Experimental investigation of methyl-orange removal using eco-friendly cost-effective materials raw fava bean peels and their formulated physical, and chemically activated carbon

The discharge of effluents from dye industries into water streams poses a significant environmental and public health risk. In response, eco-friendly adsorbents derived from agricultural waste, such as Fava Bean Peels (R–FBP), have been investigated as potential materials for the removal of such pollutants. In this study, R–FBP and their corresponding physical and chemically activated carbon (P-RFB-AC and C-FBP-AC) were synthesized using H3PO4 acid and characterized using FT-IR, and SEM analyses. An optimization process was conducted to determine the optimum conditions for achieving high Methyl Orange (M. Orange) removal efficiencies using the prepared materials, namely R–FBP, P-RFB-AC, and C-FBP-AC. The adsorption mechanism was examined by analyzing the isotherm and kinetics. The results revealed that the physical raw-activated carbon exhibited the highest removal efficiency of 96.8% compared to other materials. This outcome was achieved through the use of ANN combined with Moth Search Algorithm (MSA), which was found to be the most effective model for achieving the highest M. Orange removal efficiency from Physical raw fava bean activated carbon. Under parameters of 1000 mg/l M. Orange concentration, 2 g/l dose, 15 min contact time, and 120 rpm shaking, the best experimental and predicted removal efficiencies for physical-activated carbon fava bean rind were 96.8 RE%, 96.01 indicated RSM RE%, and 95.75 predicted ANN RE%. The highest experimental and predicted removal efficiencies for the H3PO4 chemical activated carbon fava bean peel were 94%RE. This study aimed to develop an economical solution for treating industrial wastewater contaminated with anionic M. Orange dye using raw fava bean peel and their generated activated carbon, in both physical and chemical forms. The Temkin and Langmuir isotherm models were found to best fit the data for raw fava bean peel, while Temkin agreed well with the data from physical-activated carbon. Temkin and Freundlich’s models were fitted with the H3PO4 chemical activated carbon. Pseudo-second-order kinetics was identified as the most suitable model for both physically and chemically activated carbons. Future research may explore the capacity of the produced activated carbon-based algae to extract a wider range of contaminants from contaminated wastewater. In summary, this work contributes to the development of eco-friendly and cost-effective methods for removing dyes, specifically M. Orange, from industrial effluents. By synthesizing and characterizing R–FBP and their relative activated carbon, the adsorption mechanism was studied, and the optimum conditions for achieving high M. Orange removal efficiencies were determined. The results showed that physical raw-activated carbon exhibited the highest removal efficiency, and pseudo-second-order kinetics was the most suitable model for both physically and chemically activated carbon. © 2023 The Authors

Potentials of algae-based activated carbon for the treatment of M.orange in wastewater

Activated carbon is a promising material with high efficiency in dye removal from polluted wastewater. However, commercial activated carbon is expensive and generates black color in the medium. Therefore, searching for low-cost, eco-friendly activated carbon sources such as agricultural wastes and algal biomasses is essential. Hence, this study is directed to prepare the physical and the H3PO4 chemical activated carbon from the algae ”Sargassum dent folium” and the raw algae itself and apply it for Methyl Orange (M. orange) removal from contaminated wastewater and compare its performance with the commercial activated carbon. First, adsorbent materials are prepared and involved in the optimization process for M. orange removal using some preliminary experiments, followed by Response Surface Method-ology (RSM) and Artificial Neural Network (ANN). Finally, Isotherm and kinetics are studied to explain the adsorption mechanism. In contrast to other materials, results show that physical algae-activated carbon achieves the maximum removal efficiency of 96.687%. These results are obtained from ANN combined with Moth Search Algorithm (MSA), representing the most effective model for achieving the highest M. orange removal efficiency from Physical algae activated carbon. In the algae case, the best experimental and predicted removal efficiencies are 85.9407 RE%, 88.5 indicated RSM RE%, and 85.9431 predicted ANN RE%. The best observed and predicted removal efficiencies for the H3PO4 chemical activated carbon are 89.6157 RE%, 82.38 predicted RSM RE%, and 89.5442 predicted ANN RE%. The best experimental and predicted removal efficiencies for the physical-activated carbon are 94.7935 RE%, 95.49 indicated RSM RE%, and 95.4298 predicted ANN RE%. The best observed and predicted removal efficiencies for the commercial-activated carbon are 92.2659 RE%, 96.65 predicted RSM RE%, and 92.2658 predicted ANN RE%. In the algae case, the best experimental and predicted removal efficiencies are 85.9407 %RE, 88.5 predicted RSM RE %, and 85.9431 expected ANN RE%. For the H3PO4 chemical activated carbon, the best experimental and predicted removal efficiencies are 89.6157%RE, 82.38 indicated RSM RE%, and 89.5442 predicted ANN RE%. For the physical-activated carbon, the best observed and predicted removal efficiencies are 94.7935 %RE, 95.49 predicted RSM RE%, and 95.4298 indicated ANN RE%. For the commercial-activated carbon, the best experimental and predicted removal efficiencies are 92.2659 %RE, 96.65 predicted RSM RE%, and 92.2658 predicted ANN RE%. This study intends to treat industrial wastewater contaminated with the anionic M. orange dye using raw algae and their generated activated carbon (physical and chemical forms), which are economical. It then compares the results to the effectiveness of commercial activated carbon. In the state of the raw algae, Temkin and Langmuir isotherm models best suit the data, while Temkin agrees well with the data from physical-activated carbon. Temkin and Freundlich’s models are fitted with the H3PO4 chemical activated carbon. The model that fits the raw algae physically activated carbon and H3PO4 chemical-activated carbon the best is pseudo-second-order kinetics. Future research could examine the produced activated carbon-based algae’s capacity to extract more contaminants from contaminated wastewater. This study intends to treat industrial wastewater contaminated with the anionic M. orange dye using raw algae and their generated activated carbon (physical and chemical forms), which are economical. It next compares the results to the effectiveness of commercial activated carbon. © 2023 The Authors

Review of activated carbon adsorbent material for textile dyes removal: Preparation, and modelling

Water contamination with colours and heavy metals from textile effluents has harmed the ecology and food chain, with mutagenic and carcinogenic effects on human health. As a result, removing these harmful chemicals is critical for the environment and human health. Various standard physicochemical and biological treatment technologies are used; however, there are still some difficulties. Adsorption is described as a highly successful technology for removing contaminants from textile-effluents wastewater compared to other methods. Several adsorbent materials, including nanomaterials, natural materials, and biological biomasses, are identified as effective adsorbents for textile effluents. Activated carbon preparation from these different adsorbents is an excellent pre-treatment to remove the adsorption capacity. Therefore, through this study various adsorbent types, especially activated carbon adsorbents will be discussed in addition to the factors affecting adsorption and models applied for optimising the adsorption process. © 2022

Modified fractional-order model for biomass degradation in an up-flow anaerobic sludge blanket reactor at Zenein Wastewater Treatment Plant

This paper presents a modified fractional-order model (FOM) for microorganism stimulation in an up-flow anaerobic sludge blanket (UASB) reactor treating low-strength wastewater. This study aimed to examine the famine period of methanogens due to biomass accumulation in the UASB reactor over long time periods at a constant organic loading rate (OLR). This modified model can investigate the substrate biodegradation in a UASB reactor while considering substrate diffusion into biological granules during the feast and famine periods of methanogens. The Grünwald-Letnikov numerical technique was used to indicate the effect of biomass degradation on the biogas production rate and substrate biodegradation in a UASB reactor installed at Zenein Wastewater Treatment Plant (WWTP) in Giza, Egypt. Several fractional orders were applied in the dynamic model at biomass concentrations of 20 and 4 kg/ m3 in the reactor bed and blanket zones, respectively. An OLR of 0.9 kgCOD/ m3/ day using the calibrated kinetic parameters at 11 ?C was applied to comply with the experimental outcomes. The simulation results indicate that the removal efficiency of chemical oxygen demand (COD) was maintained at approximately 55 – 65 % , whereas the biogas production rate declined from 0.35 to 0.05 m3CH4/ kgCODr in the reactor bed zone due to a decline in food to microorganism (F/M) ratio from 0.04 to 0.018 d- 1 during the sludge retention time (SRT) in the UASB reactor. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Parameter Identification of Li-ion Batteries: A Comparative Study

Lithium-ion batteries are crucial building stones in many applications. Therefore, modeling their behavior has become necessary in numerous fields, including heavyweight ones such as electric vehicles and plug-in hybrid electric vehicles, as well as lightweight ones like sensors and actuators. Generic models are in great demand for modeling the current change over time in real-time applications. This paper proposes seven dynamic models to simulate the behavior of lithium-ion batteries discharging. This was achieved using NASA room temperature random walk discharging datasets. The efficacy of these models in fitting different time-domain responses was tested through parameter identification with the Marine Predator Algorithm (MPA). In addition, each model’s term’s impact was analyzed to understand its effect on the fitted curve. The proposed models show an average absolute normalized error as low as (Formula presented.). © 2023 by the authors.

Discrete fractional-order Caputo method to overcome trapping in local optima: Manta Ray Foraging Optimizer as a case study

Enhancing the exploration and exploitation phases of the metaheuristic (MH) optimization algorithms is the key to avoiding local optima. The Manta ray foraging optimizer is a recently proposed MH optimizer. The MRFO showed a good performance in the simple optimization problems. However, it is trapped into the local optimum in the more elaborated ones due to the original algorithm’s low capability in exploiting the optimal solutions and its convergence. From this principle, in this work, a novel variant of the Manta ray foraging optimizer has been proposed for global optimization problems, engineering design optimization problems, and multi-threshold segmentation. In the proposed approach, the fractional calculus (FC) using Caputo fractional differ-sum operator has been adopted to enhance the manta rays movement in the exploitation phase via utilizing history dependency of FC to boost exploiting the optimal solutions via sharing the past knowledge over the optimization process. Moreover, to avoid premature convergence, the somersault factor has been adaptively tuned. The fractional-order Caputo Manta-Ray Foraging Optimizer (FCMRFO) has been proposed. The proposed algorithm’s sensitivity for the FC coefficients has been tested with ten-dimensional CEC2017 benchmarks. The scalability test of the proposed algorithm has been performed with 30, 50 and 100-dimensional CEC2017. Moreover, CEC2020 benchmarks with dimensions 5 and 20 have been applied for providing an extensive investigation, and the FCMRFO has been compared with recent state-of-the-art algorithms. Through utilizing the non-parametric statistical analysis and ranking test, the FCMRFO confirms its superiority and ability to avoid the local optimum in several cases. For the second part of the study, three constrained engineering design problems have been investigated; then, numerous natural images are applied to appraise the FCMRFO for multilevel threshold image segmentation. By performing several metrics, the FCMRFO proves its quality and efficiency compared to recent well-regarded algorithms in engineering applications and image segmentation. © 2021

Arithmetic optimization approach for parameters identification of different PV diode models with FOPI-MPPT

The Maximum Power Point Tracker (MPPT) provides the most efficient use of a Photo-voltaic system independent of irradiance or temperature fluctuations. This paper introduces the modeling and control of a photo-voltaic system operating at MPPT using the arithmetic optimization algorithm (AOA). The single and double Photo-voltaic models are investigated. Their optimal unknown parameters are extracted using AOA based on commercial Photo-voltaic datasheets. A comparison is performed between these optimal parameters extracted by AOA and other optimization techniques presented in the literature. These parameters generate the P – V and I – V curves for the studied models considering the temperature factor. A good match is achieved relative to the manufacturer data. A DC-DC boost converter is used as a link between the PV modules and the load. The converter duty cycle is adjusted, varying the climatic conditions using three cases: without a controller, using PI controller, and using the fractional-order PI controller (FOPI). The AOA is employed to set the optimum controllers parameters to maintain the impedance matching between the PV modules and the load. The FOPI shows a significant improvement in controlling the system performance. © 2021 THE AUTHORS

An Encryption Application and FPGA Realization of a Fractional Memristive Chaotic System

The work in this paper extends a memristive chaotic system with transcendental nonlinearities to the fractional-order domain. The extended system’s chaotic properties were validated through bifurcation analysis and spectral entropy. The presented system was employed in the substitution stage of an image encryption algorithm, including a generalized Arnold map for the permutation. The encryption scheme demonstrated its efficiency through statistical tests, key sensitivity analysis and resistance to brute force and differential attacks. The fractional-order memristive system includes a reconfigurable coordinate rotation digital computer (CORDIC) and Grünwald–Letnikov (GL) architectures, which are essential for trigonometric and hyperbolic functions and fractional-order operator implementations, respectively. The proposed system was implemented on the Artix-7 FPGA board, achieving a throughput of 0.396 Gbit/s. © 2023 by the authors.

CORDIC-Based FPGA Realization of a Spatially Rotating Translational Fractional-Order Multi-Scroll Grid Chaotic System

This paper proposes an algorithm and hardware realization of generalized chaotic systems using fractional calculus and rotation algorithms. Enhanced chaotic properties, flexibility, and controllability are achieved using fractional orders, a multi-scroll grid, a dynamic rotation angle(s) in two- and three-dimensional space, and translational parameters. The rotated system is successfully utilized as a Pseudo-Random Number Generator (PRNG) in an image encryption scheme. It preserves the chaotic dynamics and exhibits continuous chaotic behavior for all values of the rotation angle. The Coordinate Rotation Digital Computer (CORDIC) algorithm is used to implement rotation and the Grünwald–Letnikov (GL) technique is used for solving the fractional-order system. CORDIC enables complete control and dynamic spatial rotation by providing real-time computation of the sine and cosine functions. The proposed hardware architectures are realized on a Field-Programmable Gate Array (FPGA) using the Xilinx ISE 14.7 on Artix 7 XC7A100T kit. The Intellectual-Property (IP)-core-based implementation generates sine and cosine functions with a one-clock-cycle latency and provides a generic framework for rotating any chaotic system given its system of differential equations. The achieved throughputs are (Formula presented.) Mbits/s and (Formula presented.) Mbits/s for two- and three-dimensional rotating chaotic systems, respectively. Because it is amenable to digital realization, the proposed spatially rotating translational fractional-order multi-scroll grid chaotic system can fit various secure communication and motion control applications. © 2022 by the authors.