Chemical Engineering / Kimya Mühendisliği
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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 Pomza ve Nsdd-pomza ile Sabit Yataklı Kolon Reaktörde Metilen Mavisi Giderimi: Deneysel ve Modelleme Çalışması(2019) Balcı, Esin; Ökten, Hatice Eser; Genişoğlu, Mesut; Recepoğlu, Yaşar Kemal; Gören, Ayşegül YağmurNano sıfır değerlikli demir (nSDD) yüksek renk konsantrasyonlarına sahip tekstil atıksularının arıtımında ekonomik ve çevre dostu bir adsorban olarak ortaya çıkmaktadır. Ancak nSDD partikülleri sulu çözeltilerde elektrostatik etkileşimler sebebiyle kolayca topaklaşmakta ve bu da arıtma veriminin düşmesine neden olmaktadır. Dolayısıyla düşük maliyetli, doğal poröz yapıda ve ortalama 2m2/gr spesifik yüzey alanına sahip pomza, nSDD topaklaşmasını önleyici bir malzeme olarak kullanılabilir. Bu çalışmada sadece pomza ve pomzanSDD (ağırlıkça 9:1) karışımının kullanıldığı kolon reaktörde 25, 50, 75 ve 100 mg/L metilen mavisi konsantrasyonları için arıtma verimleri incelenmiştir. Pomzanın ve pomza-nSDD karışımının 100 mg/L metilen mavisi deneyindeki toplam kapasiteleri sırasıyla 2,8 ve 4,2 mg/g-adsorban olarak bulunmuştur. Özellikle düşük konsantrasyonlarda, pomza-nSDD karışımının arıtma performansını önemli ölçüde arttırdığı görülmüştür. Thomas modeli deneysel verilere uygulanmış ve modelin öngörü gücünün düşük konsantrasyonda yüksekken, yüksek konsantrasyonlarda ortalama olduğu kanısına varılmıştır.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.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: 3Citation - Scopus: 3Shallow Shell Ssta63 Resin: a Rapid Approach To Remediation of Hazardous Nitrate(Royal Society of Chemistry, 2024) Cendik, Elif; Saygi, Mugenur; Recepoğlu, Yaşar Kemal; Arar, OzgurThis study examines the potential of Purolite Shallow Shell (TM) SSTA63 anion exchange resin for mitigating nitrate ion (NO3-) contamination in aqueous environments. Through systematic experimentation, including dosage optimization, pH dependency, kinetic and desorption studies, we investigate the sorption behavior and practical applications of the resin. Results indicate that the resin effectively removes NO3- ions, with maximum efficiency achieved within 10 minutes. When 0.025 g of resin was used, 75% of NO3- was removed, whereas with 0.05 g, 89% was removed, and with 0.1 g of resin, 95% was removed. At pH 1, approximately 50% of NO3- ions were removed, with removal efficiency reaching 97% between pH 4 and 10. Sorption isotherms affirm the suitability of the Langmuir model for the current investigation. The monolayer maximum sorption capacity (qmax) value was found to be 53.65 mg g-1. The resin demonstrates robust desorption capabilities using 0.1 M hydrochloric acid (HCl), effectively desorbing NO3- above 99%, indicating easy NO3- desorption and resin regeneration. The presence of coexisting ions such as chloride (Cl-), sulfate (SO42-), and phosphate (PO43-) showed a minimal impact on NO3- removal in individual binary mixtures, with efficiencies exceeding 93%, suggesting a strong selectivity of the resin towards NO3-. Purolite SSTA63 anion exchange resin exhibited a high affinity for NO3- ions, even over other competing ions, despite the general trend of ion exchange resins to favor ions with a higher atomic number and valence. Overall, this resin presents a promising solution for NO3- removal, with implications for water treatment and environmental remediation. This study explores the potential of Purolite Shallow Shell (TM) SSTA63 anion exchange resin for mitigating nitrate ion (NO3-) contamination in aqueous environments.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 Citation - WoS: 13Citation - Scopus: 11Bottom-Up Synthesis of Platinum Dual-Atom Catalysts on Cerium Oxide(American Chemical Society, 2024) Mekkering, Martijn J.; Laan, Petrus C. M.; Troglia, Alessandro; Bliem, Roland; Kızılkaya, Ali Can; Rothenberg, Gadi; Yan, NingWe present here the synthesis and performance of dual-atom catalysts (DACs), analogous to well-known single-atom catalysts (SACs). DACs feature sites containing pairs of metal atoms and can outperform SACs due to their additional binding possibilities. Yet quantifying the improved catalytic activity in terms of proximity effects remains difficult, as it requires both high-resolution kinetic data and an understanding of the reaction pathways. Here, we use an automated bubble counter setup for comparing the catalytic performance of ceria-supported platinum SACs and DACs in ammonia borane hydrolysis. The catalysts were synthesized by wet impregnation and characterized using SEM, HAADF-STEM, XRD, XPS, and CO-DRIFTS. High-precision kinetic studies of ammonia borane hydrolysis in the presence of SACs show two temperature-dependent regions, with a transition point at 43 degrees C. Conversely, the DACs show only one regime. We show that this is because DACs preorganize both ammonia borane and water at the dual-atom active site. The additional proximal Pt atom improves the reaction rate 3-fold and enables faster reactions at lower temperatures. We suggest that the DACs enable the activation of the water-O-H bond as well as increase the hydrogen spillover effect due to the adjacent Pt site. Interestingly, using ammonia borane hydrolysis as a benchmark reaction gives further insight into hydrogen spillover mechanisms, above what is known from the CO oxidation studies.Article Citation - WoS: 14Citation - Scopus: 163D Bioprinting of mouse pre-osteoblasts and human MSCs using bioinks consisting of gelatin and decellularized bone particles(Iop Publishing Ltd, 2024) Kara, Aylin; Distler, Thomas; Akkineni, Ashwini Rahul; Tihminlioglu, Funda; Gelinsky, Michael; Boccaccini, Aldo R.One of the key challenges in biofabrication applications is to obtain bioinks that provide a balance between printability, shape fidelity, cell viability, and tissue maturation. Decellularization methods allow the extraction of natural extracellular matrix, preserving tissue-specific matrix proteins. However, the critical challenge in bone decellularization is to preserve both organic (collagen, proteoglycans) and inorganic components (hydroxyapatite) to maintain the natural composition and functionality of bone. Besides, there is a need to investigate the effects of decellularized bone (DB) particles as a tissue-based additive in bioink formulation to develop functional bioinks. Here we evaluated the effect of incorporating DB particles of different sizes (<= 45 and <= 100 mu m) and concentrations (1%, 5%, 10% (wt %)) into bioink formulations containing gelatin (GEL) and pre-osteoblasts (MC3T3-E1) or human mesenchymal stem cells (hTERT-MSCs). In addition, we propose a minimalistic bioink formulation using GEL, DB particles and cells with an easy preparation process resulting in a high cell viability. The printability properties of the inks were evaluated. Additionally, rheological properties were determined with shear thinning and thixotropy tests. The bioprinted constructs were cultured for 28 days. The viability, proliferation, and osteogenic differentiation capacity of cells were evaluated using biochemical assays and fluorescence microscopy. The incorporation of DB particles enhanced cell proliferation and osteogenic differentiation capacity which might be due to the natural collagen and hydroxyapatite content of DB particles. Alkaline phosphatase activity is increased significantly by using DB particles, notably, without an osteogenic induction of the cells. Moreover, fluorescence images display pronounced cell-material interaction and cell attachment inside the constructs. With these promising results, the present minimalistic bioink formulation is envisioned as a potential candidate for bone tissue engineering as a clinically translatable material with straightforward preparation and high cell activity.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.