Hypothesis: Harnessing electrical energy from salinity gradients, particularly for powering micro and nanoscale devices, has become a focal point of recent research attention, due to its renewable and biocompatible nature. Much of the reported research in that direction revolves around optimizing the membrane architecture and the charge distribution to maximize the induced electric potential, with no particular emphasis on the fluid rheology. However, many of the modern miniature systems, typically the bio-inspired ones, concern fluids with complex rheological characteristics, where the results for Newtonian solvents may not trivially apply. Here, we hypothesize that the interplay between interfacial electro-mechanics and the fluid rheology can influence the effectiveness of salinity-gradient-modulated electrokinetics significantly - an aspect that has largely remained overlooked.
Theory And Experiments: Here we report the first experiments supplemented by a theoretical model that unveil how that the addition of polymers in a solvent modulates the salinity gradient - induced electric potential in a microfluidic channel. Our theoretical framework considers the simplified Phan-Thien Tanner (sPTT) constitutive model, which represents the viscoelastic characteristics of fluids. Experiments were conducted with combined pressure driven and salinity gradient driven flow through microchannel involving dilute solutions of polyethylene oxide (PEO) of different molecular weights and concentrations to successfully validate the theoretical approach.
Findings: Our findings indicate that the induced electrical potential increased non-linearly with the saline concentration ratio across the microchannel, as compared traditional linear response. Our results demonstrate how the elasticity of fluid may enable realizing an optimal benefit to this effect, by arresting the viscous resistance and uplifting the elastic response via utilizing polymeric inclusions of high relaxation times. These results provide specific insights on preferential windows of augmenting the induced streaming potential by harnessing the viscoelastic nature of the solution and the imposed salt concentration, bearing critical implications in miniature energy harvesting and desalination technology.
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http://dx.doi.org/10.1016/j.jcis.2024.09.115 | DOI Listing |
Respir Res
January 2025
Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Department of Biomedical Engineering, Air Force Medical University, Xi'an, 710032, China.
Background: Acute pulmonary embolism represents the third most prevalent cardiovascular pathology, following coronary heart disease and hypertension. Its untreated mortality rate is as high as 20-30%, which represents a significant threat to patient survival. In view of the current lack of real-time monitoring techniques for acute pulmonary embolism, this study primarily investigates the potential of the pulsatility electrical impedance tomography (EIT) technique for the detection and real-time monitoring of acute pulmonary embolism through the collection and imaging of the pulsatile signal of pulmonary blood flow.
View Article and Find Full Text PDFNat Med
January 2025
Department of Neurosurgery, NYU Langone Health, New York, NY, USA.
The adoption of large language models (LLMs) in healthcare demands a careful analysis of their potential to spread false medical knowledge. Because LLMs ingest massive volumes of data from the open Internet during training, they are potentially exposed to unverified medical knowledge that may include deliberately planted misinformation. Here, we perform a threat assessment that simulates a data-poisoning attack against The Pile, a popular dataset used for LLM development.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.
This study investigates the optimization of wind energy integration in hybrid micro grids (MGs) to address the rising demand for renewable energy, particularly in regions with limited wind potential. A comprehensive assessment of wind energy potential was conducted, and optimal sizing of standalone MGs incorporating photovoltaic (PV) systems, wind turbines (WT), and battery storage (BS) systems was performed for six regions in the Kingdom Saudi Arabia. Wind resource analysis utilizing the Weibull distribution function shows that all regions exhibited Class 1 wind energy characteristics, with average annual wind power densities ranging from 36.
View Article and Find Full Text PDFSci Rep
January 2025
Laboratory of Biomedical Imaging and Data Analysis, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, Khlopina St. 11, St. Petersburg, Russia, 194021.
One of the mechanisms of calcium signalling in neurons is store-operated calcium entry (SOCE), which is activated when the calcium concentration in the smooth endoplasmic reticulum (ER) decreases and its protein-calcium sensor STIM (stromal interacting molecule) relocate to the endoplasmic reticulum and plasma membrane junctions, forms clusters and induces calcium entry. In electrically non-excitable cells, STIM1 is coupled with the positive end of a tubulin microtubule through interaction with EB1 (end-binding) protein, which controls its oligomerization, SOCE and participates in ER movement. STIM2 homologue, which is specific for mature hippocampal dendritic spines, is known to interact with EB3 protein, however, not much is known about the role of this interaction in STIM2 clustering or ER trafficking in neurons.
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January 2025
Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi, 75660, Pakistan.
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it challenging to trust predictions, particularly in uncertain cases. This sort of uncertainty can be crucial in medical image analysis; diabetic retinopathy is an example where even slight errors without an indication of confidence can have adverse impacts.
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