A large-area planar helicon plasma source with a multi-ring antenna on Linear Experimental Advanced Device (LEAD)
JOURNAL OF INSTRUMENTATION
Authors: Liu, H.; Shinohara, S.; Yu, Y.; Xu, M.; Zheng, P. F.; Wang, Z. H.; Gong, S. B.; Wang, H. J.; Zhu, Y. X.; Nie, L.; Ke, R.; Chen, Y. H.; Duan, X. R.; Ye, M. Y.
Abstract
A planar helicon plasma source with a four-ring antenna has been developed on Linear Experimental Advanced Device (LEAD) in Southwestern Institute of Physics. The diameter of the largest antenna ring is 320 mm This source is located outside of the vacuum chamber without any vacuum interface and injects radio frequency power into the chamber through a 340-mm-diameter quartz window. A low power threshold of 150 W for electromagnetic-mode to wave-mode transfer is experimentally confirmed. A large volume plasma with a density of over 10(19) m(-3) and a plasma generation efficiency (total number of electrons diveded by input power) of over 30 x 10(13) W-1 indicate the high performance of this large-area helicon plasma source, promising LEAD a suitable device for fundamental plasma physics and plasma material interaction research.
Gain characteristics estimation of heteromorphic RFID antennas using neuro-space mapping
IET MICROWAVES ANTENNAS & PROPAGATION
Authors: Shi, Weiguang; Gao, Junchao; Cao, Yu; Yu, Yang; Liu, Penghui; Ma, Yongtao; Ni, Chunya; Yan, Shuxia
Abstract
Existing gain estimation methods for radio frequency (RF) antennas often rely on rigorous and expensive experimental facilities or are only implemented for classic structure. They perform limited application scopes. To address the challenges, this study provides an accessible method for gain estimation of heteromorphic RF identification (RFID) antennas. There are three main innovations in the proposed method. An estimation framework is proposed based on neuro-space mapping technique which effectively reduces the time consumption and avoids laborsome measurement processes. A diverse extraction integration strategy is designed for training data acquisition, to balance the estimation accuracy and the training data size. A new adaptive particle swarm optimiser embedded with scale elaboration strategy is developed, which tackles the approximation problem from the gain estimation model to the gain from high-fidelity simulations. The proposed method is tested by four types of RF antennas. Simulations results demonstrate the method possesses high accuracy and strong applicability.