ArticleMicromachines2026
Quantifying and Minimizing the Variance of Gradient Insulator-Based Dielectrophoresis.
Article in Micromachines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
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Abstract
Opportunities abound in microfluidic technologies to impact how we understand extremely complex systems with many constituents which change with time and space. In these technologies, separation science plays a central role towards understanding everything from biology and healthcare to environmental monitoring to the search for life in the Solar system. Separations can amplify the capabilities of detection modalities by isolating targets and/or increasing their concentration while removing background constituents which can interfere with their sensing. In essence, separations increase the amount of information that can be gathered from a sample. The ideal features of next-generation separations capability are present in gradient insulator-based dielectrophoresis (g-iDEP), enabled by the length scale and precision of microfluidics. It acts through electric field interactions with particles, which enables unbiased (label-free) separations since all relevant particles, from atoms to cells, have an accessible response to electricity-either through linear (electrophoresis) or higher-order gradient (dielectrophoresis and related) effects. The technique isolates and concentrates, enabling improved detection function and multidimensional separations. Its foundational theoretical capabilities give it separations power on the order of 1:10
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