The new polymer inclusion membrane (PIM) with a 1-alkyltriazole matrix was used to separate palladium(II) ions from aqueous chloride solutions containing a mixture of Zn-Pd-Ni ions. The effective conditions for transport studies by PIMs were determined based on solvent extraction (SX) studies. Furthermore, the values of the stability constants and partition coefficients of M(II)-alkyltriazole complexes were determined. The values of both constants increase with the growing hydrophobicity of the 1-alkyltriazole molecule and have the highest values for the Pd(II) complexes. The initial fluxes, selectivity coefficients, and recovery factors values of for Pd, Zn and Ni were determined on the basis of membrane transport studies. The transport selectivity of PIMs were: Pd(II) > Zn(II) > Ni(II). The initial metal ion fluxes for all the cations increased with the elongation of the alkyl chain in the 1-alkyltriazole, but the selectivity coefficients decreased. The highest values of the initial fluxes at pH = 4.0 were found for Pd(II) ions. The best selectivity coefficients Pd(II)/Zn(II) and Pd(II)/Ni(II) equal to 4.0 and 13.4, respectively, were found for 1-pentyl-triazole. It was shown that the microstructure of the polymer membrane surface influences the kinetics of metal ion transport. Based on the conducted research, it was shown that the new PIMs with 1-alkyltriazole can be successfully used in an acidic medium to separate a mixture containing Pd(II), Zn(II) and Ni(II) ions.
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http://dx.doi.org/10.3390/polym13091424 | DOI Listing |
Integr Environ Assess Manag
January 2025
División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/IT de Culiacán, Culiacán, Sinaloa, México.
Eutrophication is one of the most relevant concerns due to the risk to water supply and food security. Nitrogen and phosphorus chemical species concentrations determined the risk and magnitude of eutrophication. These analyses are even more relevant in basins with intensive agriculture due to agrochemical discharges.
View Article and Find Full Text PDFAnn N Y Acad Sci
January 2025
Hainan Institute, Zhejiang University, Sanya, China.
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract denoised features of speech recognition such as linear predictive coding, Mel-frequency cepstral coefficient, and gammatone cepstral coefficient to represent AE signals.
View Article and Find Full Text PDFAcc Chem Res
January 2025
Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
ConspectusReactions of gas phase molecules with surfaces play key roles in atmospheric and environmental chemistry. Reactive uptake coefficients (γ), the fraction of gas-surface collisions that yield a reaction, are used to quantify the kinetics in these heterogeneous and multiphase systems. Unlike rate coefficients for homogeneous gas- or liquid-phase reactions, uptake coefficients are system- and observation-dependent quantities that depend upon a multitude of underlying elementary steps.
View Article and Find Full Text PDFInsights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
The distribution of fitness effects (DFE) characterizes the range of selection coefficients from which new mutations are sampled, and thus holds a fundamentally important role in evolutionary genomics. To date, DFE inference in primates has been largely restricted to haplorrhines, with limited data availability leaving the other suborder of primates, strepsirrhines, largely under-explored. To advance our understanding of the population genetics of this important taxonomic group, we here map exonic divergence in aye-ayes ( ) - the only extant member of the Daubentoniidae family of the Strepsirrhini suborder.
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