Pub Date : 2025-01-31DOI: 10.1016/j.jtice.2025.105996
Hamed Azimi , Ebrahim Ghorbani Kalhor , Seyed Reza Nabavi , Mohammad Behbahani , Mohammad Taghi Vardini
Background
Accurately predicting the specific capacity of supercapacitors (SCs) is essential for improving their energy efficiency and performance. This requires robust methods to model the complex, nonlinear relationships among variables.
Methods
In this study, the dataset was divided into three optimal clusters using k-means, based on supercapacitor capacity, each displaying distinct features. Additionally, the unclustered dataset was also analyzed. The training of Multi-Layer Perceptron (MLP) neural networks was examined using six metaheuristic algorithms. Neural network hyperparameters were optimized via grid search, and metaheuristic algorithms via random search. Performance, convergence, and adaptability were evaluated for clustered and unclustered datasets, focusing on accuracy, speed, and generalization.
Significant findings
The cluster-based MLP models demonstrated exceptional predictive accuracy, outperforming unclustered models. Notably, the MLP integrated with Invasive Weed Optimization (MLP-IWO) in cluster 2, with a population size (Np) of 40, achieved the highest coefficient of determination (R²=0.9998), representing a 105.53 % improvement compared to the best unclustered model (R² = 0.4864). Similarly, the MLP integrated with the Firefly Algorithm (MLP-FA) in clusters 1 and 3 (Np = 30) achieved R² values of 0.9983 and 0.9927, respectively. These findings highlight the effectiveness of integrating clustering with metaheuristic optimization for enhancing prediction accuracy in SCs capacity modeling.
{"title":"Data-based modeling for prediction of supercapacitor capacity: Integrated machine learning and metaheuristic algorithms","authors":"Hamed Azimi , Ebrahim Ghorbani Kalhor , Seyed Reza Nabavi , Mohammad Behbahani , Mohammad Taghi Vardini","doi":"10.1016/j.jtice.2025.105996","DOIUrl":"10.1016/j.jtice.2025.105996","url":null,"abstract":"<div><h3>Background</h3><div>Accurately predicting the specific capacity of supercapacitors (SCs) is essential for improving their energy efficiency and performance. This requires robust methods to model the complex, nonlinear relationships among variables.</div></div><div><h3>Methods</h3><div>In this study, the dataset was divided into three optimal clusters using k-means, based on supercapacitor capacity, each displaying distinct features. Additionally, the unclustered dataset was also analyzed. The training of Multi-Layer Perceptron (MLP) neural networks was examined using six metaheuristic algorithms. Neural network hyperparameters were optimized via grid search, and metaheuristic algorithms via random search. Performance, convergence, and adaptability were evaluated for clustered and unclustered datasets, focusing on accuracy, speed, and generalization.</div></div><div><h3>Significant findings</h3><div>The cluster-based MLP models demonstrated exceptional predictive accuracy, outperforming unclustered models. Notably, the MLP integrated with Invasive Weed Optimization (MLP-IWO) in cluster 2, with a population size (Np) of 40, achieved the highest coefficient of determination (R²=0.9998), representing a 105.53 % improvement compared to the best unclustered model (R² = 0.4864). Similarly, the MLP integrated with the Firefly Algorithm (MLP-FA) in clusters 1 and 3 (Np = 30) achieved R² values of 0.9983 and 0.9927, respectively. These findings highlight the effectiveness of integrating clustering with metaheuristic optimization for enhancing prediction accuracy in SCs capacity modeling.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"170 ","pages":"Article 105996"},"PeriodicalIF":5.5,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144524","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}
Pub Date : 2025-01-29DOI: 10.1016/j.jtice.2025.105989
Liang J. Jhuang , Cheng-Jui Yang , Bor-Yih Yu
Background
Converting CO2 into various fuels (e.g., light hydrocarbons, gasoline, jet fuel, diesel) through the Fischer-Tropsch (FT) reaction is a promising option in a future decarbonized economy.
Method
Four scenarios characterized by different chain propagation probabilities (α) described by the Anderson-Schultz-Flory (ASF) distribution were developed, corresponding to the production of light hydrocarbons (α=0.3), gasoline (α=0.65), jet fuel (α=0.75), and diesel (α=0.85). Deviations from the standard ASF distribution for lower carbon numbers at high ɑ values were considered. For each scenario, alternative configurations utilizing different reactor structural parameters, employing various heat transfer methods, were investigated through mathematical modeling. Multi-objective optimization, aiming to maximize conversion and minimizing costs, was conducted to determine the optimal design and operating conditions.
Significant Findings
Overall, compared to single-stage configurations, dual-stage configurations offer opportunities for cost reduction and process intensification across all four scenarios. When utilizing counter-current heat exchange, higher conversion can be achieved at a lower cost with moderate conversion levels. In contrast, configurations with co-current heat exchange tend to enhance conversion by extending the reactor length once conversion exceeds 30 %. Furthermore, when using a dual-stage configuration to produce longer hydrocarbons, it is not appropriate to produce shorter hydrocarbons as intermediates that exit from the first reactor.
{"title":"Exploration of alternative reactor configurations for the Fischer-Tropsch (FT) reaction via direct hydrogenation of carbon dioxide","authors":"Liang J. Jhuang , Cheng-Jui Yang , Bor-Yih Yu","doi":"10.1016/j.jtice.2025.105989","DOIUrl":"10.1016/j.jtice.2025.105989","url":null,"abstract":"<div><h3>Background</h3><div>Converting CO<sub>2</sub> into various fuels (e.g., light hydrocarbons, gasoline, jet fuel, diesel) through the Fischer-Tropsch (FT) reaction is a promising option in a future decarbonized economy.</div></div><div><h3>Method</h3><div>Four scenarios characterized by different chain propagation probabilities (α) described by the Anderson-Schultz-Flory (ASF) distribution were developed, corresponding to the production of light hydrocarbons (α=0.3), gasoline (α=0.65), jet fuel (α=0.75), and diesel (α=0.85). Deviations from the standard ASF distribution for lower carbon numbers at high ɑ values were considered. For each scenario, alternative configurations utilizing different reactor structural parameters, employing various heat transfer methods, were investigated through mathematical modeling. Multi-objective optimization, aiming to maximize conversion and minimizing costs, was conducted to determine the optimal design and operating conditions.</div></div><div><h3>Significant Findings</h3><div>Overall, compared to single-stage configurations, dual-stage configurations offer opportunities for cost reduction and process intensification across all four scenarios. When utilizing counter-current heat exchange, higher conversion can be achieved at a lower cost with moderate conversion levels. In contrast, configurations with co-current heat exchange tend to enhance conversion by extending the reactor length once conversion exceeds 30 %. Furthermore, when using a dual-stage configuration to produce longer hydrocarbons, it is not appropriate to produce shorter hydrocarbons as intermediates that exit from the first reactor.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105989"},"PeriodicalIF":5.5,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151277","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}
Pub Date : 2025-01-28DOI: 10.1016/j.jtice.2025.105988
S.M. Hosseini , M. Pierantozzi
Background
Deep eutectic solvents (DESs) have gained attention as innovative green solvents, but accurate prediction of their thermophysical properties is essential for practical applications. This work explored the potential of different deep learning approaches to model density, viscosity, and CO2 solubility over a wide range of temperature and pressure conditions.
Methods
A comprehensive dataset was compiled, consisting of 2218 data points for density, 148 points for viscosity, and 144 points for CO2 solubility, covering a range of DES compositions. Deep neural network (NN) architecture was employed for density prediction, while simpler artificial neural network (ANN) architectures were used for viscosity and CO2 solubility predictions.
Significant findings
The deep NN model exhibited an excellent performance in predicting the density, achieving an average absolute relative deviation (AARD%) of 0.13 % and R² value of 0.9998, indicating high accuracy and robust generalization. The ANN models for viscosity and CO2 solubility also demonstrated promising results, with AARD% values of 1.44 % and 1.11 %, respectively. The comparison with semi-empirical models further highlighted the superiority of NN approaches for characterizing these innovative solvents. This work showcases the capability of deep learning in accurately modeling the thermophysical properties of DESs, providing valuable tools for applications of these green solvents.
{"title":"Density, viscosity and CO2 solubility modeling of deep eutectic solvents from various neural network approaches","authors":"S.M. Hosseini , M. Pierantozzi","doi":"10.1016/j.jtice.2025.105988","DOIUrl":"10.1016/j.jtice.2025.105988","url":null,"abstract":"<div><h3>Background</h3><div>Deep eutectic solvents (DESs) have gained attention as innovative green solvents, but accurate prediction of their thermophysical properties is essential for practical applications. This work explored the potential of different deep learning approaches to model density, viscosity, and CO<sub>2</sub> solubility over a wide range of temperature and pressure conditions.</div></div><div><h3>Methods</h3><div>A comprehensive dataset was compiled, consisting of 2218 data points for density, 148 points for viscosity, and 144 points for CO<sub>2</sub> solubility, covering a range of DES compositions. Deep neural network (NN) architecture was employed for density prediction, while simpler artificial neural network (ANN) architectures were used for viscosity and CO<sub>2</sub> solubility predictions.</div></div><div><h3>Significant findings</h3><div>The deep NN model exhibited an excellent performance in predicting the density, achieving an average absolute relative deviation (AARD%) of 0.13 % and R² value of 0.9998, indicating high accuracy and robust generalization. The ANN models for viscosity and CO<sub>2</sub> solubility also demonstrated promising results, with AARD% values of 1.44 % and 1.11 %, respectively. The comparison with semi-empirical models further highlighted the superiority of NN approaches for characterizing these innovative solvents. This work showcases the capability of deep learning in accurately modeling the thermophysical properties of DESs, providing valuable tools for applications of these green solvents.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105988"},"PeriodicalIF":5.5,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150862","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}
Pub Date : 2025-01-28DOI: 10.1016/j.jtice.2025.105998
A. Sadeghi , M. Shariatmadar , S. Amoozadeh , A. Mahmoudi Nahavandi , M. Mahdavian
Background
Aiming to find a quantitative structure-property relationship (QSPR), researchers have implemented a variety of approaches to gain prediction power for the corrosion inhibition of chemicals. This work aims to develop a practical approach for the connection of features extracted from FTIR exploiting principal component analysis to corrosion inhibition.
Methods
To this end, an artificial neural network (ANN) was utilized to build a machine learning model based on electrochemical impedance spectroscopy (EIS) data of ten known organic synthetic substances in three different acid solutions on mild steel. Inhibition power and all EIS data points were separately taken into consideration as objectives of the model. Then, the performance of the ANN was validated by employing an unseen plant extract during the training stage.
Significant findings
The predicted data was profoundly conformed with the measured data for the plant extract, especially by employing EIS data points as objectives of the model with R2: 0.95123 and 0.94721, respectively, for the impedance and phase angle Bode plots, clarifying the robustness of the built QSPR model to predict unseen data.
{"title":"Unlocking the potential of FTIR for corrosion inhibition prediction exploiting principal component analysis: Machine learning for QSPR modeling","authors":"A. Sadeghi , M. Shariatmadar , S. Amoozadeh , A. Mahmoudi Nahavandi , M. Mahdavian","doi":"10.1016/j.jtice.2025.105998","DOIUrl":"10.1016/j.jtice.2025.105998","url":null,"abstract":"<div><h3>Background</h3><div>Aiming to find a quantitative structure-property relationship (QSPR), researchers have implemented a variety of approaches to gain prediction power for the corrosion inhibition of chemicals. This work aims to develop a practical approach for the connection of features extracted from FTIR exploiting principal component analysis to corrosion inhibition.</div></div><div><h3>Methods</h3><div>To this end, an artificial neural network (ANN) was utilized to build a machine learning model based on electrochemical impedance spectroscopy (EIS) data of ten known organic synthetic substances in three different acid solutions on mild steel. Inhibition power and all EIS data points were separately taken into consideration as objectives of the model. Then, the performance of the ANN was validated by employing an unseen plant extract during the training stage.</div></div><div><h3>Significant findings</h3><div>The predicted data was profoundly conformed with the measured data for the plant extract, especially by employing EIS data points as objectives of the model with R<sup>2</sup>: 0.95123 and 0.94721, respectively, for the impedance and phase angle Bode plots, clarifying the robustness of the built QSPR model to predict unseen data.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105998"},"PeriodicalIF":5.5,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150405","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}
Pub Date : 2025-01-28DOI: 10.1016/j.jtice.2025.105994
A. Madhan Kumar , Rami K. Suleiman , M.A. Hussein , N.O. Ogunlakin
Background
Utilizing sol-gel film as an intermediate layer is considered one of the most fascinating routes to improving the overall efficiency of protective coatings. The current study aims to expand the surface protective performance of the fusion bonded epoxy (FBE) coating using deposited sol-gel films at the interface between the FBE and steel surface.
Methods
The structure, surface microstructure, and topography were characterized for prepared sol-gel films on carbon steel (CS). Also, contact angle measurements were performed to evaluate the surface free energy and wettability of the sol-gel coated CS substrates.
Significant findings
The adhesion test results showed that the CS surface with silane films enhanced the interfacial adhesion with the FBE, providing high adhesive strength for FBE coatings. The corrosion test results showed the improved anticorrosion performance of sol-gel deposited CS surface coated with FBE by showing high impedance values after one-month exposure. The achieved results confirmed that the CS with the sol-gel films significantly enhanced the surface energy by 2.7 times and improved surface hardness by 30 % compared with the bare and interfacial adhesion bonding of the subsequent FBE coating, and provided the improvement on the anticorrosion performance of FBE films in the saline medium.
{"title":"Influence of sol-gel film on fusion bonded epoxy coatings on carbon steel: Surface, adhesion, mechanical, and corrosion protection characteristics in a saline medium","authors":"A. Madhan Kumar , Rami K. Suleiman , M.A. Hussein , N.O. Ogunlakin","doi":"10.1016/j.jtice.2025.105994","DOIUrl":"10.1016/j.jtice.2025.105994","url":null,"abstract":"<div><h3>Background</h3><div>Utilizing sol-gel film as an intermediate layer is considered one of the most fascinating routes to improving the overall efficiency of protective coatings. The current study aims to expand the surface protective performance of the fusion bonded epoxy (FBE) coating using deposited sol-gel films at the interface between the FBE and steel surface.</div></div><div><h3>Methods</h3><div>The structure, surface microstructure, and topography were characterized for prepared sol-gel films on carbon steel (CS). Also, contact angle measurements were performed to evaluate the surface free energy and wettability of the sol-gel coated CS substrates.</div></div><div><h3>Significant findings</h3><div>The adhesion test results showed that the CS surface with silane films enhanced the interfacial adhesion with the FBE, providing high adhesive strength for FBE coatings. The corrosion test results showed the improved anticorrosion performance of sol-gel deposited CS surface coated with FBE by showing high impedance values after one-month exposure. The achieved results confirmed that the CS with the sol-gel films significantly enhanced the surface energy by 2.7 times and improved surface hardness by 30 % compared with the bare and interfacial adhesion bonding of the subsequent FBE coating, and provided the improvement on the anticorrosion performance of FBE films in the saline medium.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105994"},"PeriodicalIF":5.5,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150404","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}
Pub Date : 2025-01-25DOI: 10.1016/j.jtice.2025.105992
Ndumiso Vukile Mdlovu , Ruey-Shin Juang , Wei-Ya Lo , Kuen-Song Lin
Background
Cancer therapy faces challenges in targeted drug delivery, including poor bioavailability, limited tumor accumulation, and off-target toxicity. Nanomedicine offers a promising solution, utilizing nanoparticles to improve drug stability, enhance tumor targeting, and overcome these delivery limitations. This study aimed to develop nanocomposites composed of iron oxide nanoparticles (IONPs), silica (SiO2), and poly(methacrylic acid) (PMAA) for targeted delivery of an anticancer drug, doxorubicin (DOX). The combination of these materials was intended to improve the efficiency and specificity of drug delivery in cancer therapy.
Methods
The IONPs were synthesized through a co-precipitation method and coated with SiO2 using the Stöber process, with vinyl-functionalized silane serving as a coupling agent. The IONPs@SiO2@PMMA nanocomposites were then fabricated by emulsion polymerization of PMAA, and IONPs@PMAA nanocomposites were synthesized via hydrolysis. DOX was successfully loaded into the nanocomposites. The characterization of the nanocomposites was performed using high-resolution transmission electron microscopy (HR-TEM), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Cytotoxicity was assessed, and the drug loading capacity and release behavior were analyzed using UV–visible spectroscopy.
Significant Findings
The nanocomposites exhibited negligible cytotoxicity. UV–Vis analysis revealed that increasing the concentrations of polymer and DOX enhanced the drug loading capacity, achieving a maximum of 91.2%. Drug release studies demonstrated that DOX release was sensitive to both temperature and pH, with the highest release observed at 42 °C and pH 5.4. The release rate increased by 20–35%, reaching a peak of 86.7%. Additionally, the drug loading efficiency improved with increasing PMAA contents. Kinetic analysis showed that the release of DOX followed the Korsmeyer-Peppas model, indicating Fickian diffusion as the primary release mechanism. The diffusivity of DOX was calculated to be 1.7 × 10–20 m2/s using the Crank's diffusion model. This study demonstrates a promising approach for enhancing the targeted delivery and controlled release of DOX, potentially improving cancer treatment outcomes by addressing key challenges in drug delivery.
{"title":"Hydrolysis-assisted synthesis of magnetic iron oxide-silica/poly(methacrylic acid) nanocomposites for pH- and thermo-responsive doxorubicin delivery","authors":"Ndumiso Vukile Mdlovu , Ruey-Shin Juang , Wei-Ya Lo , Kuen-Song Lin","doi":"10.1016/j.jtice.2025.105992","DOIUrl":"10.1016/j.jtice.2025.105992","url":null,"abstract":"<div><h3>Background</h3><div>Cancer therapy faces challenges in targeted drug delivery, including poor bioavailability, limited tumor accumulation, and off-target toxicity. Nanomedicine offers a promising solution, utilizing nanoparticles to improve drug stability, enhance tumor targeting, and overcome these delivery limitations. This study aimed to develop nanocomposites composed of iron oxide nanoparticles (IONPs), silica (SiO<sub>2</sub>), and poly(methacrylic acid) (PMAA) for targeted delivery of an anticancer drug, doxorubicin (DOX). The combination of these materials was intended to improve the efficiency and specificity of drug delivery in cancer therapy.</div></div><div><h3>Methods</h3><div>The IONPs were synthesized through a co-precipitation method and coated with SiO<sub>2</sub> using the Stöber process, with vinyl-functionalized silane serving as a coupling agent. The IONPs@SiO<sub>2</sub>@PMMA nanocomposites were then fabricated by emulsion polymerization of PMAA, and IONPs@PMAA nanocomposites were synthesized <em>via</em> hydrolysis. DOX was successfully loaded into the nanocomposites. The characterization of the nanocomposites was performed using high-resolution transmission electron microscopy (HR-TEM), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Cytotoxicity was assessed, and the drug loading capacity and release behavior were analyzed using UV–visible spectroscopy.</div></div><div><h3>Significant Findings</h3><div>The nanocomposites exhibited negligible cytotoxicity. UV–Vis analysis revealed that increasing the concentrations of polymer and DOX enhanced the drug loading capacity, achieving a maximum of 91.2%. Drug release studies demonstrated that DOX release was sensitive to both temperature and pH, with the highest release observed at 42 °C and pH 5.4. The release rate increased by 20–35%, reaching a peak of 86.7%. Additionally, the drug loading efficiency improved with increasing PMAA contents. Kinetic analysis showed that the release of DOX followed the Korsmeyer-Peppas model, indicating Fickian diffusion as the primary release mechanism. The diffusivity of DOX was calculated to be 1.7 × 10<sup>–20</sup> m<sup>2</sup>/s using the Crank's diffusion model. This study demonstrates a promising approach for enhancing the targeted delivery and controlled release of DOX, potentially improving cancer treatment outcomes by addressing key challenges in drug delivery.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105992"},"PeriodicalIF":5.5,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151740","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}
Pub Date : 2025-01-25DOI: 10.1016/j.jtice.2025.105974
Rafi Ur Rahman , Polgampola Chamani Madara , Alamgeer , Maha Nur Aida , Jaljalalul Abedin Jony , Hasnain Yousuf , Muhammad Quddamah Khokhar , Mengmeng Chu , Sangheon Park , Junsin Yi
Background
The evolution of photovoltaic technologies has significantly advanced tandem solar cells, including Tunnel Oxide passive contact (TOPCon), passive emitter and Rear Contact (PERC), and Heterojunction Solar Cells (HIT). These technologies are crucial for enhancing solar energy conversion efficiency and are increasingly important in tackling global energy challenges. They promise higher efficiency and stability under various environmental conditions.
Methods
In this study, we evaluated the performance of Si/Si bifacial tandem solar cells under different albedo effects, by varying albedo levels of back-reflected light (0.1 to 0.5 suns). This analysis helps understand how these cells perform with varying intensities of reflected light, which is essential for optimizing their efficiency in real-world conditions.
Significant findings
Our findings reveal that TOPCon cells excel in low albedo conditions, achieving maximum efficiencies of 26.81 % in series and 28.73 % in parallel configurations. HIT cells demonstrate superior performance in parallel configurations, with maximum efficiencies of 27.16 % in series and 27.61 % in parallel. PERC cells provide a cost-effective balance between efficiency and manufacturability, reaching maximum efficiencies of 19.76 % in series and 28.31 % in parallel configurations. These results challenge the traditional view that only high-intensity sunlight maximizes solar cell efficiency, showing that optimizing configurations under varying albedo conditions can significantly enhance performance. This study offers new insights into optimizing different tandem solar cell technologies for specific situations, providing practical guidelines for enhancing photovoltaic systems’ efficiency and stability.
{"title":"Advanced perspectives on maximizing tandem solar cell efficiency by comparative dynamics of tunnel oxide passivated contact, passivated emitter and rear contact, and heterojunction solar cells under fluctuating light intensities","authors":"Rafi Ur Rahman , Polgampola Chamani Madara , Alamgeer , Maha Nur Aida , Jaljalalul Abedin Jony , Hasnain Yousuf , Muhammad Quddamah Khokhar , Mengmeng Chu , Sangheon Park , Junsin Yi","doi":"10.1016/j.jtice.2025.105974","DOIUrl":"10.1016/j.jtice.2025.105974","url":null,"abstract":"<div><h3>Background</h3><div>The evolution of photovoltaic technologies has significantly advanced tandem solar cells, including Tunnel Oxide passive contact (TOPCon), passive emitter and Rear Contact (PERC), and Heterojunction Solar Cells (HIT). These technologies are crucial for enhancing solar energy conversion efficiency and are increasingly important in tackling global energy challenges. They promise higher efficiency and stability under various environmental conditions.</div></div><div><h3>Methods</h3><div>In this study, we evaluated the performance of Si/Si bifacial tandem solar cells under different albedo effects, by varying albedo levels of back-reflected light (0.1 to 0.5 suns). This analysis helps understand how these cells perform with varying intensities of reflected light, which is essential for optimizing their efficiency in real-world conditions.</div></div><div><h3>Significant findings</h3><div>Our findings reveal that TOPCon cells excel in low albedo conditions, achieving maximum efficiencies of 26.81 % in series and 28.73 % in parallel configurations. HIT cells demonstrate superior performance in parallel configurations, with maximum efficiencies of 27.16 % in series and 27.61 % in parallel. PERC cells provide a cost-effective balance between efficiency and manufacturability, reaching maximum efficiencies of 19.76 % in series and 28.31 % in parallel configurations. These results challenge the traditional view that only high-intensity sunlight maximizes solar cell efficiency, showing that optimizing configurations under varying albedo conditions can significantly enhance performance. This study offers new insights into optimizing different tandem solar cell technologies for specific situations, providing practical guidelines for enhancing photovoltaic systems’ efficiency and stability.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105974"},"PeriodicalIF":5.5,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150861","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}
Pub Date : 2025-01-25DOI: 10.1016/j.jtice.2025.105975
Hilal Incebay , Ahmet Kilic
Background
This research aims to develop a novel electrochemical sensor strategy from the nanocomposite obtained by incorporating praseodymium oxide nanoparticles (Pr6O11NPs) into tetrahedral boronate esters (BE1N) and to use this sensor for the accurate and sensitive detection of Favipiravir drug used in the treatment of COVID-19.
Method
BE1N, which our group previously synthesized, and Pr6O11NPs were subjected to sonication in chloroform to be completely catalyzed, and conductive Pr6O11NPs/BE1N nanocomposite suspension was obtained. Pr6O11NPs/BE1N nanocomposite suspension was immobilized on the surface of the polished glassy carbon electrode (GCE) by the drop drying method, and a working electrode defined as Pr6O11NPs/BE1N/GCE was obtained for electrochemical experiments.
Significant findings
Pr6O11NPs/BE1N/GCE was characterized and used to detect Favipiravir using the square wave voltammetry technique. Under optimal conditions, Pr6O11NPs/BE1N/GCE provided an LOD of 0.035 nM in a linear range of 1.0 nM to 20 μM for Favipiravir. Additionally, the nanovoltammetric sensor exhibited highly effective repeatability, reproducibility, and stability while demonstrating negligible performance interference against interfering species. Besides, it was confirmed that the proposed nanovoltammetric sensor could be used for the sensitive detection of Favipiravir in real samples such as pharmaceutical tablets, urine, and human blood serum.
{"title":"A voltammetric sensor based on praseodymium oxide nanoparticles immobilized on tetrahedral boronate esters for favipiravir used in the treatment of COVID-19","authors":"Hilal Incebay , Ahmet Kilic","doi":"10.1016/j.jtice.2025.105975","DOIUrl":"10.1016/j.jtice.2025.105975","url":null,"abstract":"<div><h3>Background</h3><div>This research aims to develop a novel electrochemical sensor strategy from the nanocomposite obtained by incorporating praseodymium oxide nanoparticles (Pr<sub><sub>6</sub></sub>O<sub><sub>11</sub></sub>NPs) into tetrahedral boronate esters (BE<sub><sub>1</sub></sub>N) and to use this sensor for the accurate and sensitive detection of Favipiravir drug used in the treatment of COVID-19.</div></div><div><h3>Method</h3><div>BE1N, which our group previously synthesized, and Pr<sub>6</sub>O<sub>11</sub>NPs were subjected to sonication in chloroform to be completely catalyzed, and conductive Pr<sub><sub>6</sub></sub>O<sub><sub>11</sub></sub>NPs/BE<sub><sub>1</sub></sub>N nanocomposite suspension was obtained. Pr<sub><sub>6</sub></sub>O<sub><sub>11</sub></sub>NPs/BE<sub><sub>1</sub></sub>N nanocomposite suspension was immobilized on the surface of the polished glassy carbon electrode (GCE) by the drop drying method, and a working electrode defined as Pr<sub><sub>6</sub></sub>O<sub><sub>11</sub></sub>NPs/BE<sub><sub>1</sub></sub>N/GCE was obtained for electrochemical experiments.</div></div><div><h3>Significant findings</h3><div>Pr<sub><sub>6</sub></sub>O<sub><sub>11</sub></sub>NPs/BE<sub><sub>1</sub></sub>N/GCE was characterized and used to detect Favipiravir using the square wave voltammetry technique. Under optimal conditions, Pr<sub><sub>6</sub></sub>O<sub><sub>11</sub></sub>NPs/BE<sub><sub>1</sub></sub>N/GCE provided an LOD of 0.035 nM in a linear range of 1.0 nM to 20 μM for Favipiravir. Additionally, the nanovoltammetric sensor exhibited highly effective repeatability, reproducibility, and stability while demonstrating negligible performance interference against interfering species. Besides, it was confirmed that the proposed nanovoltammetric sensor could be used for the sensitive detection of Favipiravir in real samples such as pharmaceutical tablets, urine, and human blood serum.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105975"},"PeriodicalIF":5.5,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151276","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}
Pub Date : 2025-01-25DOI: 10.1016/j.jtice.2025.105991
Yi-Wun Wang , Jang-Cheng Fang
Background
SnBi is an attractive solder owing to its low cost and step-soldering capability. However, its ductility is lower than that of conventional solder such as SnAgCu. Addition of elements to SnBi can help improve its properties. Au is considered an effective way to improve the undercooling and tensile strength of SnBi.
Methods
In this study, a solder joint of Sn56Bi2Au/Cu is reflowed at 160 °C and then subjected to solid–solid reactions from 80 to 130 °C. Fracture morphologies indicate the Au addition increases the joint ductility and reliability.
Significant Findings
The addition of minor Au causes needle-type AuSn4 to disperse in the solder. The (Au,Cu)Sn formed at the interface during the 80 °C solid–solid reaction transforms to (Cu,Au)6Sn5 and Cu3Sn as the temperature increases to 100–130 °C. The formation of intermetallic compounds has a significant effect on the reliability. Au–Sn compounds are extremely important in light-emitting diodes, while Cu–Sn compounds are commonly used as connections for die-attached devices. The aim of this study is to investigate the phase transformations among AuSn, AuSn4, Cu6Sn5, and Cu3Sn. The effects of Au addition on the microstructure and mechanical properties are also investigated.
{"title":"Minor Au element effects on phase transformation and tensile strength","authors":"Yi-Wun Wang , Jang-Cheng Fang","doi":"10.1016/j.jtice.2025.105991","DOIUrl":"10.1016/j.jtice.2025.105991","url":null,"abstract":"<div><h3>Background</h3><div>SnBi is an attractive solder owing to its low cost and step-soldering capability. However, its ductility is lower than that of conventional solder such as SnAgCu. Addition of elements to SnBi can help improve its properties. Au is considered an effective way to improve the undercooling and tensile strength of SnBi.</div></div><div><h3>Methods</h3><div>In this study, a solder joint of Sn56Bi2Au/Cu is reflowed at 160 °C and then subjected to solid–solid reactions from 80 to 130 °C. Fracture morphologies indicate the Au addition increases the joint ductility and reliability.</div></div><div><h3>Significant Findings</h3><div>The addition of minor Au causes needle-type AuSn<sub>4</sub> to disperse in the solder. The (Au,Cu)Sn formed at the interface during the 80 °C solid–solid reaction transforms to (Cu,Au)<sub>6</sub>Sn<sub>5</sub> and Cu<sub>3</sub>Sn as the temperature increases to 100–130 °C. The formation of intermetallic compounds has a significant effect on the reliability. Au–Sn compounds are extremely important in light-emitting diodes, while Cu–Sn compounds are commonly used as connections for die-attached devices. The aim of this study is to investigate the phase transformations among AuSn, AuSn<sub>4</sub>, Cu<sub>6</sub>Sn<sub>5</sub>, and Cu<sub>3</sub>Sn. The effects of Au addition on the microstructure and mechanical properties are also investigated.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105991"},"PeriodicalIF":5.5,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150788","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}
Pub Date : 2025-01-25DOI: 10.1016/j.jtice.2025.105976
Muhammad Tanveer , M.A Qadeer , Ahmad Ruhan Ali , Jineetkumar Gawad , Husnain Haider Cheema , Safeera Yasmeen , Abdulaziz Bentalib , Muhammad Tahir
Background
Two major threats to modern society are the energy problem and water pollution. Currently, developing photocatalysts that possess both high activity and recyclability to break down pollutants remains a difficult task. The study presents a photocatalyst known as the Nb2O5/TiS2 heterojunction.
Methods
This photocatalyst is created by applying TiS2 onto the surface of Nb2O5 concurrently, using the hydrothermal approach. We used various methods, such as XRD, SEM, UV–vis, BET, PL, EIS, PC, Raman, and FT-IR, to examine the crystallinity, morphology, structure, surface area, and optical qualities of the as-prepared samples.
Significant findings
The Nb2O5/TiS2@5 % photocatalyst has the ability to broaden the range of visible light that it can absorb, as well as aid in the efficient separation and transfer of charges. The enhanced light absorption, superior absorbability, smaller band gap, and higher rate of separation of photo-generated charge carriers are all responsible for the increased photocatalytic activity as well as the higher hydrogen production. It was also observed that by the increasing in the ratio of TiS2 in pure Nb2O5 the features like crystallinity, optical and morphology was also enhanced. When exposed to visible light irradiation, the breakdown rate of Rhodamine B reached its highest point (99 %) in just 56 min. Furthermore, the synthesized photocatalyst showed excellent versatility, durability, and recyclability. We developed a Z-scheme transfer channel to enhance the photocatalytic performance based on findings from radical trapping studies, optical analysis, and photo-electrochemical analysis.The Nb2O5/TiS2@5 % photocatalyst produced more hydrogen gas (14.8 mmol/gh) than their singlet components (Nb2O5, TiS2). The optimized nanocomposite (Nb2O5/TiS₂@5 %) has great reductive and oxidative properties, and the Z scheme operation makes it much more stable. This photocatalyst worked exceptionally well for deterioration, producing hydrogen quickly and efficiently. These factors make it much better for use in photocatalysis and hydrogen production.
{"title":"Sun-light-driven Z-scheme photocatalytic annihilation of Rhodamine B, Hydrogen production and stability assessment via facile hydrothermal preparation of novel nanocomposite Nb2O5/TiS2","authors":"Muhammad Tanveer , M.A Qadeer , Ahmad Ruhan Ali , Jineetkumar Gawad , Husnain Haider Cheema , Safeera Yasmeen , Abdulaziz Bentalib , Muhammad Tahir","doi":"10.1016/j.jtice.2025.105976","DOIUrl":"10.1016/j.jtice.2025.105976","url":null,"abstract":"<div><h3>Background</h3><div>Two major threats to modern society are the energy problem and water pollution. Currently, developing photocatalysts that possess both high activity and recyclability to break down pollutants remains a difficult task. The study presents a photocatalyst known as the Nb<sub>2</sub>O<sub>5</sub>/TiS<sub>2</sub> heterojunction.</div></div><div><h3>Methods</h3><div>This photocatalyst is created by applying TiS<sub>2</sub> onto the surface of Nb<sub>2</sub>O<sub>5</sub> concurrently, using the hydrothermal approach. We used various methods, such as XRD, SEM, UV–vis, BET, PL, EIS, PC, Raman, and FT-IR, to examine the crystallinity, morphology, structure, surface area, and optical qualities of the as-prepared samples.</div></div><div><h3>Significant findings</h3><div>The Nb<sub>2</sub>O<sub>5</sub>/TiS<sub>2</sub>@5 % photocatalyst has the ability to broaden the range of visible light that it can absorb, as well as aid in the efficient separation and transfer of charges. The enhanced light absorption, superior absorbability, smaller band gap, and higher rate of separation of photo-generated charge carriers are all responsible for the increased photocatalytic activity as well as the higher hydrogen production. It was also observed that by the increasing in the ratio of TiS<sub>2</sub> in pure Nb<sub>2</sub>O<sub>5</sub> the features like crystallinity, optical and morphology was also enhanced. When exposed to visible light irradiation, the breakdown rate of Rhodamine B reached its highest point (99 %) in just 56 min. Furthermore, the synthesized photocatalyst showed excellent versatility, durability, and recyclability. We developed a Z-scheme transfer channel to enhance the photocatalytic performance based on findings from radical trapping studies, optical analysis, and photo-electrochemical analysis.The Nb<sub>2</sub>O<sub>5</sub>/TiS<sub>2</sub>@5 % photocatalyst produced more hydrogen gas (14.8 mmol/gh) than their singlet components (Nb<sub>2</sub>O<sub>5</sub>, TiS<sub>2</sub>). The optimized nanocomposite (Nb<sub>2</sub>O<sub>5</sub>/TiS₂@5 %) has great reductive and oxidative properties, and the Z scheme operation makes it much more stable. This photocatalyst worked exceptionally well for deterioration, producing hydrogen quickly and efficiently. These factors make it much better for use in photocatalysis and hydrogen production.</div></div>","PeriodicalId":381,"journal":{"name":"Journal of the Taiwan Institute of Chemical Engineers","volume":"169 ","pages":"Article 105976"},"PeriodicalIF":5.5,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150865","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}
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