Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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  • Article
    Citation - WoS: 3
    Citation - Scopus: 4
    Comparison of Conventional and Machine Learning Models for Kinetic Modelling of Biomethane Production From Pretreated Tomato Plant Residues
    (Elsevier, 2025) Fidan, Berrak; Bodur, Fatma-Gamze; Oztep, Gulsh; Gungoren-Madenoglu, Tuelay; Baba, Alper; Kabay, Nalan
    Tomato plant residues (Solanum lycopersicum L.) lack sustainable applications as abundant lignocellulosic biomass after harvest. These residues can be utilized as substrates in anaerobic digestion for biomethane production, generating energy and reducing waste. The purpose of this study was to investigate the sustainable utilization of tomato plant residues for biomethane production at varying conditions and to model biological kinetics. The study aimed to evaluate the effects of varying substrate/inoculum ratios, sulfuric acid pretreatment concentrations, and yeast (Saccharomyces cerevisiae) addition on biogas and biomethane yields under mesophilic conditions (37 degrees C). Maximum biogas and biomethane yields in the studied range were obtained when the substrate/inoculum ratio was 3 (g substrate/g inoculum), the sulfuric acid concentration used for residue pretreatment was 2 %v/v, and the substrate/yeast ratio was 10 (g substrate/g yeast). The yeast ratio of 10 increased the cumulative biogas and biomethane production by 96.5 and 128.9%, respectively. Conventional models (Modified Gompertz, Cone, First-order, Logistic) and Machine Learning models (Support Vector Machine and Neural Network) were compared for biological kinetics. Machine Learning models were also observed to give good fitting results similar to conventional models. Results suggest that Machine Learning models (RMSE: 2.5833-12.0500) are reliable methods like conventional kinetic models (RMSE: 2.1796-13.4880) for forecasting biomethane production in anaerobic digestion processes and Machine Learning models can be applied without needing prior understanding of biomethane production kinetics.
  • Article
    Citation - WoS: 6
    Citation - Scopus: 4
    Regenerable Nickel Catalysts Strengthened Against H2s Poisoning in Dry Reforming of Methane
    (Elsevier, 2025) Kesan Celik, Nazli; Yasyerli, Sena; Arbag, Huseyin; Tasdemir, H. Mehmet; Yasyerli, Nail
    In 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.