Authors:
- James Carter, Department of Civil Engineering, Green Valley University, P.O. Box 1988, Green Valley Road, USA.
- Emily Tran, Institute of Sustainable Development, Coastal University, Coastal City, USA.
- David O’Connor, Engineering Department, Urban University, Urban City, USA.
- Sophia Liu, Department of Chemical Engineering, Tech University, Tech City, USA.
- William Smith, Environmental Science Department, National University, City Center, USA.
- Olivia Brown, Geo Innovations, City Park, USA.
- Daniel Johnson, Space Science Institute, Space City, USA.
- Mia Davis, Rivers Research Institute, Griffith University, Griffith City, Australia.
- Noah Martinez, Biotechnology Engineering Department, Global University, Global City, USA.
Abstract:
This study explores the effectiveness of rice husk char (RHC4) in adsorbing copper ions (Cu(II)) from aqueous solutions. To assess the properties of RHC4, a variety of physicochemical tests were conducted, including Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), and Brunauer-Emmett-Teller (BET) surface area analysis, among others. The research examined how different operational parameters—such as pH levels, contact time, Cu(II) concentration, and RHC4 dosage—influence the adsorption efficiency. Optimal conditions for maximum adsorption were identified at a contact time of 120 minutes, a pH of 6, and a dosage of 8 g/L of RHC4.
Using an artificial neural network (ANN), the study accurately predicted the percentage of Cu(II) adsorption, with the Fletcher-Reeves conjugate gradient backpropagation algorithm demonstrating the highest accuracy (mean squared error of 3.84 and R² value of 0.989). The results indicated that the adsorption process conformed to the pseudo-second-order kinetic model, suggesting a chemical adsorption mechanism. Initial adsorption occurred through boundary layer processes, followed by intraparticle diffusion. The adsorption data fit well with both Langmuir and Freundlich isotherm models, indicating high capacity and intensity. Thermodynamic assessments confirmed that the adsorption of Cu(II) onto RHC4 was a spontaneous process. The adsorption capacity of RHC4 shows promise in comparison with other agricultural waste-based adsorbents, highlighting its potential for effective Cu(II) removal from wastewater.
Keywords:
adsorption; artificial neural network; heavy metal removal; rice husk char.
Summary:
To Summarize: This research highlights the potential of rice husk char as a viable adsorbent for Cu(II) removal from water, utilizing advanced modeling techniques such as ANN to optimize the process. For further insights into related topics, consider exploring our other blog post on medical cannabis and obstructive sleep apnea. Additionally, you can find authoritative information from NHLBI regarding the implications of snoring on health. For those seeking practical solutions, check out the Snorple anti-snoring mouthpiece, noted for its effectiveness right from the first night.