceptional performance such as fast charging, long lifespan, stability, and enormous energy and power densities. Developing cost-effective energy storage systems is highly justified in light of the anticipated energy demand. For these reasons, cost-effective potassium-based electrode material is explored in this study for high-performance supercapacitor applications.</div></div><div><h3>Methods</h3><div>This study proposes a simple hydrothermal method to create a novel, cost-effective, two-dimensional potassium titanate (K₂Ti₄O₉) nanosheets as an electrode material in supercapacitors (SCs). X-ray diffraction analysis (XRD), high-resolution scanning electron microscopy studies (HR-SEM), energy dispersive X-ray analysis spectrum (EDX), Raman spectroscopy, and high-resolution transmission electron microscopy studies (HR-TEM) analysis were used to characterize the as-synthesized material. Cyclic voltammetry and galvanostatic charge-discharge techniques were employed in the electrochemical experiments.</div></div><div><h3>Significant findings</h3><div>The synthesized K₂Ti₄O₉ nanosheet-based electrode materials exhibited a remarkable specific capacitance of 324 F/g at a current density of 2 A/g for up to 8500 cycles. It also shows ∼98% coulombic efficiency and ∼94% capacitance retention at 2 A/g. Moreover, we constructed an asymmetric device and demonstrated LED light using K₂Ti₄O₉ nanosheets, which display 54 Wh/kg and 485 W/kg energy and power densities, respectively.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106044"},"PeriodicalIF":5.5,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488717","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":"Exploring peroxidase mimetic activity of carbon nano-onions for colorimetric detection of H2O2 and glucose","authors":"Zahra Leili ,&nbsp;Saeid Asadpour ,&nbsp;Zeinab Saberi","doi":"10.1016/j.jtice.2025.106029","DOIUrl":"10.1016/j.jtice.2025.106029","url":null,"abstract":"<div><h3>Background</h3><div>Developing sensing methods with nanozymes as alternatives to natural enzymes has gained significant attention from researchers.</div></div><div><h3>Methods</h3><div>In this paper, we demonstrated for the first time that carbon nano-onions (CNOs) act as a peroxidase-like mimetic activity towards the oxidation 3,3′,5,5′ tetramethylbenzidine (TMB) in association with hydrogen peroxide (H₂O₂) to produce a blue oxide TMB (oxTMB) with maximum absorption at 652 nm. Consequently, CNOs were utilized as a nanozyme for the colorimetric detection of H₂O₂ and glucose. The blue color of ox-TMB faded in the presence of glucose. The influence of various factors including acidity, temperature, time, CNOs and TMB concentrations were studied and optimized.</div></div><div><h3>Significant findings</h3><div>CNOs showed a good peroxidase-like mimetic activity. In this method, the concentration of H₂O₂ was detected in two linear ranges from 3 to 36 (nM) and from 36 to 450 (nM) with a detection limit (LOD) of 1 nM. Additionally, the results indicated that the absorption decreased with glucose concentrations ranging from 2.97 to 190 μM, achieving a LOD of 0.99 μM. The colorimetric possibility of this method was investigated in real plasma samples with recoveries of 95–103 %. Ultimately, the visual functionality of this colorimetric sensor can significantly improve and simplify the on-site detection process.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106029"},"PeriodicalIF":5.5,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479669","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":"Antimicrobial effect based on activated persulfate using nano-magnetite nanozyme immobilized on the microbial cellulose hydrogel","authors":"Shabnam Ahmadi ,&nbsp;Mohammad Hadi Dehghani ,&nbsp;Abbas Rezaee","doi":"10.1016/j.jtice.2025.106039","DOIUrl":"10.1016/j.jtice.2025.106039","url":null,"abstract":"<div><h3>Background</h3><div>The present study is to investigate the antimicrobial activity of the activated persulfate (PS) using the nanocomposite fabricated by microbial cellulose hydrogel (MCH)/nanomagnetite (Fe₃O₄) nanoparticles (NPs) as a nanozyme.</div></div><div><h3>Methods</h3><div>The main reaction parameters including nanocomposite concentration, persulfate concentration and pH values were investigated. Various analysis, such as dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), field emission-scanning electron microscopy (FE-SEM), and vibrating-sample magnetometry (VSM), were utilized to analyze the nanocomposite and the nanozyme.</div></div><div><h3>Significant findings</h3><div>The obtained results show that the nanocomposite has antimicrobial activity under optimum conditions (temperature: 25 °C, nanozyme concentration: 2 mg/mL, and solution pH: 4.0). Moreover, increasing of the antimicrobial activity of the nanocomposite is observed using 0.25 g/l PS. The nanozyme exhibits the Michaelis constant (<em>K_m</em>) of 0.32 mM and the maximum reaction velocity (<em>V_max</em>) of 0.6 10⁻⁸ mM sec⁻¹ for 3,3′,5,5′-tetramethylbenzidine (TMB). The reason for the increasing of the antimicrobial activity is due to the generation of higher active oxygen species (ROS), which improve the elimination of the <em>E. coli</em>.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106039"},"PeriodicalIF":5.5,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453156","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":"Natal Plum leaf extract as sustainable corrosion inhibitor for Brass in HNO3 medium: Integrated experimental analysis and computational electronic/atomic-scale simulation","authors":"Abdallah El-Asri ,&nbsp;Moutia Mohamed Rguiti ,&nbsp;Aaziz Jmiai ,&nbsp;Yuanhua Lin ,&nbsp;Souad EL Issami","doi":"10.1016/j.jtice.2025.106038","DOIUrl":"10.1016/j.jtice.2025.106038","url":null,"abstract":"<div><div>Background Metal corrosion and its protection remain critical areas of research due to the economic and environmental implications of material degradation. Corrosion inhibitors play a vital role in mitigating corrosion and extending the lifespan of metals. In this study, Natal Plum leaves extract (NPLE) was utilized as a green inhibitor for brass corrosion in HNO₃ solution. The eco-friendly nature of NPLE makes it a promising candidate for sustainable corrosion protection.</div><div>Methods The composition of extract phytochemicals was analyzed using gas chromatography mass spectrometry (GCMS–). The inhibition effect of NPLE on the corrosion of brass (Cu_63%-Zn_37%) in HNO₃ solution was evaluated through a combination of experimental and theoretical methods. Gravimetric analysis, electrochemical impedance spectroscopy (EIS), and polarization tests were used to quantify the degree of inhibition and assess the electrochemical behavior. The surface morphology and chemical composition of treated brass were analyzed using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). Molecular adsorption mechanisms were explored using density functional theory (DFT) calculations, highlighting the interaction between extracted molecules and the brass surface.</div><div>Significant Findings The results demonstrated that NPLE achieved an inhibition efficiency of ∼98 % at 2.5 g/L after 72 h of exposure, as shown by EIS, which revealed a substantial increase in charge transfer resistance. Polarization tests indicated mixed inhibition effects with slight cathodic prevalence, reducing the corrosion current density from 145.612 μA/cm² (uninhibited) to 10.829 μA/cm² (inhibited). SEM and EDX analyses confirmed the formation of a stable protective film on the brass surface, with improved film stability attributed to the synergy between extracted molecules. DFT calculations revealed that NPLE molecules formed strong bonds with copper atoms, while interactions with zinc were primarily physical, highlighting the extract's efficiency in protecting brass from corrosion.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106038"},"PeriodicalIF":5.5,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453155","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":"Optimization and performance enhancement of parabolic trough collectors using hybrid nanofluids and ANN modeling","authors":"Santosh Kumar Singh ,&nbsp;Arun Kumar Tiwari ,&nbsp;Wassila Ajbar","doi":"10.1016/j.jtice.2025.105984","DOIUrl":"10.1016/j.jtice.2025.105984","url":null,"abstract":"<div><h3>Background</h3><div>Enhancing the performance of renewable energy systems is pivotal to overcoming global energy challenges, with parabolic trough collectors (PTC) emerging as a promising technology for harnessing solar energy. This study focuses on the numerical modeling with various nanofluids of the PTC. Many previously reported studies on hybrid nanofluids have not adequately considered the appropriate Reynolds, Prandtl numbers and temperature, raising concerns about the reliability. This study ensures proper Reynolds numbers and inlet temperature for the investigated heat transfer fluids.</div></div><div><h3>Methods</h3><div>The model is tested with mono (Al₂O₃, TiO₂) and hybrid (Al₂O₃+TiO₂) nanofluids, with thermal analysis mathematically modelled. ANN and ANNi modeling are applied in to optimize governing parameters for the collector with working fluids.</div></div><div><h3>Findings</h3><div>Turbulence boosts heat transfer coefficient (HTC), with the hybrid nanofluid exhibiting the highest increase (86.88 %). Energy efficiency peaks at lower temperatures and fluid Reynolds numbers, while exergy efficiency rises with increasing inlet temperature and Reynolds number. The optimal performance of ANN model is achieved with four neurons in the hidden layer and a 6-4-1 architecture, with highest value of R² (0.999513) and lowest RMSE (0.000186). GA optimization shows that lower inlet fluid temperature and Reynolds number enhance thermal efficiency.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105984"},"PeriodicalIF":5.5,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445515","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":"Selected pharmaceutical pollutant recovery from wastewater by an agro-byproduct Laurus nobilis-based adsorbent: Theoretical and experimental studies","authors":"Benabbou Asmae ,&nbsp;Boucherdoud Ahmed ,&nbsp;Bestani Benaouda ,&nbsp;Yaslam Saleh Gamal Saleh ,&nbsp;Nouredine Benderdouche ,&nbsp;Çoruh Ali ,&nbsp;Joanna Sreńscek-Nazzal ,&nbsp;Beata Michalkiewicz","doi":"10.1016/j.jtice.2025.106011","DOIUrl":"10.1016/j.jtice.2025.106011","url":null,"abstract":"<div><h3>Background</h3><div>Residues generated from essential-oils extraction are steadily increasing, causing a major disposal and environmental problem that must be properly handled and used for environmental remediation.</div></div><div><h3>Method</h3><div>In this study, powdered Laurus nobilis leaves were converted into an efficient adsorbent via simultaneous treatments using CaCl₂ 20% and 40% as an impregnant and pyrolysis in the muffle furnace at 600 °C as a heating step, resulting in CA-20 and CA-40 samples respectively, in order to remove pharmaceutical pollutant from aqueous media.</div></div><div><h3>Significant findings</h3><div>Characterization methods, such as FTIR analysis, pH_zpc, SEM microscopy, Raman, XRD, BET surface area, and available porosity, were explored for physicochemical characteristics of the as-prepared material prior to its use in removing Salicylic acid from simulated wastewater. Effects of conventional parameters were also evaluated through batch experiments (dose of 0.02¹, pH=2, stirring time of 90 min). Among adsorption isotherm models used and based on <em>R²</em> and error analysis values, Sips better describes experimental data from which an adsorption capacity of 45.42 mg/g is reached. The Pseudo-second order (PSO) kinetic model best fits the experimental data, indicating the adsorption process is chemically controlled. Thermodynamics confirms the spontaneous adsorption process (∆G⁰ ranging from -27.633 to -26.024 kJ/mol) and its endothermicity (<em>∆H⁰ =</em> -57.907(kJ/mol). Laurus nobilis leaves residue were successfully and easily converted into an efficient adsorbent and used for lowering concentration of salicylic acid from wastewater.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 106011"},"PeriodicalIF":5.5,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437560","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}