Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 67, P. 106271 - 106271
Published: Oct. 5, 2024
Language: Английский
Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 67, P. 106271 - 106271
Published: Oct. 5, 2024
Language: Английский
Advanced Science, Journal Year: 2024, Volume and Issue: 11(28)
Published: May 2, 2024
Abstract Silver (Ag) is deemed a promising anode material for capacitive deionization (CDI) due to its high theoretical capacity and efficient selectivity Cl − . However, the strong volume change during conversion reaction significantly undermines cycling performance of Ag electrode. Additionally, achieving well‐dispersed in active matrix challenging, as electrodes prepared by conventional thermal reduction tend agglomerate. Herein, organic linker confinement strategy proposed, applying metal–organic framework (MOF) chemistry between nodes ligands construct Ag‐based MOF. The uniform dispersion at molecular level, confined matrix, efficiently enhances utilization sites, strengthens interfacial stability Ag. Consequently, Ag‐MOF CDI exhibits an excellent removal 121.52 mg g −1 20 mA 500 L NaCl solution, rate 60.54%. After 100 cycles, retention 96.93% achieved. Furthermore, capture mechanism elucidated through density functional theory (DFT) calculations, ex situ XRD, Raman XPS. This ingenious electrode design can offer valuable insights development high‐performance applications.
Language: Английский
Citations
27Desalination, Journal Year: 2024, Volume and Issue: 583, P. 117695 - 117695
Published: April 27, 2024
Language: Английский
Citations
20Separation and Purification Technology, Journal Year: 2024, Volume and Issue: 348, P. 127804 - 127804
Published: May 3, 2024
Language: Английский
Citations
14Separation and Purification Technology, Journal Year: 2025, Volume and Issue: unknown, P. 131778 - 131778
Published: Jan. 1, 2025
Language: Английский
Citations
1Separation and Purification Technology, Journal Year: 2025, Volume and Issue: 362, P. 131885 - 131885
Published: Jan. 31, 2025
Language: Английский
Citations
1Desalination, Journal Year: 2024, Volume and Issue: unknown, P. 118412 - 118412
Published: Dec. 1, 2024
Language: Английский
Citations
4Desalination, Journal Year: 2025, Volume and Issue: unknown, P. 118603 - 118603
Published: Jan. 1, 2025
Language: Английский
Citations
0Published: Jan. 1, 2025
Language: Английский
Citations
0Electrochimica Acta, Journal Year: 2025, Volume and Issue: unknown, P. 146024 - 146024
Published: March 1, 2025
Language: Английский
Citations
0Water, Journal Year: 2025, Volume and Issue: 17(8), P. 1169 - 1169
Published: April 14, 2025
This paper examines the application of artificial intelligence (AI) in desalination. The study explored AI techniques, including machine learning, neural networks, and genetic algorithms, to enhance system efficiency reduce energy costs. Case studies assessed impact on desalination systems, those powered by renewable sources. Key findings revealed that AI-driven systems improved water quality, reduced consumption up 50%, enabled predictive maintenance, minimizing downtime. Challenges integrating with energy-powered treatment were addressed analyzing hybrid setups combining solar, wind, battery storage reverse osmosis (RO) multi-stage flash (MSF) technologies. These demonstrated critical improvements efficiency, making more viable for arid remote areas. Fault detection algorithms maintenance emerged as pivotal applications, significantly reducing costs enhancing reliability. was concluded identifying challenges such intermittent nature complexities designing scalable systems. Future research should further refine advancing sustainable energy-efficient solutions.
Language: Английский
Citations
0