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Lignin Based Flexible Electromagnetic Shielding PU Synergized with Graphite
Jia Zhang,Yunxia Qi,Yumei Zhang,Jinchi Duan,Bairun Liu,Baijun Liu,Zhaoyan Sun,Yiquan Xu,Wei Hu,Niaona Zhang 한국섬유공학회 2021 Fibers and polymers Vol.22 No.1
In this paper, lignin (L)-based polyurethane (FeGLPU) with excellent electromagnetic shielding properties wasprepared and studied. The modified reduced iron powder was modified with KH550, and then the obtained modified reducediron powder (Fe) was mixed with lignin, polyethylene glycol 200 (PEG200), hexamethylene diisocyanate (HDI) and graphite(G) to in-situ synthesize the FeGLPU. The thermal stability, mechanical properties, electronic conductivity, and morphologyof the composite FeGLPU were characterized in detail. The electromagnetic interference shielding effectiveness (EMI SE) ofFeGLPU was tested in the frequency range of 8.2-26.5 GHz. When the content of Fe and G was fixed at 10 % and the lignincontent was 5 %, the maximum EMI SE was 21.6 dB, and the frequency width of EMI SE greater than 10 dB was 18.3 GHz. The conductivity was 4.27×10-4 S/m, and the tensile strength of Fe10G10L5PU reached 11.7 MPa. When the lignin contentincreased to be 20 %, the maximum EMI SE was 22.5 dB, and the frequency width of EMI SE greater than 10 dB was18.3 GHz. The conductivity was 1.06×10-2 S/m, and the thermal decomposition temperature T5 (5 % weight loss) reached234 °C. The obtained excellent EMI SE should be due to the synergistic effect of Fe, G and lignin. It can be observed fromthe SEM observation that the G and Fe are uniformly dispersed in PU matrix with strong interfacial interaction. It wasillustrated that the prepared FeGLPU was with efficient electromagnetic shielding properties, good mechanical properties,and high thermal stability. This lignin based electromagnetic shielding PU was proposed to have broad application prospectsdue to its low expenses and ecology friendliness.
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루머유형, 메시지 소구 유형이 루머 신뢰 및 확산 의도에 미치는 영향 수용자의 정보 처리 동기의 조절 효과를 중심으로
장금시 ( Jinchi Zhang ),조수영 ( Sooyoung Cho ) 한국PR학회 2017 PR연구 Vol.21 No.2
This study examined how the rumor types and message appeals influence on perceived credibility, word-of-mouth intention, and rebuttal word-of-mouth intention of a rumor. Also, the study employed an individual`s information processing motivation as a moderating variable. Results showed that first, rumor types had influences on perceived credibility and rebuttal word-of-mouth intention: Compared to a conspiracy rumor, people showed a higher credibility and stronger rebuttal word-of-mouth intention towards a contamination rumor. This suggests that a company need to actively deal with the contamination rumor that can bring more direct damage to the consumers. Second, the message appeals showed main effects on the three dependent variables. More specifically, compared to a rational appeal message, people showed a lower credibility and weaker word-of-mouth intention, but a stronger rebuttal intentions towards an emotional appeal rumor message. Third, there are interaction effects between two independent variables on the perceived credibility and rebuttal word-of- mouth intention. That is, in case of contamination rumor, people showed a higher credibility and weaker rebuttal intentions when it is formed in the way of a rational appeal rather than an emotional appeal. Finally, information processing motivation showed main effects on the three dependent variables. The interactions among the three variables were significant on perceived credibility and rebuttal word-of-mouth intention. More specifically, a person having a low information processing motivation showed a higher credibility and lower rebuttal word- of-mouth intention when a conspiracy rumor was formed in an emotional appeal. On the contrary, the same person showed a higher credibility and lower rebuttal word-of-mouth intention when a contamination rumor was formed in a rational appeal.
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Liang-Jie Wang,Min Guo,Kazuhide Sawada,Jie Lin,Jinchi Zhang 한국지질과학협의회 2016 Geosciences Journal Vol.20 No.1
For the purpose of comparing susceptibility mapping methods in Mizunami City, Japan, the landslide inventory was partitioned into three groups as various training and test datasets to identify the most appropriate method for creating a landslide susceptibility map. A total of fifteen landslide susceptibility maps were produced using frequency ratio, logistic regression, decision tree, weights of evidence and artificial neural network models, and the results were assessed using existing test landside points and areas under the relative operative characteristic curve (AUC). The validation results indicated that the logistic regression model could provide the highest AUC value (0.865), and a relatively high percentage of landslide points fell in the high and very high landslide susceptibility classes in this study. Furthermore, the paper also suggested that the model performances would be increased if appropriate landslide points were used for the calculation.
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Lei Chu,Liang-Jie Wang,Jiang Jiang,Xia Liu,Kazuhide Sawada,Jinchi Zhang 한국지질과학협의회 2019 Geosciences Journal Vol.23 No.2
Landslide susceptibility mapping (LSM) is a critical tool for mitigating the damages caused by geologic disasters. The selection of map units and mathematical models greatly affects the efficiency of LSM. To obtain the most appropriate combination of map units and mathematical models, four scales of catchment map units (CMUs) were analyzed and random forest (RF) and multivariate adaptive regression spline (MARSpline) models were applied in Gero City, Japan. The percentage of correctly identified landslides and the areas under the relative operating characteristic (ROC) curve were used to evaluate the model performances. The results indicate that the RF model had higher prediction accuracy than the MARSpline model, especially when the size of the CMU was 0.09 km2. A relatively high percentage of landslides fell into the high and very high landslide susceptibility classes (73%) and the lowest percentage of landslides fell into the very low landslide susceptibility classes (0.82%). The prediction-area (P-A) plots indicated that the prediction rates were higher for the RF model than the MARSpline model. The results of this study also suggest that the model accuracy can be increased if the appropriate CMU size is used. Therefore, the potential benefits of using the RF model in combination with the appropriate CMU size should be further explored using additional landslide-conditioning factors and other models.
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