In this work, a novel IL-based synergistic extraction system utilizing the ionic liquid tricaprylmethylammonium nitrate ([A336][NO 3 ]) and the commercial extractant Di(2-ethylhexyl) 2-ethylhexyl phosphonate (DEHEHP) was developed for the extraction of rare earth (RE) nitrates. Pr(III) was used as a model RE and the effects of key factors, i.e. the ratio of [A336][NO 3 ] to DEHEHP, the acidity of feed solutions, and the concentration of a salting-out reagent, were systematically studied. Our results demonstrate that the mixture of [A336][NO 3 ] and DEHEHP had an obviously synergistic extraction effect for the extraction of Pr(III). The maximum synergistic enhancement coefficient of 3.44 was attained at X A = 0.4 (v%). Alternatively, mixture of [A336][Cl] and DEHEHP hardly extracted Pr(III) from chloride media. Moreover, we investigated the Pr(III) extraction mechanism and demonstrated that Pr(III) can be extracted as the neutral complexation species Pr(NO 3 ) 3 ﹒xDEHEHP and the ion-type species [A336] y ﹒Pr(NO 3 ) 3+y . These extraction processes can effectively hamper the release of organic cation-ligands into the aqueous phase. The synergistic extraction effect is mainly derived from the enhanced solubility of the extracted species in the ionic liquid phase. The extraction behaviors of Pr(III) could be properly described byLangmuir and pseudo-second-order rate equations. Increased temperature was unfavorable for the extraction reaction but greatly improved the extraction rate.Interestingly, the mixed IL extraction system has an obviously synergistic extraction effect for light REs (LREs, La -Eu), but an anti-synergistic effect for heavy REs (HREs, Gd -Lu, Y), thus, indicating that our synergistic extraction system is helpful for the separation of LREs from HREs. In addition, the high selectivity between REs and non-REs suggested that the recovery of REs from a complicated high-salt leachate could be highly possible. It demonstrates that the IL-based synergistic extraction strategy developed in this work is promising and sustainable, and as a result, the development of an IL-based synergistic extraction process for the recovery of REs is straightforwardly envisaged.

Millions of adults have diabetes across the globe and the overall cost for managing diabetic patients has reached up to approximately 250 million. A major constraint in existing ontology-based systems for diagnosing and treating diabetes is the presence of semantic inconsistencies and lack of a comprehensive clinical approach primarily due to consideration of a limited number of classes in the model. In this research, we are focused on building an ontology-based model for diabetic patients by collecting detailed diabetic knowledge of subjects for further diagnosis and treatment. The concept of semantic resources to electronic health record standards is an essential factor for semantic interoperability in remote health monitoring. This study applies semantic web ontology language for developing ontology-based model for diabetic patients to aid doctors in reaching an efficient diagnostic decision about the status of diabetes by applying Semantic Web Rule Language. A total of 766 medical records from clinical environment were selected in this study, and 269 of them were known for developing diabetes. The experimental results suggest that the proposed solution is more accurate in managing diabetes compared to other medical applications. The performance analysis of the ontology-based model for diabetic patients regarding the accuracy of disease prediction, diagnosing diabetes, and recommending medicine is 95%, 98%, and 85%, respectively.

Adsorption of AuCl4− by HCSs is based on a reduction–deposition coupled mechanism and glycine can improve adsorption efficiency and rate.

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