Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study
Cephalexin (CFX) residues in the environment represent a major threat to human health worldwide. Herein we investigate the use of novel approaches in deep learning in order to understand the mechanisms and optimal conditions for the sorption of cephalexin in water onto an acidic pretreated jackfruit...
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| Format: | Article |
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MDPI AG
2022-07-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/14/14/2243 |
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| author | Adel Ali Al-Gheethi Mohammad Shafiq Mohd Salleh Efaq Ali Noman Radin Maya Saphira Radin Mohamed Rich Crane Rafidah Hamdan Mu. Naushad |
| author_facet | Adel Ali Al-Gheethi Mohammad Shafiq Mohd Salleh Efaq Ali Noman Radin Maya Saphira Radin Mohamed Rich Crane Rafidah Hamdan Mu. Naushad |
| author_sort | Adel Ali Al-Gheethi |
| collection | DOAJ |
| description | Cephalexin (CFX) residues in the environment represent a major threat to human health worldwide. Herein we investigate the use of novel approaches in deep learning in order to understand the mechanisms and optimal conditions for the sorption of cephalexin in water onto an acidic pretreated jackfruit peel adsorbent (APJPA). The interaction between the initial concentration of CFX (10–50 mg/100 mL), APJAP dosage (3–10 mg/100 mL), time (10–60 min), and the pH (4–9), was simulated using the one-factor-at-a-time method. APJPA was characterized by FESEM images showing that APJPA exhibits a smooth surface devoid of pores. FTIR spectra confirmed the presence of -C-O, C–H, C=C, and -COOH bonds within the APJPA. Maximum removal was recorded with 6.5 mg/100 mL of APJAP dosage, pH 6.5, after 35 min and with 25 mg/100 mL of CFX, at which the predicted and actual adsorption were 96.08 and 98.25%, respectively. The simulation results show that the dosage of APJAP exhibits a high degree of influence on the maximum adsorption of CFX removal (100%) between 2 and 8 mg dose/100 mL. The highest adsorption capacity of APJAP was 384.62 mg CFX/g. The simulation for the effect of pH determined that the best pH for the CFX adsorption lies between pH 5 and 8. |
| first_indexed | 2024-03-09T05:39:46Z |
| format | Article |
| id | doaj.art-159e1bbb690c40f08bb65b817954e3cb |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T05:39:46Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-159e1bbb690c40f08bb65b817954e3cb2023-12-03T12:25:26ZengMDPI AGWater2073-44412022-07-011414224310.3390/w14142243Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model StudyAdel Ali Al-Gheethi0Mohammad Shafiq Mohd Salleh1Efaq Ali Noman2Radin Maya Saphira Radin Mohamed3Rich Crane4Rafidah Hamdan5Mu. Naushad6Department of Civil Engineering, Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat 86400, MalaysiaDepartment of Civil Engineering, Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat 86400, MalaysiaDepartment of Civil Engineering, Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat 86400, MalaysiaDepartment of Civil Engineering, Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat 86400, MalaysiaCamborne School of Mines, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QD, UKDepartment of Civil Engineering, Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat 86400, MalaysiaDepartment of Chemistry, College of Science, King Saud University (KSU), Riyadh P.O. Box 2455, Saudi ArabiaCephalexin (CFX) residues in the environment represent a major threat to human health worldwide. Herein we investigate the use of novel approaches in deep learning in order to understand the mechanisms and optimal conditions for the sorption of cephalexin in water onto an acidic pretreated jackfruit peel adsorbent (APJPA). The interaction between the initial concentration of CFX (10–50 mg/100 mL), APJAP dosage (3–10 mg/100 mL), time (10–60 min), and the pH (4–9), was simulated using the one-factor-at-a-time method. APJPA was characterized by FESEM images showing that APJPA exhibits a smooth surface devoid of pores. FTIR spectra confirmed the presence of -C-O, C–H, C=C, and -COOH bonds within the APJPA. Maximum removal was recorded with 6.5 mg/100 mL of APJAP dosage, pH 6.5, after 35 min and with 25 mg/100 mL of CFX, at which the predicted and actual adsorption were 96.08 and 98.25%, respectively. The simulation results show that the dosage of APJAP exhibits a high degree of influence on the maximum adsorption of CFX removal (100%) between 2 and 8 mg dose/100 mL. The highest adsorption capacity of APJAP was 384.62 mg CFX/g. The simulation for the effect of pH determined that the best pH for the CFX adsorption lies between pH 5 and 8.https://www.mdpi.com/2073-4441/14/14/2243adsorptioncephalexindeep learningoptimizationsimulation models |
| spellingShingle | Adel Ali Al-Gheethi Mohammad Shafiq Mohd Salleh Efaq Ali Noman Radin Maya Saphira Radin Mohamed Rich Crane Rafidah Hamdan Mu. Naushad Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study Water adsorption cephalexin deep learning optimization simulation models |
| title | Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study |
| title_full | Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study |
| title_fullStr | Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study |
| title_full_unstemmed | Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study |
| title_short | Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study |
| title_sort | cephalexin adsorption by acidic pretreated jackfruit adsorbent a deep learning prediction model study |
| topic | adsorption cephalexin deep learning optimization simulation models |
| url | https://www.mdpi.com/2073-4441/14/14/2243 |
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