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Separation of specific ions from water could enable recovery and reuse of essential metals and nutrients, but established membrane technologies lack the high-precision selectivity needed to facilitate a circular resource economy. In this work, we investigate whether the cation/cation selectivity of a composite cation-exchange membrane (CEM), or a thin polymer selective layer on top of a CEM, may be limited by the mass transfer resistance of the underlying CEM. In our analysis, we utilize a layer-by-layer technique to modify CEMs with a thin polymer selective layer (∼50 nm) that has previously shown high selectivity toward copper over similarly sized metals. While these composite membranes have a CuCl/MgCl selectivity up to 33 times larger than unmodified CEMs in diffusion dialysis, our estimates suggest that eliminating resistance from the underlying CEM could further increase selectivity twofold. In contrast, the CEM base layer has a smaller effect on the selectivity of these composite membranes in electrodialysis, although these effects could become more pronounced for ultrathin or highly conductive selective layers. Our results highlight that base layer resistance prevents selectivity factors from being comparable across diffusion dialysis and electrodialysis, and CEMs with low resistance are necessary for providing highly precise separations with composite CEMs.
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http://dx.doi.org/10.1021/acs.est.3c00445 | DOI Listing |
Invest Ophthalmol Vis Sci
September 2025
University of Health Science, Haseki Training and Research Hospital, Department of Ophthalmology, Istanbul, Turkey.
Purpose: The purpose of this study was to assess the reflectivity of the outer retinal layers (ORLs) in patients with central serous chorioretinopathy (CSCR) and to examine the relationship between the dimensions of the subretinal fluid (SRF) and ORL.
Methods: This retrospective, cross-sectional study included 33 eyes of 33 patients with CSCR and 33 age- and gender-matched controls. Unnormalized and relative reflectivities for the retinal pigment epithelium (RPE), the external limiting membrane (ELM), and the ellipsoid zone (EZ), as well as SRF height, base width, and area, were measured on optical coherence tomography images.
J Integr Neurosci
August 2025
School of Computer Science, Guangdong Polytechnic Normal University, 510665 Guangzhou, Guangdong, China.
Background: Emotion recognition from electroencephalography (EEG) can play a pivotal role in the advancement of brain-computer interfaces (BCIs). Recent developments in deep learning, particularly convolutional neural networks (CNNs) and hybrid models, have significantly enhanced interest in this field. However, standard convolutional layers often conflate characteristics across various brain rhythms, complicating the identification of distinctive features vital for emotion recognition.
View Article and Find Full Text PDFACS Nano
September 2025
Key Laboratory of Applied Surface and Colloid Chemistry (Ministry of Education), School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an 710119, P. R. China.
Transition metal chalcogenides (TMCs) have garnered significant attention as high-capacity anode materials, yet the unconventional role of the Cu collector meditating atomic-level substitution of metal-site cations by Cu ions during electrochemical cycling remains mechanistically unclear. To address this, herein, Cu-doped MoSe@C ultrathin nanosheets were synthesized via the solvothermal process and carbonization strategies. A systematic investigation was conducted to elucidate the underlying driving forces for Cu substitution at Mo sites and the crucial regulatory effects of solid electrolyte interphase (SEI) formation.
View Article and Find Full Text PDFMed Teach
September 2025
NordSim, Center for Skills Training and Simulation, Aalborg University Hospital, Aalborg, Denmark.
Background: Assessing skills in simulated settings is resource-intensive and lacks validated metrics. Advances in AI offer the potential for automated competence assessment, addressing these limitations. This study aimed to develop and validate a machine learning AI model for automated evaluation during simulation-based thyroid ultrasound (US) training.
View Article and Find Full Text PDFJ Dent
September 2025
Department of Restorative Dentistry, Faculty of Dentistry, Malaya University, Kuala Lumpur, Malaysia. Electronic address:
Objectives: to evaluate the effect of smear-layer deproteinization using papain gel and SPRG-adhesive on marginal-gap, anti-demineralization of enamel and dentin after chemical pH cycling and assess acid-base resistance zone (ABRZ) characteristics.
Methods: Cylindrical cavities were prepared cervically in thirty-two extracted premolars. Teeth were divided into two pretreatment groups (n=16); deproteinization with papain enzyme gel (Papacarie Due, Brazil) for 60 second, and no-deproteinization.