عنوان المقالة:Optimization of Heavy Metals Biosorption via Artificial Neural Network: A Case Study of Cobalt (II) Sorption by Pseudomonas alcaliphila NEWG-2 Optimization of Heavy Metals Biosorption via Artificial Neural Network: A Case Study of Cobalt (II) Sorption by Pseudomonas alcaliphila NEWG-2
د زياد موسى عبد المعطي | Zeiad Moussa Abd El-Moati | 6770
نوع النشر
مقال علمي
المؤلفون بالعربي
الملخص الانجليزي
The definitive screening design (DSD) and artificial neural network (ANN) were conducted for modeling the biosorption of Co(II) by Pseudomonas alcaliphila NEWG-2. Factors such as peptone, incubation time, pH, glycerol, glucose, K2HPO4, and initial cobalt had a significant effect on the biosorption process. MgSO4 was the only insignificant factor. The DSD model was invalid and could not forecast the prediction of Co(II) removal, owing to the significant lack-of-fit (P < 0.0001). Decisively, the prediction ability of ANN was accurate with a prominent response for training (R2 = 0.9779) and validation (R2 = 0.9773) and lower errors. Applying the optimal levels of the tested variables obtained by the ANN model led to 96.32 ± 2.1% of cobalt bioremoval. During the biosorption process, Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy, and scanning electron microscopy confirmed the sorption of Co(II) ions by P. alcaliphila. FTIR indicated the appearance of a new stretching vibration band formed with Co(II) ions at wavenumbers of 562, 530, and 531 cm–1. The symmetric amino (NH2) binding was also formed due to Co(II) sorption. Interestingly, throughout the revision of publications so far, no attempt has been conducted to optimize the biosorption of Co(II) by P. alcaliphila via DSD or ANN paradigm.
تاريخ النشر
31/05/2022
الناشر
Frontiers in Microbiology
رقم المجلد
رقم العدد
رابط DOI
10.3389/fmicb.2022.893603
رابط الملف
تحميل (0 مرات التحميل)
الكلمات المفتاحية
cobalt, biosorption, Pseudomonas alcaliphila NEWG-2, definitive screening design, artificial neural network
رجوع