Results 241 to 250 of about 3,785,220 (369)
Ultra‐low LOD H2O2 Sensor Based on Synergistic Nernst Potential Effect
Due to the synergistic effect of ENernst,H2O2${E}_{\mathrm{Nernst},\ {\mathrm{H}}_{2}{\mathrm{O}}_{2}}$ and ENernst,H+${E}_{\mathrm{Nernst},\ {\mathrm{H}}^{+}}$, the proposed sensors in this study can achieve ultralow H2O2 detection limit as low as 1.8 × 10−12 M based on the stacked PEDOT: BTB/PEDOT: PSS semiconducting layer.
Zhaoqun Wang+12 more
wiley +1 more source
Secure Wireless Communication for Correlated Legitimate User and Eavesdropper Channels via Movable-Antenna Enhanced Frequency Diverse Array. [PDF]
Wu X, Shao H, Lin J, Pan Y, Xiong W.
europepmc +1 more source
System-Level Power Optimization for Wireless Multimedia Communication
Ramesh Karri, D.J. Goodman
openalex +1 more source
Model checking dependability attributes of wireless group communication [PDF]
Mieke Massink+2 more
openalex +1 more source
In summary, a universal EGaIn‐based DIW printing strategy is presented for fabricating wideband stretchable antennas. The printed antenna achieves an operating bandwidth of 3.75–8.21 GHz (fractional bandwidth: 75%), a peak gain of 1.8 dB and a radiation efficiency of 76.6%, surpassing state‐of‐the‐art stretchable antennas. More importantly, the antenna
Xiangyu Guo+6 more
wiley +1 more source
A shared aperture multiport antenna for rural wireless communication and safety monitoring using TVWS, ISM, and 5G mmWave bands. [PDF]
Sufian MA+6 more
europepmc +1 more source
Sandwich Miura‐Ori Enabled Large Area, Super Resolution Tactile Skin for Human–Machine Interactions
Sandwich Miura‐ori based tactile skin achieves large area sensing and super resolution, due to the interactions between different cells. It can also decouple external loads because of the special deformation mechanism. The curved tactile skin can be installed on robotic arms and achieve straightforward control and interactions, showing its great ...
Qian Xu+9 more
wiley +1 more source
Retraction: Application of deep neural network and deep reinforcement learning in wireless communication. [PDF]
PLOS ONE Editors.
europepmc +1 more source