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Guoxi Luo

Researcher at Xi'an Jiaotong University

Publications -  75
Citations -  897

Guoxi Luo is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Electrode & Piezoelectricity. The author has an hindex of 11, co-authored 57 publications receiving 438 citations. Previous affiliations of Guoxi Luo include Huazhong University of Science and Technology & University of California, Berkeley.

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Direct-Write, Self-Aligned Electrospinning on Paper for Controllable Fabrication of Three-Dimensional Structures

TL;DR: Near-field electrospinning (NFES) is applied to directly write arbitrarily shaped 3D structures through consistent and spatially controlled fiber-by-fiber stacking of polyvinylidene fluoride (PVDF) fibers, which enables the design and controlled fabrication of electrospun3D structures such as grids, walls, hollow cylinders, and other 3D logos.
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Gelatin methacryloyl-based tactile sensors for medical wearables.

TL;DR: A robust chemical bonding and a reliable encapsulation approach are introduced to overcome detachment and water-evaporation issues in hydrogel biosensors and successful monitoring of various human physiological and motion signals demonstrates the potential of GelMA tactile sensors for wearable biosensing applications.
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The quantitative characterization of the concentration and dispersion of multi-walled carbon nanotubes in suspension by spectrophotometry

TL;DR: In this paper, a simple method for characterizing the concentration and dispersion state of MWCNTs in suspension or polymer composites quantitatively by spectrophotometry was developed.
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Self-sustained autonomous wireless sensing based on a hybridized TENG and PEG vibration mechanism

TL;DR: A VR train monitoring demonstration has been conducted showing the great prospect of the self-sustainable WSN in harsh environments.
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System level design of wireless sensor node powered by piezoelectric vibration energy harvesting

TL;DR: A complete system level coupling circuit model is established to predict the performance characteristics of the piezoelectric vibration energy harvester (PVEH) and can set up a reference to optimize system parameters for WSN powered by PVEH.