Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Ruiyang CHEN"'
Autor:
Yi-Han Luo, Baoqi Shi, Wei Sun, Ruiyang Chen, Sanli Huang, Zhongkai Wang, Jinbao Long, Chen Shen, Zhichao Ye, Hairun Guo, Junqiu Liu
Publikováno v:
Light: Science & Applications, Vol 13, Iss 1, Pp 1-12 (2024)
Abstract The analysis of optical spectra—emission or absorption—has been arguably the most powerful approach for discovering and understanding matter. The invention and development of many kinds of spectrometers have equipped us with versatile ye
Externí odkaz:
https://doaj.org/article/05bd41bdc94f4d7781dcbad1a24ca5d0
Publikováno v:
Materials, Vol 17, Iss 12, p 2953 (2024)
This paper presents a comprehensive study of the impact of quenching roll speed on enhancing the low-temperature toughness of a low-carbon copper-containing steel. The microstructure characteristics, such as the prior austenite grains, and the distri
Externí odkaz:
https://doaj.org/article/0a029ef5b2924f88ae74b7c2bbafee28
Autor:
Yu Xie, Tirumala Uday Kumar Nutakki, Di Wang, Xinglei Xu, Yu Li, Mohammad Nadeem Khan, Ahmed Deifalla, Yasser Elmasry, Ruiyang Chen
Publikováno v:
Case Studies in Thermal Engineering, Vol 53, Iss , Pp 103938- (2024)
Effective cooling solutions become increasingly crucial as micro-electrical devices advance in complexity and miniaturization. Microchannel heat sinks (MCHSs) are one of the solutions, and researchers are continuously exploring innovative designs and
Externí odkaz:
https://doaj.org/article/76b422c0f326446f973593bf2c909762
Publikováno v:
Advanced Intelligent Systems, Vol 5, Iss 12, Pp n/a-n/a (2023)
Diffractive optical neural networks (DONNs) are emerging as high‐throughput and energy‐efficient hardware platforms to perform all‐optical machine learning (ML) in machine vision systems. However, the current demonstrated applications of DONNs
Externí odkaz:
https://doaj.org/article/2591c4993f0b495a9f2c6e2249faa3dd
Autor:
Huamin Zheng, Wei Sun, Xingxing Ding, Haoran Wen, Ruiyang Chen, Baoqi Shi, Yi-Han Luo, Jinbao Long, Chen Shen, Shan Meng, Hairun Guo, Junqiu Liu
Publikováno v:
APL Photonics, Vol 8, Iss 12, Pp 126110-126110-9 (2023)
Dissipative Kerr solitons formed in high-Q optical microresonators provide a route to miniaturized optical frequency combs that can revolutionize precision measurements, spectroscopy, sensing, and communication. In the past decade, a myriad of integr
Externí odkaz:
https://doaj.org/article/927ac661f5e244b09beaab8bc003279d
Publikováno v:
Chemical Physics Impact, Vol 6, Iss , Pp 100164- (2023)
A highly active low-temperature MnOx wrapped cubic CeO2 (Ce@Mn) catalyst has been developed for the selective catalytic reduction of NOx by NH3. This core-shell catalyst exhibited over 90% NOx conversion at 100–300 °C, and also displayed high tole
Externí odkaz:
https://doaj.org/article/c2ec8d7214ba4fd4a283f2425abdd7ac
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Ionizing radiation (IR) can cause damage to the structure and function of salivary glands. Our research group independently synthesized the ROS scavenger, HL-003. The aim of this study was to explore the protective effects and underlying mec
Externí odkaz:
https://doaj.org/article/daff6228703743e1b9c3fb830226353e
Autor:
Yongliang Wang, Baoqiang Liu, Ruiyang Chen, Yunfei Wang, Zhidong Han, Chunfeng Wang, Ling Weng
Publikováno v:
Materials, Vol 16, Iss 13, p 4759 (2023)
Silica nanoparticles (nano-silica) were used as synergistic agents with ammonium polyphosphate (APP) and pentaerythritol (PER) to enhance flame retardancy of polypropylene (PP) in this research. The composites were prepared using a melt-mixing method
Externí odkaz:
https://doaj.org/article/b6a86a46416f4dd99cfe89b0f2cffc44
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing base
Externí odkaz:
https://doaj.org/article/f70eb5ef627d42bea283df2da64a8c8e
Publikováno v:
Entropy, Vol 25, Iss 2, p 268 (2023)
Poor chip solder joints can severely affect the quality of the finished printed circuit boards (PCBs). Due to the diversity of solder joint defects and the scarcity of anomaly data, it is a challenging task to automatically and accurately detect all
Externí odkaz:
https://doaj.org/article/8dc7458128984e1289cdff84dc5cc1f1