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4A沸石对聚丙烯/聚磷酸铵/硼酸锌-线型三嗪杂化成炭剂材料的催化成炭和协效阻燃 被引量:1
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作者 胡焕波 刘肇闻 +1 位作者 赵天瑜 吴唯 《高分子材料科学与工程》 EI CAS CSCD 北大核心 2022年第9期51-57,共7页
针对聚磷酸铵(APP)与硼酸锌-线型三嗪杂化成炭剂(MCA-K-ZB)组成的膨胀阻燃剂(IFR)在对聚丙烯(PP)阻燃中形成的炭层强度不够高、易被燃烧中气态物质气流冲破的问题,文中在IFR(m(APP):m(MCA-K-ZB)=3:1)中添加4A沸石作为成炭协效剂,通过极... 针对聚磷酸铵(APP)与硼酸锌-线型三嗪杂化成炭剂(MCA-K-ZB)组成的膨胀阻燃剂(IFR)在对聚丙烯(PP)阻燃中形成的炭层强度不够高、易被燃烧中气态物质气流冲破的问题,文中在IFR(m(APP):m(MCA-K-ZB)=3:1)中添加4A沸石作为成炭协效剂,通过极限氧指数测试、垂直燃烧测试、锥形量热测试、热重分析、扫描电镜-能谱分析、红外光谱和激光拉曼光谱分析等方法,研究了4A沸石对PP/IFR的催化成炭协效作用和机理。结果表明,4A沸石使PP/IFR燃烧中不再出现膨胀炭层被热流或气流冲破的现象,有效降低了PP燃烧的剧烈程度。4A沸石可促使APP与MCA-K-ZB在PP燃烧中形成芳环交联结构残炭和更多石墨化残炭,提高致密炭层厚度,以此提高炭层强度和阻燃效果。当4A沸石质量分数为1%、IFR质量分数为22%时,PP的LOI值达到33.1%,通过V-0等级,无滴落,实现了低IFR添加量高阻燃性的预期目标。 展开更多
关键词 聚丙烯 膨胀阻燃 4A沸石 成炭 协效
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Development of Scientific Research Management in Big Data Era
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作者 Bin Wang zhaowen liu 《国际计算机前沿大会会议论文集》 2018年第1期1-1,共1页
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Prediction of Cancer-Associated piRNA–mRNA and piRNA–lncRNA Interactions by Integrated Analysis of Expression and Sequence Data
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作者 Yajun liu Junying Zhang +4 位作者 Aimin Li zhaowen liu Zhongzhen He Xiguo Yuan Shouheng Tuo 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2018年第2期115-125,共11页
piwi-interactingRNAs(piRNAs) are valuable biomarkers, but functional studies are still very limited.Recent research shows that piRNA-mediated cleavage acts on Transposable Elements(TEs), messengerRNAs(mRNAs), and long... piwi-interactingRNAs(piRNAs) are valuable biomarkers, but functional studies are still very limited.Recent research shows that piRNA-mediated cleavage acts on Transposable Elements(TEs), messengerRNAs(mRNAs), and long non-codingRNAs(lncRNAs). This study aimed to predict cancer-associated piRNA-mRNA and piRNA-lncRNA interactions as well as piRNA regulatory functions. Four cancer types(BRCA, HNSC, KIRC,and LUAD) were investigated. Interactions were identified by integrated analysis of the expression and sequence data. For the expression analysis, only piRNA–mRNA and piRNA–lncRNA pairs with expression profiles that were significantly inversely correlated were retained to reduce false-positive rates during the prediction. For the sequence analysis, miRanda was used for the target prediction. We identified 198 piRNA–mRNA and 10 piRNA–lncRNA pairs. Unlike mRNA and lncRNA expressions, the piRNA expression was relatively consistent across the cancer types. Furthermore, the identified piRNAs were consistent with previously published cancer biomarkers, such as piRNA-36741, piR-21032, and piRNA-57125. More importantly, predicted piRNA functions were determined by constructing an interaction network, and piRNA targets were placed in gene ontology categories related to the cancer hallmarks "activating invasion and metastasis" and "sustained angiogenesis". 展开更多
关键词 CO-EXPRESSION piRNA-mRNA INTERACTION piRNA-IncRNA INTERACTION integrated analysis target predictior
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