Artificial intelligence-driven assessment of critical inputs for lead adsorption by agro-food wastes in wastewater treatment DOI Creative Commons
Zarifeh Raji, Isa Ebtehaj, Hossein Bonakdari

et al.

Chemosphere, Journal Year: 2024, Volume and Issue: 368, P. 143801 - 143801

Published: Nov. 1, 2024

Due to environmental concerns and economic value, the adsorption process using agricultural wastes is one of promising methods remove lead (Pb) from contaminated water. The relationships between waste properties, conditions, maximum Pb capacity selected adsorbents have not been adequately explored. A thorough understanding these interactions crucial for optimizing processes enhancing efficiency as sustainable adsorbents. To assess by identify key influencing factors, three artificial intelligence techniques, namely Extreme Learning Machine (ELM), Adaptive Nuro-Fuzzy Inference Systems (ANFIS), Group Method Data Handling (GMDH) employed in this study. Seven input variables, time, ratio, initial ion concentration, type wastes, pH, temperature, agitation speed, 771 data points were used inputs model development, while quantity adsorbed was chosen target parameter. best combinations with seven 127 models defined analyzed ELM integrated cross-validation technique. results highlighted that concentration most critical factor heavy metal adsorption, temperature least important factor. top models, utilizing variable(s), then modeled ANFIS GMDH. Subsequently, all compared. GMDH four variables (initial adsorbent, speed) demonstrated highest performance terms accuracy simplicity.

Language: Английский

Recovery of valuable metals from spent hydrodesulfurization (HDS) catalysts: A comprehensive research review and specific industrial cases DOI
Haoran Yu, Shuo Liu, Ali Yaraş

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 379, P. 124920 - 124920

Published: March 10, 2025

Language: Английский

Citations

0

Immobilisation of endogenous phosphorus and lead in sediments by composite water purification sludge hydrochar DOI
Ying Liu,

Liwenze He,

Yu Chen

et al.

Environmental Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: March 27, 2025

Sediment is a critical component of aquatic ecosystems, that acts as natural sink for diverse pollutants such heavy metals and phosphorus (P). However, the current research on sediment remediation has predominantly focused single contaminants. In this study, novel composite material, calcium peroxide/lanthanum-loaded hydrochar (CaO2–LaHyd), was synthesised through hydrothermal carbonisation water purification sludge, followed by sequential loading lanthanum ions nano-calcium peroxide. The adsorption capacities CaO2–LaHyd P Pb were evaluated via experiments, their passivation mechanisms investigated capping simulations. Materials characterised using scanning electron microscopy, X-ray photoelectron spectroscopy, diffraction, energy-dispersive spectroscopy. Results indicated exhibited maximum 66.05 mg·g⁻¹ 230.41 Pb. simulated addition 5% significantly reduced phosphate concentrations in overlying water. slow release oxygen from peroxide improves redox conditions, suppresses endogenous release, decreases interstitial levels. Speciation analysis revealed promoted transformation into stable forms while reducing bioavailable fractions. Concurrently, it enhanced passivation, thereby mitigating leaching risks sediment.

Language: Английский

Citations

0

Optimizing Cu2+ adsorption prediction in Undaria pinnatifida using machine learning and isotherm models DOI
Haoran Chen, Rui Zhang,

Xiaohan Qu

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: unknown, P. 138202 - 138202

Published: April 1, 2025

Language: Английский

Citations

0

β-Cyclodextrin/Graphene Oxide Multilayer Composite Membrane: A Novel Sustainable Strategy for High-Efficiency Removal of Pharmaceuticals and Personal Care Products DOI Open Access
Ziyang Zhang, Ying Yang, Zibo Tang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3322 - 3322

Published: April 8, 2025

The efficient removal of pharmaceuticals and personal care products (PPCPs) from aqueous solutions using conventional adsorbents is hindered by low adsorption capacity, insufficient selectivity, poor regeneration performance, limited stability. In this study, a multilayer β-CD/GO membrane was successfully prepared via layer-by-layer coating with β-cyclodextrin (β-CD) graphene oxide (GO). combines the host–guest complexation ability β-CD abundant oxygen-containing functional groups GO to enhance targeted PPCPs (CTD, SMZ, DCF) solutions. adsorbent overcomes separation difficulties performance powdered adsorbents, structure can significantly structural stability increase number sites. Batch experiments showed that optimal for occurred at pH 4 in absence coexisting ions. With increasing values range 4–9, capacities CTD, DCF slightly decreased 14.37, 13.69, 13.01 mg/g, respectively, slowly 4.88, 3.51, 3.26 mg/g as ion concentrations increased 0 0.20 mol/L. mechanism systematically investigated through kinetics, isotherms, thermodynamics. processes were well described both pseudo-first-order pseudo-second-order kinetic models (R2 > 0.984), suggesting hybrid involving physisorption chemisorption. isotherm results indicated CTD followed Langmuir model = 0.923), whereas SMZ better Freundlich 0.984–0.988). exhibited high maximum 35.56, 43.29, 39.49 respectively. Thermodynamic analyses exothermic (ΔH0 −86.16 −218.49 J/mol/K) non-spontaneous (ΔG0 9.84–11.56, 9.50–12.54, 10.09–14.46 kJ/mol). maintained efficiency over 58.45–71.73% after five consecutive cycles, demonstrating reusability practical applications. mechanisms include electrostatic interactions, hydrogen bonding, hydrophobic π-π EDA interactions. This study offers promising environmentally friendly

Language: Английский

Citations

0

Prediction of Cr6+ removal on the biosorbent from pine cone residue with machine learning simulations DOI

Joaquim G.G.S. Bento,

Luidy F. Senra,

Lana S. Maia

et al.

Surfaces and Interfaces, Journal Year: 2025, Volume and Issue: unknown, P. 106460 - 106460

Published: April 1, 2025

Language: Английский

Citations

0

Optimization of crystal violet adsorption using sulfuric acid activated kamugu nut shell carbon: a factorial design approach DOI

A. Basker,

Thangavelu Thayumanavan, Velusamy Arul

et al.

Biomass Conversion and Biorefinery, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Language: Английский

Citations

0

Machine learning modeling of thermally assisted biodrying process for municipal sludge DOI
Kaiqiang Zhang,

Ningfung Wang

Waste Management, Journal Year: 2024, Volume and Issue: 188, P. 95 - 106

Published: Aug. 10, 2024

Language: Английский

Citations

3

Concentration division for adsorption coefficient prediction using machine learning with Abraham descriptors: data-splitting approach comparison and critical factors identification DOI

Zhenguo Qi,

Shifa Zhong, Xin Huang

et al.

Carbon, Journal Year: 2024, Volume and Issue: 230, P. 119573 - 119573

Published: Aug. 28, 2024

Language: Английский

Citations

3

Supervised machine learning-based categorization and prediction of uranium adsorption capacity on various process parameters DOI Creative Commons

Niken Siwi Pamungkas,

Zico Pratama Putra, Hendra Adhi Pratama

et al.

Journal of Hazardous Materials Advances, Journal Year: 2024, Volume and Issue: 17, P. 100523 - 100523

Published: Nov. 9, 2024

Language: Английский

Citations

3

Machine learning models with innovative outlier detection techniques for predicting heavy metal contamination in soils DOI
Ram Proshad, S Asha,

Rong Kun Jason Tan

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 481, P. 136536 - 136536

Published: Nov. 19, 2024

Language: Английский

Citations

2