Sorption, kinetic, thermodynamics and artificial neural network modelling of phenol and 3-amino-phenol in water on composite iron nano-adsorbent

Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective

The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency and sustainability of wastewater treatment plants (WWTPs). This paper explores the application of ANN-based models in WWTPs, focusing on the latest published research work, by presenting the effectiveness of ANNs in predicting, estimating, and treatment of diverse types of wastewater. Furthermore, this review comprehensively examines the applicability of the ANNs in various processes and methods used for wastewater treatment, including membrane and membrane bioreactors, coagulation/flocculation, UV-disinfection processes, and biological treatment systems. Additionally, it provides a detailed analysis of pollutants viz organic and inorganic substances, nutrients, pharmaceuticals, drugs, pesticides, dyes, etc., from wastewater, utilizing both ANN and ANN-based models. Moreover, it assesses the techno-economic value of ANNs, provides cost estimation and energy analysis, and outlines promising future research directions of ANNs in wastewater treatment. AI-based techniques are used to predict parameters such as chemical oxygen demand (COD) and biological oxygen demand (BOD) in WWTP influent. ANNs have been formed for the estimation of the removal efficiency of pollutants such as total nitrogen (TN), total phosphorus (TP), BOD, and total suspended solids (TSS) in the effluent of WWTPs. The literature also discloses the use of AI techniques in WWT is an economical and energy-effective method. AI enhances the efficiency of the pumping system, leading to energy conservation with an impressive average savings of approximately 10%. The system can achieve a maximum energy savings state of 25%, accompanied by a notable reduction in costs of up to 30%.

State-of-art advances on removal, degradation and electrochemical monitoring of 4-aminophenol pollutants in real samples: A review

p_Aminophenol, namely 4-aminophenol (4-AP), is an aromatic compound including hydroxyl and amino groups contiguous together on the benzene ring, which are suitable chemically reactive, amphoteric, and alleviating agents in nature. Amino phenols are appropriate precursors for synthesizing oxazoles and oxazines. However, since the toxicity of aniline and phenol can harm human and herbal organs, it is essential to improve a reliable technique for the determination of even a trace amount of amino phenols, as well as elimination or (bio)degradation/photodegradation of it to protect both the environment and people's health. For this purpose, various analytical methods have been suggested up till now, including spectrophotometry, liquid chromatography, spectrofluorometric and capillary electrophoresis, etc. However, some drawbacks such as the requirement of complex instruments, high costs, not being portable, slow response time, low sensitivity, etc. prevent them to be employed in a wide range and swift in-situ applications. In this regard, besides the efforts such as (bio)degradation/photodegradation or removal of 4-AP pollutants from real samples, electroanalytical techniques have become a promising alternative for monitoring them with high sensitivity. In this review, it was aimed to emphasize and summarize the recent advances, challenges, and opportunities for removal, degradation, and electrochemical sensing 4-AP in real samples. Electroanalytical monitoring of amino phenols was reviewed in detail and explored the various types of electrochemical sensors applied for detecting and monitoring in real samples. Furthermore, the various technique of removal and degradation of 4-AP in industrial and urban wastes were also deliberated. Moreover, deep criticism of multifunctional nanomaterials to be utilized as a catalyst, adsorbent/biosorbent, and electroactive material for the fabrication of electrochemical sensors was covered along with their unique properties. Future perspectives and conclusions were also criticized to pave the way for further studies in the field of application of up-and-coming nanostructures in environmental applications.

Water and wastewater quality prediction: current trends and challenges in the implementation of artificial neural network

Traditional freshwater supplies have been over-abstracted in the current global problem of water scarcity. Through the analysis of complex experimental and real-time data, to improve the activity of water and wastewater treatment (WWT) systems, an artificial neural network (ANN), a computational model inspired by the human brain, and its variants were created. This review paper focuses on recent trends and advances in modeling and simulating different water and wastewater systems using ANN. This study uses ANN in watershed management, impurity removal from wastewater, and wastewater treatment plants. According to the literature review, ANN can predict nonlinear, linear, and complex systems with high accuracy and well control. Finally, the limitations and future scope of ANNs were discussed. ANN proved itself in the prediction of various water and WWT processes. Still, implementation has practical challenges, which include a lack of data availability, poorly built models, timely updates in developed models, and low repeatability. The use of a proper toolbox, faster computing power, and proper domain knowledge makes the practical implementation of ANN successful. As a result, ANN can build a solid foundation for attracting and motivating investigators to work in this region in the forthcoming.

Microwave assist sorption of crystal violet and Congo red dyes onto amphoteric sorbent based on upcycled Sepia shells

A new sorbent based on Sepia shells (cuttlefish bones) has been synthesized (SSBC) and tested for the sorption of cationic dye (crystal violet, CV) and an anionic dye (congo red, CR). SSBC was produced by reaction of sepia shells powder with urea in the presence of formaldehyde. In the first part of the work, the sorbent was characterized using scanning electron microscopy, energy dispersive X-ray analysis, Fourier-transform infra-red spectrometry and titration (for determining pH_PZC). In a second step, sorption properties were tested on the two dyes through the study of pH effect, sorbent dosage, temperature and ionic strength; the sorption isotherms and uptake kinetics were analyzed at the optimum pH: Langmuir equation fits isotherm profiles while the kinetic profile can be described by the pseudo-second order rate equation. Maximum sorption capacities reach up to 0.536 mmol g^-1 for CV and 0.359 mmol g^-1 for CR, at pH 10.6 and 2.4, respectively. The comparison of sorption properties at different temperatures shows that the sorption is endothermic. Processing to the sorption under microwave irradiation (microwaved enforced sorption, MES) increases mass transfer and a contact time as low as 1 min is sufficient under optimized conditions (exposure time and power) reaching the equilibrium, while 2-3 h were necessary for "simple" sorption. Dye desorption was successfully tested using 0.5 M solutions of NaOH and HCl for the removal of CR and CV, respectively. The sorbent can be re-used for a minimum of four cycles of sorption/desorption. Finally, the sorbent was successfully tested on spiked tap water and real industrial wastewater.