Machine Learning-Guided Prediction and Interpretation of Rhodamine B Removal by Biochar Derived from Marine Biomass
Yazarlar (5)
Doç. Dr. Dilek GÜMÜŞ Sinop Üniversitesi, Türkiye
Doç. Dr. Fatih GÜMÜŞ Sinop Üniversitesi, Türkiye
Elif Nihan Kadıoğlu
Ondokuz Mayis Üniversitesi
Ondokuz Mayis Üniversitesi
Elif Nihan Kadıoğlu
Arş. Gör. Handan Atalay Eroğlu Ondokuz Mayis Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Water, Air, & Soil Pollution (Q2) | ||
| Dergi ISSN | 0049-6979 Dergi Bilgileri (2026) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2026 |
| Cilt / Sayı / Sayfa | 237 / 377 / 377–0 | DOI | 10.1007/s11270-025-09054-z |
| Makale Linki | https://doi.org/10.1007/s11270-025-09054-z | ||
| UAK Araştırma Alanları |
Su Kirliliği ve Kontrolü
|
||
| Özet |
| This study aims to provide a sustainable solution for dye removal by developing environmentally friendly and renewable resource-based adsorbents. In this context, the removal of Rhodamin B (RhB) dye from aqueous solutions was investigated using composite biochar obtained from the seaweed species Ulva lactuca –Cystoseira sensu lato. The characterization of the adsorbent, which draws attention with its high surface area (797.91 m2/g), porous structure and rich functional groups, was carried out by SEM, FTIR and BET analyses. The data obtained as a result of adsorption experiments were evaluated with kinetic and isotherm models; the pseudo-second-order kinetic model (R2 = 0.993) and Freundlich isotherm (R2 = 0.994) successfully reflected the chemical and multi-layered nature of the process. In this context, the adsorption data were modelled with four different machine learning algorithms (Random … |
| Anahtar Kelimeler |
| Adsorption | Composite biochar | Machine Learning | Rhodamine B | SHAP analysis |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 1 |