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GaN nanorods gas sensor for highly sensitive n-butanol detection at room temperature
Shuai Han,Yongming Fu,Donghui Li,Dan Han,Qinjun Sun 대한금속·재료학회 2023 ELECTRONIC MATERIALS LETTERS Vol.19 No.3
Safe and effi cient detection of hazardous n-butanol gas is very great signifi cance to the health of workers and researchers inchemical environments. In this work, we successfully developed a GaN gas sensor by a simple solvothermal method and alow-temperature nitridation process. Material characterization results show that one-dimensional nanorods structures wereobtained and the products presented a superior growth orientation along with (101) plane. The gas sensing test results showthat the sensor exhibits excellent responsivity, repeatability, and selectivity to n-butanol at room temperature. The responseand recovery time of the sensor to 200 ppm n-butanol gas was 45 s/34 s. Gas adsorption model and electron depletion layertheory were established to understand the n-butanol sensing mechanism. This work provides the possibility for its realapplication in n-butanol detection with safe and effi cient at room temperature.
One-step synthesis of mesoporous sulfated zirconia nanoparticles with anionic template
Hongping Pu,Yongming Luo,Liuyi Zhang,Dongquan Du,Caiyun Han,Hongyin Li,Jiangyan Li 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.10
Mesoporous sulfated zirconia nanoparticles (MSZNP) with high surface area have been synthesized by using sodium dodecyl sulfate (C12H25OSO3Na, SDS), both as a template and a sulfating agent via one-step route. On the basis of FT-IR, EDS together with NH3-TPD analyses, the SO42− anion, originated from the hydrophilic head of SDS, can be incorporated into ZrO2 to form MSZNP with super-acidity. The phase transition of ZrO2 from tetragonal to monoclinic phase was effectively inhibited by the presence of SO42−, and the formation mechanism was illustrated in detail. MSZNP(550) achieved far higher activity than CSZ(550) in transesterification of soybean oil with methanol due to the synergistic effect of strong acidity, high BET surface area and the formation of mesostructure.
Zhao, Xu-Ye,Cui, Yongm,Jiang, Shu-Fang,Liu, Ke-Jun,Han, Hai-Qiong,Liu, Xiao-Su,Li, Yali Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.2
Our aims were to evaluate the clinical performance of human telomerase RNA gene component (hTERC gene) amplification assay with high-risk human papillomavirus (HR-HPV) DNA test of Hybrid Capture 2 DNA test (HC2), for the detection of high grade cervical precancerous lesions and cancer (CIN 2+). In addition, the association shown between hTERC gene amplification and HPV DNA test positive in women with and without cervical neoplasia was assessed. There were 92 women who underwent cytology, HR-HPV DNA test, hTERC gene amplification test, colposcopy and biopsy. We compared the clinical performance of hTERC gene test along with HR-HPV DNA test of women with colposcopy and routine screening. The samples were histology-confirmed high-grade cervical intraepithelial neoplasia (CIN 2) or worse (CIN2+) as the positive criterion. The test of hTERC gene showed the hTERC gene amplification positivity increased with the severity of histological abnormality and cytological abnormality. The test of hTERC gene showed higher specificity than HR-HPV DNA test for high-grade lesions (84.4% versus 50%) and also higher positive predictive value (90.4% versus 76.5%). Our results predicted that hTERC gene amplification demonstrated more specific performance for predicting the risk of progression and offer a strong potential as a tool for triage in cervical cancer screening, with the limited sensitive as HR-HPV DNA test.
A Hybrid Public Opinion Analysis Method Based on Improved Clustering and Mutual Information
Zhiqiang Geng,Xia Tang,Yikang Zhang,Yongming Han 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.3
The Internet is frequently used as a medium for exchange of information and opinions, and it is imperative to conduct public opinion analysis to get people’s opinions well understood and guided. In this paper a hybrid public opinion analysis method based on improved clustering and mutual information is proposed. During feature extraction, the weights of words are modified based on Part-of-Speech Tagging to reduce the dimensions of original texts. As for clustering, a novel density peak algorithm is improved and combined with binary search algorithm to determine the cluster number K and initial centers for KMeans. Then hot words extraction, sentiment analysis and trend analysis for each cluster are processed with mutual information to mine useful knowledge to help decision-making. Extensive experiments are conducted on Hadoop, and the results show that our hybrid Public Opinion Analysis method is quite effective and has certain significance.