Experimental and DFT investigation of ceria-nanocomposite decorated AC derived from groundnut shell for efficient removal of methylene-blue from wastewater effluent

Alshabib, Muntathir; Oluwadamilare, Musa Azeez; Tanimu, Abdulkadir; Abdulazeez, Ismail; Alhooshani, Khalid; Ganiyu, Saheed A.

doi:10.1016/j.apsusc.2020.147749

Cited by 52 publications

(13 citation statements)

References 89 publications

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“…Due to this, excited electrons easily migrate to NAD + /NADP + via Rh complex and efficiently regenerate NADH/NADPH coenzyme. This mechanism theoretically confirms the presence of Z‐scheme nature 63‐66 …”

Section: Resultssupporting

confidence: 76%

Solar light‐assisted rod‐shaped CPTF @ FACC photocatalyst: An efficient platform for oxygenation reactions and coenzymes regeneration

Chaubey

Singh

et al. 2022

Intl J of Energy Research

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Solar light active oxygenation reactions and coenzyme regenerations are play crucial role in the area of pharmaceutical industry. The highly selective and efficient synthesis of oxygen-containing molecules in an environmental friendly manner is challenging at both industrial and laboratory level. Here, we proposed a new synthetic approach for oxygenation reactions along with coenzyme regenerations using flexible-activated carbon cloth (FACC) oriented covalent (C) tetrakis(4-carboxyphenyl) porphyrin (P) and thiourea (T)-based framework (F), namely, CPTF@FACC photocatalyst. CPTF@FACC exhibits excellent solar light-harvesting ability, well-distinct photocatalytic centers, high molar extinction coefficient, excellent charge transport ability, and suitable optical band gap, which make the photocatalyst more efficient for oxygenation (sulfoxidation and epoxidation) reactions along with coenzyme regenerations. The oxygenation reactions were carried out in isopropyl alcohol via in situ production of hydrogen peroxide (H 2 O 2 ) under solar light using CPTF@FACC photocatalyst with high yields (~97%-98%). Finally, the CPTF@FACC photocatalyst also show a benchmark example in the coenzymes regeneration with high yields 81.1% and 73.1% for NADH and NADPH in 2 h, respectively.

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Section: Resultssupporting

confidence: 76%

Solar light‐assisted rod‐shaped CPTF @ FACC photocatalyst: An efficient platform for oxygenation reactions and coenzymes regeneration

Chaubey

Singh

et al. 2022

Intl J of Energy Research

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“…The environment is polluted by the wastewater collected from the industrial wastage and domestic purpose wastage. The wastewater treatment has been carried out in the different influent [25] Activated carbon from walnut cake using the fractional factorial design Activated carbon Aravind et.al (2021) [26] Using morphological operator for activated carbon for dye removal Activated carbon Alshabib et.al (2021) [27] Wastewater treatment using DFT in activated carbon Methylene-blue Wang et.al (2021) [28] Adsorption of dyes on an activated carbon Carbon Zhu et.al (2021) [29] Carbon-based materials adsorption Tetracycline and sulfamethoxazole Adsorption Science & Technology indicators to protect our environment. Therefore, wastewater treatment plants purify the polluted water and keep our environment clean and returned back our environment properly for the surveying of the human being.…”

Section: Review Of Literaturementioning

confidence: 99%

An Intelligent Carbon-Based Prediction of Wastewater Treatment Plants Using Machine Learning Algorithms

Hilal

Althobaiti

Eisa

et al. 2022

Adsorption Science & Technology

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Purification of polluted water and return back to the agriculture field is the wastewater treatment for plants. Contaminated water causes illness and health emergencies of public. Also, health risk due release of toxic contaminants brings problem to all living beings. At present, sensors are used in waste water treatment and transfer data via internet of things (IoT). Prediction of wastewater quality content which is presence of total nitrogen (T-N) and total phosphorous (T-P) elements, chemical oxygen demand (COD), biochemical demand (BOD), and total suspended solids (TSS) is associated with eutrophication that should be prevented. This may leads to algal bloom and spoils aquatic life which is consumed by human. The presence of nitrogen and phosphorous elements is in the content of wastewater, and these elements are associated with eutrophication which should be prevented. Adsorption of T-N and T-P activated carbon was predictable as one of the most promising methods for wastewater treatment. Many research works have been done. The issues are inefficiency in the prediction of wastewater treatment. To overcome this issue, this paper proposed fusion of B-KNN with the ELM algorithm that is used. The accuracy of the BKNN-ELM algorithm in classification of water quality status produced the highest accuracy of the highest accuracy which is K = 9 and k = 10 with rate of accuracy which is 93.56%, and the lowest accuracy is K = 1 of 65.34 % . Experiment evaluation shows that a total suspended solid predicted by proposed model is 91 with accuracy of 93%. The relative error rate of prediction is 12.03 which is lesser than existing models.

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“…The adsorption value data were collected directly from the tables or extracted from the Supplementary Material data and graphs with Getdata 2.21 in the published papers. Ultimately, 350 sets of adsorption experimental data of different dyes on the agro-waste AC were selected [ 15 , 16 , 22 , 25 , 26 , 30 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. Some of data were missing and needed to be deleted, because dealing with missing data could cause errors in our whole dataset.…”

Section: Methodsmentioning

confidence: 99%

“…Recently, agricultural wastes have received considerable attention due to their abundant surface functional groups, porous structures, additional inorganic minerals, and high surface area. Many researchers study the dyes’ adsorption on various agro-waste materials such as corn cobs [ 18 ], oil cake [ 19 ], rice husk [ 20 ], sugarcane bagasse [ 21 ], gram husk [ 22 ], sawdust [ 23 ], pine cone [ 24 ], tobacco residue [ 25 ], white sugar [ 26 ], Astragalus bisulcatus tree [ 27 ], tea residue [ 28 ], vinasse [ 29 ], groundnut shell [ 30 ], and so on. This class of activated carbons have a valuable potential for the wastewater dye removal.…”

Section: Introductionmentioning

confidence: 99%

A Study on Machine Learning Methods’ Application for Dye Adsorption Prediction onto Agricultural Waste Activated Carbon

et al. 2021

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The adsorption of dyes using 39 adsorbents (16 kinds of agro-wastes) were modeled using random forest (RF), decision tree (DT), and gradient boosting (GB) models based on 350 sets of adsorption experimental data. In addition, the correlation between variables and their importance was applied. After comprehensive feature selection analysis, five important variables were selected from nine variables. The RF with the highest accuracy (R2 = 0.9) was selected as the best model for prediction of adsorption capacity of agro-waste using the five selected variables. The results suggested that agro-waste characteristics (pore volume, surface area, agro-waste pH, and particle size) accounted for 50.7% contribution for adsorption efficiency. The pore volume and surface area are the most important influencing variables among the agro-waste characteristics, while the role of particle size was inconspicuous. The accurate ability of the developed models’ prediction could significantly reduce experimental screening efforts, such as predicting the dye removal efficiency of agro-waste activated carbon according to agro-waste characteristics. The relative importance of variables could provide a right direction for better treatments of dyes in the real wastewater.

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Experimental and DFT investigation of ceria-nanocomposite decorated AC derived from groundnut shell for efficient removal of methylene-blue from wastewater effluent

Cited by 52 publications

References 89 publications

Solar light‐assisted rod‐shaped CPTF @ FACC photocatalyst: An efficient platform for oxygenation reactions and coenzymes regeneration

Solar light‐assisted rod‐shaped CPTF @ FACC photocatalyst: An efficient platform for oxygenation reactions and coenzymes regeneration

An Intelligent Carbon-Based Prediction of Wastewater Treatment Plants Using Machine Learning Algorithms

A Study on Machine Learning Methods’ Application for Dye Adsorption Prediction onto Agricultural Waste Activated Carbon

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