Water contamination with paints causes a colour agent to the water that negatively affects the environment, organisms, and humans. Different physicochemical processes are applied for wastewater treatment; however, they have many drawbacks such as high cost, generating toxic waste, and non-effective at low concentrations. Adsorption is considered a promising technique for pollutant removal from polluted wastewater. Commercial activated carbon, nano-materials, and natural biological materials are used as adsorbents in adsorption. This chapter focuses on discussing the adsorption process, the factors affecting the adsorption, different adsorption materials, and the isothermal, kinetic, and thermodynamic models. © 2023 selection and editorial matter, Irene Samy Fahim and Lobna A. Said; individual chapters, the contributors.
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
A review of coagulation explaining its definition, mechanism, coagulant types, and optimization models; RSM, and ANN
The textile business is one of the most hazardous industries since it produces several chemicals, such as dyes, which are released into water streams with ef-fluents. For the survival of the planet’s life and the advancement of humanity, water is a crucial resource. One of the anthropogenic activities that pollute and consume water is the textile industry. Thus, the purpose of the current effort is to Apply coagulation as a Physico-chemical and biological treatment strat-egy with different techniques and mechanisms to treat the effluent streams of textile industries. The discharge of these effluents has a negative impact on the environment, marine life, and human health. Therefore, the treatment of these effluents before discharging is an important matter to reduce their adverse ef-fect. Many physico-chemical and biological treatment strategies for contaminants removal from polluted wastewater have been proposed. Coagulation is thought to be one of the most promising physico-chemical strategies for removing con-taminants and colouring pollutants from contaminated water. Coagulation is accompanied by a floculation process to aid precipitation, as well as the collection of the created sludge following the treatment phase. Different commercial, and natural coagulants have been applied as a coagulants in the process of coagulation. Additionally, many factors such as; pH, coagulant dose, pollu-tants concentration are optimized to obtain high coagulants removal capacity. This review will discuss the coagulation process, coagulant types and aids in addition to the factors affecting the coagulation process. Additionally, a brief comparison between the coagulation process, and the other processes; princi-ple, advantages, disadvantages, and their efficiency were discussed throgh the review. Furthermore, it discusses the models and optimization techniques used for the coagulation process including response surface methodology (RSM), ar-tificial neural network (ANN), and several metaheuristic algorithms combined with ANN and RSM for optimization in previous work. The ANN model has more accurate results than RSM. The ANN combined with genetic algorithm gives an accurate predicted optimum solution. © 2023 The Authors
Crystal violet removal using bimetallic Fe0–Cu and its composites with fava bean activated carbon
Nano zero-valent iron (nZVI), bimetallic nano zero-valent iron-copper (Fe0– Cu), and fava bean activated carbon-supported bimetallic nano zero-valent iron-copper (AC-Fe0-Cu) are synthesized and characterized using DLS, zeta potential, FT-IR, XRD, and SEM. The maximum removal capacity is demonstrated by bimetallic Fe0–Cu, which is estimated at 413.98 mg/g capacity at pH 7, 180 min of contact duration, 120 rpm shaking speed, ambient temperature, 100 ppm of C.V. dye solution, and 1 g/l dosage. The elimination capability of the H2SO4 chemical AC-Fe0-Cu adsorbent is 415.32 mg/g under the same conditions but with a 150 ppm C.V. dye solution. The H3PO4 chemical AC-Fe0-Cu adsorbent achieves a removal capacity of 413.98 mg/g under the same conditions with a 350 ppm C.V. dye solution and a 1.5 g/l dosage. Optimal conditions for maximum removal efficiency are determined by varying pH (3–9), time intervals (15–180 min), and initial dye concentrations (25–1000 ppm). Kinetic and isothermal models are used to fit the results of time and concentration experiments. The intra-particle model yields the best fit for bimetallic Fe0–Cu, H2SO4 chemical AC- Fe0–Cu, and H3PO4 chemical AC-Fe0-Cu, with corrected R-Squared values of 0.9656, 0.9926, and 0.964, respectively. The isothermal results emphasize the significance of physisorption and chemisorption in concentration outcomes. Response surface methodology (RSM) and artificial neural networks (ANN) are employed to optimize the removal efficiency. RSM models the efficiency and facilitates numerical optimization, while the ANN model is optimized using the moth search algorithm (MSA) for optimal results. © 2023
Preparation and Characterization of nZVI, Bimetallic Fe 0-Cu, and Fava Bean Activated Carbon-Supported Bimetallic AC-F e 0-Cu for Anionic Methyl Orange Dye Removal
Nano zero-valent iron (nZVI), bimetallic Nano zero-valent iron-copper (Fe 0- Cu), and fava bean activated carbon-supported with bimetallic Nano zero-valent iron-copper (AC-F e 0-Cu) were prepared and characterized by DLS, FT-IR, XRD, and SEM. The influence of the synthesized adsorbents on the adsorption and removal of soluble anionic methyl orange (M.O) dye was investigated using UV-V spectroscopy. The influence of numerous operational parameters was studied at varied pH (3–9), time intervals (15–180 min), and dye concentrations (25–1000 ppm) to establish the best removal conditions. The maximum removal efficiency of M.O. using the prepared adsorbent materials reached about 99%. The removal efficiency is modeled using response surface methodology (RSM). The Bimetallic Fe -Cu, the best experimental and predicted removal efficiency is 96.8% RE. For the H2SO4 chemical AC- Fe -Cu, the best experimental and removal efficiency is 96.25% RE. The commercial AC-Fe0–Cu, the best experimental and predicted removal efficiency is 94.93%RE. This study aims to produce low-cost adsorbents such as Bimetallic Fe0-Cu, and Fava Bean Activated Carbon-Supported Bimetallic AC-Fe0-Cu to treat the industrial wastewater from the anionic methyl orange (M.O) dye and illustrate its ability to compete H2SO4 chemical AC-Fe0-Cu, and commercial AC-Fe0-Cu. © 2023, The Author(s).
Artificial Neural Network Chaotic PRNG and simple encryption on FPGA
Artificial Neural Networks (ANNs) are remarkably able to fit complex functions, making them useful in various applications and systems. This paper uses ANN to fit the Pehlivan–Uyaroglu Chaotic System (PUCS) to produce an Artificial Neural Network Chaotic Pseudo-Random Number Generator (ANNC-PRNG). The proposed PRNG imitates the PUCS chaotic system’s properties and attractor shape. The proposed ANNC-PRNG is implemented in a simple image encryption system on the Xilinx Kintex-7 Genesys 2 Field Programmable Gate Array (FPGA) board. Hardware realization of an ANN trained on chaotic time series has not been presented before. The proposed ANN can be used for different numerical methods or chaotic systems, including fractional-order systems while keeping the same resources despite the methodsÂ’ complexity or chaotic systemsÂ’ complexity. Extensive testing for the ANNC-PRNG was done to prove the randomness of the produced outputs. The proposed ANNC-PRNG and the encryption system passed various well-established security and statistical tests and produced good results compared to recent similar research. The encryption system is robust against different attacks. The proposed hardware architecture is fast as it reaches a maximum frequency of 12.553 MHz throughput of 301 Mbit/s. © 2023 Elsevier Ltd
An Efficient Multi-Secret Image Sharing System Based on Chinese Remainder Theorem and Its FPGA Realization
Multi-Secret Image Sharing (MSIS) is important in information security when multiple images are shared in an unintelligible form to different participants, where the images can only be recovered using the shares from participants. This paper proposes a simple and efficient ( n,n )-MSIS system for colored images based on XOR and Chinese Remainder Theorem (CRT), where all the n share are required in the recovery. The system improves the security by adding dependency on the input images to be robust against differential attacks, and by using several delay units. It works with even and odd number of inputs, and has a long sensitive system key design for the CRT. Security analysis and a comparison with related literature are introduced with good results including statistical tests, differential attack measures, and key sensitivity tests as well as performance analysis tests such as time and space complexity. In addition, Field Programmable Gate Array (FPGA) realization of the proposed system is presented with throughput 530 Mbits/sec. Finally, the proposed MSIS system is validated through software and hardware with all statistical analyses and proper hardware resources with low power consumption, high throughput and high level of security. © 2013 IEEE.
Ternary SRAM circuit designs with CNTFETs
Static random-access memory (SRAM) is a cornerstone in modern microprocessors architecture, as it has high power consumption, large area, and high complexity. Also, the stability of the data in the SRAM against the noise and the performance under the radian exposure are main concern issues. To overcome these limitations in the quest for higher information density by memory element, the ternary logic system has been investigated, showing promising potential compared with the conventional binary base. Moreover, carbon nanotube field effect transistor (CNTFET) is a new alternative device with proper features like low power consumption and threshold voltage dependency on diameter. This paper proposes a new design for ternary SRAM using CNTFET and its evaluation by comparing it against two other designs in many aspects. Moreover, we investigated the static noise margin for the three designs to discuss their stability. Furthermore, we studied the reliability of the designs by evaluating the soft errors effect. © 2023 John Wiley & Sons Ltd.
High-performance fractional anisotropic diffusion filter for portable applications
Anisotropic diffusion is one of the most effective methods used in image processing. It can be used to eliminate the small textures of an image while preserving its significant edges. In this paper, a new anisotropic diffusion filter is proposed based on a fractional calculus kernel rather than integer kernel to improve the overall performance of the filter. Integer and fractional anisotropic filters are implemented using the Genesys-2 FPGA kit to utilize the efficiency of parallelism in FPGAs. Integer and fractional anisotropic filters are tested against the achievable PSNR value vs the number of iterations. The proposed fractional anisotropic filter has a better PSNR value using a smaller number of iterations, reducing the power and area compared to integer anisotropic filter. The proposed filter can be used in image smoothing, edge detection, image segmentation, image denoising, and cartooning. In addition, the proposed filter reduces the power consumption by 58.2% compared to integer-order filters, which makes the proposed filter suitable for battery-based applications. © 2023, The Author(s).
On the Design Flow of the Fractional-Order Analog Filters Between FPAA Implementation and Circuit Realization
This work explicitly states the design flows of the fractional-order analog filters used by researchers throughout the literature. Two main flows are studied: the FPAA implementation and the circuit realization. Partial-fraction expansion representation is used to prepare the approximated fractional-order response for implementation on FPAA. The generalization of the second-order active RC analog filters based on opamp from the integer-order domain to the fractional-order domain is presented. The generalization is studied from both mathematical and circuit realization points of view. It is found that the great benefit of the fractional-order domain is that it adds more degrees of freedom to the filter design process. Simulation and experimental results match the expected theoretical analysis. © 2013 IEEE.