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25篇 您的检索式:作者名="Isleyen"
    题名 作者 年代 出处 被引量
1V_2O_5-TiO_2催化剂光催化降解2,4-二氯苯酚:催化剂载体和表面活性剂的影响(英文)显示文摘采用固态分散法成功制备了表面活性剂修饰的不同V_2O_5含量的二元氧化物催化剂,运用X射线衍射、漫反射光谱、红外光谱、扫描电镜和N_2吸附-脱附法对该纳米复合物进行了表征,并在紫外光照射下考察了其光催化降解2,4-二氯苯酚的性能.结果表明,50 wt%,V_2O_5-TiO_2(记为50V_2O_5-TiO_2)表现出比单纯V_2O_5,TiO_2和P25更高的光催化活性,V_2O_5和TiO_2之间的相互作用会影响二元氧化物催化剂的光催化效率.CTAB和HTAB的修饰显著增加了50V_2O_5-TiO_2样品的催化效率,其中(50V_2O_5-TiO_2)-CTAB催化剂在反应30 min后表现出最高的2,4-二氯苯酚降解率(100%)和反应速率(2.22 mg/(L·min)).表面活性剂的加入能修饰二元氧化物中V_2O_5和TiO_2的光学和电子性质,从而显著提高其光催化活性.Eda Sinirtas Meltem Isleyen Gulin Selda Pozan Soylu 2016Chinese Journal of Catalysis2016,37,4:3
2Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species显示文摘Parrish Z D Whit J C Isleyen M 2006Chemosphere2006,64,4:1
3Quantitative determination of fexofenadine显示文摘Isleyen EAO Ozden T 0,,1:1
4Usefulness of the Neutrophil-to-Lymphocyte Ratio to Predict Bare-Metal Stent Restenosis显示文摘Turak O Ozcan F Isleyen A 0,,:1
5Quantitative determination of fexofenadine in human plasma by HPLC-MS显示文摘Isleyen EAO Ozden T Ozilhan S 2007Chromatograp hia2007,66,1:1
6Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species显示文摘Parrish Z D White J C Isleyen M 2006Chemosphere2006,64,:1
7Uptake of weathered p,p-DDE by plants pecies effective at accumulating soil elements显示文摘WHITE J C PARRISH Z D MEHMET ISLEYEN 2005Microchemical Journal2005,81,:1
8Uptake by cu- curbitaceae of soil-borne contaminants depends upon plant genotype and pollutant properties显示文摘MATTINA M I ISLEYEN M EITZER 2006Environmental Science Technology2006,40,6:1
9Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species显示文摘PARRISH Z D WHITE J C MEHMET ISLEYEN 2006Chemosphere2006,64,:1
10Influence of citric acid amendments on the availability of weathered PCBs to plant and earthworm species 显示文摘White J C Panfish Z D Isleyen M 2006International Journal of Phytoremediation2006,8,1:1
11Quantitative determination of fexofenadine in human plasma by HPLC-MS显示文摘Isleyen EAO Ozden T Ozilhan S 2007Chromatographia2007,66,1:1
12Uptake by Cucurbitaceae ofsoil -borne contaminants depends upon plant genotype and pollutantproperties显示文摘Mattina M J I Isleyen M Eitzer B D 2006Environmental Science & Technology2006,40,6:1
13Usefulness of the Neutrophil-to-L- ymphocyte Ratio to Predict Bare-Metal Stent Restenosis 显示文摘Turak O Ozcan F Isleyen A 2012Am J Cardiol2012,110,10:1
14Evaluation of mathematical models for flexible job-shop scheduling problems 显示文摘DEMIR Y KUR SAT ISLEYEN S 2013Applied Mathematical Modelling2013,37,3:1
15Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species显示文摘Parrish Z D White J C Isleyen M 0,,04:1
16Accumulation of weathered polycyclic aromatic hydrocarbons (PAl/s) by plant and earthworm species显示文摘Parrish ZD White JC Isleyen M Gent MP Iannucci- Berger W Eitzer BD Kelsey JW MaRina MI 2006Chemosphere2006,64,4:1
17Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species显示文摘Parrish Z D White J C Isleyen M 2006Chemosphere2006,64,4:1
18Interpretable deep learning for roof fall hazard detection in underground mines显示文摘Roof falls due to geological conditions are major hazards in the mining industry,causing work time loss,injuries,and fatalities.There are roof fall problems caused by high horizontal stress in several largeopening limestone mines in the eastern and midwestern United States.The typical hazard management approach for this type of roof fall hazards relies heavily on visual inspections and expert knowledge.In this context,we proposed a deep learning system for detection of the roof fall hazards caused by high horizontal stress.We used images depicting hazardous and non-hazardous roof conditions to develop a convolutional neural network(CNN)for autonomous detection of hazardous roof conditions.To compensate for limited input data,we utilized a transfer learning approach.In the transfer learning approach,an already-trained network is used as a starting point for classification in a similar domain.Results show that this approach works well for classifying roof conditions as hazardous or safe,achieving a statistical accuracy of 86.4%.This result is also compared with a random forest classifier,and the deep learning approach is more successful at classification of roof conditions.However,accuracy alone is not enough to ensure a reliable hazard management system.System constraints and reliability are improved when the features used by the network are understood.Therefore,we used a deep learning interpretation technique called integrated gradients to identify the important geological features in each image for prediction.The analysis of integrated gradients shows that the system uses the same roof features as the experts do on roof fall hazards detection.The system developed in this paper demonstrates the potential of deep learning in geotechnical hazard management to complement human experts,and likely to become an essential part of autonomous operations in cases where hazard identification heavily depends on expert knowledge.Moreover,deep learning-based systems reduce expert exposure to hazardous conditions.Ergin Isleyen Sebnem Duzgun R.McKell Carter 2021Journal of Rock Mechanics and Geotechnical Engineering2021,13,6:1
19Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by plant and earthworm species显示文摘Parrish Z D White J C Isleyen M 2006Chemosphere2006,64,:1
20Uptake by Cucurbitaceae of soil-borne contaminants depends upon plant genotype and pollutant properties 显示文摘Mattina M I Isleyen M Eitzer B D Iannucci-Berger W White J C 2006Environmental Science & Technology2006,40,6:1
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