Zobrazeno 1 - 10
of 1 186
pro vyhledávání: '"WANG Zhenlin"'
Publikováno v:
Nanophotonics, Vol 13, Iss 8, Pp 1239-1278 (2024)
In recent years, metasurface, as a representative of micro- and nano-optics, have demonstrated a powerful ability to manipulate light, which can modulate a variety of physical parameters, such as wavelength, phase, and amplitude, to achieve various f
Externí odkaz:
https://doaj.org/article/25c1d081d6eb415ba01f998855786db4
Publikováno v:
Chinese Journal of Magnetic Resonance, Vol 40, Iss 2, Pp 122-135 (2023)
In order to improve the reliability of two-dimensional nuclear magnetic resonance (2D NMR) measurement in shale oil reservoirs, the T2-T1 2D NMR response characteristics and influencing factors of shale oil reservoirs were analyzed in three scenarios
Externí odkaz:
https://doaj.org/article/499992d6bae44481b9fbcfda957842a1
Autor:
Yuan Quan, Ge Qin, Chen Linsen, Zhang Yi, Yang Yuhang, Cao Xun, Wang Shuming, Zhu Shining, Wang Zhenlin
Publikováno v:
Nanophotonics, Vol 12, Iss 13, Pp 2295-2315 (2023)
Unlike traditional optical components, which rely on the gradual accumulation of light along the optical path over a distance much larger than the wavelength to form a wavefront, metasurfaces manipulate light field properties on the wavelength thickn
Externí odkaz:
https://doaj.org/article/29ac8544fed7466387571c22e1a30d4f
Publikováno v:
发电技术, Vol 43, Iss 5, Pp 718-730 (2022)
A new scheme of lithium ion battery and super capacitor hybrid energy storage system in wind farm was proposed. The original wind power was decomposed by the wavelet packet frequency division technology to obtain the compensation power of the hybrid
Externí odkaz:
https://doaj.org/article/2b609db891d7488a82ab6ed616e9c641
Autor:
Chen, Mengwen, Wang, Chenyu, Jia, Kunpeng, Tian, Xiao-Hui, Tang, Jie, Zhu, Chunxi, Gu, Xiaowen, Zhao, Zexing, Wang, Zikang, Ye, Zhilin, Tang, Ji, Zhang, Yong, Yan, Zhong, Qian, Guang, Jin, Biaobing, Wang, Zhenlin, Zhu, Shi-Ning, Xie, Zhenda
While thin film lithium niobate (TFLN) is known for efficient signal generation, on-chip signal amplification remains challenging from fully integrated optical communication circuits. Here we demonstrate the first continuous-wave-pump optical paramet
Externí odkaz:
http://arxiv.org/abs/2411.10721
Autor:
Wang Zhenlin
Publikováno v:
SHS Web of Conferences, Vol 179, p 03026 (2023)
Currently, vocational education in China is in an important turning point of improving quality and excellence, and building a modern vocational education system is an urgent task facing vocational education. At present, there are still problems in vo
Externí odkaz:
https://doaj.org/article/bbf0a3028d474b0ba8d3a5098294122b
Autor:
Li, Zhongfu, Li, Shiqi, Yan, Bei, Chan, Hsun-Chi, Li, Jing, Guan, Jun, Bi, Wengang, Xiang, Yuanjiang, Gao, Zhen, Zhang, Shuang, Zhan, Peng, Wang, Zhenlin, Xie, Biye
Emergent collective modes in lattices give birth to many intriguing physical phenomena in condensed matter physics. Among these collective modes, large-area modes typically feature small-level spacings, while a mode with stable frequency tends to be
Externí odkaz:
http://arxiv.org/abs/2401.10928
Autor:
Zhang, Xiaoxuan, Gupta, Tryaksh, Wang, Zhenlin, Trewartha, Amalie, Anapolsky, Abraham, Garikipati, Krishna
In this work, we present a computational framework for coupled electro-chemo-(nonlinear) mechanics at the particle scale for solid-state batteries. The framework accounts for interfacial fracture between the active particles and solid electrolyte due
Externí odkaz:
http://arxiv.org/abs/2309.13463
Autor:
Li, Chuandong, Sha, Sai, Zeng, Yangqing, Yang, Xiran, Luo, Yingwei, Wang, Xiaolin, Wang, Zhenlin
As more data-intensive tasks with large footprints are deployed in virtual machines (VMs), huge pages are widely used to eliminate the increasing address translation overhead. However, once the huge page mapping is established, all the base page regi
Externí odkaz:
http://arxiv.org/abs/2307.10618
Autor:
Lu, Yuzhe, Qin, Yilong, Zhai, Runtian, Shen, Andrew, Chen, Ketong, Wang, Zhenlin, Kolouri, Soheil, Stepputtis, Simon, Campbell, Joseph, Sycara, Katia
Out-of-distribution (OOD) data poses serious challenges in deployed machine learning models, so methods of predicting a model's performance on OOD data without labels are important for machine learning safety. While a number of methods have been prop
Externí odkaz:
http://arxiv.org/abs/2305.15640