Metilen Mavisinin Sulu Çözeltilerden Diospyros Kaki L. Kabuğuna Adsorpsiyonu: İzoterm ve Yapay Sinir Ağı Modellemesi

Year 2025, Volume: 15 Issue: 1, 134 - 146, 01.03.2025

Züleyha Reçber

https://doi.org/10.21597/jist.1563250

Abstract

Bu çalışmada; metilen mavisi boyar maddesinin sulu çözeltilerden giderimi için Diospyros kaki L. kabuğunun adsorpsiyon potansiyeli incelenmiştir. Temas süresi, pH, adsorbent miktarı, başlangıç boya konsantrasyonu, sıcaklık ve karıştırma hızının boya giderim verimi üzerindeki etkileri araştırılmıştır. Adsorpsiyon 60 dakikada dengeye ulaşmıştır. Adsorbent miktarı arttıkça boya giderim verimi artarken adsorpsiyon kapasitesi düşmüştür. Başlangıç pH’sının sistem performansı üzerinde etkin bir parametre olduğu gözlemlenmiş ve en yüksek boyar madde giderim verimi pH 8’de elde edilmiştir. Adsorpsiyon mekanizmasını belirlemek için Langmuir ve Freundlich izoterm modelleri kullanılmış ve Freundlich izoterm modelinin deneysel verilere daha uygun olduğu tespit edilmiştir. 1 g/L adsorbent miktarı, 250 rpm karıştırma hızı, 100 mg/L başlangıç boyar madde konsantrasyonu, 25 ºC sıcaklık ve 6.68 pH’da 120 dakikalık temas süresinde %85.14’lük giderim verimine ulaşılmıştır. Sulu çözeltiden metilen mavi giderimini tahmin etmek için yapay sinir ağı modeli geliştirilmiştir. Xgboost algoritması ile en küçük ortalama kare hata (MSE) ve en büyük belirleme katsayısı (R2) değerleri sırasıyla 6.99 ve 0.99969 olarak belirlenmiştir. Sonuçlar Diospyros kaki L. kabuğunun metilen mavisi boyar maddesinin sulu çözeltilerden giderimi için etkili bir adsorbent olarak kullanılabileceğini ve yapay sinir ağının makul bir tahmin performansı sağladığını, geliştirilen yapay sinir ağı modeline dayalı simülasyonlar, farklı koşullar altında renk giderim sürecinin davranışını tahmin edebileceğini göstermiştir.

Keywords

Adsorpsiyon, Boya giderimi, Yapay sinir ağı, Diospyros kaki L

Adsorption of Methylene Blue from Aqueous Solutions onto Diospyros Kaki L. Bark : Isotherm and Artificial Neural Network Modeling

Abstract

In this study; adsorption potential of Diospyros kaki L. bark for removal of methylene blue dye from aqueous solutions was investigated. The effects of contact time, pH, adsorbent amount, initial dye concentration, temperature and stirring speed on dye removal efficiency were investigated and optimized. Adsorption reached equilibrium in 60 minute. While dye removal efficiency increased as adsorbent amount increased, adsorption capacity decreased. It was observed that initial pH was an effective parameter on system performance and the highest dye removal efficiency was obtained at pH 10. Langmuir and freundlich isotherm models were used to determine the adsorption mechanism and it was found that the Freundlich model was more suitable for the experimental data. 85.14% removal efficiency was achieved at 1 g/L adsorbent amount, 250 rpm stirring speed, 100 mg/L initial dye concentration, 25 ºC temperature and 6.8 pH in 120 min contact time. An artificial neural network model was developed to predict methylene blue removal from aqueous solution. The smallest mean square error (MSE) and the maximum coefficient of determination (R2) values were determined as 6.99 and 0.99969 by the Xgboost algorithm, respectively. The results showed that Diospyros kaki L. bark can be used as an effective adsorbent for methylene blue removal from aqueous solutions and the artificial neural network provided reasonable prediction performance, and simulations based on the developed artificial neural network model could predict the behavior of the color removal process under different conditions.

Keywords

Adsorption, Dye removal, Artificial neuron network, Diospyros kaki L.

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