Chemical Engineering / Kimya Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/14
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Article Citation - WoS: 5Citation - Scopus: 5Automated Deep Learning Model Development Based on Weight Sensitivity and Model Selection Statistics(Pergamon-elsevier Science Ltd, 2025) Yalcin, Damla; Deliismail, Ozgun; Tuncer, Basak; Boy, Onur Can; Bayar, Ibrahim; Kayar, Gizem; Sildir, HasanCurrent sustainable production and consumption processes call for technological integration with the realm of computational modeling especially in the form of sophisticated data-driven architectures. Advanced mathematical formulations are essential for deep learning approach to account for revealing patterns under nonlinear and complex interactions to enable better prediction capabilities for subsequent optimization and control tasks. Bayesian Information Criterion and Akaike Information Criterion are introduced as additional constraints to a mixed-integer training problem which employs a parameter sensitivity related objective function, unlike traditional methods which minimize the training error under fixed architecture. The resulting comprehensive optimization formulation is flexible as a simultaneous approach is introduced through algorithmic differentiation to benefit from advanced solvers to handle computational challenges and theoretical issues. Proposed formulation delivers 40% reduction, in architecture with high accuracy. The performance of the approach is compared to fully connected traditional methods on two different case studies from large scale chemical plants.Article Citation - WoS: 6Citation - Scopus: 4Regenerable Nickel Catalysts Strengthened Against H2s Poisoning in Dry Reforming of Methane(Elsevier, 2025) Kesan Celik, Nazli; Yasyerli, Sena; Arbag, Huseyin; Tasdemir, H. Mehmet; Yasyerli, NailIn this study, alumina-supported bimetallic Ni-Cu and trimetallic Ni-Cu-Ce catalysts were synthesized to improve catalysts resistant to coke formation and sulfur poisoning for dry reforming of methane (DRM). The effects of parameters such as feed composition, synthesis method, and H2S concentration using the catalyst with the best activity were also investigated. To determine the physical and chemical properties of the synthesized catalysts, XRD, N2 adsorption-desorption, TGA-DTA, ICP-OES, SEM-EDX, XPS, and DRIFTS analyses were performed. XRD analysis showed that the fresh Ni-Cu catalysts have elemental nickel and gamma- alumina phases in their structures. In addition to these structures, the CeO2 crystal structure was determined for the Ni-Cu-Ce catalyst. Type IV isotherm with H1 hysteresis indicating uniform mesoporous structure was obtained with all the catalysts. The activities of the synthesized catalysts in DRM were performed in the presence of different concentrations of H2S (2 ppm, 50 ppm, and 500 ppm) in a fixed bed reactor at 750 degrees C using a gas chromatography-equipped system. The alumina-supported 8Ni-3Cu-8Ce catalyst prepared by the impregnation method exhibited a higher and more stable activity comparing the bimetallic Ni-Cu catalyst in the presence of H2S. Adding copper and cerium to the nickel catalyst has a curative effect on resistance to coke formation and sulfur poisoning. Excess CO2 in the feed stream increased the H2S poisoning resistance of the catalyst. To analyze the reactor exit stream in catalytic activity using different feed stream compositions such as H2S+He, H2S+CO2+He, and H2S+CO2+CH4+He, FTIR with a gas cell was used. The formation of carbonyl sulfide (COS) and H2O, which occurs due to the possible reaction between CO2 and H2S, was observed. Regeneration studies showed that the catalyst could undergo regeneration with a low oxygen concentration (0.3 % O2 in He). 8Ni-3Cu-8Ce@SGA, which gave 71 % CH4 conversion in the first minute of the reaction test in the presence of 50 ppm H2S, was regenerated after completely losing its activity at the end of 5 h. 66 % CH4 conversion was achieved when tested again in the absence of H2S (CH4/CO2/Ar:1/1/1). The 8Ni-3Cu-8Ce@SGA catalyst was deemed worthy of investigation for industrial applications.Book Part A Study on Absorption and Reflection of Infrared Light by the Uncoated and Al Coated Surfaces of Polymer Films Techniques(Apple Academic Press, 2014) Arkış, Esen; Balköse, DevrimPolymer films coated with a thin layer of aluminum or aluminum oxide are extensively used in food packing as heat shields. The infrared rays were not transmitted through the films and were reflected protecting the contents from the harmful effects of infrared light. The quantitative measurement of the film thickness and infrared light reflection and absorption capacities of aluminum coated films used as packing materials were possible using infrared spectroscopy. © 2015 by Apple Academic Press, Inc.Book Part Advances in Nanocomposite Membranes for CO2 Removal(Elsevier, 2024) Marpani,F.; Othman,N.H.; Alias,N.H.; Mat Shayuti,M.S.; Alsoy Altınkaya, SacideNanocomposite membranes have emerged as a promising solution for efficient carbon dioxide (CO2) removal in gas separation processes. These membranes combine polymeric matrices with inorganic nanofillers to synergize the excellent separation performance of inorganic materials with the mechanical stability of polymers. The choice of nanofillers, such as porous and nonporous materials, significantly influences the gas permeability and selectivity of the resulting nanocomposite membranes. Porous fillers with interstitial channels and large surface areas are found to selectively adsorb CO2, enhancing membrane separation performance. On the other hand, nonporous fillers alter the polymer chain orientation, influencing gas separation differently. The 1D, 2D, and 3D morphologies of nanofillers offer unique properties in terms of surface-to-volume ratio, permeability, and selectivity. The fabrication of nanocomposite membranes also plays a crucial role, and advances in materials and manufacturing techniques have enabled the design of high-performing membranes. Asymmetric and symmetric configurations have been explored to optimize separation efficiency. Nevertheless, challenges such as aging, compaction, and swelling need to be addressed to ensure the long-term stability of nanocomposite membranes. Future research should focus on developing advanced theoretical models to better predict gas permeation behaviors in these membranes. Overall, nanocomposite membranes offer a promising avenue for efficient CO2 removal, contributing to sustainable environmental practices and energy production. © 2024 Elsevier Ltd. All rights reserved.Book Part Calcium Soap Lubricants(CRC Press, 2015) İzer, Alaz; Kahyaoğlu, Tuğçe Nefise; Balköse, DevrimThe reparation and characterization of calcium stearate (CaSt2) and a lubricant by using calcium stearate were aimed at in this study. Calcium stearate powder was prepared from sodium stearate and calcium chloride by precipitation from aqueous solutions. CaSt2 and the Light Neutral Base oil were mixed together to obtain lubricating oil. It was found that CaSt2 had a melting temperature of 142.8 °C and in base oil it had a lower melting point, above 128 °C. It was dispersed as lamellar micelles as the optical micrographs had shown. From rate of settling the size of dispersed particles were found to be 1.88 µm and 0.11 µm for lubricants having 1% and 2% CaSt2, respectively. The friction coefficient and wear scar diameter of base oil 0.099 and 1402 nm were reduced to 0.0730 and 627.61 nm respectively for the lubricant having 1% CaSt2. Lower wear scar diameter (540 nm) was obtained for lubricant with 2% CaSt2. CaSt2 improved the lubricating property of the base oil but did not improve its oxidative and thermal stability. © 2015 by Apple Academic Press, Inc.Article Citation - WoS: 1Citation - Scopus: 1Optimized Lithium(I) Recovery From Geothermal Brine of Germencik, Türkiye, Utilizing an Aminomethyl Phosphonic Acid Chelating Resin(Taylor and Francis Ltd., 2025) Recepoğlu, Y.K.This study investigates the performance of Lewatit TP 260 ion exchange resin for the efficient recovery of lithium (Li(I)) from geothermal water sourced from the Germencik Geothermal Power Plant in Türkiye. A series of batch sorption experiments were performed to evaluate the influence of key parameters, including resin dosage, solution pH, temperature, initial Li(I) concentration, and contact time, on the Li(I) recovery process. The optimal conditions were determined to be a resin dose of 0.5 g per 25 mL of geothermal water, pH in the range of 6–8, and a temperature of 25°C. Under these conditions, the resin achieved a maximum Li(I) recovery rate of 71% from the geothermal water. Sorption isotherms were further analyzed using the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) models. Among these, the Langmuir model provided the best fit (R² = 0.9841), suggesting a maximum sorption capacity (qm) of 4.31 mg/g. Continuous recovery experiments conducted in column mode confirmed the practical applicability of Lewatit TP 260, achieving a total sorption capacity of 0.41 mg Li(I)/mL resin. The findings exhibit the potential of this resin as a viable sorbent for sustainable Li(I) extraction from geothermal brines, supporting the development of green energy technologies and contributing to the circular economy. © 2024 Taylor & Francis Group, LLC.Article Citation - WoS: 15Citation - Scopus: 16A Machine Learning Ensemble Approach for Predicting Solar-Sensitive Hybrid Photocatalysts on Hydrogen Evolution(IOP Publishing, 2024) Bakır, Rezan; Orak, Ceren; Yuksel, AsliHydrogen, as the lightest and most abundant element in the universe, has emerged as a pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such as high energy density and zero emissions upon combustion, make it a promising candidate for addressing the pressing challenges of climate change and transitioning towards a clean and renewable energy future. In an effort to improve efficiency and reduce experimental costs, we adopted machine learning techniques in this study. Our focus turned to predictive analyses of hydrogen evolution values using three photocatalysts, namely, graphene-supported LaFeO3 (GLFO), graphene-supported LaRuO3 (GLRO), and graphene-supported BiFeO3 (GBFO), examining their correlation with varying levels of pH, catalyst amount, and H2O2 concentration. To achieve this, a diverse range of machine learning models are used, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), XGBoost, Gradient Boosting, and AdaBoost-each bringing its strengths to the predictive modeling arena. An important step involved combining the most effective models-Random Forests, Gradient Boosting, and XGBoost-into an ensemble model. This collaborative approach aimed to leverage their collective strengths and improve overall predictability. The ensemble model emerged as a powerful tool for understanding photocatalytic hydrogen evolution. Standard metrics were employed to assess the performance of our ensemble prediction model, encompassing R squared, Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). The yielded results showcase exceptional accuracy, with R squared values of 96.9%, 99.3%, and 98% for GLFO, GBFO, and GLRO, respectively. Moreover, our model demonstrates minimal error rates across all metrics, underscoring its robust predictive capabilities and highlighting its efficacy in accurately forecasting the intricate relationships between GLFO, GBFO, and GLRO values and their influencing factors.Article Mini modular plant design for ethylene production using Martian atmosphere on Mars(Elsevier, 2024) Deliismail, Özgün; Şeker, ErolA main shift in the competitive landscape of technology development is in 3D printing of complex articles made of variety of materials due to faster manufacturing and less human error in the production. In fact, it seems to be a viable candidate for the construction of structures for terrestrial and extraterrestrial life in future. Thus, new or damaged equipment in space explorations could be replaced instantly, and habitats could be manufactured using 3D printing in varying gravitational fields in the solar system. Among 3D printing materials, HDPE is commonly used in the projects, such as a prototype manufacturing or pipes or damp-proof membrane. This study initially focused on the preliminary design of the self-sustaining mini ethylene production plant from Martian atmosphere with scale-out architecture. UniSIM® was integrated with MATLAB® via CAPE-OPEN extension to design mini-ethylene production plant at low gravity. Ethylene capacity was found as 17.71 tons/year for 100 modules. © 2023 COSPARArticle Simultaneous Topology Design and Optimization of Pde Constrained Processes Based on Mixed Integer Formulations(Elsevier, 2024) Ertürk, Emrullah; Deliismail, Özgün; Şıldır, HasanSimultaneous topological design and optimization of complex processes that are described by partial differential equations is a challenging but promising research area. Widely adopted nested and sequential approaches are mostly applicable based on heuristic solutions, hindering the theoretical improvement potential due to decentralized decision-making in subsequent stages with a significant number of trial-and-error procedures. This study introduces a mixed integer formulation addressing the governing equations and case-dependent topological constraints at each discretization point, enabling solutions through rigorous solvers under process-related constraints and objectives. Nonlinear expressions in the formulations are further tailored using piecewise linear approximations, still representing the major nonlinear trends through a mixed-integer linear nature to favor global optimality and benefit from computational advancements, when needed. Heat and Stokes flow problems are used as case studies to demonstrate the applicability of the methodology. © 2024 Elsevier B.V.Article Citation - WoS: 4Citation - Scopus: 5Breakthrough Curve Analysis of Phosphorylated Hazelnut Shell Waste in Column Operation for Continuous Harvesting of Lithium From Water(Elsevier, 2024) Recepoğlu, Yaşar Kemal; Arar, Ozguer; Yuksel, AsliIn batch-scale operations, biosorption employing phosphorylated hazelnut shell waste (FHS) revealed excellent lithium removal and recovery efficiency. Scaling up and implementing packed bed column systems necessitates further design and performance optimization. Lithium biosorption via FHS was investigated utilizing a continuous-flow packed-bed column operated under various flow rates and bed heights to remove Li to ultra-low levels and recover it. The Li biosorption capacity of the FHS column was unaffected by the bed height, however, when the flow rate was increased, the capacity of the FHS column decreased. The breakthrough time, exhaustion time, and uptake capacity of the column bed increased with increasing column bed height, whereas they decreased with increasing influent flow rate. At flow rates of 0.25, 0.5, and 1.0 mL/min, bed volumes (BVs, mL solution/mL biosorbent) at the breakthrough point were found to be 477, 369, and 347, respectively, with the required BVs for total saturation point of 941, 911, and 829, while the total capacity was calculated as 22.29, 20.07, and 17.69 mg Li/g sorbent. In the 1.0, 1.5, and 2.0 cm height columns filled with FHS, the breakthrough times were 282, 366, and 433 min, respectively, whereas the periods required for saturation were 781, 897, and 1033 min. The three conventional breakthrough models of the Thomas, Yoon-Nelson, and Modified Dose-Response (MDR) were used to properly estimate the whole breakthrough behavior of the FHS column and the characteristic model parameters. Li's extremely favorable separation utilizing FHS was evidenced by the steep S-shape of the breakthrough curves for both parameters flow rate and bed height. The reusability of FHS was demonstrated by operating the packed bed column in multi-cycle mode, with no appreciable loss in column performance.