scholarly journals Aluminum nanoparticle films with an enhanced hot-spot intensity for high-efficiency SERS

2020 ◽  
Vol 28 (7) ◽  
pp. 9174
Author(s):  
Zhen Li ◽  
Chonghui Li ◽  
Jing Yu ◽  
Zhaoxiang Li ◽  
Xiaofei Zhao ◽  
...  
2021 ◽  
Author(s):  
Hongxia Qian ◽  
Zhifeng Liu ◽  
Zhengang Guo ◽  
Mengnan Ruan ◽  
Weiguo Yan

Investigating high-efficiency, low-cost and abundant photoelectrode materials has always been a hot spot for researchers to attention in photoelectrochemical (PEC) system. Here we firstly study the PEC performance of ternary...


Author(s):  
Y. Hirao ◽  
G. Su ◽  
K. Sugiyama ◽  
T. Narabayashi ◽  
M. Mori ◽  
...  

When LOCA occurs in proposed nuclear reactor systems, the coolability of the core would be kept by the SI core injection system and therefore the probability of the core meltdown is negligible small. In this research work, we make it clear that the coolability of the RPV bottom is secured even if a part of the core should melt and a substantial amount of debris should be deposited on the lower plenum. In this report, we examined experimentally the coolability of the RPV bottom that a Zircaloy-based loose debris layer is deposited on. We set up a heat supply section made by SUS304 on the loose debris layer and measured the heat flux released into the loose debris bed and the temperature at the lower surface of the heat supply section. In addition, we measured the temperature distribution at the bottom of the loose debris bed. It became clear in this study that the coolability depends on the amount of coolant supplied, and the hot spot would not occur when coolant is supplied. Even if a hotspot should occur in the oxidization of loose metal debris accompanied with rapid heat generation. It is found that when a small amount of coolant can be supplied, it disappears because of a high capillary force of oxidized loose debris. So it is confirmed that the soundness of RPV is basically maintained.


2019 ◽  
Vol 22 (1) ◽  
pp. 4-15
Author(s):  
YongJei Lee ◽  
SooHyun O

By operationalizing two theoretical frameworks, we forecast crime hot spots in Colorado Springs. First, we use a population heterogeneity (flag) framework to find places where the hot spot forecasting is consistently successful over months. Second, we use a state dependence (boost) framework of the number of crimes in the periods prior to the forecasted month. This algorithm is implemented in Microsoft Excel®, making it simple to apply and completely transparent. Results shows high accuracy and high efficiency in hot spot forecasting, even if the data set and the type of crime we used in this study were different from what the original algorithm was based on. Results imply that the underlying mechanisms of serious and non-serious crime for forecasting are different from each other. We also find that the spatial patterns of forecasted hot spots are different between calls for service and crime event. Future research should consider both flag and boost theories in hot spot forecasting.


2019 ◽  
Vol 23 (2) ◽  
pp. 174-201 ◽  
Author(s):  
YongJei Lee ◽  
O SooHyun ◽  
John E. Eck

Real-time crime hot spot forecasting presents challenges to policing. There is a high volume of hot spot misclassifications and a lack of theoretical support for forecasting algorithms, especially in disciplines outside the fields of criminology and criminal justice. Transparency is particularly important as most hot spot forecasting models do not provide their underlying mechanisms. To address these challenges, we operationalize two different theories in our algorithm to forecast crime hot spots over Portland and Cincinnati. First, we use a population heterogeneity framework to find places that are consistent hot spots. Second, we use a state dependence model of the number of crimes in the time periods prior to the predicted month. This algorithm is implemented in Excel, making it extremely simple to apply and completely transparent. Our forecasting models show high accuracy and high efficiency in hot spot forecasting in both Portland and Cincinnati context. We suggest previously developed hot spot forecasting models need to be reconsidered.


2013 ◽  
Vol 411-414 ◽  
pp. 3150-3153
Author(s):  
Yu Bin Ji ◽  
Jia Zheng ◽  
Ning Chen ◽  
Dong Xue Song ◽  
Yan Dong ◽  
...  

socarbostyril alkaloids is a kind of alkaloid does not contain basic nitrogen atoms and is represented by hydroxylated benzophenanthridone or isoquinolinone types of structure. The most widely known compounds of this group are narciclasine, lycoricidine , and pancratistatin. They have demonstrated to inhibite the proliferation of many human cancer cells, and at the same time have no affect on normal human cells under a certain dose, they have a high efficiency and low toxicity in antitumor area. Now this kind of compound has been a hot spot research to antitumor workers. The present paper reviews the origin and the antitumor function of the Isocarbostyril alkaloids.


2013 ◽  
Vol 443 ◽  
pp. 359-362
Author(s):  
Zhi Hao Yin ◽  
Yong Yang

With the technology development, wireless network has been the important combination of current high and new technology. In order to confirm communication performance and different high-efficiency satisfaction of various users, relay question research of wireless network communication is the hot spot. Take the advantage of cooperation diversity technique can diverse each node in the network system. Moreover, optimize the relationship among each node is the important method of communication technology. This article evaluates relay questions in the wireless network communication. It analyzes relay and protocol, explains three transmission methods in network communication, discuss selection algorithm of multi-relay, and combines genetic algorithm and selection algorithm of multi-relay. In the end, this article provides part of the core codes.


Nano Letters ◽  
2016 ◽  
Vol 16 (11) ◽  
pp. 7203-7209 ◽  
Author(s):  
Dmitry Sivun ◽  
Cynthia Vidal ◽  
Battulga Munkhbat ◽  
Nikita Arnold ◽  
Thomas A. Klar ◽  
...  

2021 ◽  
Author(s):  
Shanshan Lin ◽  
Jianguo liu ◽  
Longlong Ma

The catalytic hydrogenation of organic substrates containing many unsaturated functional groups is an important step in the industrial preparation of fine chemicals and has always been a hot spot in basic catalysis research. For example, the phenethyl alcohol obtained by the preferential hydrogenation of the C=O group of acetophenone is a valuable intermediate for the production of spices, flavors, and medicines. Furthermore, as the demand for 1-phenylethanol (PhE) continues to increase, the catalytic hydrogenation of acetophenone (AP) is becoming more and more important. The hydrogenation of acetophenone is a complex multi-step reaction. At present, relatively few catalytic systems are used in this reaction. The enantioselective hydrogenation on heterogeneous catalysts is due to its inherent operational and economic advantages, such as the atomic economy. It is one of the most ideal methods as it is easy to separate and recycle the catalyst. However, the traditional synthesis way in batch reactors usually takes a long time with an unsatisfying conversion which is not conducive to industrialization. Heterogeneous non-precious metal catalysts are advantageous for their implementation in flow reactor systems for industrial applications due to their ease of separation, low cost, and environmental protection. Herein, we report the first use of non-noble metal Ni-supported graphene-based catalysts for hydrogenation of acetophenone to phenylethanol with high efficiency in the flow reactor which can significantly improve mass and heat transfer. The conversion rate after optimizing the reaction conditions can be as high as 99.14% with a satisfactory conversion rate of 97.77%. This catalyst is magnetic and has good cyclability. After 48 hours of uninterrupted continuous experiments, the Ni-based catalyst still maintains high catalytic activity, the conversion rate still reaches 88.44%, and the catalyst structure remains intact and stable.


2017 ◽  
Vol 130 ◽  
pp. 77-86 ◽  
Author(s):  
Shifeng Deng ◽  
Zhen Zhang ◽  
Chenhui Ju ◽  
Jingbing Dong ◽  
Zhengyue Xia ◽  
...  

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