Adsorbent Materials for Water Treatment: Innovations in Pollutant Removal

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Environmental and Green Processes".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 791

Special Issue Editors


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Chemical Engineering Department, State University of Maringá, Maringá 87020-900, PR, Brazil
Interests: environmental preservation; water treatment process
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Guest Editor
Postgraduate Program in Chemical Engineering/Department of Chemical Engineering, Universidade Tecnológica Federal do Paraná, St. Doutor Washington Subtil Chueire, 330 - Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil
Interests: adsorption; water treatment; material synthesis

Special Issue Information

Dear Colleagues,

The quest for innovative water treatment solutions, particularly pollutant removal, has led to significant advancements in developing adsorbent materials. This Special Issue of "Adsorbent Materials for Water Treatment: Innovations in Pollutant Removal" aims to provide a comprehensive overview of the latest research and innovations in this field.

Key Highlights:

  1. Nanotechnology: the utilization of nanotechnology has been a game-changer, with nanoparticles demonstrating exceptional adsorption capacities due to their high surface-area-to-volume ratios, making them ideal for water purification.
  2. Electrochemical and Sorption Methods: these techniques have proven to be effective for the removal of a wide range of pollutants. Electrochemical processes can induce pollutant degradation, while sorption methods capture contaminants through physical or chemical interactions.
  3. Hybrid Systems: the synergy of combining different treatment methods, such as adsorption with biological processes or membrane filtration, enhances the overall efficiency of pollutant removal.
  4. Green Remediation: there is a growing emphasis on sustainable approaches that minimize environmental impacts, utilizing bioremediation and phytoremediation strategies that are both effective and eco-friendly.
  5. Machine Learning and AI: the integration of machine learning and artificial intelligence in adsorption processes has led to better prediction models for pollutant behavior and the optimization of treatment conditions.
  6. Emerging Adsorbent Materials: the exploration of new materials such as biochar, metal–organic frameworks (MOFs), magnetic materials, and carbon nanotubes has opened up new avenues for efficient pollutant capture and removal.
  7. Starch-Based Adsorbents: as a renewable resource, starch and its derivatives have been modified to enhance their adsorption properties, offering a cost-effective and biodegradable solution for water treatment.
  8. Bioadsorption: the use of biological materials for adsorption has gained traction due to their natural affinity for certain pollutants and their low environmental impact.
  9. Regeneration and Recycling: focusing on the reuse of spent adsorbents, researchers are developing regeneration techniques to reduce waste and treatment costs, promoting a circular economy in water treatment.
  10. Interdisciplinary Approaches: the complexity of water treatment demands collaboration across multiple disciplines, fostering innovation through the cross-pollination of ideas and technologies.

This Special Issue showcases the latest findings in adsorbent materials for water treatment, highlighting the innovative approaches that are driving the field forward. As the world confronts increasing water pollution challenges, these innovations are crucial for developing sustainable and effective water treatment solutions.

Dr. Maria Angélica Simões Dornellas Barros
Dr. Thiago Peixoto De Araújo
Guest Editors

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Keywords

  • adsorbent materials
  • water treatment
  • pollutant removal
  • nanotechnology
  • electrochemical methods
  • sorption technologies
  • hybrid treatment systems
  • green remediation
  • metal–organic frameworks (MOFs)
  • magnetic materials
  • starch-based adsorbents
  • bioadsorption

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Published Papers (1 paper)

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Research

24 pages, 6888 KiB  
Article
Methylene Blue Removal Using Activated Carbon from Olive Pits: Response Surface Approach and Artificial Neural Network
by Tijen Over Ozcelik, Esra Altintig, Mehmet Cetinkaya, Dilay Bozdag Ak, Birsen Sarici and Asude Ates
Processes 2025, 13(2), 347; https://doi.org/10.3390/pr13020347 - 27 Jan 2025
Viewed by 642
Abstract
This study evaluated the efficiency of methylene blue (MB) removal by using activated carbon produced from olive pits. The activated carbon (OPAC) was characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET). The adsorption process was optimized in two [...] Read more.
This study evaluated the efficiency of methylene blue (MB) removal by using activated carbon produced from olive pits. The activated carbon (OPAC) was characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET). The adsorption process was optimized in two stages using factorial design. Based on the existing literature, the first stage selected the most influential variables (reaction time, dosage, pH, and dye concentration). Response surface methodology (RSM) and artificial neural network (ANN) approaches have been combined to optimize and model the adsorption of MB. To assess the optimal conditions for MB adsorption, RSM was initially applied using four controllable operating parameters. Throughout the optimization process, various independent variables were employed, including initial dye concentrations ranging from 25 to 125 mg/L, adsorbent dosages ranging from 0.1 to 0.9 g/L, pH values spanning from 1 to 9, and contact times ranging from 15 to 75 min. Moreover, the R2 value (R2 = 0.9804) indicates that regression can effectively forecast the response of the adsorption process within the examined range. Thermodynamic studies were performed for three different temperatures between 293 and 303 K. Isothermal analysis parameters and negative Gibbs free energy indicate that the process is spontaneous and favorable. The data best fit the Langmuir model. This research showcases the effectiveness of optimizing and predicting the color removal process through the combined RSM-ANN approach. It highlights the effectiveness of adsorption using OPAC as a viable primary treatment method for the removal of color from wastewater-containing dyes. Full article
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