Efficient Adsorption of Ionic Liquids in Water Using −SO3H-Functionalized MIL-101(Cr): Adsorption Behavior and Mechanism DOI

Ling Zhang,

Shuai Ma, Sumei Hu

et al.

Langmuir, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 18, 2024

With the increasing application of ionic liquids (ILs) in industrial areas, removal ILs from aqueous media has attracted considerable attention due to their potential environmental impact. In this study, we investigated adsorption behavior and mechanism water using metal–organic framework material MIL-101(Cr) its sulfonated derivative MIL-101(Cr)-SO3H. It was observed that MIL-101(Cr)-SO3H exhibited notably elevated capacity (1.19 mmol/g) rapid kinetics (1.66 g/mmol·min–1) for [C4mim]Cl comparison unmodified form, underscoring impact strategic sulfonation on enhancing adsorption. Also, showcased effective various featuring diverse cations varying anions, highlighting broad-spectrum capture capacities. The process is less influenced by type anions. contrast, enhanced [C16mim]Cl demonstrated length alkyl chain ILs' cation exerted a more significant influence than head tail group. This enhancement attributed synergistic interplay pore filling, electrostatic interactions, hydrophobic micelle enrichment. These findings provided valuable insights into optimizing design materials efficient IL pollutants.

Language: Английский

Utilizing Artificial Intelligence and Machine Learning for Enhanced Recycling Efforts DOI
Nikita Kandpal,

Nishant Singhal,

Harsh Vardhan Lavaniya

et al.

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 65 - 82

Published: Jan. 16, 2025

One industry that has benefitted largely from the integration of Artificial Intelligence (AI) and machine learning (ML) in its processes is recycling, providing significant advancements waste management towards sustainability environmental conservation. This chapter highlights application AI ML various streams (plastic, electronic food, paper, textile, metal etc. wastage). These systems use AI-powered image recognition sorting to better separate materials, helping increasing efficiency chemical recycling technologies; meanwhile algorithms enable cleaner for handling chemicals material recovery. Increased precision removal valuable components via automated disassembly predictive analytics. Using helped increase operational efficiency, resources recovery but also shown clear contributions environment overall ensure sustainable future ahead.

Language: Английский

Citations

0
Artificial intelligence based detection and control strategies for river water pollution: A comprehensive review DOI
Deepak L. Bhatt, Mamata Swain, Dhananjay Yadav

et al.

Journal of Contaminant Hydrology, Journal Year: 2025, Volume and Issue: 271, P. 104541 - 104541

Published: March 17, 2025

Language: Английский

Citations

0
Optimization of Extreme Learning Machine with Metaheuristic Algorithms for Modelling Water Quality Parameters of Tamburawa Water Treatment Plant in Nigeria DOI
Sani I. Abba, Quoc Bao Pham, Anurag Malik

et al.

Water Resources Management, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Language: Английский

Citations

2
Artificial intelligence in industrial operations management: a bibliometric analysis DOI Creative Commons

E Nunes,

Américo Chalupa Ramos Pinto,

Inaray de Sousa Passos

et al.

Revista de Gestão e Secretariado (Management and Administrative Professional Review), Journal Year: 2024, Volume and Issue: 15(10), P. e4210 - e4210

Published: Oct. 7, 2024

Considering the exponential growth of research on Artificial Intelligence (AI) in industrial operations management, this study aims to map scientific landscape through a bibliometric analysis. The employed data from Web Science, focusing key terms such as "AI," "industrial operations," and "management." Using VOSviewer, co-occurrence networks citation analyses were generated identify trends gaps. results reveal significant contributions countries like United States China, emphasizing AI's role enhancing efficiency innovation industries. findings provide foundation for future practical implementation strategies operations.

Language: Английский

Citations

0
Efficient Adsorption of Ionic Liquids in Water Using −SO3H-Functionalized MIL-101(Cr): Adsorption Behavior and Mechanism DOI

Ling Zhang,

Shuai Ma, Sumei Hu

et al.

Langmuir, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 18, 2024

With the increasing application of ionic liquids (ILs) in industrial areas, removal ILs from aqueous media has attracted considerable attention due to their potential environmental impact. In this study, we investigated adsorption behavior and mechanism water using metal–organic framework material MIL-101(Cr) its sulfonated derivative MIL-101(Cr)-SO3H. It was observed that MIL-101(Cr)-SO3H exhibited notably elevated capacity (1.19 mmol/g) rapid kinetics (1.66 g/mmol·min–1) for [C4mim]Cl comparison unmodified form, underscoring impact strategic sulfonation on enhancing adsorption. Also, showcased effective various featuring diverse cations varying anions, highlighting broad-spectrum capture capacities. The process is less influenced by type anions. contrast, enhanced [C16mim]Cl demonstrated length alkyl chain ILs' cation exerted a more significant influence than head tail group. This enhancement attributed synergistic interplay pore filling, electrostatic interactions, hydrophobic micelle enrichment. These findings provided valuable insights into optimizing design materials efficient IL pollutants.

Language: Английский

Citations

0