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: 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 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: 6Citation - Scopus: 6Inverse Effects of Lanthanide Co-Doping on the Photocatalytic Hydrogen Production and Dye Degradation Activities of Cu Doped Sol-Gel Tio<sub>2</Sub>(Elsevier, 2023) Yurtsever, Husnu Arda; Erzin, Kubilay; Ciftcioglu, Muhsin; Yurtsever, Hüsnü Arda; Erzin, Kubilay; Çiftçioğlu, MuhsinCopper doped and lanthanide-copper co-doped titania powders were prepared by sol-gel technique and the effects of co-doping on the photocatalytic reduction and oxidation activities of titania were investigated in this work. Characterization studies indicated that a reduced structure was formed due to the presence of Ti3+ species in copper doped titania powder and a more stable structure was formed when lanthanides were used as co-dopants. Copper doped powder had a significantly higher activity in photocatalytic hydrogen production (1037 mu mol/g/h) than the co-doped powders (similar to 400 mu mol/g/h). The oxidation activities of co-doped powders however were determined to be about 2 times higher than that of the copper doped powder. The decrease in the reduction activity was attributed to the decrease in the number of Ti3+ sites, whereas the increase in oxidation activity was probably a result of the increase in the surface area and dye adsorption due to lanthanide co-doping.Article Citation - WoS: 6Citation - Scopus: 6Synthesis of a Novel Cellulose-Based Adsorbent From Olive Tree Pruning Waste for Removal of Boron From Aqueous Solution(Springer Science and Business Media Deutschland GmbH, 2024) Altınbaş, B.F.; Yüksel, A.This work investigated the valorization of olive tree pruning debris as a biosorbent for the removal of environmentally hazardous boron from aqueous solution using batch adsorption. For this purpose, a novel, waste-based, boron selective biosorbent from olive tree pruning waste (N-OPW) was synthesized. Alkali pretreatment, followed by glycidyl-methacrylate (GMA) grafting and providing boron selectivity with n-methyl-d-glucamine (NMDG) steps, was applied to the biomass, respectively. N-OPW was characterized using SEM, TGA, and FT-IR analyses. N-OPW showed excellent boron biosorption capacity (21.80 mg/g) in an operation pH range between 2 and 12. The equilibrium was attained in 2 h and the Freundlich isotherm (R2 = 0.997) and pseudo-second-order kinetics (R2 = 0.99) provided the strongest match to experimental data. According to thermodynamic studies, boron adsorption was exothermic (ΔH = −34.14 kJ/mol). The reusability tests with real geothermal water showed that adsorbent had no significant decrease in boron removal capacity while desorbing >99% of the boron adsorbed for three cycles of adsorption/desorption. Results indicated that a promising, reusable, and boron selective biosorbent was successfully synthesized while utilizing olive pruning waste. Graphical abstract: (Figure presented.) © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.Article Citation - WoS: 16Citation - Scopus: 15Ultrasound-Assisted Dopamine Polymerization: Rapid and Oxidizing Agent-Free Polydopamine Coatings on Membrane Surfaces(Royal Society of Chemistry, 2021) Cihanoğlu, Aydın; Schiffman, Jessica D.; Alsoy Altınkaya, SacideHerein, we report a controllable pathway to accelerate the polymerization kinetics of dopamine using ultrasound as a trigger. The use of ultrasound was demonstrated to dramatically accelerate the slow liquid phase reaction kinetics and increase the deposition rate of the polydopamine coating on the surface of polymeric membranes.Article Citation - WoS: 7Citation - Scopus: 7Modification of Grape Pulp With Citric Acid for the Production of Natural Ion Exchanger Resin and Removal of Pb (ii) and Cd (ii) From Aqueous Solutions: Kinetic, Thermodynamics, and Mechanism(Springer, 2021) Arslanoğlu, Esra; Eren, Muhammet Ş. A.; Arslanoğlu, Hasan; Çiftçi, HarunIn this study, grape pulp (MGP) modified with NaOH and citric acid was used in the production of natural ion exchangers. The effects of parameters such as initial pH, MGP dosage, temperature, initial metal ion concentration, and contact time on the removal of Pb (II) and Cd (II) ions from aqueous solutions using modified materials were investigated by batch experiments. It was found that the experimental kinetic data fit the second-order model, and the activation energy for Pb (II) and Cd (II) adsorption processes were 20.68 and 38.61 kj mol(-1), respectively. Although the initial adsorption rate increases with increasing temperature, the adsorption efficiency slightly decreases. It was calculated that the equilibrium data fit the Langmuir isotherm better, and the maximum adsorption capacities for Pb (II) and Cd (II) adsorption processes were approximately 1.496 and 1.022 mmol g(-1) at 25 degrees C, respectively. Thermodynamic analysis has shown that the adsorption processes of Pb (II) and Cd (II) are exothermic (Delta H degrees(Pb) = -35.68 kj mol(-1), Delta H degrees(Cd) = -21.19 kj mol(-1)) and have a self-developing character.Article Effects of Span 60 Template and Freeze Drying on Zinc Borate Produced From Zinc Nitrate Hexahydrate and Borax Decahydrate(Taylor and Francis Ltd., 2022) Alp, Burcu; Gönen, Mehmet; Atakul Savrık, Sevdiye; Balköse, DevrimZinc borate is an important additive to polymers and lubricants. The process variables such as reactant concentration, presence of template in precipitating medium and drying method determine the composition and particle size of zinc borates. In the present study, zinc borate precipitate obtained by mixing aqueous zinc nitrate and borax decahydrate solutions was dried either by conventional method or by freeze drying. The products were well characterized by advanced methods. Zinc borate from 1 mol dm(-3) reactants had (2.1 +/- 0.5)x(2.5 +/- 0.5)x(1.3 +/- 0.2) mu m and (0.5 +/- 0.1)x(1.3 +/- 0.1)x(0.028 +/- 0.01) mu m dimensions by conventional and freeze drying respectively. Individual particles smaller in size is obtained since the particles are not agglomerated due to absence of surface tension of liquid water for case of freeze drying. Planar particles agglomerated into 20 to 60 mu m crystals in the presence of template Span 60 in 1 mol dm(-3) reactants for conventional drying. Nano zinc borate particles with primary particle size of (46 +/- 9) nm were obtained by decreasing the reactant concentration to 0.1 mol dm(-3). The primary particle size was decreased to (40 +/- 3) nm by addition of Span 60 to dilute solutions. However zinc borate nanoparticles obtained from dilute solutions adhered to each other forming agglomerates during conventional drying. Their freeze drying would allow formation of a freely flowing nano powder.Article Citation - WoS: 15Citation - Scopus: 17Fabrication, Characterization, and Adsorption Applications of Low-Cost Hybride Activated Carbons From Peanut Shell-Vinasse Mixtures by One-Step Pyrolysis(Springer, 2021) Arslanoğlu, Esra; Eren, Muhammet Şakir Abdullah; Arslanoğlu, Hasan; Çiftçi, HarunThe present work aims to develop an innovative, alternative, fast, and cost-effective one-step pyrolysis method for activated carbon production using peanut shell and vinasse mixture. This facile procedure is based on single-step carbonization treatment at a temperature range of 400-800 degrees C. Different carbonization time (15-360 min), impregnation ratio (1-3 g/g), impregnation time (3-24 h), and nitrogen flow rate (300 and 600 ml/min) were examined. The chemical and physical properties of the activated carbon examined by SEM-EDX, FT-IR analysis, particle size distribution, iodine number, pH(zpc), BET surface area, and surface functional group analysis by Boehm's titration. The results illustrate that the values of BET surface area, total pore volume, average pore diameter, iodine number, pH(zpc), and carbon content of activated carbon were found as 1290.5 m(2)/g, 0.5667 cm(3)/g, 21.2 angstrom, 1258.4 mg/g, 5.7, and 86.89%, respectively.Article Citation - WoS: 22Citation - Scopus: 23Bioactive Snail Mucus-Slime Extract Loaded Chitosan Scaffolds for Hard Tissue Regeneration: the Effect of Mucoadhesive and Antibacterial Extracts on Physical Characteristics and Bioactivity of Chitosan Matrix(IOP Publishing, 2021) Perpelek, Merve; Tamburacı, Sedef; Aydemir, Selma; Tıhmınlıoğlu, Funda; Baykara, Başak; Karakaşlı, Ahmet; Havıtçıoğlu, HasanBiobased extracts comprise various bioactive components and they are widely used in tissue engineering applications to increase bioactivity as well as physical characteristics of biomaterials. Among animal sources, garden snail Helix aspersa has come into prominence with its antibacterial and regenerative extracts and show potential in tissue regeneration. Thus, in this study, bioactive H. aspersa extracts (slime, mucus) were loaded in chitosan (CHI) matrix to fabricate porous scaffolds for hard tissue regeneration. Physical, chemical properties, antimicrobial activity was determined as well as in vitro bioactivity for bone and cartilage regeneration. Mucus and slime incorporation enhanced mechanical properties and biodegradation rate of CHI matrix. Scanning electron microscopy images showed that the average pore size of the scaffolds decreased with higher extract content. Mucus and slime extracts showed antimicrobial effect on two bacterial strains. In vitro cytotoxicity, osteogenic and chondrogenic activity of the scaffolds were evaluated with Saos-2 and SW1353 cell lines in terms of Alkaline phosphatase activity, biomineralization, GAG, COMP and hydroxyproline content. Cell viability results showed that extracts had a proliferative effect on Saos-2 and SW1353 cells when compared to the control group. Mucus and slime extract loading increased osteogenic and chondrogenic activity. Thus, the bioactive extract loaded CHI scaffolds showed potential for bone and cartilage regeneration with enhanced physical properties and in vitro bioactivity.