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Temperature gradient-induced Marangoni convection has attracted much attention for basic research and applications since it provides an effective means for mass and heat transfer through a liquid surface flow. Here the authors first propose a general principle to enhance such surface flow by hindering its transition to recirculation flow using an external field. They subsequently identify ferrofluid and use it validate the principle since its reduced magnetic susceptibility at higher temperatures will make the heated surface liquid stay on the surface by a thermomagnetic body force. Using a laser beam to create a heated local surface and a magnet beneath the ferrofluid to provide a vertical field, a high speed and long-range Marangoni flow is confirmed experimentally and further supported by computational fluid dynamics simulations. To demonstrate possible applications, the authors show a self-driving pipeless liquid conveyor belt that can efficiently transfer heat from a source to sink without external power. The demonstration of enhanced Marangoni convection opens new avenue to explore interfacial fluid dynamics and its wide applications.

The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adom.202201534.

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In the development of modern science and technology innovation, identity authentication technology in daily life and work in the field of application more and more, among which fingerprint recognition, facial recognition, voice recognition, vein recognition, iris recognition, etc., are not easy to forge the characteristics, so it is the main content of research scholars in various countries. Especially for palmar vein recognition technology, because this recognition technology has the characteristics of stability and uniqueness, the characteristic area of palmar vein is large, so more and more research topics are proposed. In the traditional sense of the hand vein recognition method, although has obtained the high accuracy, but need to manually during the recognition image design and gathering more features, need to study during the data preprocessing high quality hand vein image, so how to make use of artificial intelligence algorithm is optimized, are the major risks to the present study. In this paper, based on the understanding of the development status of palm vein recognition technology and the basic principle of Unet depth prediction and projection transformation, a palm vein recognition method based on feature fusion network is proposed. The final results show that compared with the traditional palm-vein recognition method, the proposed algorithm has stronger features, expression ability and generalization ability.

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We demonstrate a versatile microfluidic pump using laser streaming from optical fiber facet and sewing needle tip. The high-speed directional jet flow successfully drives fluid inside a capillary tube, paving the way for biomedical applications.